essay on role of scientists in society

The Vital Role of Scientists in Shaping our World

This essay about the indispensable role of scientists in society paints a comprehensive picture of their contributions across various domains. It outlines how scientists are not just confined to academic research but actively drive progress and innovation, significantly impacting healthcare, technology, environmental sustainability, and social justice. The essay emphasizes their crucial role in advancing human knowledge, solving complex global challenges, and ensuring the ethical application of scientific advancements. It also highlights their responsibilities in fostering scientific literacy and engaging with the public and policymakers to bridge the gap between knowledge and action. Through their work, scientists are portrayed as pivotal figures in shaping a future that values equity, sustainability, and the well-being of humanity, making them guardians of both our understanding and our world’s future.

PapersOwl showcases more free essays that are examples of Scientist.

How it works

Amidst the intricate fabric of contemporary civilization, scientists assume a pivotal role, not solely as truth-seekers but as the bedrock of advancement and ingenuity. Their endeavors transcend the confines of laboratories and scholarly publications, profoundly influencing every dimension of our existence, ranging from healthcare and technology to ecological sustainability and societal equity. This exposition delves into the manifold contributions of scientists to society, illuminating their indispensable role in propelling human understanding, tackling intricate quandaries, and confronting global dilemmas that characterize our era.

Scientists, through their tireless pursuit of enlightenment, perennially occupy the vanguard of augmenting human comprehension of the natural realm. This pursuit of enlightenment is not an end unto itself but rather a conduit to unveil novel principles and phenomena that may be leveraged for the amelioration of society. Breakthroughs in technology and medicine, exemplified by the advent of vaccines, sustainable energy sources, and digital communication platforms, stem directly from scientific inquiry. These strides have not only elevated quality of life but have also catalyzed fresh avenues for further exploration and innovation.

Furthermore, scientists assume a pivotal role in untangling intricate quandaries that traverse national boundaries and impact humanity at large. Predicaments posed by climate change, pandemics, and food security necessitate a global riposte underpinned by scientific inquiry and evidence-based policies. Scientists, by furnishing elucidation on these quandaries through their research, empower policymakers to craft judicious decisions that steer societies towards sustainable resolutions. Their expertise is indispensable in devising strategies to assuage the ramifications of climate change, augmenting healthcare outcomes, and ensuring judicious utilization of resources.

In addition to their contributions to knowledge and quandary-resolution, scientists also wield considerable influence in redressing issues of societal equity. The application of science in forensic investigations, for instance, has been instrumental in exculpating the erroneously accused and upholding justice. Similarly, environmental scientists contribute to the battle against environmental degradation, advocating for policies that safeguard vulnerable ecosystems and communities beleaguered by pollution and climate change. Through their endeavors, scientists champion the cause of equity, guaranteeing that the fruits of innovation and progress are accessible to all echelons of society.

Furthermore, scientists shoulder the onus of engaging with the populace and policymakers, translating intricate scientific tenets into actionable insights. By fostering enhanced comprehension of science and its societal implications, scientists can bridge the chasm between knowledge and action, ensuring that scientific progress is harnessed ethically and responsibly. Their role as educators and communicators is pivotal in fostering scientific literacy, an imperative for an enlightened citizenry capable of making decisions that sculpt the trajectory of our planet’s future.

Hence, the role of scientists in society is multifaceted and irreplaceable. Their contributions transcend mere scholarly accolades, permeating every facet of contemporary existence and laying the groundwork for a future illuminated by knowledge, propelled by innovation, and guided by the tenets of sustainability and equity. As we navigate the convolutions of the 21st century, the significance of scientists and their endeavors cannot be overstated. They are not merely architects of our comprehension of the world but also stewards of our posterity, ensuring that the march of progress is harmonized with the principles of equity, sustainability, and human flourishing.

Cite this page

The Vital Role of Scientists in Shaping Our World. (2024, Mar 01). Retrieved from https://papersowl.com/examples/the-vital-role-of-scientists-in-shaping-our-world/

"The Vital Role of Scientists in Shaping Our World." PapersOwl.com , 1 Mar 2024, https://papersowl.com/examples/the-vital-role-of-scientists-in-shaping-our-world/

PapersOwl.com. (2024). The Vital Role of Scientists in Shaping Our World . [Online]. Available at: https://papersowl.com/examples/the-vital-role-of-scientists-in-shaping-our-world/ [Accessed: 20 Apr. 2024]

"The Vital Role of Scientists in Shaping Our World." PapersOwl.com, Mar 01, 2024. Accessed April 20, 2024. https://papersowl.com/examples/the-vital-role-of-scientists-in-shaping-our-world/

"The Vital Role of Scientists in Shaping Our World," PapersOwl.com , 01-Mar-2024. [Online]. Available: https://papersowl.com/examples/the-vital-role-of-scientists-in-shaping-our-world/. [Accessed: 20-Apr-2024]

PapersOwl.com. (2024). The Vital Role of Scientists in Shaping Our World . [Online]. Available at: https://papersowl.com/examples/the-vital-role-of-scientists-in-shaping-our-world/ [Accessed: 20-Apr-2024]

Don't let plagiarism ruin your grade

Hire a writer to get a unique paper crafted to your needs.

Our writers will help you fix any mistakes and get an A+!

Please check your inbox.

You can order an original essay written according to your instructions.

Trusted by over 1 million students worldwide

1. Tell Us Your Requirements

2. Pick your perfect writer

3. Get Your Paper and Pay

Hi! I'm Amy, your personal assistant!

Don't know where to start? Give me your paper requirements and I connect you to an academic expert.

short deadlines

100% Plagiarism-Free

Certified writers

• Table of Contents
• Random Entry
• Chronological
• Editorial Information
• About the SEP
• Editorial Board
• How to Cite the SEP
• Special Characters
• Advanced Tools
• Support the SEP
• PDFs for SEP Friends
• Make a Donation
• SEPIA for Libraries
• Entry Contents

Bibliography

Academic tools.

• Friends PDF Preview
• Author and Citation Info
• Back to Top

The Social Dimensions of Scientific Knowledge

Study of the social dimensions of scientific knowledge encompasses the effects of scientific research on human life and social relations, the effects of social relations and values on scientific research, and the social aspects of inquiry itself. Several factors have combined to make these questions salient to contemporary philosophy of science. These factors include the emergence of social movements, like environmentalism and feminism, critical of mainstream science; concerns about the social effects of science-based technologies; epistemological questions made salient by big science; new trends in the history of science, especially the move away from internalist historiography; anti-normative approaches in the sociology of science; turns in philosophy to naturalism and pragmatism. This entry reviews the historical background to current research in this area and features of contemporary science that invite philosophical attention.

The philosophical work can roughly be classified into two camps. One acknowledges that scientific inquiry is in fact carried out in social settings and asks whether and how standard epistemology must be supplemented to address this feature. The other treats sociality as a fundamental aspect of knowledge and asks how standard epistemology must be modified or reformed from this broadly social perspective. Concerns in the supplementing approach include such matters as trust and accountability raised by multiple authorship, the division of cognitive labor, the reliability of peer review, the challenges of privately funded science, as well as concerns arising from the role of scientific research in society. The reformist approach highlights the challenge to normative philosophy from social, cultural, and feminist studies of science while seeking to develop philosophical models of the social character of scientific knowledge and inquiry. It treats the questions of the division of cognitive labor, expertise and authority, the interactions of science and society, etc., from the perspective of philosophical models of the irreducibly social character of scientific knowledge. Philosophers employ both formal modeling techniques and conceptual analysis in their efforts to identify and analyze epistemologically relevant social aspects of science.

1. Historical Background

2. big science, trust, and authority, 3. science in society.

• 4. Social, Cultural, and Feminist Studies of Science
• 5. Models of the Social Character of Knowledge
• 6. Social Direction of Science
• 7. Conclusion

Works Cited

Further reading, other internet resources, related entries.

Philosophers who study the social character of scientific knowledge can trace their lineage at least as far as John Stuart Mill. Mill, Charles Sanders Peirce, and Karl Popper all took some type of critical interaction among persons as central to the validation of knowledge claims.

Mill’s arguments occur in his well-known political essay On Liberty, (Mill 1859) rather than in the context of his logical and methodological writings, but he makes it clear that they are to apply to any kind of knowledge or truth claim. Mill argues from the fallibility of human knowers to the necessity of unobstructed opportunity for and practice of the critical discussion of ideas. Only such critical discussion can assure us of the justifiability of the (true) beliefs we do have and can help us avoid falsity or the partiality of belief or opinion framed in the context of just one point of view. Critical interaction maintains the freshness of our reasons and is instrumental in the improvement of both the content and the reasons of our beliefs. The achievement of knowledge, then, is a social or collective, not an individual, matter.

Peirce’s contribution to the social epistemology of science is commonly taken to be his consensual theory of truth: “The opinion which is fated to be ultimately agreed to by all who investigate is what we mean by truth, and the object represented is the real.” (Peirce 1878, 133) While often read as meaning that the truth is whatever the community of inquirers converges on in the long run, the notion is interpretable as meaning more precisely either that truth (and “the real”) depends on the agreement of the community of inquirers or that it is an effect of the real that it will in the end produce agreement among inquirers. Whatever the correct reading of this particular statement, Peirce elsewhere makes it clear that, in his view, truth is both attainable and beyond the reach of any individual. “We individually cannot hope to attain the ultimate philosophy which we pursue; we can only seek it for the community of philosophers.” (Peirce 1868, 40). Peirce puts great stock in instigating doubt and critical interaction as means to knowledge. Thus, whether his theory of truth is consensualist or realist, his view of the practices by which we attain it grants a central place to dialogue and social interaction.

Popper is often treated as a precursor of social epistemology because of his emphasis on the importance of criticism in the development of scientific knowledge. Two concepts of criticism are found in his works (Popper 1963, 1972) and these can be described as logical and practical senses of falsification. The logical sense of falsification is just the structure of a modus tollens argument, in which a hypothesis is falsified by the demonstration that one of its logical consequences is false. This is one notion of criticism, but it is a matter of formal relations between statements. The practical sense of falsification refers to the efforts of scientists to demonstrate the inadequacies of one another’s theories by demonstrating observational shortcomings or conceptual inconsistencies. This is a social activity. For Popper the methodology of science is falsificationist in both its logical and practical senses, and science progresses through the demonstration by falsification of the untenability of theories and hypotheses. Popper’s logical falsificationism is part of an effort to demarcate genuine science from pseudo science, and has lost its plausibility as a description of scientific methodology as the demarcation project has come under challenge from naturalist and historicist approaches in philosophy of science. While criticism does play an important role in some current approaches in social epistemology, Popper’s own views are more closely approximated by evolutionary epistemology, especially that version that treats cognitive progress as the effect of selection against incorrect theories and hypotheses. In contrast to Mill’s views, for Popper the function of criticism is to eliminate false theories rather than to improve them.

The work of Mill, Peirce, and Popper is a resource for philosophers presently exploring the social dimensions of scientific knowledge. However, the current debates are framed in the context of developments in both philosophy of science and in history and social studies of science following the collapse of the logical empiricist consensus. The philosophers of the Vienna Circle are conventionally associated with an uncritical form of positivism and with the logical empiricism that replaced American pragmatism in the 1940s and 1950s. According to some recent scholars, however, they saw natural science as a potent force for progressive social change. (Cartwright, Cat, and Chang 1996; Giere and Richardson, eds., 1996; Uebel 2005) With its grounding in observation and public forms of verification, science for them constituted a superior alternative to what they saw as metaphysical obscurantism, an obscurantism that led not only to bad thinking but to bad politics. While one development of this point of view leads to scientism, the view that any meaningful question can be answered by the methods of science; another development leads to inquiry into what social conditions promote the growth of scientific knowledge. Logical empiricism, the version of Vienna Circle philosophy that developed in the United States, focused on logical, internal aspects of scientific knowledge and discouraged philosophical inquiry into the social dimensions of science. These came into prominence again after the publication of Thomas Kuhn’s Structure of Scientific Revolutions (Kuhn 1962). A new generation of sociologists of science, among them Barry Barnes, Steven Shapin, and Harry Collins, took Kuhn’s emphasis on the role of non-evidential community factors in scientific change even further than he had and argued that scientific judgment was determined by social factors, such as professional interests and political ideologies (Barnes 1977, Shapin 1982, Collins 1983). This family of positions provoked a counter-response among philosophers. These responses are marked by an effort to acknowledge some social dimensions to scientific knowledge while at the same time maintaining its epistemological legitimacy, which they take to be undermined by the new sociology. At the same time, features of the organization of scientific inquiry compel philosophers to consider their implications for the normative analysis of scientific practices.

The second half of the twentieth century saw the emergence of what has come to be known as Big Science: the organization of large numbers of scientists bringing different bodies of expertise to a common research project. The original model was the Manhattan Project, undertaken during the Second World War to develop an atomic weapon in the United States. Theoretical and experimental physicists located at various sites across the country, though principally at Los Alamos, New Mexico, worked on sub-problems of the project under the overall direction of J. Robert Oppenheimer. While academic and military research have since been to some degree separated, much experimental research in physics, especially high energy particle physics, continues to be pursued by large teams of researchers. Research in other areas of science as well, for example the work comprehended under the umbrella of the Human Genome Project, has taken on some of the properties of Big Science, requiring multiple forms of expertise. In addition to the emergence of Big Science, the transition from small scale university or even amateur science to institutionalized research with major economic impacts supported by national funding bodies and connected across international borders has seemed to call for new ethical and epistemological thinking. Moreover, the consequent dependence of research on central funding bodies and increasingly, private foundations or commercial entities, prompts questions about the degree of independence of contemporary scientific knowledge from its social and economic context.

John Hardwig (1985) articulated one philosophical dilemma posed by large teams of researchers. Each member or subgroup participating in such a project is required because each has a crucial bit of expertise not possessed by any other member or subgroup. This may be knowledge of a part of the instrumentation, the ability to perform a certain kind of calculation, the ability to make a certain kind of measurement or observation. The other members are not in a position to evaluate the results of other members’ work, and hence, all must take one anothers’ results on trust. The consequence is an experimental result, (for example, the measurement of a property such as the decay rate or spin of a given particle) the evidence for which is not fully understood by any single participant in the experiment. This leads Hardwig to ask two questions, one about the evidential status of testimony, and one about the nature of the knowing subject in these cases. With respect to the latter, Hardwig says that either the group as a whole, but no single member, knows or it is possible to know vicariously. Neither of these is palatable to him. Talking about the group or the community knowing smacks of superorganisms and transcendent entities and Hardwig shrinks from that solution. Vicarious knowledge, knowing without oneself possessing the evidence for the truth of what one knows, requires, according to Hardwig, too much of a departure from our ordinary concepts of knowledge.

The first question is, as Hardwig notes, part of a more general discussion about the epistemic value of testimony. Much of what passes for common knowledge is acquired from others. We depend on experts to tell us what is wrong or right with our appliances, our cars, our bodies. Indeed, much of what we later come to know depends on what we previously learned as children from our parents and teachers. We acquire knowledge of the world through the institutions of education, journalism, and scientific inquiry. Philosophers disagree about the status of beliefs acquired in this way. Here is the question: If A knows that p on the basis of evidence e , B has reason to think A trustworthy and B believes p on the basis of A ’s testimony that p , does B also know that p ? Some philosophers, as Locke and Hume seem to have, argue that only what one has observed oneself could count as a good reason for belief, and that the testimony of another is, therefore, never on its own sufficient warrant for belief. Thus, B does not know simply on the basis of A ’s testimony but must have additional evidence about A ’s reliability. While this result is consistent with traditional philosophical empiricism and rationalism, which emphasized the individual’s sense experience or rational apprehension as foundations of knowledge, it does have the consequence that we do not know most of what we think we know.

A number of philosophers have recently offered alternative analyses focusing on one or another element in the problem. Some argue that testimony by a qualified expert is itself evidential, (Schmitt 1988), others that the expert’s evidence constitutes good reason for, but is not itself evidential for the recipient of testimony (Hardwig 1985, 1988), others that what is transmitted in testimony is knowledge and not just propositional content and thus the question of the kind of reason a recipient of testimony has is not to the point (Welbourne 1981).

However this dispute is resolved, questions of trust and authority arise in a particularly pointed way in the sciences, and Hardwig’s dilemma for the physics experiment is also a specific version of a more general phenomenon. A popular conception of science, fed partly by Popper’s falsificationism, is that it is epistemically reliable because the results of experiments and observational studies are checked by independent repetition. In practice, however, only some results are so checked and many are simply accepted on trust. Not only must positive results be accepted on trust, but claims of failure to replicate as well as other critiques must be also. Thus, just as in the non-scientific world information is accepted on trust, so in science, knowledge grows by depending on the testimony of others. What are the implications of accepting this fact for our conceptions of the reliability of scientific knowledge?

The philosopher of biology, David Hull, argued in his (1988) that because the overall structure of reward and punishment in the sciences is a powerful incentive not to cheat, further epistemological analysis of the sciences is unnecessary. What scientists have to lose is their reputation, which is crucial to their access to grants, collaborations, prizes, etc. So the structure itself guarantees the veridicality of research reports. But some celebrated recent episodes, such as the purported production of “cold fusion” were characterized by the failure of replication attempts to produce the same phenomenon. And, while the advocates of cold fusion were convinced that their experiments had produced the phenomenon, there have also been cases of outright fraud. Thus, even if the structure of reward and punishment is an incentive not to cheat, it does not guarantee the veridicality of every research report.

On Hull’s view, the scientific community seeks true theories or adequate models. Credit, or recognition, accrues to individuals to the extent they are perceived as having contributed to that community goal. That is, individual scientists seek reputation and recognition, to have their work cited as important and as necessary to further scientific progress. Cheating, by misreporting experimental results or other misconduct, will be punished by loss of reputation. But this depends on strong guarantees of detection. Absent such guarantees, there is as strong an incentive to cheat, to try to obtain credit without necessarily having done the work, as not to cheat.

Both Alvin Goldman (Goldman, 1995, 1999) and Philip Kitcher (1993) have treated the potential for premature, or otherwise (improperly) interested reporting of results to corrupt the sciences as a question to be answered by means of decision theoretic models. The decision theoretic approach to problems of trust and authority treats both credit and truth as utilities. The challenge then is to devise formulas that show that actions designed to maximize credit also maximize truth. Kitcher, in particular, develops formulas intended to show that even in situations peopled by non-epistemically motivated individuals (that is, individuals motivated more by a desire for credit than by a desire for truth), the reward structure of the community can be organized in such a way as to maximize truth and foster scientific progress. One consequence of this approach is to treat scientific fraud and value or interest infused science as the same problem. One advantage is that it incorporates the motivation to cheat into the solution to the problem of cheating. But one may wonder how effective this solution really is. Increasingly, we learn of problematic behavior in science based industries, such as the pharmaceutical industry. Results are withheld or distorted, authorship is manipulated. Hot areas, such as stem cell research, cloning, or gene modification, have been subjected to fraudulent research. Thus, even if the structure of reward and punishment is an in principle incentive not to cheat, it does not guarantee the reliability of every research report. The decision theoretic model needs to include at least one more parameter, namely the anticipated likelihood of detection within a relevant timeframe.

Community issues have also been addressed under the banners of research ethics and of peer review. One might think that the only ethical requirements on scientists are to protect their research subjects from harm and, as professional scientists, to seek truth above any other goals. This presupposes that seeking truth is a sufficient guide to scientific decision-making. Heather Douglas, in her critical study of the ideal of value-freedom (Douglas 2009), rejects this notion. Douglas draws on her earlier study of inductive risk (Douglas 2000) to press the point that countless methodological decisions required in the course of carrying out a single piece of research are underdetermined by the factual elements of the situation and must be guided by an assessment of the consequences of being wrong. Science is not value-free, but can be protected from the deleterious effects of values if scientists take steps to mitigate the influence of inappropriate values. One step is to distinguish between direct and indirect roles of values; another is the articulation of guidelines for individual scientists. Values play a direct role when they provide direct motivation to accept or reject a theory; they play an indirect role when they play a role in evaluating the consequences of accepting or rejecting a claim, thus influencing what will count as sufficient evidence to accept or reject. The responsibility of scientists is to make sure that values do not play a direct role in their work and to be transparent about the indirect roles of values. A number of writers have taken issue with the tenability of Douglas’s distinction between direct and indirect. Steel and Whyte (2012) examine testing guidelines developed by pharmaceutical companies to point out that the very same decision may be motivated by values playing a direct role or playing an indirect role. If the point is to prohibit practices such as withholding negative results, then it shouldn’t matter whether the practice is motivated by values functioning directly or indirectly. Elliott (2011) questions whether only harmful consequences should be considered. If science is to be useful to policy makers, then questions of relative social benefit should also be permitted to play a role. Finally the cognitive activities demanded by Douglas’s ethical prescriptions for scientists seem beyond the capacities of individual scientists. This point will be pursued below.

Torsten Wilholt (2013) argues that the research situation is more complicated than the epistemic vs. nonepistemic tradeoff implied by the decision theoretic approach. In part because of the difficulties in achieving the degree of knowledge required to realize Douglas’s ethical prescriptions, he argues that the reliance called for in science extends beyond the veridicality of reported results to the values guiding the investigators relied upon. Most research involves both results expressed statistically (which requires choice of significance threshold and balancing chances of Type I vs. Type II error) and multiple steps each requiring methodological decisions. These decisions, Wilholt argues, represent trade-offs among the reliability of positive results, the reliability of negative results, and the power of the investigation. In making these tradeoffs, the investigator is per force guided by an evaluation of the consequences of the various possible outcomes of the study. Wilholt extends the arguments about inductive risk offered originally by Richard Rudner and elaborated by Heather Douglas to propose that, in relying on another’s results I am relying not only on their competence and truthfulness, but on their making methodological decisions informed by the same valuations of outcomes as I have. This attitude is more than epistemic reliance, but a deeper attitude: one of trust that we are guided by the same values in a shared enterprise. For Wilholt, then, scientific inquiry engages ethical norms as well as epistemic norms. Formal or mechanical solutions such as those suggested by the application of decision theoretic models are not sufficient, if the community must be held together by shared ethical values.

Peer review and replication are methods the scientific community, indeed the research world in general, employs to assure consumers of scientific research that the work is credible. Peer review both of research proposals and of research reports submitted for publication screens for quality, which includes methodological competence and appropriateness as well as for originality and significance, while replication is intended to probe the robustness of results when reported experiments are carried out in different laboratories and with slight changes to experimental conditions. Scholars of peer review have noted various forms of bias entering into the peer review process. In a review of the literature, Lee, Sugimoto, Zhang, and Cronin (2013) report documented bias along gender, language, nationality, prestige, and content as well as such problems as lack of inter-reviewer reliability consistency, confirmation bias, and reviewer conservatism. Lee (2012) argues that a Kuhnian perspective on values in science interprets lack of inter-reviewer consistency as variation in interpretation, applicability, and weight assigned to shared values by different members of the scientific community. Lee and colleagues (2013) argue that journal editors must take much more action than is currently taken to require that researchers make their raw data and other relevant trial information available to enable peer reviewers to conduct their work adequately.

One issue that has yet to be addressed by philosophers is the gap between the ideal of replication resulting in confirmation, modification, or retraction and the reality. This ideal lies behind the assumptions of efficacy of structures of reward and sanction. Only if researchers believe that their research reports will be probed by efforts at replication will the threat of sanctions against faulty or fraudulent research be realistic. John Ioannidis and collaborators (Tatsioni, Bonitsis, and Ioannidis 2007; Young, N.S. Ioannidis, and Al-Ubaydli 2008) have shown how infrequently attempts to replicate are actually made and, even more strikingly, how contradicted results persist in the literature. This is an issue that goes beyond individuals and beyond large research collaborators to the scientific community in general. It underscores Wilholt’s contention that the scientific community must be held together by bonds of trust, but much more empirical and philosophical work is needed to address how to proceed when such trust is not justified. The demonstration of widespread lack of replicability on studies in psychology and in biomedical research has prompted debate about the causes and the seriousness of the alleged crisis (Loken and Gelman 2017; Ioannidis 2007; Redish, Kummerfeld, Morris, and Love 2018).

Winsberg, Huebner, and Kukla (2013) draw attention to a different kind of supra-empirical, ethical issue raised by the contemporary situation of multiple authorship. What they call “radically collaborative research” involves investigators with different forms of expertise, as in Hardwig’s example, and as is now common across many fields, collaborating to generate an experimental result. For Winsberg, Huebner, and Kukla, the question is not merely reliability, but accountability. Who can speak for the integrity of the research when it has been conducted by researchers with a variety not just of interests, but of methodological standards, most opaque one to another? Winsberg, Huebner, and Kukla argue that a model of the social collaboration is needed as much as a model of the data or of the instruments. They argue further that the laissez-faire Wisdom of Crowds model (according to which local differences in methodological standards will cancel each other out), while perhaps adequate if the question is one of reliability, is not adequate for addressing these issues of accountability. They do not themselves, however, offer an alternative model.

Work on the role of science in society encompasses both general models of the public authority of science and analysis of particular research programs that have a bearing on public life. In their early work, Steve Fuller and Joseph Rouse were both concerned with political dimensions of cognitive authority. Rouse, whose (1987) integrated analytic and continental philosophy of science and technology, sought to develop what might be called a critical pragmatism. This perspective facilitated an analysis of the transformative impact of science on human life and social relations. Rouse emphasized the increased power over individual lives that developments in science make possible. This can only be said to have increased with the development of information technology. Fuller (1988) partially accepted the empirical sociologists’ claim that traditional normative accounts of scientific knowledge fail to get a purchase on actual scientific practices, but took this as a challenge to relocate the normative concerns of philosophers. These should include the distribution and circulation of knowledge claims. The task of social epistemology of science, according to Fuller, should be regulation of the production of knowledge by regulating the rhetorical, technological, and administrative means of its communication. While there has not been much uptake of Fuller’s proposals as articulated, Lee’s work mentioned above begins to make detailed recommendations that take into account the current structures of funding and communication.

One key area of socially relevant interdisciplinary science is risk assessment, which involves both research on the effects of various substances or practices and the evaluation of those effects once identified. The idea is to gain an understanding of both positive effects and of negative effects and a method of evaluating these. This involves integrating the work of specialists in the kind of substance whose risks are under assessment (geneticists, chemists, physicists), biomedical specialists, epidemiologists, statisticians, and so on. In these cases, we are dealing not only with the problems of trust and authority among specialists from different disciplines, but also with the effects of introducing new technologies or new substances into the world. The risks studied are generally of harm to human health or to the environment. Interest in applying philosophical analysis to risk assessment originated in response to debates about the development and expansion of nuclear power-generating technologies. In addition, the application of cost-benefit analysis and attempts to understand decision-making under conditions of uncertainty became topics of interest as extensions of formal modeling techniques (Giere 1991). These discussions intersect with debates about the scope of rational decision theory and have expanded to include other technologies as well as applications of scientific research in agriculture and in the myriad forms of biological engineering. Essays on the relation between science and social values in risk research collected in the volume edited by Deborah Mayo and Rachelle Hollander (1991) attempt to steer a course between uncritical reliance on cost-benefit models and their absolute rejection. Coming from a slightly different angle, the precautionary principle represents an approach shifting the burden of proof in regulatory decisions from demonstration of harm to demonstration of safety of substances and practices. Carl Cranor (2004) explores versions of the principle and defends its use in certain decision contexts. Shrader-Frechette (2002) has advocated models of ethically weighted cost-benefit analysis and greater public involvement in risk assessment. In particular she (Shrader-Frechette 1994, 2002) has argued for including members of the public in deliberations about health effects of and reasonable exposure limits on environmental pollutants, especially radioactive materials. Philosophers of science have also worked to make visible the ways in which values play a role in the research assessing the effects of techno-scientifically produced substances and practices themselves, as distinct from the challenges of assigning values to identified risks and benefits.

Douglas (2000) is an influential study of toxicological research on effects of exposure to dioxins. Douglas set her analysis in the framework of inductive risk introduced by Richard Rudner (1953) and also explored by Carl Hempel (1965). The ampliative character of inductive inference means that the premises can be true (and even strongly supportive) and the conclusion false. Rudner argued that this feature of inductive inference means that scientists ought to take the consequences of being wrong into account when determining how strong the evidence for a hypothesis needs to be before accepting the hypothesis. [But see Jeffrey (1956) for a different view.] Douglas proposes that such considerations reach deeper into the scientific process than the acceptance of a conclusion based on the evidence to the construction of the evidence itself. Scientists must make decisions about levels of statistical significance, how to balance the chance of false positives against the chance of false negatives. They must determine protocols for deciding borderline cases in their tissue samples. They must select among possible dose-response models. Deciding in one way has one set of social consequences, and in another way another, opposing, set of consequences. Douglas claims that scientists ought to take these risks into account when making the relevant methodological decisions. Since, even in her examples, public health considerations point in one direction and economic considerations point in another, in the end it is not clear just what responsibility can reasonably be assigned to the individual scientist.

In addition to risk assessment, philosophers have begun thinking about a variety of research programs and methods that affect human wellbeing. Lacey (2005), for example, delineates the contrasting values informing industrial, conventional agriculture on the one hand and small-scale agroecology on the other. Cartwright (2012), elaborated in Cartwright and Hardie (2012), is primarily a critical analysis of the reliance on randomized control trials to support policy decisions in economic development, medicine, and education. These fail to take account of variations in contexts of application that will affect the outcome. Cartwright’s focus on a particular methodological approach is an extension of philosophers’ traditional engagement in areas of controversy in which philosophical analysis might make a difference. Philip Kitcher’s (1985), which took on sociobiology, and Elliott Sober and David Sloan Wilson’s (1998), an extensive argument for group level selection, are examples that focus on content and methodology of extensions of evolutionary theory.

Climate change research has provoked several quite different kinds of analysis. As a complex interdisciplinary field, its evidential structure leaves it vulnerable to challenge. Opponents of limiting the use of fossil fuels have exploited those vulnerabilities to sow public doubts about the reality and/or causes of climate change (Oreskes and Conway 2011). Parker 2006, Lloyd 2010, Parker 2010, Winsberg 2012 have, respectively, investigated strategies for reconciling apparent inconsistencies among climate models, the differences between model-based projections and strictly inductive projections, methods for assessing and communicating the uncertainties inherent in climate models. Philosophers have also considered how to interpret the (American) public’s susceptibility to the climate change deniers. Philip Kitcher (2012) interprets it as lack of information amid a plethora of misinformation and proposes methods for more effective communication of reputable science to the public. Anderson (2011), on the contrary, contends that members of the public are perfectly able to evaluate the reliability of contradictory assessments by following citation trails, etc., whether on the internet or in hard copies of journals. Her view is that the reluctance to accept the reality of climate change is a reluctance to abandon familiar ways of life, which is what averting climate-caused disaster requires all to do. Finally, there is an ethical and political question once the inevitability of climate change is accepted: how should the burdens of taking action be distributed? The industrialized West is responsible for most of the carbon pollution up to the end of the 20th century, but developing nations trying to industrialize have contributed an increasing share, and will continue to do so, in the 21st century. Who bears the burden? And if the effects will only be felt by generations in the future, why should present generations take actions whose harms will be felt now and whose benefits lie in the future and will not be experienced by those bearing the costs? Broome (2008) explores the intergenerational issues, while Raina (2015) explores the global dimensions.

Two additional areas of ongoing scientific controversy are the biological reality (or not) of race and the biology of gender differences. Developments in genetics, and documented racial differences in health, have thrown doubt on earlier anti-realist views of race, such as those articulated by Stephen J. Gould (1981) and Richard Lewontin (Lewontin, Rose, and Kamin 1984). Spencer (2012, 2014) argues for a sophisticated form of biological racial realism. Gannett (2003) argues that biological populations are not independent objects that can provide data relevant to racial realism, while Kaplan and Winther (2013) argue that no claims about race can be read from biological theory or data. The reality and basis of observed gender differences were the subject of much debate in the late 20th century(See Fausto-Sterling 1992). These issues have crystallized in the early 21st century in debates about the brain and cognition drawing the attention of philosophers of biology and cognitive scientists. Rebecca Jordan-Young (2010), Cordelia Fine (2010), and Bluhn, Jacobson and Maibom, eds. (2012) all explore, with an aim of debunking, claims of gendered brains.

3. Social, Cultural, and Feminist Studies of Science

Kuhn’s critique of logical empiricism included a strong naturalism. Scientific rationality was to be understood by studying actual episodes in the history of science, not by formal analyses developed from a priori concepts of knowledge and reason (Kuhn 1962, 1977). Sociologists and sociologically inclined historians of science took this as a mandate for the examination of the full spectrum of scientists’ practices without any prior prejudice as to which were epistemically legitimate and which not. That very distinction came under suspicion from the new social scholars, often labeled “social constructivists.” They urged that understanding the production of scientific knowledge required looking at all the factors causally relevant to the acceptance of a scientific idea, not just at those the researcher thinks should be relevant.

A wide range of approaches in social and cultural studies of science has come under the umbrella label of “social constructivism.” Both terms in the label are understood differently in different programs of research. While constructivists agree in holding that those factors treated as evidential, or as rationally justifying acceptance, should not be privileged at the expense of other causally relevant factors, they differ in their view of which factors are causal or worth examination. Macro-analytic approaches, such as those associated with the so-called Strong Programme in the Sociology of Scientific Knowledge, treat social relations as an external, independent factor and scientific judgment and content as a dependent outcome. Micro-analyses or laboratory studies, on the other hand, abjure the implied separation of social context and scientific practice and focus on the social relations within scientific research programs and communities and on those that bind research-productive and research-receptive communities together.

Researchers also differ in the degree to which they treat the social and the cognitive dimensions of inquiry as independent or interactive. The researchers associated with the macro-analytic Strong Programme in the Sociology of Scientific Knowledge (Barry Barnes, David Bloor, Harry Collins, Donald MacKenzie, Andrew Pickering, Steve Shapin) were particularly interested in the role of large scale social phenomena, whether widely held social/political ideologies or group professional interests, on the settlement of scientific controversies. Some landmark studies in this genre include Andrew Pickering’s (1984) study of competing professional interests in the interpretation of high energy particle physics experiments, and Steven Shapin and Simon Shaffer’s (1985) study of the controversy between Robert Boyle and Thomas Hobbes about the epistemological relevance of experiments with vacuum pumps.

The micro-sociological or laboratory studies approach features ethnographic study of particular research groups, tracing the myriad activities and interactions that eventuate in the production and acceptance of a scientific fact or datum. Karin Knorr Cetina’s (1981) reports her year-long study of a plant science laboratory at UC Berkeley. Bruno Latour and Steven Woolgar’s (1986) study of Roger Guillemin’s neuroendocrinology laboratory at the Salk Institute is another classic in this genre. These scholars argued in subsequent work (Knorr-Cetina 1983; Latour, 1987) that their form of study showed that philosophical analyses of rationality, of evidence, of truth and knowledge, were irrelevant to understanding scientific knowledge. Sharon Traweek’s (1988) comparative study of the cultures of Japanese and North American high energy physics communities pointed to the parallels between cosmology and social organization but abstained from making extravagant or provocative epistemological claims. The efforts of philosophers of science to articulate norms of scientific reasoning and judgment were, in the view of both macro- and micro-oriented scholars, misdirected, because actual scientists relied on quite different kinds of considerations in the practice of science.

Until recently, apart from a few anomalous figures like Caroline Herschel, Barbara McClintock, and Marie Curie, the sciences were a male preserve. Feminist scholars have asked what bearing the masculinity of the scientific profession has had on the content of science and on conceptions of scientific knowledge and practice. Drawing both on work by feminist scientists that exposed and critiqued gender biased science and on theories of gender, feminist historians and philosophers of science have offered a variety of models of scientific knowledge and reasoning intended to accommodate the criticism of accepted science and the concomitant proposal and advocacy of alternatives. Evelyn Keller (1985) proposed a psycho-dynamic model of knowledge and objectivity, arguing that a certain psychological profile, facilitated by typical patterns of masculine psychological development, associated knowledge and objectivity with domination. The association of knowledge and control continues to be a topic of concern for feminist thinkers as it is also for environmentally concerned critics of the sciences. In this connection, see especially Lacey’s (2005) study of the controversy concerning transgenic crops. Other feminists turned to Marxist models of social relations and developed versions of standpoint theory, which holds that the beliefs held by a group reflect the social interests of that group. As a consequence, the scientific theories accepted in a context marked by divisions of power such as gender will reflect the interests of those in power. Alternative theoretical perspectives can be expected from those systematically excluded from power. (Harding 1986; Rose 1983; Haraway 1978).

Still other feminists have argued that some standard philosophical approaches to the sciences can be used to express feminist concerns. Nelson (1990) adopts Quine’s holism and naturalism to analyze debates in recent biology. Elizabeth Potter (2001) adapts Mary Hesse’s network theory of scientific inference to analyse gendered aspects of 17th century physics. Helen Longino (1990) develops a contextual empiricism to analyze research in human evolution and in neuroendocrinology. In addition to the direct role played by gender bias, scholars have attended to the ways shared values in the context of reception can confer an a priori implausibility on certain ideas. Keller (1983) argued that this was the fate of Barbara McClintock’s unorthodox proposals of genetic transposition. Stephen Kellert (1993) made a similar suggestion regarding the then resistance to so-called chaos theory, that is the use of non-linear dynamics to model processes like climate change.

What the feminist and empirical sociological analyses have in common is the view that the social organization of the scientific community has a bearing on the knowledge produced by that community. There are deep differences, however, in their views as to what features of that social organization are deemed relevant and how they are expressed in the theories and models accepted by a given community. The gender relations focused on by feminists went unrecognized by sociologists pursuing macro- or microsociological research programs. The feminist scientists and scholars further differ from the scholars in empirical social and cultural studies of science in their call for alternative theories and approaches in the sciences. These calls imply that philosophical concerns with truth and justification are not only legitimate but useful tools in advancing feminist transformative goals for the sciences. As can be seen in their varying treatments of objectivity, however, philosophical concepts are often reworked in order to be made applicable to the content or episodes of interest (See Anderson 2004, Haraway 1988, Harding 1993, Keller 1985, Longino 1990, Nelson 1990, Wylie 2005)

In addition to differences in analysis of philosophical concepts like objectivity, rationality, or truth, feminist philosophers of science have also debated the proper role of contextual (sometimes called, “external” or “social”) values. Some feminists argue that, given that values do play a role in scientific inquiry, socially progressive values ought to shape not only decisions about what to investigate but also the processes of justification. Philosophers of science should incorporate exemplification of the right values in their accounts of confirmation or justification. Others are less certain about the identification of the values that should and those that should not inform the conduct of science. These philosophers are dubious that a consensus exists, or is even possible in a pluralistic society, on what constitute the values that ought to guide inquiry. In an exchange with Ronald Giere, Janet Kourany (2003a, 2003b) argues that not only science, but philosophy of science ought to be concerned with the promotion of socially progressive values. Giere (2003) replies that what counts as socially progressive will vary among philosophers, and that in a democracy, it is unlikely that a unanimous or near unanimous consensus regarding the values to inform philosophical analysis or scientific inquiry could be achieved either in the larger society or in the smaller social subset of philosophers of science.

4. Models of the Social Character of Knowledge

Since 1980, interest in developing philosophical accounts of scientific knowledge that incorporate the social dimensions of scientific practice has been on the increase. Some philosophers see attention to the social as a straightforward extension of already developed approaches in epistemology. Others, inclined toward some form of naturalism, have taken the work in empirical social studies of science discussed above seriously. They have, however, diverged quite considerably in their treatment of the social. Some understand the social as biasing or distorting, and hence see the social as opposed to or competing with the cognitive or epistemic. These philosophers see the sociologists’ disdain for normative philosophical concerns as part of a general debunking of science that demands a response and defense. Some philosophers see the social aspects of science as incidental to deep questions about knowledge, but informative about certain tendencies in scientific communities. Others treat the social as instead constitutive of rationality. These differences in conception of the role and nature of the social inform differences in the several approaches to modeling the sociality of inquiry and knowledge discussed below.

Contemporary philosophers pursue both formal and informal modeling approaches in addressing the social character of knowledge. Those pursuing formal models tend to bracket questions about rationality, objectivity, or justification and concentrate on mathematically investigating the effects of community structures on features of the pursuit of knowledge and its diffusion in a community. Those pursuing informal models are more interested in understanding the role of the community in enhancing or constituting desired features of inquiry such as rationality and objectivity and in thinking about the ways knowledge is realized

Communication and the division of cognitive labor. Among the first issues to be investigated using formal techniques was the division of cognitive labor. While big science projects such as discussed by Hardwig pose a problem of integrating disparate elements of the solution to a question, the division of cognitive labor concerns the appropriate or optimal distribution of efforts towards solving a given problem. If everyone follows the same research strategy to solve a problem or answer a question, then a solution lying outside that strategy will not be reached. If such a solution is better than any attainable via the shared strategy, the community fails to attain the better solution. But how can it be rational to adopt a research strategy other than the one deemed at the time most likely to succeed? Philip Kitcher in his (1993) was concerned to offer an alternative to the strong programme’s proposal that controversy and the persistence of alternative research programs were a function of the varying social or ideological commitments of researchers. However, he also acknowledged that if researchers followed only the strategy judged at the time most likely to lead to truth, they would not pursue unorthodox strategies that might lead to new discoveries. He therefore labeled the observed fact that researchers pursued different approaches to the same problem as the division of cognitive labor and proposed a decision model that attributed the pursuit of a nonorthodox (maverick) research strategy to a rational calculation about the chances of a positive payoff. This chance was calculated on the basis of the likelihood of the maverick strategy being successful (or more successful than the orthodox approach), the numbers of peers pursuing orthodox or other maverick strategies, and the anticipated reward of success. A community can allocate research resources in such a way as to maintain the balance of orthodox and maverick scientists most likely to facilitate progress. Thus, scientific progress can tolerate and indeed benefits from a certain amount of “impure” motivation. Michael Strevens (2003) argued instead that the pursuit of maverick research strategies was to be expected as a consequence of the priority rule. The priority rule refers to the practice of referring to a law or object with the name of the first individual to articulate or perceive and identify it. Think of Boyle’s Law, Halley’s comet, the Planck constant, Avogadro’s number, etc. There’s no such reward attached to pursuing a research strategy devised by another and “merely” adding to what that individual has already discovered. The rewards of research come from being first. And to be first requires pursuing a novel problem or strategy. The division of cognitive labor, understood as different researchers pursuing different research strategies, is a simple effect of the priority rule. Muldoon and Weisberg (2011) reject both Kitcher’s and Strevens’s accounts as presupposing unrealistically uniform and ideal agents. In reality, they observe, scientists have at best imperfect knowledge of the entire research situation, do not know the entirety of the research landscape, and when they do know, know different things. They do not have sufficient information to employ the decision methods Kitcher and Strevens attribute to them. Muldoon and Weisberg propose agent-based modeling as a means to represent the imperfect, non-overlapping, and partial knowledge of the agents deciding what research problems and strategies to pursue. Solomon’s advocacy of dissensus discussed below can be understood as rejecting the premises of the problem. From that point of view the aim of scientific organization ought to be to promote disagreement.

Kevin Zollman, following Bala and Goyal (1998), used network theory to model different possible communication structures. The aim of Zollman (2007, 2013) is to investigate what difference communication structures make to the chances of a scientific community settling on a correct (or incorrect) theory or hypothesis and to the speed by which such a consensus is reached. Networks consist of nodes and edges that connect them. The nodes can represent individuals or any group that has uniform beliefs. The nodes can have values of believe or not believe and consensus consists in all nodes in the network taking the same value. Zollman investigates three possible communication structures: the cycle, in which each node is connected only to nodes on either side of it in the cycle; the wheel, in which there is a central node to which all other nodes are exclusively connected; and the complete, in which each node is connected to every other node. Using the mathematics of network theory, Zollman proves the somewhat counterintuitive thesis that the network with limited communication, the cycle, has the highest probability of consensus on the correct hypothesis, while the network with the densest communication, the complete, has a non-negligible probability of consensus (from which departure is not possible) on the incorrect hypothesis. Zollman (2010) also uses this method to investigate the division of labor problem, although he comes at it from a slightly different point of view that do Kitcher or Strevens. Structures with sparse or limited communication are more likely to arrive at the correct hypothesis, but because they take longer to reach consensus, different research approaches may persist in such communities. Under the right circumstances, this will prevent foreclosure on the incorrect hypothesis. Zollman implicitly blames a dense communication structure for the premature abandonment of the bacterial hypothesis of peptic ulcers. Diversity is a good thing as long as the evidence is not decisive, and if the acid hypothesis, which held sway until a new staining method showed the presence of Helicobacter pylori , had been slower to diffuse into the community, the bacterial hypothesis might have been preserved long enough to be better supported.

While Zollman presents his results as an alternative method to the reward mechanisms discussed by Kitcher, Strevens, and Muldoon and Weisberg, they do not include a mechanism for establishing any of the network structures as the preferred communication system for a scientific community. Kitcher and the others were concerned with how agents might be motivated to pursue a theory or method whose chance of success was either unknown or thought unlikely. Funding bodies like governmental science foundations and private foundations provide or can provide the relevant reward structure. Prize-giving bodies, like the Nobel Foundation or the Kavli Foundation, as well as historical practice, entrench the priority rule. Both of these are community methods that can motivate the choice to pursue high risk, high reward research. It is not clear how communities would select communication structures, nor what kind of system would be able to enforce a structure. Rosenstock, O’Connor, and Bruner (2017) point out in addition that Zollman’s results are very sensitive to how parameters of the models are set. Adjust the number of nodes or the probabilities assigned to the alternative strategies/hypotheses and the Zollman effect disappears. The probability of consensus on the incorrect hypothesis in the densely connected communication structure reduces to close to zero with more nodes or greater disparity of assigned probabilities to alternatives.

O’Connor and other colleagues have used evolutionary game theory to model other community phenomena such as the persistence of minority disadvantage in scientific communities (Rubin & O’Connor 2018), scientific polarization (O’Connor & Weatherall 2017), diversity (O’Connor & Bruner 2017), conservatism in science (O’Connor forthcoming). While not necessarily claiming that these game theoretic models are fully descriptive of the phenomena they model, these theorists do claim that given certain initial conditions, certain undesirable social situations (like the disadvantage accruing to minority status) are to be expected rather than being understood as perversions of scientific practice. This would suggest that some ways of addressing those undesirable social outcomes may not be effective and that alternative measures ought to be sought in case of failure.

Sociality, rationality, and objectivity. Philosophers who treat the social as biasing or distorting tend to focus on the constructivists’ view that there are no universal principles of rationality or principles of evidence that can be used to identify in any context-independent way which factors are evidential and which not. Reconciliationists tend to argue that what is correct in the sociologists’ accounts can be accommodated in orthodox accounts of scientific knowledge. The key is sifting the correct from the exaggerated or misguided. Integrationists read the relevance of the sociologists’ accounts as supporting the development of new accounts of rationality or objectivity, rather than as grounds for rejecting the cogency of such normative ideals.

Philosophers concerned to defend the rationality of science against sociological misrepresentations include Larry Laudan (1984) James Brown (1989, 1994), Alvin Goldman (1987, 1995) and Susan Haack (1996). The details of these philosophers’ approaches differ, but they agree in holding that scientists are persuaded by what they regard as the best evidence or argument, the evidence most indicative of the truth by their lights, and in holding that arguments and evidence are the appropriate focus of attention for understanding the production of scientific knowledge. When evidential considerations have not trumped non-evidential considerations, we have an instance of bad science. They read the sociologists as arguing that a principled distinction between evidential and nonevidential considerations cannot be drawn and devote considerable effort to refuting those arguments. In their positive proposals for accommodating the social character of science, sociality is understood as a matter of the aggregation of individuals, not their interactions, and public knowledge as simply the additive outcome of many individuals making sound epistemic judgments. Individual rationality and individual knowledge are thus the proper focus of philosophers of science. Exhibiting principles of rationality applicable to individual reasoning is sufficient to demonstrate the rationality of science, at least in its ideal form.

Reconciliationists include Ronald Giere, Mary Hesse, and Philip Kitcher. Giere (1988) models scientific judgment using decision theory. This permits incorporating scientists’ interests as one of the parameters of the decision matrix. He also advocates a satisficing, rather than optimizing, approach to modeling the decision situation, thus enabling different interests interacting with the same empirical base to support different selections as long as they are consistent with that base. Mary Hesse (1980) employs a network model of scientific inference that resembles W.V.O. Quine’s web of belief in that its constituents are heterogeneous in character, but all subject to revision in relation to changes elsewhere in the network. She understands the social factors as coherence conditions operating in tandem with logical constraints to determine the relative plausibility of beliefs in the network.

The most elaborate reconciliationist position is that developed in Philip Kitcher’s (1993). In addition to modeling relations of authority and the division of cognitive labor as described above, he offers what he terms a compromise between extreme rationalists and sociological debunkers. The compromise model appeals to a principle of rationality, which Kitcher calls the External Standard. It is deemed external because it is proposed as holding independently of any particular historical, cultural or social context. Thus, not only is it external, but it is also universal. The principle applies to change of belief (or shift from one practice to another, in Kitcher’s broader locution), not to belief. It treats a shift (in practice or belief) as rational if and only “the process through which the shift was made has a success ratio at least as high as that of any other process used by human beings (ever) ...” (Kitcher 1993, 303). Kitcher’s compromise proposes that scientific ideas develop over time and benefit from the contributions of many differently motivated researchers. This is the concession to the sociologically oriented scholars. In the end, however, those theories that are rationally accepted are those that satisfy Kitcher’s External Standard. Kitcher thus joins Goldman, Haack, and Laudan in the view that it is possible to articulate a priori conditions of rationality or of epistemic warrant that operate independently of, or, perhaps one might say, orthogonally to, the social relations of science.

A third set of models is integrationist in character. Integrationists use the observations of sociologists of science to develop alternative accounts of scientific rationality and objectivity. Nelson (1990) focuses on a slightly different aspect of Quine’s holism than does Hesse. Nelson uses Quine’s arguments against the independently foundational status of observation statements as the basis for what she calls a feminist empiricism. According to Nelson, no principled distinction can be made between the theories, observations, or values of a community. What counts as evidence, in her view, is fixed by the entire complex of a community’s theories, value commitments, and observations. There is neither knowledge nor evidence apart from such a shared complex. The community is the primary knower on this view and individual knowledge is dependent on the knowledge and values of the community.

Miriam Solomon’s social empiricism is focused on scientific rationality (Solomon 2001). It, too, involves denying a universal principled distinction among the causes of belief. Solomon draws on contemporary cognitive science literature to argue that what are traditionally called biases are simply among the kinds of “decision vector” that influence belief. They are not necessarily undesirable elements from which science needs to be protected, and can be productive of insight and rational belief. Salience and availability (of data, of measurement technologies), also called cold biases, are decision vectors as much as social ideologies or other motivational factors, “hot biases.” The distinctive feature of Solomon’s social empiricism is her contrast between individual and community rationality. Her (2001) urges the pluralistic view that a community is rational when the theories it accepts are those that have unique empirical successes. Individuals can persist in beliefs that are (from a panoptic perspective) less well supported than others on this view, if the totality of available evidence (or empirical data) is not available to them, or when their favored theory accounts for phenomena not accounted for other theories, even when those may have a greater quantity of empirical successes. What matters to science, however, is that the aggregated judgments of a community be rational. A community is rational when the theories it accepts are those with all or with unique empirical successes. It is collectively irrational to jettison a theory with unique empirical successes. Thus, the community can be rational even when its members are, as judged by traditional epistemic standards, individually irrational. Indeed, individual irrationality can contribute to community rationality in that individuals committed to a theory that accounts for their data keep that data in the range of phenomena any theory accepted by the entire community must eventually explain. In addition to empirical success, Solomon proposes an additional normative criterion. In order to secure appropriate distribution of scientific effort, biases must be appropriately distributed in the community. Solomon proposes a scheme for ascertaining when a distribution is normatively appropriate. Thus, for Solomon, a scientific community is rational when biases are appropriately distributed and it accepts only a theory with all or theories with unique empirical successes as the normative epistemological condition. Rationality accrues only to a community, and not to the individuals constituting the community. As in Zollman’s network models, consensus just is all members of the community assigning the same value (T/F) to a hypothesis or theory.

Finally, in Longino’s critical contextual empiricism, the cognitive processes that eventuate in scientific knowledge are themselves social (Longino 1990, 2002). Longino’s starting point is a version of the underdetermination argument: the semantic gap between statements describing data and statements expressing hypotheses or theories to be confirmed or disconfirmed by that data. This gap, created by the difference in descriptive terms used in the description of data and in the expression of hypotheses, means that evidential relations cannot be formally specified and that data cannot support one theory or hypothesis to the exclusion of all alternatives. Instead, such relations are mediated by background assumptions. Eventually, in the chain of justification, one reaches assumptions for which no evidence is available. If these are the context in which evidential relations are constituted, questions arise concerning how the acceptance of such assumptions can be legitimated. According to Longino, the only check against the arbitrary dominance of subjective (metaphysical, political, aesthetic) preference in such cases is critical interaction among the members of the scientific community or among members of different communities. There is no higher authority or transcendent aperspectival position from which it is possible to adjudicate among foundational assumptions. Longino takes the underdetermination argument to express in logical terms the point made by the sociologically oriented researchers: the individuals participating in the production of scientific knowledge are historically, geographically, and socially situated and their observations and reasoning reflect their situations. This fact does not undermine the normative enterprise of philosophy, but requires its expansion to include within its scope the social interactions within and between scientific communities. What counts as knowledge is determined by such interactions.

Longino claims that scientific communities do institutionalize some critical practices (for example, peer review), but argues that such practices and institutions must satisfy conditions of effectiveness in order to qualify as objective. She argues, therefore, for the expansion of scientific norms such as accuracy and consistency to include norms that apply to communities. These are (1) the provision of venues in which critical interaction can take place, (2) the uptake of critical intervention as demonstrated in change of belief distribution in the community over time in a way that is sensitive to the critical discourse taking place within that community, (3) public accessibility of the standards that regulate discourse, and (4) tempered equality of intellectual authority. By this latter condition, perhaps the most controversial of her proposed norms, Longino means that any perspective has a prima facie capacity to contribute to the critical interactions of a community, though equal standing can be lost owing to failure to engage or to respond to criticism. In her 2002, Longino argues that the cognitive processes of science, such as observation and reasoning, are themselves social processes. Thus the interactions subject to community norms extend not only to discussion of assumptions in finished research, but to the constructive processes of research as well.

Solomon and Longino differ on where they locate normativity and on the role and effectiveness of deliberative processes in actual scientific inquiry. Solomon attends to the patterns of acceptance and to the distribution of decision vectors, regardless of the interactions among community members, while Longino attends to deliberative processes and interactions. They may also differ in their views of what constitutes scientific success.

One set of issues that has yet to give rise to extended philosophical reflection is the question how civilizational differences are expressed in scientific work (See Bala 2008). Here, too, there is a micro- and a macro- version. At the micro level, one might ask how the interactional culture of individual laboratories or theoretical subcommunities is or is not expressed in the outcome of their research. At the macro level one might be asking how large scale cultural features are reflected in the content and practice of science in a given cultural formation. For example, Joseph Needham argued that features of the culture of ancient China directed their technical and intellectual ingenuity into channels that foreclosed the development of anything like the science that developed in Western Europe in the 14th through the 17th centuries. Other cultures developed some aspects of what we now think of as a cosmopolitan or global scientific culture (for example, the mathematics and astronomy of 10th through 14th century Islamic and South Asian scholars) independently of the early modern physics developed in Western and Central Europe. The papers in Habib and Raina (2001) address aspects of these questions with respect to the history of science in India.

Unity, Plurality and the Aims of Inquiry. The variety of views on the degree of sociality assignable to the epistemological concepts of science lead to different views concerning the ultimate character of the outcome of inquiry. This difference can be summarized as the difference between monism and pluralism. Monism, as characterized in Kellert, Longino, and Waters (2006), holds that the goal of inquiry is and should be a unified, comprehensive, and complete account of phenomena (whether all phenomena, or the phenomena specific to a particular domain of inquiry). If this is so, then the norms of assessment should be informed by this goal and there should be one standard by which theories, models, and hypotheses in the sciences are assessed. Deviation from an accepted theoretical framework is problematic and requires explanation, such as the explanations offered for the division of cognitive labor. Monism, with its commitment to ultimate unity, requires ways to reconcile competing theories or to adjudicate controversy so as to eliminate competition in favor of the one true or best theory. Pluralism, on the other hand, holds that the observed plurality of approaches within a science is not necessarily a flaw but rather reflects the complexity of the phenomena under investigation in interaction with the limitations of human cognitive capacities and the variety of human cognitive as well as pragmatic interests in representations of those phenomena.

Among pluralists, a diversity of views is to be found. Suppes (1978) emphasized the mutual untranslatability of the descriptive terms developed in the course of scientific specialization. Such incommensurability will resist evaluation by a common measure. Cartwright’s (1999) invocation of a dappled world emphasizes the complexity and diversity of the natural (and social) world. Scientific theories and models are representations of varying degrees of abstraction that manage to apply at best partially to whatever phenomena they purport to represent. To the extent they are taken to represent actual process in the real world, they must be hedged by ceteris paribus clauses. Scientific laws and models attach to patches of the world, but not to a seamlessly law-governed whole. Mitchell’s (2002, 2009) integrative pluralism is a rejection of the goal of unification by either reduction to a single (fundamental) level of explanation or abstraction to a single theoretical representation, in favor of a more pragmatically inflected set of explanatory strategies. The success for any particular investigation is answerable to the goals of the investigation, but there may be multiple compatible accounts reflecting both the contingency and partiality of the laws/generalizations that can figure in explanations and the different goals one may bring to investigation of the same phenomenon. The explanations sought in any particular explanatory situation will draw on these multiple accounts as appropriate for the level of representation adequate to achieve its pragmatic ends. Mitchell’s defense of integrative pluralism rests on both the partiality of representation and the complexity of the phenomena to be explained.

Kellert, Longino, and Waters advance a pluralism that sees multiplicity not only among but within levels of analysis. Furthermore they see no reason to require that the multiple accounts be compatible. The multiplicity of noncongruent empirically adequate accounts helps us appreciate the complexity of a phenomenon without being in a position to generate a single account of that complexity. They do not hold that all phenomena will support ineliminable pluralism, but that there are some phenomena that will require mutually irreducible or incompatible models. Which these are is determined by examining the phenomena, the models, and the match between phenomena and models. Like Mitchell, Kellert, Longino, and Waters hold that pragmatic considerations (broadly understood) will govern the choice of model to be used in particular circumstances. Both forms of pluralism (compatibilist and noncompatibilist) abandon the notion that there is a set of natural kinds whose causal interactions are the basis for fundamental explanations of natural processes. The noncompatibilist is open to multiple classification schemes answerable to different pragmatic interests in classifying. To this extent the noncompatibilist pluralist embraces a view close to the promiscuous realism articulated by John Dupré (1993). The compatibilist, or integrative pluralist, on the other hand, must hold that there is a way that different classification schemes can be reconciled to support the envisioned integration of explanatory models.

Pluralism receives support from several additional approaches. Giere (2006) uses the phenomenon of color vision to support a position he calls perspectival realism. Like the colors of objects, scientific representations are the result of interactions between human cognitive faculties and the world. Other species have different visual equipment and perceive the world differently. Our human cognitive faculties, then, constitute perspectives. We could have been built differently and hence perceived the world differently. Perspectival realism leads to pluralism, because perspectives are partial. While van Fraassen’s (2008) does not take a position on pluralism vs. monism (and as an empiricist and antirealist van Fraassen would not have to), its emphasis on the partiality and perspective dependence of measurement provides a complementary point of entry to such diversity. Solomon (2006) urges a yet more welcoming attitude towards multiplicity. In her view, dissensus is a necessary component of well-functioning scientific communities and consensus can be epistemologically pernicious. In an extension of the arguments in Solomon (2001) she argues that different models and theoretical representations will be associated with particular insights or specific data that are likely to be lost if the aim is to integrate or otherwise combine the models to achieve a consensus understanding. The activity of integrating two or more models is different from the process of one model from a set of alternatives coming eventually to have all the empirical successes distributed among the other models. In her examination of consensus conferences called by the United States National Institutes of Health (Solomon 2011), Solomon finds that such conferences do not resolve existing dissent in the scientific community. Instead, they tend to take place after a consensus has emerged in the research community and are directed more to the communication of such consensus to outside communities (such as clinicians, insurers, health policy experts, and the public) than to the assessment of evidence that might warrant consensus.

Researchers committed to a monist or unified science will see plurality as a problem to be overcome, while researchers already committed to a deeply social view of science will see plurality as a resource of communities rather than a problem. The diversity and partiality that characterizes both a local and the global scientific community characterize the products of those communities as well as the producers. Universalism and unification require the elimination of epistemologically relevant diversity, while a pluralist stance promotes it and the deeply social conception of knowledge that follows.

Sociality and the structure of scientific knowledge. Attention to the social dimensions of scientific knowledge and the consequent potential for plurality has prompted philosophers to rethink the structure of what is known. Many philosophers (including Giere, Kitcher, and Longino) who advocate forms of pluralism invoke the metaphor of maps to explain how scientific representations can be both partial and adequate. Maps only represent those features of the territory mapped that are relevant for the purpose for which the map is drawn. Some maps may represent the physical area bounded by state boundaries, others may represent the population size, or the relative abundance/poverty of natural resources. Winther (forthcoming) explores the variety of kinds of maps used in science and philosophical use of the map metaphor. But the map metaphor is only one of several ways to rethink the structure of scientific knowledge.

Other philosophers draw more heavily on cognitive science. Giere (2002) takes a naturalist approach to modeling, not so much the distribution of cognitive labor, but the distribution of cognition. This approach takes a system or interactive community as the locus of cognition, rather than the individual agent. Nersessian (2006) extends distributed cognition to model-based reasoning in the sciences. Models are artifacts that focus the cognitive activity of multiple individuals in particular settings. Knowledge is distributed across the minds interacting about the artifacts in that setting. Paul Thagard draws on the increasingly interdisciplinary (and hence social) nature of cognitive science itself to argue that not only does cognitive science (or certain lines of analysis in cognitive science) support a conception of cognition as distributed among interacting agents, but that this conception can be turned back upon cognitive science itself. (Thagard 2012). Finally Alexander Bird (2010) reflects on the sense of knowledge required for attributions such as: “the biomedical community now knows that peptic ulcers are often caused by the bacterium Helicobacter pylori .” Or “There was an explosive growth in scientific knowledge in the twentieth century.” Bird faults other social epistemologists for still making such collective knowledge supervenient on the states of individuals. Instead, he argues, we should understand social knowing as a functional analogue of individual knowing. Both are dependent on the existence and proper functioning of the relevant structures: reasoning and perception for individuals; libraries and journals and other social structures, for collectivities. Scientific knowledge is an emergent effect of collective epistemic interactions, concretized in the texts that have been designated as vehicles for the preservation and communication of that knowledge

5. Social Direction of Science

Modern science has been regarded as both a model of democratic self-governance and an activity requiring and facilitating democratic practices in its supporting social context (Popper 1950, Bronowski 1956). In this perspective, science is seen as embedded in and dependent on its supporting social context, but insulated in its practices from the influence of that context. As the reach of science and science-based technologies has extended further and further into the economy and daily life of industrialized societies, new attention is paid to the governance of science. Regardless of one’s views about the social character of knowledge, there are further questions concerning what research to pursue, what social resources to devote to it, who should make such decisions, and how they should be made.

Philip Kitcher (2001) has opened these questions to philosophical scrutiny. While Kitcher largely endorses the epistemological views of his (1993), in the later work he argues that there is no absolute standard of the significance (practical or epistemic) of research projects, nor any standard of the good apart from subjective preferences. The only non-arbitrary way to defend judgments concerning research agendas in the absence of absolute standards is through democratic means of establishing collective preferences. Kitcher, thus, attempts to spell out procedures by which decisions concerning what research directions to pursue can be made in a democratic manner. The result, which he calls well-ordered science, is a system in which the decisions actually made track the decisions that would be a made by a suitably constituted representative body collectively deliberating with the assistance of relevant information (concerning, e.g., cost and feasibility) supplied by experts.

Kitcher’s “well-ordered science” has attracted attention from other philosophers, from scientists, and from scholars of public policy. Winning praise as a first step, it has also elicited a variety of criticisms and further questions. The criticisms of his proposal range from worries about the excessive idealism of the conception to worries that it will enshrine the preferences of a much smaller group than those who will be affected by research decisions. Kitcher’s proposal at best works for a system in which all or most scientific research is publicly funded. But the proportion of private, corporate, funding of science compared to that of public funding has been increasing, thus calling into question the effectiveness of a model that presupposes largely public control (Mirowski and Sent 2002, Krimsky 2003). Kitcher’s model, it should be noted, still effects a significant separation between the actual conduct of research and decisions concerning the direction of research and scholars who see a more intimate relation between social processes and values in the context and those in the conduct of research will be dissatisfied with it. Kitcher himself (Kitcher 2011) seems to relax the separation somewhat.

The counterfactual character of the proposal raises questions about the extent to which well-ordered science really is democratic. If the actual decisions do not need to be the result of democratic procedures but only to be the same as those that would result from such procedures, how do we know which decisions those are without actually going through the deliberative exercise? Even if the process is actually carried out, there are places, e.g. in choice of experts whose advice is sought, which permit individual preferences to subvert or bias the preferences of the whole (Roth 2003). Furthermore, given that the effects of scientific research are potentially global, while democratic decisions are at best national, national decisions will have an effect well beyond the population represented by the decision makers. Sheila Jasanoff has also commented that even in contemporary industrialized democracies there are quite different science governance regimes. There is not one model of democratic decision making, but many, and the differences translate into quite different policies (Jasanoff 2005).

In his (2011) Kitcher abandons the counterfactual approach as he brings the ideal of well-orderedness into contact with actual debates in and about contemporary science. His concern here is the variety of ways in which scientific authority has been eroded by what he terms “chimeric epistemologies.” It’s not enough to say that the scientific community has concluded that, say, the MMR vaccine is safe, or that the climate is changing in a way that requires a change in human activities. In a democratic society, there are many other voices claiming authority, whether on presumed evidential grounds or as part of campaigns to manipulate public opinion. Kitcher suggests mechanisms whereby small groups trusted by their communities might develop the understanding of complicated technical issues through tutoring by members of the relevant research communities and then carry this understanding back to the public. He also endorses James Fishkin’s (2009) experiments in deliberative polling as a means to bring members of the public committed to different sides of a technical issue together with the scientific exponents of the issue and in a series of exchanges that cover the evidence, the different kinds of import different lines of reasoning possess, and the other elements of a reasoned discussion, bring the group to a consensus on the correct view. The pluralist and pragmatically inclined philosophers discussed in the previous section might worry that there is not a single correct view towards which such an encounter ought to converge, but that a broader discussion that incorporates deliberation about aims and values might produce sufficient (temporary) convergence to ground action or policy.

6. Conclusion

Philosophical study of the social dimensions of scientific knowledge has been intensifying in the decades since 1970. Social controversies about the sciences and science based technologies as well as developments in philosophical naturalism and social epistemology combine to drive thinking in this area forward. Scholars in a number of cognate disciplines continue to investigate the myriad social relations within scientific communities and between them and their social, economic, and institutional contexts.

While this area first came to prominence in the so-called science wars of the 1980s, attending to social dimensions of science has brought a number of topics to philosophical attention. The phenomenon of Big Science has encouraged philosophers to consider the epistemological significance of such phenomena as trust and cognitive interdependence and the division of cognitive labor. The increased economic and social dependence on science-based technologies has prompted attention to questions of inductive risk and the role of values in assessing hypotheses with social consequences. The controversies over health risks of certain vaccines, over the measurement of environmental pollution, and over the causes of climate change have expanded philosophy of science from its more accustomed areas of logical and epistemological analysis to incorporate concerns about the communication and uptake of scientific knowledge and the ethical dimensions of superficially factual debates.

Partly in response to the work of scholars in the social studies of science, partly in response to the changing role of scientific inquiry through the 20th and into the 21st centuries, philosophers have sought ways to either accommodate the (tenable) results of the sociologists and cultural historians or to modify traditional epistemological concepts used in the analysis of scientific knowledge. These investigations in turn lead to new thinking about the structure and location of the content of knowledge. While debates within philosophy of science between and among adherents to one or another of the models of the sociality of knowledge will continue, an important future step will be a fuller encounter between individual-based social epistemology with its focus on testimony and disagreement as transactions among individuals and the more fully social epistemologies that take social relations or interaction as partially constitutive of empirical knowledge.

• Anderson, Elizabeth, 2004. “Uses of Value Judgments in Science” Hypatia , 19, 1–24.
• –––. 2011. “Democracy, Public Policy, and Lay Assessments of Scientific Testimony,” Episteme , 8(2): 144–164.
• Bala, Arun, 2008. The Dialogue of Civilizations in the Birth of Modern Science , New York, NY: Macmillan.
• Bala, Venkatesh, and Sanjeev Goyal, 1998. “Learning from Neighbors,” Review of Economic Studies , 65: 565–621.
• Barnes, Barry, 1977. Interests and the Growth of Knowledge , New York: Routledge.
• –––, and David Bloor, 1982. “Relativism, Rationalism, and the Sociology of Knowledge,” in Rationality and Relativism , Martin Hollis and Steven Lukes (eds.), Oxford: Basil Blackwell, pp. 21–47.
• Bird, Alexander, 2010, “Social Knowing: The Social Sense of ‘Scientific Knowledge’” Philosophical Perspectives , 24: 23–56.
• Bronowski, Jacob, 1956. Science and Human Values , New York: Harper and Bros.
• Brown, James, 1989. The Rational and the Social , London: Routledge.
• –––, 1994. Smoke and Mirrors: How Science Reflects Reality , New York: Routledge.
• Cartwright, Nancy, 1999, The Dappled World , Cambridge: Cambridge University Press.
• –––, 2012, “Will This Policy Work for You?” Philosophy of Science , 79(5): 973–989.
• –––, and Jeremy Hardie, 2012. Evidence-Based Policy: A Practical Guide to Doing It Better , New York: Oxford University Press.
• –––, and Jordi Cat, Lola Fleck, and Hasok Chang, 1996. Otto Neurath: Philosophy Between Science and Politics , New York: Cambridge University Press.
• Collins, Harry, 1983. “An Empirical Relativist Programme in the Sociology of Scientific Knowledge,” in Science Observed: Perspectives on the Social Study of Science , London: Sage, pp. 115–140.
• Cranor, Carl F., 2004. “Toward Understanding Aspects of the Precautionary Principle,” Journal of Medicine and Philosophy , 29(3): 259–79.
• Douglas, Heather, 2000. “Inductive Risk and Values in Science,” Philosophy of Science , 67(4): 559–579>
• –––, 2009. Science, Policy, and the Value-Free Ideal , Pittsburgh, PA: University of Pittsburgh Press.
• Dupré, John, 1993. The Disorder of Things , Cambridge, MA: Harvard University Press.
• Elliot, Kevin, 2011. “Direct and Indirect Roles for Values in Science,” Philosophy of Science , 78(2): 303–324
• Fausto-Sterling, Anne, 1992. Myths of Gender , New York, NY: Basic Books.
• Fine, Arthur, 2007. “Relativism, Pragmatism, and the Practice of Science,” in New Pragmatists , Cheryl Misak (ed.), Oxford: Oxford University Press, pp. 50–67.
• Fine, Cordelia, 2010, Delusions of Gender , New York, NY: W.W. Norton and Company.
• Fuller, Steve, 1988. Social Epistemology , Bloomington, IN: Indiana University Press.
• Gannett, Lisa, 2003, “Making Populations: Bounding Genes in Space and Time,” Philosophy of Science , 70(5): 989–1001.
• Giere, Ronald, 1988. Explaining Science: A Cognitive Approach , Chicago: University of Chicago Press.
• –––, 1991. “Knowledge, Values, and Technological Decisions: A Decision Theoretical Approach,” in Acceptable Evidence: Science and Values in Risk Management , Deborah Mayo and Rachelle Hollander (eds.), pp. 183–203, New York: Oxford University Press.
• –––, 2002. “Scientific Cognition as Distributed Cognition,” in Cognitive Bases of Science Peter Carruthers, Stephen Stitch, and Michael Siegal (eds.), Cambridge, UK: Cambridge University Press.
• –––, 2003. “A New Program for Philosophy of Science?” Philosophy of Science , 70(1): 15–21.
• –––, 2006. Scientific Perspectivism , Chicago, IL: University of Chicago Press.
• –––, and Alan Richardson (eds.), 1996. Origins of Logical Empiricism (Minnesota Studies in the Philosophy of Science, Vol. XVI), Minneapolis, MN: University of Minnesota Press.
• Goldman, Alvin, 1987. “The Foundations of Social Epistemics,” Synthese , 73(1): 109–144.
• –––, 1995. “Psychological, Social and Epistemic Factors in the Theory of Science,” in PSA 1994: Proceedings of the 1994 Biennial Meeting of the Philosophy of Science Association , Richard Burian, Mickey Forbes, and David Hull (eds.), East Lansing, MI: Philosophy of Science Association, pp. 277–286.
• –––, 1999. “Science”, Knowledge in a Social World (Chapter 8), New York: Oxford University Press, pp. 224–271, .
• Gould, Stephen J., 1981. The Mismeasure of Man , New York, NY: W.W. Norton and Company.
• Haack, Susan, 1996. “Science as Social: Yes and No,” in Feminism, Science, and the Philosophy of Science , Lynn Hankinson Nelson and Jack Nelson (eds.), Dordrecht: Kluwer Academic Publishers, pp. 79–94.
• Habib, S. Irfan and Dhruv Raina, 2001. Situating the History of Science: Dialogues with Joseph Needham , New Delhi, IN: Oxford University Press.
• Haraway, Donna, 1978. “Animal Sociology and a Natural Economy of the Body Politic (Part II),” Signs , 4(1): 37–60.
• –––, 1988. “Situated Knowledges,” Feminist Studies , 14(3): 575–600.
• Harding, Sandra. 1986. The Science Question in Feminism , Ithaca, NY: Cornell University Press.
• –––, 1993. “Rethinking Standpoint Epistemology,” in Feminist Epistemologies , Linda Alcoff and Elizabeth Potter (eds.), New York: Routledge, pp. 49–82.
• Hardwig, John, 1985. “Epistemic Dependence,” Journal of Philosophy , 82(7): 335–349.
• –––, 1988. “Evidence, Testimony, and the Problem of Individualism,” Social Epistemology , 2(4): 309–21.
• Hempel, Carl G., 1965. “Science and Human Values,” Scientific Explanation and Other Essays , New York: The Free Press, pp. 81–96.
• Hesse, Mary, 1980. Revolutions and Reconstructions in the Philosophy of Science , Bloomington, IN: Indiana University Press.
• Hull, David, 1988. Science As a Process: An Evolutionary Account of the Social and Conceptual Development of Science , Chicago: University of Chicago Press.
• Ioannidis, John, 2005. “Why Most Published Research Findings are False,” PLOS Medicine 2(8): 696–701.
• Jasanoff, Sheila, 2005. Designs on Nature: Science and Democracy in Europe and the United States , Princeton: Princeton University Press.
• Jeffrey, Richard C., 1956. “Valuation and Acceptance of Scientific Hypotheses,” Philosophy of Science , 23(3): 237–246.
• Jordan-Young, Rebecca, 2010. Brain Storm , Cambridge, MA: Harvard University Press.
• Kaplan, Jonathan, and Rasmus Winther, 2013. “Prisoners of Abstraction? The Theory and Measure of Genetic Variation, and the Very Concept of Race,” Biological Theory , 7(4): 401–12.
• Keller, Evelyn Fox, 1983. A Feeling for the Organism: The Life and Work of Barbara McClintock , San Francisco: W.H. Freeman.
• –––, 1985. Reflections on Gender and Science , New Haven: Yale University Press.
• Kellert, Stephen, 1993. In the Wake of Chaos , Chicago: University of Chicago Press.
• Kellert, Stephen, Helen Longino, and C. Kenneth Waters (eds.), 2006. Scientific Pluralism (Minnesota Studies in the Philosophy of Science, Vol. XIX), Minneapolis: University of Minnesota Press.
• Kitcher, Phillip, 1985. Vaulting Ambition , Cambridge, MA: MIT Press.
• –––, 1993. The Advancement of Science: Science Without Legend, Objectivity Without Illusions , Oxford: Oxford University Press.
• –––, 2001. Science, Truth, and Democracy , New York: Oxford University Press.
• –––, 2011. Science in a Democratic Society , Amherst, NY: Prometheus Press.
• Knorr-Cetina, Karin, 1981. The Manufacture of Knowledge , Oxford: Pergamon Press.
• –––, 1983. “The Ethnographic Study of Scientific Work: Toward a Constructivist Interpretation of Science,” in Science Observed , Knorr-Cetina and Michael Mulkay (eds.), London: Sage, pp. 115–177.
• Kourany, Janet, 2003a. “A Philosophy of Science for the Twenty-First Century,” Philosophy of Science , 70(1): 1–14.
• –––, 2003b, “Reply to Giere,” Philosophy of Science , 70(1): 22–26.
• –––, 2010. Philosophy of Science After Feminism , New York, NY: Oxford University Press.
• Krimsky, Sheldon, 2003. Science in the Private Interest , Lanham: Rowman and Littlefield.
• Kuhn, Thomas, 1962. The Structure of Scientific Revolutions , Chicago: University of Chicago Press.
• –––, 1977. The Essential Tension: Selected Studies in Scientific Tradition and Change , Chicago: University of Chicago Press.
• Lacey, Hugh, 2005. Values and Objectivity: The Controversy over Transgenic Crops , Lanham: Rowman and Littlefield.
• Latour, Bruno. 1987. Science in Action , Cambridge, MA: Harvard University Press.
• ––– and Steven Woolgar, 1986. Laboratory Life: The Construction of Scientific Facts , 2nd edition, Princeton: Princeton University Press.
• Laudan, Larry, 1984a. “The Pseudo-Science of Science?” in Scientific Rationality: The Sociological Turn , James Brown (ed.), Dordrecht: D. Reidel, pp. 41–74.
• Lee, Carole J., 2012. “A Kuhnian Critique of Psychometric Research on Peer Review,” Philosophy of Science , 79(5): 859–870.
• Lee, Carole J., Cassidy R. Sugimoto, Guo Zhang, and Blaise Cronin, 2013, “Bias in Peer Review,” Journal of the American Society for Information Science and Technology , 64(1): 2–17.
• Lewontin, Richard, Steven Rose, and Leon Kamin, 1984. Not in Our Genes , New York, NY: Pantheon.
• Loken, Eric, and Andrew Gelman, 2017. “Measurement Error and the Replication Crisis,” Science , 355(6325): 584–585.
• Longino, Helen E., 1990. Science as Social Knowledge: Values and Objectivity in Scientific Inquiry , Princeton: Princeton University Press.
• –––, 2002. The Fate of Knowledge , Princeton: Princeton University Press.
• Mayo, Deborah, and Rachelle Hollander (eds.), 1991. Acceptable Evidence: Science and Values in Risk Management , New York: Oxford University Press.
• Mill, John Stuart, 1859. On Liberty , London: John W. Parker and Son; reprinted 1974, 1982, Gertrude Himmelfarb (ed.), Harmondsworth: Penguin.
• Mirowski, Philip, and Esther-Mirjam Sent (eds.), 2002. Science Bought and Sold , Chicago: University of Chicago Press.
• Mitchell, Sandra, 2002. “Integrative Pluralism,” Biology and Philosophy , 17: 55–70.
• Muldoon, Ryan, and Michael Weisberg, 2011. “Robustness and Idealization in Models of Cognitive Labor,” Synthese , 183: 161–174.
• Needham, Joseph, 1954. Science and Civilization in China , Cambridge: Cambridge University Press.
• Nersessian, Nancy J., 2006. “Model-Based Reasoning in Distributed Cognitive Systems,” Philosophy of Science , 73(5): 699–709.
• Nelson, Lynn Hankinson, 1990. Who Knows: From Quine to Feminist Empiricism , Philadelphia: Temple University Press.
• O’Connor, Cailin, forthcoming. “The Natural Selection of Conservative Science,” Studies in the History and Philosophy of Science A , first online 27 September 2018. doi:10.1016/j.shpsa.2018.09.007
• –––, and Justin Bruner, 2019. “Dynamics and Diversity in Epistemic Communities,” Erkenntnis , 84: 1: 101–119.
• –––, and James Weatherall, 2017. “Scientific Polarization,” European Journal for Philosophy of Science , 8(3): 855–75.
• Oreskes, Naomi, and Eric Conway, 2011. Merchants of Doubt , New York, NY: Bloomsbury Press.
• Parker, Wendy, 2006. “Understanding Pluralism in Climate Modeling,” Foundations of Science , 11(4): 349–368.
• –––, 2010. “Predicting Weather and Climate,” Studies in History and Philosophy of Science (Part B), 41(3): 263–272.
• Peirce, Charles S., 1868. “Some Consequences of Four Incapacities,” Journal of Speculative Philosophy , 2: 140–157; reprinted in C.S. Peirce, Selected Writings , Philip Wiener (ed.), New York: Dover Publications, 1958, pp. 39–72.
• –––, 1878. “How to Make Our Ideas Clear,” Popular Science Monthly , 12: 286–302; reprinted in C.S. Peirce, Selected Writings , Philip Wiener (ed.), New York: Dover Publications, 1958, pp. 114–136.
• Pickering, Andrew, 1984. Constructing Quarks: A Sociological History of Particle Physics , Edinburgh: Edinburgh University Press.
• Popper, Karl, 1950. The Open Society and its Enemies , Princeton: Princeton University Press.
• –––, 1963. Conjectures and Refutations , London: Routledge and Kegan Paul.
• –––, 1972. Objective Knowledge , Oxford: Oxford University Press.
• Potter, Elizabeth, 2001. Gender and Boyle’s Law of Gases , Bloomington: Indiana University Press.
• Raina, Rajeswari (ed.), 2015. Science, Technology, and Development in India: Encountering Values , New Delhi: Orient Black Swan.
• Redish, A. David, Erich Kummerfeld, Rebecca Lea Morris, and Alan C. Love, 2018. “Opinion: Why Reproducibility Failures Are Essential to Scientific Inquiry,” PNAS , 115(20): 5042–46.
• Rose, Hilary, 1983. “Hand, Brain, and Heart,” Signs , 9(1): 73–96.
• Rosenstock, Sarita, Justin Bruner, and Cailin O’Connor, 2017. “In Epistemic Networks, Is Less Really More?” Philosophy of Science , 84: 324–52.
• Roth, Paul, 2003. “Kitcher’s Two Cultures,” Philosophy of the Social Sciences , 33(3): 386–405.
• Rouse, Joseph, 1987. Knowledge and Power: Toward a Political Philosophy of Science , Ithaca: Cornell University Press.
• Rubin, Hannah, and Cailin O’Connor, 2018. “Discrimination and Collaboration in Science,” Philosophy of Science , 85: 380–402.
• Rudner, Richard, 1953. “The Scientist Qua Scientist Makes Value Judgments,” Philosophy of Science , 20(1): 1–6.
• Schmitt, Frederick, 1988. “On the Road to Social Epistemic Interdependence,” Social Epistemology , 2: 297–307.
• Shapin, Steven, 1982. “The History of Science and Its Sociological Reconstruction,” History of Science , 20: 157–211.
• –––, and Simon Schaffer, 1985. Leviathan and the Air Pump , Princeton: Princeton University Press.
• Shrader-Frechette, Kristin, 1994. “Expert Judgment and Nuclear Risks: The Case for More Populist Policy,” Journal of Social Philosophy , 25: 45–70.
• –––, 2002. Environmental Justice: Creating Equality; Reclaiming Democracy , New York: Oxford University Press.
• Sober, Elliott, and David Sloan Wilson, 1998. Unto Others , Cambridge, MA: Harvard University Press
• Solomon. Miriam, 1992. “Scientific Rationality and Human Reasoning,” Philosophy of Science , 59(3): 439–54.
• –––, 1994a. “Social Empiricism,” Noûs , 28(3): 323–343.
• –––, 1994b. “A More Social Epistemology,” in Socializing Epistemology: The Social Dimensions of Knowledge , Frederick Schmitt (ed.), Lanham: Rowman and Littlefield Publishers, pp. 217–233.
• –––, 2001. Social Empiricism , Cambridge, MA: MIT Press.
• –––, 2006. “Groupthink versus The Wisdom of Crowds: The Social Epistemology of Deliberation and Dissent,” The Southern Journal of Philosophy , XLIV: 28–42.
• –––, 2011. “Group Judgment and the Medical Consensus Conference,” Handbook of the Philosophy of Science: Philosophy of Medicine , Fred Gifford (ed.), Amsterdam: Elsevier, pp. 239–254.
• Spencer, Quayshawn, 2012. “What Biological Racial Realism Should Mean” Philosophical Studies , 159: 181–204.
• –––, 2014. “Biological Theory and the Metaphysics of Race; A Reply to Kaplan and Winther,” Biological Theory , 8: 114–120.
• Steele, Daniel and Kyle Whyte, 2012. “Environmental Justice, Values, and Scientific Expertise” Kennedy Institute of Ethics Journal , 22(2): 163–182.
• Strevens, Michael, 2003. “The Role of the Priority Rule in Science,” Journal of Philosophy , 100: 55–79.
• Tatsioni, Athina, with Nikolaos Bonitsis, and John Ioannidis, 2007. “The Persistence of Contradicted Claims in the Literature,” Journal of the American Medical Association , 298(21): 2517–26.
• Thagard, Paul, 2012. The Cognitive Science of Science: Explanation, Discovery, and Conceptual Change , Cambridge, MA: MIT Press.
• Traweek, Sharon, 1988. Beamtimes and Lifetimes: The World of High Energy Physicists , Cambridge, MA: Harvard University Press.
• Uebel, Thomas, 2004. “Political Philosophy of Science in Logical Empiricism: The Left Vienna Circle,” Studies in History and Philosophy of Science , 36: 754–773.
• van Fraassen, Bas, 2008. Scientific Representation , New York: Oxford University Press.
• Welbourne, Michael, 1981. “The Community of Knowledge,” Philosophical Quarterly , 31(125): 302–314.
• Wilholt, Torsten, 2013. “Epistemic Trust in Science,” British Journal for the Philosophy of Science , 24(2): 233–253.
• Winsberg, Eric, 2012. “Values and Uncertainties in the Predictions of global Climate Models,” Kennedy Institute of Ethics Journal , 22(2): 111–137.
• –––, Bryce Huebner, and Rebecca Kukla, 2014. “Accountability and Values in Radically Collaborative Research,” Studies in History and Philosophy of Science (Part A), 46: 16–23.
• Winther, Rasmus Grønfeldt, forthcoming. When Maps Become the World , Chicago, IL: University of Chicago Press.
• Wylie, Alison, 2002. Thinking from Things , Los Angeles: University of California Press.
• Young, N.S., with John Ioannidis, O. Al-Ubaydli, 2008. “Why Current Publication Practices May Harm Science,” Public Library of Science Medicine , 5(10): e201, doi:10.1371/journal.pmed.0050201
• Zollman, Kevin, 2007. “The Communication Structure of Epistemic Communities,” Philosophy of Science , 74: 574–87.
• –––, 2010. “The Epistemic Benefit of Transient Diversity,” Erkenntnis , 72(1): 17035.
• –––, 2013. “Network Epistemology: Communication in Epistemic Communities,” Philosophy Compass , 8(1): 15–27
• Daston, Lorraine, and Peter Galison, 2010. Objectivity , Cambridge, MA: MIT Press.
• Elliott, Kevin, 2017. A Tapestry of Values: An Introduction to Values in Science , Oxford: Oxford University Press.
• Fleck, Ludwig, 1973. The Genesis and Development of a Scientific Fact , Chicago: University of Chicago Press.
• Hacking, Ian, 1999. The Social Construction of What? , Cambridge, MA. Harvard University Press.
• Latour, Bruno, 2004. Politics of Nature: How to Bring the Sciences into Democracy , Cambridge, MA: Harvard University Press.
• Levi, Isaac, 1980. The Enterprise of Knowledge , Cambridge, MA: MIT Press.
• Radder, Hans (ed.), 2010. The Commodification of Scientific Research , Pittsburgh, PA: University of Pittsburgh Press.
• McMullin, Ernan (ed.), 1992. Social Dimensions of Scientific Knowledge , South Bend: Notre Dame University Press.
• Sismondo, Sergio, 1996. Science Without Myth , Albany: State University of New York Press.

How to cite this entry . Preview the PDF version of this entry at the Friends of the SEP Society . Look up topics and thinkers related to this entry at the Internet Philosophy Ontology Project (InPhO). Enhanced bibliography for this entry at PhilPapers , with links to its database.

[Please contact the author with suggestions.]

-->contextualism-epistemic --> | epistemology: evolutionary | epistemology: social | ethics: environmental | feminist philosophy, interventions: epistemology and philosophy of science | feminist philosophy, topics: perspectives on science | Kuhn, Thomas | Mill, John Stuart | naturalism | Peirce, Charles Sanders | Popper, Karl | pragmatism | Quine, Willard Van Orman | rationality: historicist theories of | scientific objectivity | scientific revolutions | testimony: epistemological problems of

Copyright © 2019 by Helen Longino < hlongino @ stanford . edu >

• Accessibility

Support SEP

Mirror sites.

View this site from another server:

• Info about mirror sites

The Stanford Encyclopedia of Philosophy is copyright © 2023 by The Metaphysics Research Lab , Department of Philosophy, Stanford University

Library of Congress Catalog Data: ISSN 1095-5054

Science benefiting society: the role of the right to science

• Download event
• Add to google
• Add to Outlook
• Add to Office365

The expansion of scientific knowledge has led to breakthroughs on some key challenges and to important societal evolutions. Yet, science’s full potential will remain untapped unless there is a steadfast commitment to a human rights-based approach, with the right to science at the centre. Currently, this right to science is being undermined by two worrisome trends: the persisting inequalities of access to scientific knowledge and the applications of scientific progress; and the vicious circle of erosion of trust in science and infringements on scientific freedom and the safety of scientists.

How protecting the right to science can benefit society was the subject of the fifth UNESCO Chairs Seminar. The debate took place against the backdrop of commemorations of the 75th anniversary of the  Universal Declaration of Human Rights (UDHR), celebrated throughout 2023, in which the right to science is enshrined in Article 27. This right is also reinforced in another of the foundational documents of the international human rights, the  1966 International Covenant on Economic, Social and Cultural Rights (ICESCR, article 15).

Ângela Melo, Director of the UNESCO Division for Research, Ethics and Inclusion, Social and Human Sciences Sector, opened the debate by underscoring that the right to science still needs to earn an equal place along with other rights: a point further reinforced by subsequent panelists who lamented that political and civil rights are still prioritised over economic, social and cultural rights. Since the 1990s, she highlighted, UNESCO has been working to strengthen the foundations of this right. Among others, she highlighted the  2017 UNESCO Recommendation on Science and Scientific Researchers and the  2021 Recommendation on Open Science . Recently, the Organization has collaborated with researchers to develop  policy briefs on the right to science and a  massive open online course (MOOC) on science and human rights – the first educational content of its kind.

Waking the “sleeping beauty”

It is time to translate rights into obligations as regards this right, opined Monika Plozza, Research Associate and PhD Candidate at the University of Lucerne, Advisor on the Human Right to Science for the Geneva Science Diplomacy Anticipator (GESDA), Switzerland. She highlighted that article 15 of the ICESCR was flexibly worded to evolve (as with many human rights instruments) and that “benefits” and “applications” are broad terms. In her opinion, recent developments meant that the right to science was about to exit its “sleeping beauty state”, thanks to the  2020 General Comment of The Committee for Economic Social and Cultural Rights , which elaborated on how Article 15 can become effective. However, whilst this general comment should be seen as a catalyst, according to Plozza, state-led pathways under the UN auspices were still to be employed, including the Universal Periodic Review , as well as monitoring before UN human rights treaty bodies.

The second speaker, Helle Porsdam, Professor of History and Cultural Rights, UNESCO Chair in Cultural Rights, University of Copenhagen, Denmark, drew attention to the nature of the right to science as a cultural right. At a very minimum, Article 15 entails: the protection of researchers from undue influence on their independent judgement; that researchers can define the main aims of their research and methodologies; the freedom to question the ethical value of and the right to withdraw from projects if researchers’ consciences so dictate; the right to collaborate with other researchers; and the sharing of scientific data and analysis amongst researchers, with policy-makers and the public. She also acknowledged that there is a tension between the right of citizens to participate in science and the freedom of researchers – posing the society-wide question of where the line should be drawn and which should be the defining considerations.

Democratic participation: key to the right to science

Juan Pablo Bohoslavsky, Researcher at the Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina addressed the democratic participation in science. He drew attention to at least two areas in which scientific freedom is linked to participation. The first is how the benefits of scientific progress are distributed. Open parliamentary discussions with greater citizen involvement lead to stronger knowledge and transparent decision-making, which in turn raise the degree of trust in ensuing policies. The other area is how scientists participate in public discussions. Research on COVID-19 response committees found that economists, sociologists, anthropologists, lawyers and human rights scholars were largely absent from the composition of those bodies to the benefit of experts from biomedical and public health fields - resulting in a narrow public policy response. Furthermore, these committees were not independent from government and their discussions not made public.

The rich discussion with participants, moderated by Konstantinos Tararas, Programme Specialist for the Section for Inclusion, Rights and Intercultural Dialogue, highlighted examples of co-creation of knowledge with local communities through a rights-based approach, as well as surfacing issues such as artificial intelligence, scientific literacy, traditional knowledge, intellectual property and ethics. Speakers further touched on the need for transdisciplinary approaches for robust science policymaking, as well as the need for the academy to better communicate findings with the public, particularly in current times of populism and anti-expert sentiment. Challenges – such as the anti-vax movement and contrarians to climate change – call for scaling up efforts. The teaching of human rights, including the right to science whose existence is insufficiently known, underpins this work. Informing future scholars will help them defend their own academic freedom and be able to better disseminate science, as a human right. 

Related items

• Social and human sciences
• Gender equality
• Future of education
• Recommendation on Science and Scientific Researchers
• Country page: France
• See more add

More on this subject

Other recent events

Event 19th Committee for the Protection of Cultural Property in the Event of Armed Conflict 10 December 2024 - 11 December 2024

Event 19th Committee for the Protection of Cultural Property in the Event of Armed Conflict 10 December 2024 - 12 December 2024

Event UNESCO Global Alliance on the Science of Learning for Education – Annual Meeting 2 December 2024

On Being a Scientist: Responsible Conduct in Research, Second Edition (1995)

Chapter: the scientist in society.

Government agencies, including the National Science Foundation and Public Health Service, enforce laws and regulations that deal with misconduct in science. At the Public Health Service in Washington, D.C., complaints can be referred to the appropriate office through the Office of Research Integrity. At the National Science Foundation in Arlington, Virginia, complaints can be directed to the Office of the Inspector General. Within universities, research grant officials can provide guidance on whether federal rules may be involved in filing a complaint.

Many institutions have prepared written materials that offer guidance in situations involving professional ethics. Volume II of Responsible Science: Ensuring the Integrity of the Research Process (National Academy Press, Washington, D.C., 1993) reprints a number of these documents. Sigma Xi, a national society of research scientists headquartered in Research Triangle Park, North Carolina, the American Association for the Advancement of Science in Washington, D.C., and other scientific and engineering professional organizations also are prepared to advise scientists who encounter cases of possible misconduct.

The research system exerts many pressures on beginning and experienced researchers alike. Principal investigators need to raise funds and attract students. Faculty members must balance the time spent on research with the time spent teaching undergraduates. Industrial sponsorship of research introduces the possibility of conflicts of interest.

All parts of the research system have a responsibility to recognize and respond to these pressures. Institutions must review their own policies, foster awareness of research ethics, and ensure that researchers are aware of the policies that are in place. And researchers should constantly be aware of the extent to which ethically based decisions will influence their success as scientists.

THE SCIENTIST IN SOCIETY

This booklet has concentrated on the responsibilities of scientists for the advancement of science, but scientists have additional responsibilities to society. Even scientists conducting the most fundamental research need to be aware that their work can ultimately have a great impact on society. Construction of the atomic bomb and the development of recombinant DNA—events that grew out of basic research on the nucleus of the atom and investigations of certain bacterial enzymes, respectively—are two examples of how seemingly arcane areas of science can have tremendous societal consequences.

The occurrence and consequences of discoveries in basic research are virtually impossible to foresee. Nevertheless, the scientific community must recognize the potential for such discoveries and be prepared to address the questions that they raise. If scientists do find that their discoveries have implications for some important aspect of public affairs, they have a responsibility to call attention to the public issues involved. They might set up a suitable public forum involving experts with different perspectives on the issue at hand. They could then seek to develop a

consensus of informed judgment that can be disseminated to the public. A good example is the response of biologists to the development of recombinant DNA technologies—first calling for a temporary moratorium on the research and then helping to set up a regulatory mechanism to ensure its safety.

This document cannot describe the many responsibilities incumbent upon researchers because of science's function in modern society. The bibliography lists several volumes that examine the social roles of scientists in detail. The important point is that science and technology have become such integral parts of society that scientists can no longer isolate themselves from societal concerns. Nearly half of the bills that come before Congress have a significant scientific or technological component. Scientists are increasingly called upon to contribute to public policy and to the public understanding of science. They play an important role in educating nonscientists about the content and processes of science.

In fulfilling these responsibilities scientists must take the time to relate scientific knowledge to society in such a way that members of the public can make an informed decision about the relevance of research. Sometimes researchers reserve this right t o themselves, considering nonexperts unqualified to make such judgments. But science offers only one window on human experience. While upholding the honor of their profession, scientists must seek to avoid putting scientific knowledge on a pedestal above knowledge obtained through other means.

Many scientists enjoy working with the public. Others see this obligation as a distraction from the work they would like to be doing. But concern and involvement with the broader uses of scientific knowledge are essential if scientists are to retain the public's trust.

The research enterprise has itself been changing as science has become increasingly integrated into everyday life. But the core values on which the enterprise is based—honesty, skepticism, fairness, collegiality, openness—remain unchanged. These values have helped produce a research enterprise of unparalleled productivity and creativity. So long as they remain strong, science—and the society it serves—will prosper.

Since the first edition of On Being a Scientist was published in 1989, more than 200,000 copies have been distributed to graduate and undergraduate science students. Now this well-received booklet has been updated to incorporate the important developments in science ethics of the past 6 years and includes updated examples and material from the landmark volume Responsible Science (National Academy Press, 1992).

The revision reflects feedback from readers of the original version. In response to graduate students' requests, it offers several case studies in science ethics that pose provocative and realistic scenarios of ethical dilemmas and issues.

On Being a Scientist presents penetrating discussions of the social and historical context of science, the allocation of credit for discovery, the scientist's role in society, the issues revolving around publication, and many other aspects of scientific work. The booklet explores the inevitable conflicts that arise when the black and white areas of science meet the gray areas of human values and biases.

Written in a conversational style, this booklet will be of great interest to students entering scientific research, their instructors and mentors, and anyone interested in the role of scientific discovery in society.

READ FREE ONLINE

Welcome to OpenBook!

You're looking at OpenBook, NAP.edu's online reading room since 1999. Based on feedback from you, our users, we've made some improvements that make it easier than ever to read thousands of publications on our website.

Do you want to take a quick tour of the OpenBook's features?

Show this book's table of contents , where you can jump to any chapter by name.

...or use these buttons to go back to the previous chapter or skip to the next one.

Jump up to the previous page or down to the next one. Also, you can type in a page number and press Enter to go directly to that page in the book.

Switch between the Original Pages , where you can read the report as it appeared in print, and Text Pages for the web version, where you can highlight and search the text.

To search the entire text of this book, type in your search term here and press Enter .

Share a link to this book page on your preferred social network or via email.

View our suggested citation for this chapter.

Ready to take your reading offline? Click here to buy this book in print or download it as a free PDF, if available.

Get Email Updates

Do you enjoy reading reports from the Academies online for free ? Sign up for email notifications and we'll let you know about new publications in your areas of interest when they're released.

An official website of the United States government

The .gov means it's official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you're on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings
• Browse Titles

NCBI Bookshelf. A service of the National Library of Medicine, National Institutes of Health.

National Academy of Sciences (US), National Academy of Engineering (US), and Institute of Medicine (US) Committee on Science, Engineering, and Public Policy. On Being a Scientist: Responsible Conduct in Research. Washington (DC): National Academies Press (US); 1995.

On Being a Scientist: Responsible Conduct in Research.

• Hardcopy Version at National Academies Press

The Scientist in Society

Any research organization requires generous measures of the following:

• social space for personal initiative and creativity;
• time for ideas to grow to maturity;
• openness to debate and criticism;
• hospitality toward novelty; and
• respect for specialized expertise.

[These] may sound too soft and old-fashioned to stand up against the cruel modern realities of administrative accountability and economic stringency. On the contrary, I believe that they are fundamental requirements for the continued advancement of scientific knowledge—and, of course, for its eventual social benefits.

—John Ziman, Prometheus Bound: Science in a Dynamic Steady State, Cambridge University Press, New York, 1994, p. 276.

This booklet has concentrated on the responsibilities of scientists for the advancement of science, but scientists have additional responsibilities to society. Even scientists conducting the most fundamental research need to be aware that their work can ultimately have a great impact on society. Construction of the atomic bomb and the development of recombinant DNA—events that grew out of basic research on the nucleus of the atom and investigations of certain bacterial enzymes, respectively—are two examples of how seemingly arcane areas of science can have tremendous societal consequences.

The occurrence and consequences of discoveries in basic research are virtually impossible to foresee. Nevertheless, the scientific community must recognize the potential for such discoveries and be prepared to address the questions that they raise. If scientists do find that their discoveries have implications for some important aspect of public affairs, they have a responsibility to call attention to the public issues involved. They might set up a suitable public forum involving experts with different perspectives on the issue at hand. They could then seek to develop a consensus of informed judgment that can be disseminated to the public. A good example is the response of biologists to the development of recombinant DNA technologies—first calling for a temporary moratorium on the research and then helping to set up a regulatory mechanism to ensure its safety.

This document cannot describe the many responsibilities incumbent upon researchers because of science's function in modern society. The bibliography lists several volumes that examine the social roles of scientists in detail. The important point is that science and technology have become such integral parts of society that scientists can no longer isolate themselves from societal concerns. Nearly half of the bills that come before Congress have a significant scientific or technological component. Scientists are increasingly called upon to contribute to public policy and to the public understanding of science. They play an important role in educating nonscientists about the content and processes of science.

In fulfilling these responsibilities scientists must take the time to relate scientific knowledge to society in such a way that members of the public can make an informed decision about the relevance of research. Sometimes researchers reserve this right t o themselves, considering nonexperts unqualified to make such judgments. But science offers only one window on human experience. While upholding the honor of their profession, scientists must seek to avoid putting scientific knowledge on a pedestal above knowledge obtained through other means.

Many scientists enjoy working with the public. Others see this obligation as a distraction from the work they would like to be doing. But concern and involvement with the broader uses of scientific knowledge are essential if scientists are to retain the public's trust.

The research enterprise has itself been changing as science has become increasingly integrated into everyday life. But the core values on which the enterprise is based—honesty, skepticism, fairness, collegiality, openness—remain unchanged. These values have helped produce a research enterprise of unparalleled productivity and creativity. So long as they remain strong, science—and the society it serves—will prosper.

THE NATIONAL RESEARCH COUNCIL AND SERVICE TO SOCIETY One way in which scientists serve the needs of the broader society is by participating in the activities of the National Research Council, which is administered by the National Academy of Sciences, the National Academy of Engineering, and the Institute o f Medicine. The National Research Council brings together leaders from academe, industry, government, and other sectors to address critical national issues and provide advice to the U.S. government and its citizens. Over the course of a typical year, about 650 committees involving approximately 6,400 individuals study societally important issues that involve science and technology. All of these experts volunteer their time to serve on study committees, plan and participate in seminars, review documents , and otherwise assist in the work of the institution. Study committees work independently of government, sponsors, and special-interest groups. Continuous oversight and formal anonymous review of the results of the studies enhance objectivity and quality.

• Cite this Page National Academy of Sciences (US), National Academy of Engineering (US), and Institute of Medicine (US) Committee on Science, Engineering, and Public Policy. On Being a Scientist: Responsible Conduct in Research. Washington (DC): National Academies Press (US); 1995. The Scientist in Society.
• PDF version of this title (831K)

Recent Activity

• The Scientist in Society - On Being a Scientist The Scientist in Society - On Being a Scientist

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

Connect with NLM

National Library of Medicine 8600 Rockville Pike Bethesda, MD 20894

Web Policies FOIA HHS Vulnerability Disclosure

Help Accessibility Careers

Essay on the Role of Science and Democracy in Society

Cite this chapter.

• Xu Liangying  

Part of the book series: Boston Studies in the Philosophy of Science ((BSPS,volume 179))

362 Accesses

In his memorial speech delivered before Marx’s tomb in 1883, Engels gave an apt evaluation of the role of science in society by saying that “science is a revolutionary force that serves to push history forward,” “a revolutionary force in the highest sense.” The term, ‘revolutionary force,’ used here has two meanings. First, science moves ahead of production, guiding the development of production and thus becoming a direct productive force. As early as 1843–44, when Engels wrote his first article examining the capitalist economic system from a socialist perspective entitled ‘An Outline Critique of Political Economy,’ he advanced the thesis that natural science is a productive force. He regarded scientific invention and scientific thinking as key spiritual elements among labor factors, as the main factors of production. By 1857–58, Marx expounded on this viewpoint even more explicitly in ‘An Outline Critique of Political Economy (Draft).’ Human society is built on the basis of production, and furthermore, productive forces are the most active and revolutionary factor in production. Science, as the most active component of productive forces, naturally becomes a revolutionary force that pushes human society forward.

Journal of Dialectics of Nature (1) (1981) 3-6.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

• Available as PDF
• Read on any device
• Instant download
• Own it forever
• Available as EPUB and PDF
• Compact, lightweight edition
• Dispatched in 3 to 5 business days
• Free shipping worldwide - see info
• Durable hardcover edition

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Unable to display preview.  Download preview PDF.

See Aiyinsidan wenji [Collected Works of Albert Einstein], Shangwu yinshuguan [Commercial Press] (1979) Vol. 3 , pp. 189-180.

Google Scholar  

Liening xuanji [Selected Works of V. I. Lenin], Renmin chubanshe [People’s Publishing House] (1972) Vol. 2 , p. 628.

Download references

You can also search for this author in PubMed   Google Scholar

Editor information

Editors and affiliations.

Chinese Academy of Science, Beijing, China

Fan Dainian ( Research Professor ) ( Research Professor )

Boston University, USA

Robert S. Cohen

Rights and permissions

Reprints and permissions

Copyright information

© 1996 Springer Science+Business Media Dordrecht

About this chapter

Liangying, X. (1996). Essay on the Role of Science and Democracy in Society. In: Dainian, F., Cohen, R.S. (eds) Chinese Studies in the History and Philosophy of Science and Technology. Boston Studies in the Philosophy of Science, vol 179. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-8717-4_2

Download citation

DOI : https://doi.org/10.1007/978-94-015-8717-4_2

Publisher Name : Springer, Dordrecht

Print ISBN : 978-90-481-4546-1

Online ISBN : 978-94-015-8717-4

eBook Packages : Springer Book Archive

Share this chapter

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Publish with us

Policies and ethics

• Find a journal
• Track your research

• school Campus Bookshelves
• menu_book Bookshelves
• perm_media Learning Objects
• login Login
• how_to_reg Request Instructor Account
• hub Instructor Commons
• Download Page (PDF)
• Download Full Book (PDF)
• Periodic Table
• Physics Constants
• Scientific Calculator
• Reference & Cite
• Tools expand_more
• Readability

selected template will load here

This action is not available.

0.3: The Role of Science in Society

• Last updated
• Save as PDF
• Page ID 94557

The Role of Science in Society

• Please read and watch the following Mandatory Resources
• Reading the material for understanding, and taking notes during videos, will take approximately 1.5 hours.
• If on a mobile device, use the Contents menu at the top of the page OR the links at the bottom of the page.

Learning Objectives

• Appreciate the importance of science in culture and society;
• Compare and contrast basic and applied science;
• Explain how scientists disseminate their work;
• Describe characteristics of Indigenous ways of knowing about the natural world;
• Identify how the process of science and Indigenous ways of knowing may complement one another.

Science and Culture

From the United Nations Educational, Scientific and Cultural Organization (UNESCO):

"Science is the greatest collective endeavor. It contributes to ensuring a longer and healthier life, monitors our health, provides medicine to cure our diseases, alleviates aches and pains, helps us to provide water for our basic needs – including our food, provides energy and makes life more fun, including sports, music, entertainment and the latest communication technology. Last but not least, it nourishes our spirit.

Science generates solutions for everyday life and helps us to answer the great mysteries of the universe. In other words, science is one of the most important channels of knowledge. It has a specific role, as well as a variety of functions for the benefit of our society: creating new knowledge, improving education, and increasing the quality of our lives.

Science must respond to societal needs and global challenges. Public understanding and engagement with science, and citizen participation including through the popularization of science are essential to equip citizens to make informed personal and professional choices. Governments need to make decisions based on quality scientific information on issues such as health and agriculture, and parliaments need to legislate on societal issues which necessitate the latest scientific knowledge. National governments need to understand the science behind major global challenges such as climate change, ocean health, biodiversity loss and freshwater security.

To face sustainable development challenges, governments and citizens alike must understand the language of science and must become scientifically literate. On the other hand, scientists must understand the problems policy-makers face and endeavor to make the results of their research relevant and comprehensible to society.

Challenges today cut across the traditional boundaries of disciplines and stretch across the lifecycle of innovation -- from research to knowledge development and its application. Science, technology and innovation must drive our pursuit of more equitable and sustainable development" (2021).

Two Types of Science: Basic Science and Applied Science

The scientific community has been debating for the last few decades about the value of different types of science. Is it valuable to pursue science for the sake of simply gaining knowledge, or does scientific knowledge only have worth if we can apply it to solving a specific problem or to bettering our lives? This question focuses on the differences between two types of science: basic science and applied science .

Basic science or “pure” science seeks to expand knowledge regardless of the short-term application of that knowledge. It is not focused on developing a product or a service of immediate public or commercial value. The immediate goal of basic science is knowledge for knowledge’s sake, though this does not mean that, in the end, it may not result in a practical application.

In contrast, applied science or “technology,” aims to use science to solve real-world problems, making it possible, for example, to improve a crop yield, find a cure for a particular disease, or save animals threatened by a natural disaster (Figure \(\PageIndex{1}\)). In applied science, the problem is usually defined for the researcher.

Some individuals may perceive applied science as “useful” and basic science as “useless.” A question these people might pose to a scientist advocating knowledge acquisition would be, “What for?” A careful look at the history of science, however, reveals that basic knowledge has resulted in many remarkable applications of great value. Many scientists think that a basic understanding of science is necessary before an application is developed; therefore, applied science relies on the results generated through basic science. Other scientists think that it is time to move on from basic science and instead to find solutions to actual problems. Both approaches are valid. It is true that there are problems that demand immediate attention; however, few solutions would be found without the help of the wide knowledge foundation generated through basic science.

One example of how basic and applied science can work together to solve practical problems occurred after the discovery of DNA structure led to an understanding of the molecular mechanisms governing DNA replication. Strands of DNA, unique in every human, are found in our cells, where they provide the instructions necessary for life. During DNA replication, DNA makes new copies of itself, shortly before a cell divides. Understanding the mechanisms of DNA replication enabled scientists to develop laboratory techniques that are now used to identify genetic diseases, pinpoint individuals who were at a crime scene, and determine paternity. Without basic science, it is unlikely that applied science would exist.

Another example of the link between basic and applied research is the Human Genome Project, a study in which each human chromosome was analyzed and mapped to determine the precise sequence of DNA subunits and the exact location of each gene. (The gene is the basic unit of heredity; an individual’s complete collection of genes is his or her genome). Other less complex organisms have also been studied as part of this project in order to gain a better understanding of human chromosomes. The Human Genome Project relied on basic research carried out with simple organisms and, later, with the human genome (Figure \(\PageIndex{2}\)). An important end goal eventually became using the data for applied research, seeking cures and early diagnoses for genetically related diseases.

While research efforts in both basic science and applied science are usually carefully planned, it is important to note that some discoveries are made by serendipity , that is, by means of a fortunate accident or a lucky surprise. Penicillin was discovered when biologist Alexander Fleming accidentally left a petri dish of Staphylococcus bacteria open. An unwanted mold grew on the dish, killing the bacteria. The mold turned out to be Penicillium , and a new antibiotic was discovered. Even in the highly organized world of science, luck—when combined with an observant, curious mind—can lead to unexpected breakthroughs.

Watch this video to see how science is playing a role in understanding Peary caribou in Canada. Question after watching: What type of research is this? Basic or applied?

Reporting Scientific Work

Whether scientific research is basic science or applied science, scientists must share their findings in order for other researchers to expand and build upon their discoveries. Collaboration with other scientists—when planning, conducting, and analyzing results—are all important for scientific research. For this reason, important aspects of a scientist’s work are communicating with peers and disseminating results to peers. Scientists can share results by presenting them at a scientific meeting or conference, but this approach can reach only the select few who are present. Instead, most scientists present their results in peer-reviewed manuscripts that are published in scientific journals. Peer-reviewed manuscripts are scientific papers that are reviewed by a scientist’s colleagues, or peers. These colleagues are qualified individuals, often experts in the same research area, who judge whether or not the scientist’s work is suitable for publication. The process of peer review helps to ensure that the research described in a scientific paper or grant proposal is original, significant, logical, and thorough. Grant proposals, which are requests for research funding, are also subject to peer review. Scientists publish their work so other scientists can reproduce their experiments under similar or different conditions to expand on the findings. The experimental results must be consistent with the findings of other scientists.

A scientific paper is very different from creative writing. Although creativity is required to design experiments, there are fixed guidelines when it comes to presenting scientific results. First, scientific writing should be concise and accurate. A scientific paper needs to be succinct but detailed enough to allow peers to reproduce the experiments.

The scientific paper consists of several specific sections—introduction, materials and methods, results, and discussion. This structure is sometimes called the “ IMRaD ” format. There are usually acknowledgment and reference sections as well as an abstract (a concise summary) at the beginning of the paper. There might be additional sections depending on the type of paper and the journal where it will be published; for example, some review papers require an outline.

The introduction starts with brief, but broad, background information about what is known in the field. A good introduction also gives the rationale of the work; it justifies the work carried out and is where the hypothesis or research question driving the research will be presented. The introduction may also briefly mention the results of the paper. The introduction refers to the published scientific work of others and therefore requires citations following the style of the journal. Using the work or ideas of others without proper citation is considered plagiarism .

The materials and methods section includes a complete and accurate description of the substances used, and the method and techniques used by the researchers to gather data. The description should be thorough enough to allow another researcher to repeat the experiment and obtain similar results, but it does not have to be verbose. This section will also include information on how measurements were made and what types of calculations and statistical analyses were used to examine raw data. Although the materials and methods section gives an accurate description of the experiments, it does not discuss them.

Some journals require a results section followed by a discussion section, but some may combine both. If the journal does not allow the combination of both sections, the results section simply narrates the findings without any further interpretation. The results are presented by means of tables or graphs, but no duplicate information should be presented. In the discussion section, the researcher will interpret the results, describe how variables may be related, and attempt to explain the observations. It is indispensable to conduct an extensive literature search to put the results in the context of previously published scientific research. Therefore, proper citations are included in this section as well.

Finally, a  conclusion section may be used to summarize the importance of the experimental findings. Most often, the conclusions are included in the discussion. While the scientific paper almost certainly answered one or more scientific questions that were stated, any good research should lead to more questions. Therefore, a well-done scientific paper leaves doors open for the researcher and others to continue and expand on the findings.

Review articles do not follow the IMRAD format because they do not present original scientific findings, or primary literature; instead, they summarize and comment on findings that were published as primary literature and typically include extensive reference sections. They follow specific methods of searching and summarizing the scientific literature, to ensure that their findings are reproducible.

Indigenous Science

The following text may be different than text that you have come across before in a science context because Indigenous Science will be woven throughout the content. You will find this content as green call-out boxes throughout this text.

Now that you have read this unit, the following piece has been included to provide you with another perspective on science and culture. Consider this not as an alternative to what you have already learned but an examination of how each can contribute to a better understanding of nature, the world, and its importance. Indigenous Science, explained below, is formally known to many biologists and ecologists as Traditional Ecological Knowledge (TEK); this text will use TEK throughout the rest of the Units.

Indigenous Connections

It is important to balance and consider Indigenous Science, that which recognizes the knowledge inherent in each culture: "every culture and every society has its own science, and its function is sustaining its mother society and culture” (Yamada, 1970, p. 585).  Cultural diversity suggests that Western Science (WS) and Indigenous Science (IS) should be viewed as co-existing or parallel. Hatcher, Marshall, and Marshall (2009, p. 15) describe Indigenous Science metaphorically as a “living knowledge” that requires less dependence on knowledge transfer from books and requires “knowledge gardening with living knowledge keepers,” which differs from Western Science. As you study biology, it is important to balance and consider the traditional contexts of Indigenous Science (IS) with Western Science (WS) evidence and reason. 

The traditional wisdom component of IS—the values and ways of decision-making relating to science knowledge—is particularly rich in time-tested approaches that foster sustainability and environmental integrity. Western Science (WS) is the most dominant science in the world today and is widely thought of as 'officially sanctioned science'. However, because WS has been implicated in many of the world’s ecological disasters—pesticide contamination, introduced species, dams and water diversions that have impacted salmon and other indigenous species—it seems that reliance on Western Science alone can be seen as increasingly problematic and even counterproductive.

The process of generating or learning Indigenous ways of living in nature is coming to know (Cajete, 2000; Peat, 1994), a phrase that connotes a journey. Coming to know differs from a Eurocentric science process to know or to discover that connotes a destination, such as a patent or published record of discovery. Indigenous coming to know is a journey toward wisdom or a journey of wisdom in action, not a discovery of knowledge (Aikenhead & Ogawa, 2007). For Michell (2005), coming to know includes the goal of living in harmony with nature for the survival of the community. “Nature provides a blueprint of how to live well and all that is necessary to sustain life” (Michell, 2005, p. 39).

TEK combines current observation with wisdom, knowledge, and experience that has been acquired over thousands of years of direct human contact with specific environments. TEK interprets how the world works from the cultural perspective unique to a particular group of Indigenous peoples. Although the term TEK came into widespread use in the 1980’s, TEK itself is timeless and predates written record (Corsiglia & Snively, 1997). The stories and testimonies of Indigenous peoples are usually related to a home place or territory. TEK embodies both remembered sensory information built upon repeated observation, and formal understandings that are usually transmitted orally in story form or ceremonial form with abstract principles and important information encapsulated in metaphor (Cruikshank, 1991; Turner, Ignace, & Ignace, 2000). Perhaps the most useful way to think about Indigenous Science is that it is complementary to Western Science and not a replacement for it. Rooted in different worldviews, Indigenous and Western Science are not easy to combine, and it may not be desirable to meld the two. Each knowledge system is legitimate in its own right. The two kinds of knowledge may be pursued separately but in parallel, enriching one another as needed (Berkes, 2012). As such, weaving TEK with western science throughout this text will help you develop a deeper understanding of key biology concepts from multiple perspectives.

Numerous traditional peoples’ scientific and technological contributions have been incorporated in modern applied sciences such as ecology, biology, medicine, architecture, engineering, geology, pharmacology, agriculture, horticulture, agronomy, metallurgy, navigation, astronomy, animal husbandry, fish and wildlife management, nautical science, plant breeding, and military and political science (Berkes, 2012; Turner & Peacock, 2005; Deur & Turner, 2005; Turner, 2014a, 2014b; Weatherford, 1988, 1991). The truth is, directly or indirectly, we are all benefiting from Indigenous scientific and technological innovations every time we dine, clothe ourselves, travel or go to the doctor.

TEK provides invaluable time-tested resource management practices that can be used alongside WS to develop more workable and effective approaches to current resource management strategies than either could accomplish alone. In fact, it has become a policy requirement in Canada, and in particular Northern Canada, that TEK be incorporated into environmental assessments affecting wildlife management including: migratory birds, species at risk, forest practices, and fisheries management (Usher, 2000).

Some of the contributions of TEK and Indigenous Science scholarship to contemporary environmental knowledge, conservation and resource management worldwide (acknowledged by Western scientists) are outlined below:

• Perceptive investigations of traditional environmental knowledge systems provide important biological and ecological insights (Berkes 2012; Houde, 2007; Turner & Peacock, 2005; Turner, 2014a, 2014b; Usher, 2000; Warren, 1997).
• Help locate rare and endangered species and provide cost-effective shortcuts for investigating the local resource bases. Local knowledge makes it possible to survey and map in a few days what would otherwise take months, for example, soil types, plant and animal species, migration pathways, and aggregation sites (Berkes, 2012; Usher, 2000; Warren, 1997).
• Provide knowledge of time-tested resource management practices and can be used to develop workable approaches to current resource management strategies (Houde, 2007; Turner & Peacock, 2005; Usher, 2000; Warren, et. al., 1993).
• Provides time-tested in-depth knowledge of the local area (past and present) that can be triangulated with WS resulting in more accurate environmental assessment and impact statements. People who depend on local resources for their livelihood are often able to assess the true costs and benefits of development better than any evaluator from outside (Houde, 2007; Warren, et. al, 1993; 1997).
• Provides experience-based value statements about appropriate and ethical behavior with respect to animals and the environment (Berkes, 2012; Deur & Turner, 2005; Turner, 2014a, 2014b; Houde, 2007; Usher, 2000).

A key point here is that scientists may be unable to understand the complexity of ecosystems, especially northern or distant ecosystems, through sporadic observations, as opposed to lived experience.

Recognition of the importance of incorporating IS and TEK in environmental planning is explicitly addressed in reports and agreements in Canada and internationally. The Brundtland Commission report,  Our Common Future  (WCED: World Commission on Environment and Development, 1987), recognized the role of TEK in sustainable development; and the  Convention on Biological Diversity, Agenda 21  (UN Conference on the Environment, 1993), declared that Indigenous people possess important traditional scientific knowledge. The document  Science for the Twenty-first Century: A new Commitment  (UNESCO: United Nations Educational, Scientific and Cultural Organization, 2000), set new standards for respecting, protecting and utilizing Indigenous Knowledge. Working scientists worldwide, associated with hundreds of institutes, are collaborating with Elders and knowledge holders to collect and document examples of TEK and IS knowledge; this includes institutes in the US, Canada, Middle and South America, Africa, Europe, Australia, New Zealand, India, Russia, China and Japan.

Adapted from:  Knowing Home: Braiding Indigenous Science with Western Science, Book 1  by Gloria Snively and Wanosts'a7 Lorna Williams (CC-NC-SA)

Watch the three videos above as examples of the TEK and WS working together.  Question after watching: Do you know of other examples of TEK and IS from your province or region? 

Indigenous Connection

Find an article entitled "First Nations communities bring expertise to Canada’s scientific research" here from the Journal  Nature :  https://www.nature.com/articles/d41586-021-03060-x

References:

UNESCO. (2021). Science for Society. United Nations Education, Science, and Culture Organization. From:  https://en.unesco.org/themes/science-society

Essay on Importance of Science in Our Life

Science is a systematic process in which various theories, formulas, laws, and thoughts are analysed and evaluated in order to determine the truth about the facts of anything.

This systematic process studies and generates new knowledge from any kind of activity that occurs in the nature around us or in the universe, of which we are a tiny part.

Table of Contents

Science is essential.

• Importance of Science in Society
• Frequently Asked Questions – FAQs

Science is a methodical process of extracting true facts from any given thought by adhering to a set of rules known as methodology.

It includes the following:

• Observation: The observations are made based on the collected data and measurements.
• Evidence: If any evidence is gathered for further processing of data evaluation.
• Experiment : Using the data and evidence gathered, experiments are carried out to test the assumption.
• Initiation: Identify the facts based on data and evidence analysis.
• Re-examination and complex analysis: To ensure the veracity and authenticity of the results, the data and evidence are examined several times and critically analysed.
• Verification and review of the results: The results of the experiment are verified and tested by experts to ensure that they are correct.

Science is concerned with generating new knowledge and proving new hypotheses by collecting and analysing data in a systematic manner.

There are numerous scientific disciplines:

• Astrophysics
• Climate science
• Atmospheric science

Importance of science in society

Science and technology play an important role in today’s changing world. Everything from the road to the buildings, the shop to the educational instructions is the result of modern science and technology. Almost everything we see in society is the result of applied science and technology. Even the toothpaste we use to clean our teeth after waking up in the morning and before going to bed at night are products of science and technology.

Electricity

The discovery of electricity was the first modern scientific marvel. It has altered our way of life, society, and culture. It’s a fantastic source of power and energy.

The radio and television Lights, fans, electric irons, mills, factories, and refrigerators are all powered by electricity.

Transport and Communication

Science has simplified and shortened our communication. Ships, boats, trains, buses, and cars can be found on the seas, rivers, and roads. All of these are scientific gifts.

Telegraph, telephone, fax, and wireless communication are also important modes of communication. Trains, steamers, aeroplanes, buses, and other modes of transportation make communication quick and easy.

Medicine and Surgery

• It elevates one’s overall standard of living, quality of life, and life expectancy.
• It aids in detecting and treating diseases, ailments, and conditions.
• It dissects the molecular mechanism of any disease and helps to develop drugs and pharmaceuticals.
• Basic Medical Sciences, in addition to curative care, sow the seeds of preventive care.
• It teaches researchers, doctors, scientists, and even laypeople about living a healthy lifestyle.
• It fosters a fundamental understanding of medical science principles, which may be useful in the future.

Agriculture

A great deal of agricultural research was conducted, which resulted in the production of artificial fertilisers, which are now a basic requirement for all agricultural activities. Agricultural education is now taught in schools across the country. Scientists have gone so far as to study the genomic makeup of plants to select crops that can withstand harsh climate changes. Improved farming techniques have been developed using new technologies such as computer science and biotechnology.

Science has played an important role in agriculture, and the two cannot be separated. Science must be used to help produce better yields on a small piece of land for the world to be able to provide enough food for all of its citizens.

Read more: Chemistry of Life

New scientific understanding may result in new applications.

The discovery of the structure of DNA, for example, was a major breakthrough. It served as the foundation for research that would eventually lead to many practical applications, such as DNA fingerprinting, genetically engineered crops, and genetic disease tests.

New technological developments may result in new scientific discoveries.

For example, the development of DNA copying and sequencing technologies has resulted in significant advances in many areas of science.

Scientific research may be motivated by potential applications.

For example, the possibility of engineering microorganisms to produce drugs for diseases such as malaria motivates many microbe genetics researchers to continue their research.

Frequently Asked Questions on Essay on Importance of Science in Our Life

What role does science play in our lives.

It helps us live a longer and healthier life by monitoring our health, providing medicine to cure our diseases, alleviating aches and pains, assisting us in providing water for our basic needs – including our food – providing energy and making life more enjoyable by including sports, music, entertainment, and cutting-edge communication technology.

How has science influenced our daily lives?

Science has changed how we live and what we believe since the invention of the plough. Science has allowed man to pursue societal concerns such as ethics, aesthetics, education, and justice, to create cultures, and to improve human conditions by making life easier.

How has science made our lives easier?

When scientific discoveries are combined with technological advancements, machines make managing our lives easier. Science has created everything from household appliances to automobiles and aeroplanes. Farmers can now save their crops from pests and other problems thanks to advances in science.

What is the social significance of science and technology?

The essence of how science and technology contribute to society is the creation of new knowledge and then the application of that knowledge to improve human life and solve societal problems.

Why is science education important in the 21st century?

Exemplary science education can offer a rich context for developing many 21st-century skills, such as critical thinking, problem solving, and information literacy, especially when instruction addresses the nature of science and promotes the use of science practices.

Leave a Comment Cancel reply

Your Mobile number and Email id will not be published. Required fields are marked *

Request OTP on Voice Call

Post My Comment

• Share Share

Register with BYJU'S & Download Free PDFs

Register with byju's & watch live videos.

• Call us for a consultation 1-800-391-2391
• Partnering with ABS
• Client Communications
• There are no suggestions because the search field is empty.

• How We Help
• Who We Serve
• ABS BioAccelerator
• Human Biospecimens
• Cell Culture Services
• Cell Line Engineering
• Cell and Tissue Preparations
• Cell and Tissue Analysis
• Sample Storage and Logistics Services
• Case Studies
• White Papers
• Achievements
• Career Opportunities

What are the Roles of Scientists in Society?

Many years ago, in a former life, I taught high school biology. The first day, I told my students that they could use their textbooks or any book to take any test that I would I give. They were surprised, and most thought that class would be very easy despite my explanations that it would not be. They were surprised again when they found that it was not as easy as they thought. This was because I asked them to think and reason with the information at hand.

Study was still necessary. In the real world, one can look up a wealth of information. Some of it has more validity, while others do not. It is the ability to evaluate, test, and reason with that information that is of value. That is what I tried to teach using the basic facts of science as a backdrop for developing a thoughtful approach to understanding scientific problems and other issues. For example, I would ask them how one might approach developing a novel cancer treatment or investigating the effects of oxygen depletion in the oceans on the environment and human health.

One might think that this was too much for high school students. It was not. Many of them responded with a college level of understanding. Even students, who others said were lost causes, were able to understand. Given the right approach, learning and solving problems are rewarding for most people. Providing an approach to solving problems is far more beneficial than handing out a list of information to memorize. This reminiscing led me back to the present, and how some of us may sell short those who do not agree with or understand our positions.

Science is a systematic quest for truth. It strives to search for unbiased facts that can be tested and verified. Truth and verifiable information are of value to everyone. The discoveries of science make our lives better in a multitude of ways ranging from cures for diseases to increased food supplies. Of course, one may argue about many things, but the facts behind these debates should hopefully be less contentious. This is especially the case when those facts are open to verifiable and reproducible testing.

For most scientists, the hope is that their search for truth will ultimately benefit society. The fruits of that search becomes evident through publications, presentations at scientific meetings, and eventually perhaps as a more effective drug, a safer and more efficient battery, faster internet speeds, etc. For many of us that is enough. We do our work and experimentally test its validity. We may be recognized by our peers, and over time our discoveries may have a positive impact upon society, but is that enough? Should we expect more of ourselves?

The pursuit of truth through science has both intrinsic and practical value. However, the value of that truth is less impactful if it is not actively shared. Society is experiencing many difficult issues and their solutions require the types of unbiased information that science can provide. Our work is valuable. Its value increases if it is communicated and acted upon.

From Galileo to the present, the sharing of scientific information is not without its challenges. It may take courage to share information in the face of fear and confusion. With our increasing reliance on science and technology, a widespread basic understanding of scientific processes is even more necessary. Most people are more than capable of that understanding if given the opportunity. Once that understanding is achieved, this methodology can be applied to most of the problems that we face.

Sharing and learning are likely to be more effective if approached with the goal of seeking truth and mutual benefit rather than winning an argument. Effective sharing and communication require empathy and patience. This is not easy to achieve, but it is likely to yield more than confrontation or attitudes of superiority. A good starting point may be to understand that most of us are trying to do the best we can with our current knowledge.

On a societal level, supporting an educational system that values the scientific method over memorization benefits everyone. Scientific methodology should not just be the province of scientists. Reason and a search for truth should not be confined to the laboratory. By making the scientific method part of the curriculum as mentoring and listening to one another, we all benefit. Science can help to address many of the ills of this world if we make it a tool that is available to everyone.

Share this article

Related articles

The Crucial Role of Facility Efficiency in Pharma and Biotech

Efficiency is a cornerstone of success in the highly competitive and demanding fields of pharmaceuticals and biotechnology. Within laboratories, achieving and maintaining facility efficiency is essential to ensure that research and development processes run smoothly, deadlines are met, and resources are used optimally. In this article, we will explore why facility efficiency matters, focusing on key practices like implementing the 5S methodology, ensuring each hood has its own supplies, and the benefits they bring to scientists in these industries.  

Thank You and Happy New Year!

Another year comes rapidly to a close. 2023 was a year of accelerating changes. I t is likely that 2024 will bring even more transformation in how we live and work . AI and other technologies will hasten the pace.   

A New Paradigm for Transforming and Accelerating Research

Let’s begin with a few questions. What are your goals and those of your organization? Is it to grow cells? Is it to find and acquire human biospecimens? Is it to inventory and store biological samples? These tasks are important, but they are not your mission or the value proposition of your organization. 

ABS BioAccelerator - A New Way to Accelerate the Success of Growing Bioscience Companies

ABS’ Mission is to save and improve lives by making the discovery of drugs and diagnostics faster, easier, and more reliable. Our mission is to make your Mission more successful. As an extension of our mutual mission, we have founded the ABS BioAccelerator to speed up the success of growing life science companies.  

Subscribe Here!

Free your resources to complete your projects on time..

ISO9001:2015 Certified

Get ABS Updates

• Terms of Use
• Privacy Policy

© Copyright 2014 - 2024 ABS Inc., All Rights Reserved

• International edition
• Australia edition
• Europe edition

What is the scientist's role in society and how do we teach it?

Will Hutton recently set alarm bells ringing regarding the importance of postgraduate training in UK universities , pointing to the decline in the numbers of English graduates going on to study at postgraduate level. But should we also be concerned about whether our current training of science PhDs and postdoctoral researchers prepares them for future employment?

This is particularly critical given that only one in 10 postdocs can now expect to find senior posts in academia, usually after years as research assistants supported by short-term grants. Many science PhDs will need to find employment in fields other than those for which their training prepared them .

Our lives are increasingly affected, for better or worse, by innovations in science; some of these innovations we rely on to present future threats. Developments in fields ranging from gene technology to energy production offer real benefits to society, but also raise wider societal questions. We urgently need a better understanding of where, and how, science and technology fit into the cultural and industrial life of the nation. Scientists should become more proactive in providing advice to politicians and policy-makers where proposed new policies involve knowledge they possess from their research.

Yet there is often a disconnect between our policy-makers and the scientific community. The nation would gain much if these two elements of our public life could be brought closer to create some better joined-up thinking. There should be some preparation, in their postgraduate training, for this aspect of the scientist's role in society.

Training for most postgraduate scientists starts – and too often ends – in the laboratory, despite the fact that due to the shortage of senior university posts, many will need to deploy their skills elsewhere. With today's emphasis on obtaining funding, the focus in universities is on achieving "high research ratings" through research published in premier league journals. This is not a bad objective, but in the process, preparing PhD students and postdocs for careers outside academia receives scant attention.

There should be a widening of training and experience to fit them for roles outside mainstream research. They should be encouraged to see the relevance and political consequences of science and technology in general, and the relevance of their field of science in particular to national policy. They should be prepared to be proactive in explaining the nature of scientific evidence to those who ultimately make the policy decisions.

Published research is rarely black or white and there are significant areas of uncertainty and debate among experts in areas such as, for example, climate change, insecticides and bee health, and badgers and bovine TB. The policy-makers err towards a consensus view rather than a sound understanding of the underlying science.

The scientist's role should therefore be to interpret evidence for them and bring perspective, particularly where there is a body of evidence pointing in a different direction. It would also be of benefit if the fundamental concepts behind the "scientific method" could be more widely applied to policy-making.

Postgraduate and postdoctoral researchers should learn something of the way that policy is made and assessed – and the routes available to provide information and advice to the policy-makers. Newton's Apple Foundation was established to help bridge this gap between the science community and the policy-making processes. Over the past four years, it has run workshops in universities, in Westminster and elsewhere to introduce early career researchers to the world of policy-making.

Researchers are brought into contact with those in parliament, government and the civil service with the main objective to help them understand that they have a part to play in the process. Crucially, they are given positive examples where scientists have affected policy thinking, such as their influence on the 2008 human fertilisation and embryology act and the reconsideration of the EU directive which would prevent the use of MRI in hospitals.

Approaching 1,000 students have taken part in these workshops, and the demand for them is increasing. The great majority are naive about how policy is made. However, feedback indicates that attending has awakened an appreciation of the importance of scientific evidence and advice in policymaking.

In training PhD candidates and postdocs, we should be offering a wider experience to open them up to other career options outside the academic research environment. These include in industrial R&D and management, the civil service and even non-scientific roles in businesses and the professions. They should be helped to understand where science and technology fit into the life of the nation, and where they will find useful roles in which their knowledge and experience will be valued.

Michael W Elves is chairman and Ian Gibson is president of president of Newton's Apple Foundation

This content is brought to you by Guardian Professional . Looking for your next university role? Browse Guardian jobs for hundreds of the latest academic, administrative and research posts

• Universities
• Learning and teaching
• Higher education policy
• Higher education
• Science (Education)

Comments (…)

Most viewed.

Role of Science in Making India for Students and Children

500+ words essay on role of science in making india.

In the last few years, science has helped a lot in the development of India. Science has contributed to all the sectors. Science has improved the global economy, increased employment opportunities, saved millions of lives and has played a major role in a lot of industries. Science is very important for the growth and development of India. It even plays a key role in our daily lives. Every country should invest as much as possible in research and development for scientific technologies. In this essay on the role of science in making India we will see how science has helped India to grow in different sectors.

How Indian Scientists have Helped India Grow?

When it comes to Indian Scientists, the first name comes to my mind is CV Raman. CV Raman was the first Asian who won the Nobel Prize. His work was related to light and sound. He investigated that when light passes through a transparent material, some of the deflected light waves see the change in its amplitude and wavelength.

APJ Abdul Kalam is the second name that comes in my mind in Indian Scientists. APJ Abdul Kalam worked as an Aerospace engineer with ISRO and DRDO. He was also president of India from 2002 to 2007. Abdul Kalam contributed a lot to Aerospace. One of the contributions is deploying Rohini Satellite near Earth’s orbit. A few more names are Homi Bhabha, Visvesvaraya, V Radhakrishnan, Satyendra Nath Bose and many more… 

Get the huge list of more than 500 Essay Topics and Ideas

How has Science Increased Employment Opportunities?

Whenever any new technology is discovered it leads to new industries. For example, if any new scientific device is invented it will require eligible professionals to control the device. Such inventions help in increasing employment opportunities. This also helps in growth in many businesses which in turn develops the Indian economy.

Curing Diseases and Saving Lives

In the last few years, medical science has evolved so much and saved billions of lives. New technologies like wireless brain sensors, artificial organs, smart inhalers, robotic surgery, virtual reality are making work easier for thousands of doctors around the world. And also these technologies are saving millions of lives and curing diseases. 

Role in Agriculture Sector

Science has played a very major role in the Agriculture sector. Food is one of the basic needs of our lives. And science has now invented so many new agriculture techniques which have increased production drastically. The old mundane techniques farmers used to follow was very slow, expensive, and required too much effort.

Science has made everything a lot easier for farmers. Improved facilities in irrigation, modern fertilizers, advanced equipment, and pesticides are all helping farmers to work faster, and save more money. 

Science has helped us a lot in many ways and it will keep helping. Everyone should not only invest as much as possible in science and technology but also should stay aware of all new technologies developed around the world. 

FAQs on Science

Q.1 Why is Science important in daily lives?

A – Science plays an important role in our daily lives, for example, what medicines are you taking, the food you eat, the equipment you use for cooking, clothes you are wearing and much more.

Customize your course in 30 seconds

Which class are you in.

• Travelling Essay
• Picnic Essay
• Our Country Essay
• My Parents Essay
• Essay on Favourite Personality
• Essay on Memorable Day of My Life
• Essay on Knowledge is Power
• Essay on Gurpurab
• Essay on My Favourite Season
• Essay on Types of Sports

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Download the App

Maintenance work is planned for Wednesday 1st May 2024 from 9:00am to 11:00am (BST).

During this time, the performance of our website may be affected - searches may run slowly and some pages may be temporarily unavailable. If this happens, please try refreshing your web browser or try waiting two to three minutes before trying again.

We apologise for any inconvenience this might cause and thank you for your patience.

Environmental Science: Nano

2023 outstanding papers published in the environmental science journals of the royal society of chemistry.

a Hong Kong Baptist University, Hong Kong, China

b Carnegie Mellon University Department of Chemistry, Pittsburgh, PA, USA

c Department of Civil and Resource Engineering, Dalhousie University, Halifax, Nova Scotia, Canada

d Lancaster Environment Centre, Lancaster University, UK

e Universidade Católica Portuguesa, Portugal

f Harvard John A. Paulson School of Engineering and Applied Science, Harvard University, Cambridge, USA

g Department of Civil and Environmental Engineering, Virginia Tech, Blacksburg, Virginia, USA

A graphical abstract is available for this content

• This article is part of the themed collection: Outstanding Papers 2023 – Environmental Science: Nano

Article information

Download citation, permissions.

Z. Cai, N. Donahue, G. Gagnon, K. C. Jones, C. Manaia, E. Sunderland and P. J. Vikesland, Environ. Sci.: Nano , 2024,  11 , 1329 DOI: 10.1039/D4EN90012J

To request permission to reproduce material from this article, please go to the Copyright Clearance Center request page .

If you are an author contributing to an RSC publication, you do not need to request permission provided correct acknowledgement is given.

If you are the author of this article, you do not need to request permission to reproduce figures and diagrams provided correct acknowledgement is given. If you want to reproduce the whole article in a third-party publication (excluding your thesis/dissertation for which permission is not required) please go to the Copyright Clearance Center request page .

Read more about how to correctly acknowledge RSC content .

Social activity

Search articles by author, advertisements.

• MyU : For Students, Faculty, and Staff

Fall 2024 CSCI Special Topics Courses

Cloud computing.

Meeting Time: 09:45 AM‑11:00 AM TTh  Instructor: Ali Anwar Course Description: Cloud computing serves many large-scale applications ranging from search engines like Google to social networking websites like Facebook to online stores like Amazon. More recently, cloud computing has emerged as an essential technology to enable emerging fields such as Artificial Intelligence (AI), the Internet of Things (IoT), and Machine Learning. The exponential growth of data availability and demands for security and speed has made the cloud computing paradigm necessary for reliable, financially economical, and scalable computation. The dynamicity and flexibility of Cloud computing have opened up many new forms of deploying applications on infrastructure that cloud service providers offer, such as renting of computation resources and serverless computing.    This course will cover the fundamentals of cloud services management and cloud software development, including but not limited to design patterns, application programming interfaces, and underlying middleware technologies. More specifically, we will cover the topics of cloud computing service models, data centers resource management, task scheduling, resource virtualization, SLAs, cloud security, software defined networks and storage, cloud storage, and programming models. We will also discuss data center design and management strategies, which enable the economic and technological benefits of cloud computing. Lastly, we will study cloud storage concepts like data distribution, durability, consistency, and redundancy. Registration Prerequisites: CS upper div, CompE upper div., EE upper div., EE grad, ITI upper div., Univ. honors student, or dept. permission; no cr for grads in CSci. Complete the following Google form to request a permission number from the instructor ( https://forms.gle/6BvbUwEkBK41tPJ17 ).

CSCI 5980/8980 

Machine learning for healthcare: concepts and applications.

Meeting Time: 11:15 AM‑12:30 PM TTh  Instructor: Yogatheesan Varatharajah Course Description: Machine Learning is transforming healthcare. This course will introduce students to a range of healthcare problems that can be tackled using machine learning, different health data modalities, relevant machine learning paradigms, and the unique challenges presented by healthcare applications. Applications we will cover include risk stratification, disease progression modeling, precision medicine, diagnosis, prognosis, subtype discovery, and improving clinical workflows. We will also cover research topics such as explainability, causality, trust, robustness, and fairness.

Registration Prerequisites: CSCI 5521 or equivalent. Complete the following Google form to request a permission number from the instructor ( https://forms.gle/z8X9pVZfCWMpQQ6o6  ).

Visualization with AI

Meeting Time: 04:00 PM‑05:15 PM TTh  Instructor: Qianwen Wang Course Description: This course aims to investigate how visualization techniques and AI technologies work together to enhance understanding, insights, or outcomes.

This is a seminar style course consisting of lectures, paper presentation, and interactive discussion of the selected papers. Students will also work on a group project where they propose a research idea, survey related studies, and present initial results.

This course will cover the application of visualization to better understand AI models and data, and the use of AI to improve visualization processes. Readings for the course cover papers from the top venues of AI, Visualization, and HCI, topics including AI explainability, reliability, and Human-AI collaboration.    This course is designed for PhD students, Masters students, and advanced undergraduates who want to dig into research.

Registration Prerequisites: Complete the following Google form to request a permission number from the instructor ( https://forms.gle/YTF5EZFUbQRJhHBYA  ). Although the class is primarily intended for PhD students, motivated juniors/seniors and MS students who are interested in this topic are welcome to apply, ensuring they detail their qualifications for the course.

Visualizations for Intelligent AR Systems

Meeting Time: 04:00 PM‑05:15 PM MW  Instructor: Zhu-Tian Chen Course Description: This course aims to explore the role of Data Visualization as a pivotal interface for enhancing human-data and human-AI interactions within Augmented Reality (AR) systems, thereby transforming a broad spectrum of activities in both professional and daily contexts. Structured as a seminar, the course consists of two main components: the theoretical and conceptual foundations delivered through lectures, paper readings, and discussions; and the hands-on experience gained through small assignments and group projects. This class is designed to be highly interactive, and AR devices will be provided to facilitate hands-on learning.    Participants will have the opportunity to experience AR systems, develop cutting-edge AR interfaces, explore AI integration, and apply human-centric design principles. The course is designed to advance students' technical skills in AR and AI, as well as their understanding of how these technologies can be leveraged to enrich human experiences across various domains. Students will be encouraged to create innovative projects with the potential for submission to research conferences.

Registration Prerequisites: Complete the following Google form to request a permission number from the instructor ( https://forms.gle/Y81FGaJivoqMQYtq5 ). Students are expected to have a solid foundation in either data visualization, computer graphics, computer vision, or HCI. Having expertise in all would be perfect! However, a robust interest and eagerness to delve into these subjects can be equally valuable, even though it means you need to learn some basic concepts independently.

Sustainable Computing: A Systems View

Meeting Time: 09:45 AM‑11:00 AM  Instructor: Abhishek Chandra Course Description: In recent years, there has been a dramatic increase in the pervasiveness, scale, and distribution of computing infrastructure: ranging from cloud, HPC systems, and data centers to edge computing and pervasive computing in the form of micro-data centers, mobile phones, sensors, and IoT devices embedded in the environment around us. The growing amount of computing, storage, and networking demand leads to increased energy usage, carbon emissions, and natural resource consumption. To reduce their environmental impact, there is a growing need to make computing systems sustainable. In this course, we will examine sustainable computing from a systems perspective. We will examine a number of questions:   • How can we design and build sustainable computing systems?   • How can we manage resources efficiently?   • What system software and algorithms can reduce computational needs?    Topics of interest would include:   • Sustainable system design and architectures   • Sustainability-aware systems software and management   • Sustainability in large-scale distributed computing (clouds, data centers, HPC)   • Sustainability in dispersed computing (edge, mobile computing, sensors/IoT)

Registration Prerequisites: This course is targeted towards students with a strong interest in computer systems (Operating Systems, Distributed Systems, Networking, Databases, etc.). Background in Operating Systems (Equivalent of CSCI 5103) and basic understanding of Computer Networking (Equivalent of CSCI 4211) is required.

• Future undergraduate students
• Future transfer students
• Future graduate students
• Future international students
• Diversity and Inclusion Opportunities
• Learn abroad
• Living Learning Communities
• Mentor programs
• Programs for women
• Student groups
• Visit, Apply & Next Steps
• Information for current students
• Departments and majors overview
• Departments
• Undergraduate majors
• Graduate programs
• Integrated Degree Programs
• Additional degree-granting programs
• Online learning
• Academic Advising overview
• Academic Advising FAQ
• Academic Advising Blog
• Appointments and drop-ins
• Academic support
• Commencement
• Four-year plans
• Honors advising
• Policies, procedures, and forms
• Career Services overview
• Resumes and cover letters
• Jobs and internships
• Interviews and job offers
• CSE Career Fair
• Major and career exploration
• Graduate school
• Collegiate Life overview
• Scholarships
• Diversity & Inclusivity Alliance
• Anderson Student Innovation Labs
• Information for alumni
• Get engaged with CSE
• Upcoming events
• CSE Alumni Society Board
• Alumni volunteer interest form
• Golden Medallion Society Reunion
• 50-Year Reunion
• Alumni honors and awards
• Outstanding Achievement
• Alumni Service
• Distinguished Leadership
• Honorary Doctorate Degrees
• Nobel Laureates
• Alumni resources
• Alumni career resources
• Alumni news outlets
• CSE branded clothing
• International alumni resources
• Inventing Tomorrow magazine
• Update your info
• CSE giving overview
• Why give to CSE?
• College priorities
• Give online now
• External relations
• Giving priorities
• Donor stories
• Impact of giving
• Ways to give to CSE
• Matching gifts
• CSE directories
• Invest in your company and the future
• Recruit our students
• Connect with researchers
• K-12 initiatives
• Diversity initiatives
• Research news
• Give to CSE
• CSE priorities
• Corporate relations
• Information for faculty and staff
• Administrative offices overview
• Office of the Dean
• Academic affairs
• Finance and Operations
• Communications
• Human resources
• Undergraduate programs and student services
• CSE Committees
• CSE policies overview
• Academic policies
• Faculty hiring and tenure policies
• Finance policies and information
• Graduate education policies
• Human resources policies
• Research policies
• Research overview
• Research centers and facilities
• Research proposal submission process
• Research safety
• Award-winning CSE faculty
• National academies
• University awards
• Honorary professorships
• Collegiate awards
• Other CSE honors and awards
• Staff awards
• Performance Management Process
• Work. With Flexibility in CSE
• K-12 outreach overview
• Summer camps
• Outreach events
• Enrichment programs
• Field trips and tours
• CSE K-12 Virtual Classroom Resources
• Educator development
• Sponsor an event