Brian Nosek

Brian Nosek

Co-founder and Executive Director

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Brian Nosek’s research and applied interests are to understand how people and systems produce values-misaligned behavior; to develop, implement, and evaluate solutions to align behavior with values; and, to improve research methods and culture to accelerate progress in science. Brian co-developed the Implicit Association Test, a method that advanced research and public interest in implicit bias. Nosek co-founded three non-profit organizations: Project Implicit to advance research and education about implicit bias, the Society for the Improvement of Psychological Science to improve the research culture in his home discipline, and the Center for Open Science (COS) to improve rigor, transparency, integrity, and reproducibility across research disciplines. Brian is Executive Director of COS and a professor at the University of Virginia. Brian received his undergraduate degree in Psychology with minors in Computer Science and Women’s Studies from Cal Poly, San Luis Obispo in 1995, and his PhD in Psychology from Yale in 2002. He received honorary doctorates in science from Ghent University (2019) and University of Bristol (2022).

Professional Summary

Theoretical Contributions to Research Methodology

I spend a lot of time thinking about how to improve the scientific method. For example, I believe that replication is important for developing and improving scientific theories, and that precommitment is important for reducing unwanted bias. My theoretical and empirical research on improving methodology has shaped the initiatives offered through the Center for Open Science. Illustrative contributions:

  1. Nosek, B. A., & Errington, T. M. (2020). What is Replication? PLOS Biology, 18(3), e30000691.
  2. Nosek, B. A., Ebersole, C. R., DeHaven, A., Mellor, D. M. (2018). The preregistration revolution. Proceedings for the National Academy of Sciences, 115, 2600-2606.
  3. Munafò, M. R., Nosek, B. A., Bishop, D. V. M., Button, K. S., Chambers, C. D., Percie du Sert, N., Simonsohn, U., Wagenmakers, E-J., Ware, J. J., & Ioannidis, J. P. A. (2017). A manifesto for reproducible science. Nature Human Behavior, 1, 0021.
  4. Button, K. S., Ioannidis, J. P. A., Mokrysz, C., Nosek, B. A., Flint, J., Robinson, E. S. J., & Munafo, M. R. (2013). Power failure: Why small sample size undermines the reliability of neuroscience. Nature Reviews Neuroscience, 14, 1-12.

Vision for the Research Culture

Science is a social system. The norms and reward systems created by institutions and structures promote and constrain the actions of researchers. Researchers themselves have motivations, biases, and values that can accelerate or impede discovery. I investigate how the current research culture operates and hypothesize systemic changes that could improve science. Also, I drew on the behavior change literature to develop a theory of change to improve the research culture. This model informs how the Center for Open Science does its work. Illustrative contributions:

  1. Nosek, B. A., & Bar-Anan, Y. (2012). Scientific utopia: I. Opening scientific communication. Psychological Inquiry, 23, 217-243. (Open Access)
  2. Nosek, B. A., Spies, J. R., & Motyl, M. (2012). Scientific utopia: II. Restructuring incentives and practices to promote truth over publishability. Perspectives on Psychological Science, 7, 615-631.
  3. Uhlmann, E. L., Ebersole, C., Chartier, C., Errington, T., Kidwell, M., Lai, C. K., McCarthy, R., Riegelman, A., Silberzahn, R., & Nosek, B. A. (2019). Scientific utopia III: Crowdsourcing science. Perspectives on Psychological Science, 14, 711-733.
  4. Nosek, B. A., Alter, G., Banks, G. C., Borsboom, D., Bowman, S. D., …, & Yarkoni, T. (2015). Promoting an open research culture. Science, 348, 1422-1425. (Open access)

Applied Metascience

The Society for the Improvement of Psychological Science and the Center for Open Science are entrepreneurial efforts to improve science. I want to understand whether initiatives and interventions supported by these organizations or others work as theorized, and what unintended consequences occur that must be addressed. Continuous evaluation is critical for justifying whether to bring interventions to scale and to clarify the boundary conditions on their appropriate use. Illustrative contributions:

  1. Soderberg, C. K., Errington, T. M., Schiavone, S. R., Bottesini, J., Singleton Thorn, F., Vazire, S., Esterling, K. M., & Nosek, B. A. (2021). Initial evidence of research quality of Registered Reports compared to the standard publishing model. Nature Human Behaviour, 5, 990-997. (Open access)
  2. Plemmons, D. K., Baranski, E. N., Harp, K., Lo, D., Soderberg, C. K., Errington, T. M., Nosek, B. A., & Esterling, K. M. (2020). A randomized trial of a lab-embedded discourse intervention to improve research ethics. Proceedings for the National Academy of Sciences, 117, 1389-1394.
  3. Kidwell, M. C., Lazarevic, L. B., Baranski, E., Hardwicke, T. E., Piechowski, S., Falkenberg, L-S., Kennett, C., Slowik, A., Sonnleitner, C., Hess-Holden, C., Errington, T. M., Fiedler, S., & Nosek, B. A. (2016). Badges to acknowledge open practices: A simple, low-cost, effective method for increasing transparency. PLOS Biology, 14, e1002456.


With many collaborators, I have worked on replication projects to gather evidence about reproducibility and credibility of research, and to demonstrate how replication can be conducted effectively to clarify confidence in research claims. Collectively, these projects provide an evidence base of the opportunity for improving research credibility. Illustrative contributions:

  1. Errington, T. M., Denis, A., Perfito, N., Iorns, E., & Nosek, B. A. (2021). Challenges for assessing reproducibility and replicability in preclinical cancer biology. eLife, 10, e67995.
  2. Errington, T. M., Mathur, M., Soderberg, C. K., Denis, A., Perfito, N., Iorns, E., & Nosek, B. A. (2021). Investigating the replicability of preclinical cancer biology. eLife, 10, e71601.
  3. Ebersole, C. R., Mathur, M. B., Baranski, E., Bart-Plange, D., Buttrick, N. R., Chartier, C. R., Corker, K. S., ... & Nosek, B. A. (2020). Many Labs 5: Testing pre-data collection peer review as an intervention to increase replicability. Advances in Methods and Practices in Psychological Science, 3, 309-331.
  4. Klein, R. A., Vianello, M., Hasselman, F., Adams, B. G., Adams, R. B., ... & Nosek, B. A. (2018). Many labs 2: Investigating variation in replicability across sample and setting. Advances in Methods and Practices in Psychological Science, 1, 443-490.
  5. Open Science Collaboration. (2015). Estimating the reproducibility of psychological science. Science, 349(6251), aac4716. (Open access)

Evaluating Research Credibility

Replication is just one of many possible tools to assess the credibility of research claims. With colleagues, I am working on objective, human assessment, and machine learning strategies to assess research credibility. Identifying effective tools that are less resource intensive than replication could improve appreciation of uncertainty, evidenced-based attention of decision makers, and effective allocation of research resources to address uncertainty and accelerate discovery. Illustrative contributions:

  1. Alipourfard, N., Arendt, B., Benjamin, D. M., Benkler, N., Bishop, M. M., … & Wu, J. (2021). Systematizing Confidence in Open Research and Evidence (SCORE). SocArXiv.
  2. Camerer, C. F., Dreber, A., Holzmeister, F., Ho, T-H., Huber, J., Johannesson, M., Kirchler, M., Nave, G., Nosek, B. A., Pfeiffer, T., Altmejd, A., Buttrick, N., Chan, T., Chen, Y., Forsell, E., Gampa, A., Heikensten, E., Hummer, L., Imai, T., Isaksson, S., Manfredi, D., Rose, J., Wagenmakers, E-J., Wu, H. (2018). Evaluating Replicability of Social Science Experiments in Nature and Science between 2010 and 2015. Nature Human Behaviour, 2, 637-644. (Open access)
  3. Nosek, B. A., Hardwicke, T. E., Moshontz, H., Allard, A., Corker, K. S., Dreber, A., Fidler, F., Hilgard, J., Kline Struhl, M., Nuijten, M., Rohrer, J., Romero, F., Scheel., A., Scherer, L., Schönbrodt, F., & Vazire, S. (2022). Replicability, Robustness, and Reproducibility in Psychological Science. Annual Review of Psychology, 73, 719-748.
  4. Dreber, A., Pfeiffer, T., Almenberg, J., Isaksson, S., Wilson, B., Chen, Y., Nosek, B. A., & Johannesson, M. (2016). Using prediction markets to estimate the reproducibility of scientific research. Proceedings of the National Academy of Sciences, 112, 15343-15347.

Morality and Ideology

A basic research interest that informs my applied work is in the structure and function of belief systems. How do we conceive of right and wrong? Why do people have different values? How do values and beliefs influence behavior? Illustrative contributions:

  1. Graham, J., Haidt, J., & Nosek, B. A. (2009). Liberals and conservatives rely on different sets of moral foundations. Journal of Personality and Social Psychology, 96, 1029-1046. (Open access)
  2. Hawkins, C. B., & Nosek, B. A. (2012). Motivated independence? Implicit party identity predicts political judgments among self-proclaimed independents. Personality and Social Psychology Bulletin, 38, 1441-1455. (Open access)
  3. Jost, J. T., Banaji, M. R., & Nosek, B. A. (2004). A decade of system justification theory: Accumulated evidence of conscious and unconscious bolstering of the status quo. Political Psychology, 25, 881-919. (Open access)

Implicit Bias

Another basic research interest is in thoughts and feelings that occur outside of conscious awareness or control. I co-developed implicit measures such as the IAT and GNAT, and have investigated their properties and relationship of the associations they assess with self-reported attitudes and behavior. Also, I co-founded and directed Project Implicit, a non-profit research and education organization that popularized the concept of implicit bias, and produced massive shared datasets that are the basis of hundreds of research applications. Illustrative contributions:

  1. Bar-Anan, Y., & Nosek, B. A. (2014). A comparative investigation of seven indirect attitude measures. Behavior Research Methods, 46, 668-688.
  2. Nosek, B. A., & Hansen, J. J. (2008). The associations in our heads belong to us: Searching for attitudes and knowledge in implicit evaluation. Cognition and Emotion, 22, 553-594. (Open access)
  3. Nosek, B. A., & Smyth, F. L. (2007). A multitrait-multimethod validation of the Implicit Association Test: Implicit and explicit attitudes are related but distinct constructs. Experimental Psychology, 54, 14-29. (Open access)
  4. Nosek, B. A. (2005). Moderators of the relationship between implicit and explicit evaluation. Journal of Experimental Psychology: General, 134, 565-584. (Open access)
  5. Nosek, B. A., Banaji, M. R., & Greenwald, A. G. (2002). Math = male, me = female, therefore math ≠ me. Journal of Personality and Social Psychology, 83, 44-59. (Open access)

Changing Implicit Bias

Finally, I am interested in fundamental research on the formation and change of associations that may exist distinct from our self-reported, endorsed evaluations. Illustrative contributions:

  1. *Forscher, P. S., *Lai, C. K., Axt, J. R., Ebersole, C. R., Herman, M., Devine, P. G., & Nosek, B. A. (2019). A meta-analysis of procedures to change implicit measures. Journal of Personality and Social Psychology, 117, 522-559. *co-first authors (Open access)
  2. Lai, C. K., Marini, M., Lehr, S. A., Cerruti, C., Shin, J. L., Joy-Gaba, J. A., Ho, A. K., Teachman, B. A., Wojcik, S. P., Koleva, S. P., Frazier, R. S., Heiphetz, L., Chen, E., Turner, R. N., Haidt, J., Kesebir, S., Hawkins, C. B., Schaefer, H. S., Rubichi, S., Sartori, G., Dial, C. M., Sriram, N., Banaji, M. R., & Nosek, B. A. (2014). Reducing implicit racial preferences: I. A comparative investigation of 17 interventions. Journal of Experimental Psychology: General, 143, 1765-1785. (Open access)
  3. Smith, C. T., Ratliff, K. A., & Nosek, B. A. (2012). Rapid assimilation: Automatically integrating new information with existing beliefs. Social Cognition, 30, 199-219.

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