Biography:Michal Kosinski

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Michal Kosinski
(Michał Kosiński)
Head and shoulders photo of Michal Kosinski
Born (1982-05-08) May 8, 1982 (age 44)
Warsaw, Poland
CitizenshipAmerican, Polish
Education
OccupationProfessor
Years active1999-present
EmployerStanford University
Known for
  • Research on predicting psychological traits from digital footprints
  • First article warning against Cambridge Analytica
TitleAssociate professor, Stanford University
Websitemichalkosinski.com

Michal Kosinski is an associate professor of Organizational Behavior at Stanford University, a computational psychologist, and a psychometrician. His research spans computational psychometrics, the privacy risks of digital footprints, facial recognition, and the psychology of artificial intelligence.[1]

He has co-authored the textbook Modern Psychometrics and published over 80 peer-reviewed papers in journals including Nature Computational Science, Scientific Reports, Proceedings of the National Academy of Sciences, Psychological Science, Journal of Personality and Social Psychology, and Machine Learning, that have been cited over 28,000 times according to Google Scholar.[2]

He is among the top 1% of Highly Cited Researchers according to Clarivate.[3] His research inspired a cover of The Economist,[4] a 2014 theatre play "Privacy", and was discussed in thousands of books, press articles, podcasts, and documentaries. Kosinski was behind the first press article warning against Cambridge Analytica published in The Guardian.[5] His research demonstrated the privacy risks of digital footprints and showed that personality-based targeting can increase the effectiveness of mass persuasion.

Kosinski appeared in the documentaries iHuman (2019) and Do You Trust This Computer (2018).

Education

Kosinski holds a doctorate in psychology from the University of Cambridge and master's degrees in psychometrics and in social psychology.[6] He previously served as a post-doctoral scholar at Stanford's Computer Science Department, as the deputy director of the University of Cambridge Psychometrics Centre, and as a researcher at Microsoft Research (Machine Learning Group).[7]

Research

In 2013, Kosinski and David Stillwell published a paper entitled "Private Traits and Attributes Are Predictable from Digital Records of Human Behavior".[8] They claimed that Facebook Likes reveal personal traits and sensitive attributes, from sexual and political orientation to mental health. "Individual traits and attributes can be predicted to a high degree of accuracy based on records of users' Likes," they wrote. In 2012, Facebook patented a method doing precisely what Kosinski and Stillwell did, "Determining user personality characteristics from social networking system communications and characteristics".[9]

In 2015, Kosinski, Youyou, and Stillwell published a study in PNAS reporting that computer-based personality judgments derived from Facebook Likes were more accurate than judgments made by friends, family members, and spouses.[10]

In 2017, Kosinski, Matz, Nave, and Stillwell published a PNAS study reporting that psychologically tailored advertising messages could increase the effectiveness of digital mass persuasion.[11]

In 2017, Kosinski co-published a paper showing that modern artificial intelligence can predict someone's sexual orientation based on facial images.[12][13][14] The research was conducted on over 130,000 pictures and used existing facial recognition systems and AI algorithm. Their AI could predict the sexual orientation of gay men 81% of the time, while a human would be right 61% of the time.[15]

In 2021, Kosinski published a study in Scientific Reports demonstrating that facial recognition technology can predict political orientation from naturalistic facial images with 72% accuracy, substantially better than chance or conventional methods such as personality questionnaires.[16]

Since 2023, Kosinski's research has increasingly focused on the cognitive and social capacities of large language models. In a 2023 study in Scientific Reports, Digutsch and Kosinski compared semantic activation in GPT-3 with human lexical decision data, reporting that GPT-3's semantic activation broadly mirrored human patterns but was more strongly driven by semantic similarity than by associative relatedness.[17] In Nature Computational Science, Hagendorff, Fabi, and Kosinski tested OpenAI language models on cognitive-reflection and semantic-illusion tasks, reporting that human-like intuitive errors emerged in larger pre-ChatGPT models but were reduced in ChatGPT.[18] In 2024, Kosinski published a study in PNAS evaluating eleven large language models on false-belief tasks used to study theory of mind, reporting that older models solved no tasks while GPT-4 solved 75% of the tasks, matching the performance of six-year-old children reported in previous studies.[19] Related work examined language-model agency through negotiation games and the extent to which large language models encode public perceptions of public figures' personalities.[20][21][22]

Mypersonality database

Kosinski and David Stillwell co-created the myPersonality Facebook application and database, which became a major research resource for social scientists. A 2015 article in American Psychologist stated that the myPersonality application was owned by Stillwell and Kosinski, and that their Facebook-based psychological studies had attracted over 10 million participants.[23]

Controversies

His research on facial recognition systems raised controversy. Kosinski and Wang stated that their findings were intended to expose the risks posed by existing computer-vision technologies, writing that such systems could threaten the privacy and safety of gay men and women.[12]

While Deputy Director of the University of Cambridge Psychometrics Centre, Kosinski was approached by departmental colleague Aleksandr Kogan about a potential collaboration with SCL Group, Cambridge Analytica's parent company.[24] The Centre's co-director David Stillwell first declined to share its data, as it had been collected for academic purposes; an alternative was proposed in which Kogan would collect new data and pass it through the Centre's prediction models.[24] Kogan testified that he calculated a price of $500,000 for the Centre's models ("I thought, all right, maybe we will give the Psychometrics Centre $500,000 for the modelling aspect"); SCL considered the price too high and "instructed [Kogan] to remove them from the project."[24] Kogan subsequently built his own Facebook app independently; he confirmed in 2017 that "no data or models from the psychometrics centre were ever used for anything with SCL." Kosinski raised a formal complaint with university authorities, calling Kogan's approach "highly unethical," leading to legal undertakings prohibiting any use of the Centre's work in the project.[25] In November 2014, Kosinski contacted The Guardian and provided documents about the Kogan-SCL connection; the newspaper's resulting December 2015 article was the first press report about Cambridge Analytica's data practices.[26][27] No official investigation, including those by the FTC, UK ICO, and UK Parliament, has identified Kosinski as involved with Cambridge Analytica.[28][29]

See also

References

  1. ↑ "Dr. Michal Kosinski website". http://www.michalkosinski.com. 
  2. ↑ "Michal Kosinski". https://scholar.google.co.uk/citations?user=01-XV0YAAAAJ&hl=en. 
  3. ↑ "Web of Science". https://www.webofscience.com/wos/author/record/237117. 
  4. ↑ "What machines can tell from your face | Sep 9th 2017" (in en). The Economist. https://www.economist.com/weeklyedition/2017-09-09. 
  5. ↑ "Ted Cruz campaign using firm that harvested data on millions of unwitting Facebook users" (in en). 2015-12-11. http://www.theguardian.com/us-news/2015/dec/11/senator-ted-cruz-president-campaign-facebook-user-data. 
  6. ↑ "Michal Kosinski, PhD - Curriculum Vitae" (in en-US). https://www.michalkosinski.com/curriculum-vitae. 
  7. ↑ Kosinski, Dr Michal (2013-07-06). "Dr Michal Kosinski" (in en). https://www.psychometrics.cam.ac.uk/about-us/directory/michal-kosinski. 
  8. ↑ Kosinski, Michal; Stillwell, David; Graepel, Thore (2013-04-09). "Private traits and attributes are predictable from digital records of human behavior" (in en). Proceedings of the National Academy of Sciences 110 (15): 5802–5805. doi:10.1073/pnas.1218772110. ISSN 0027-8424. PMID 23479631. Bibcode: 2013PNAS..110.5802K. 
  9. ↑ Nowak, Michael & Dean Eckles, "Determining user personality characteristics from social networking system communications and characteristics", US patent 8825764, published 2014-09-02, assigned to Facebook Inc.
  10. ↑ Youyou, Wu; Kosinski, Michal; Stillwell, David (2015). "Computer-based personality judgments are more accurate than those made by humans". Proceedings of the National Academy of Sciences 112 (4): 1036–1040. doi:10.1073/pnas.1418680112. PMID 25583507. Bibcode: 2015PNAS..112.1036Y. 
  11. ↑ Matz, Sandra C.; Kosinski, Michal; Nave, Gideon; Stillwell, David J. (2017). "Psychological targeting as an effective approach to digital mass persuasion". Proceedings of the National Academy of Sciences 114 (48): 12714–12719. doi:10.1073/pnas.1710966114. PMID 29133409. Bibcode: 2017PNAS..11412714M. 
  12. ↑ 12.0 12.1 Wang, Yilun; Kosinski, Michal (2018). "Deep neural networks are more accurate than humans at detecting sexual orientation from facial images". Journal of Personality and Social Psychology 114 (2): 246–257. doi:10.1037/pspa0000098. PMID 29389215. 
  13. ↑ "Advances in AI are used to spot signs of sexuality". The Economist. https://www.economist.com/science-and-technology/2017/09/09/advances-in-ai-are-used-to-spot-signs-of-sexuality. 
  14. ↑ "'I was shocked it was so easy': meet the professor who says facial recognition can tell if you're gay". July 7, 2018. http://www.theguardian.com/technology/2018/jul/07/artificial-intelligence-can-tell-your-sexuality-politics-surveillance-paul-lewis. 
  15. ↑ "What machines can tell from your face". The Economist. https://www.economist.com/leaders/2017/09/09/what-machines-can-tell-from-your-face. 
  16. ↑ Kosinski, Michal (2021). "Facial recognition technology can expose political orientation from naturalistic facial images". Scientific Reports 11 (1). doi:10.1038/s41598-020-79310-1. PMID 33431957. Bibcode: 2021NatSR..11..100K. 
  17. ↑ Digutsch, Jan; Kosinski, Michal (2023). "Overlap in meaning is a stronger predictor of semantic activation in GPT-3 than in humans". Scientific Reports 13 (1). doi:10.1038/s41598-023-32248-6. PMID 36977744. Bibcode: 2023NatSR..13.5035D. 
  18. ↑ Hagendorff, Thilo; Fabi, Sarah; Kosinski, Michal (2023). "Human-like intuitive behavior and reasoning biases emerged in large language models but disappeared in ChatGPT". Nature Computational Science 3 (10): 833–838. doi:10.1038/s43588-023-00527-x. PMID 38177754. 
  19. ↑ Kosinski, Michal (2024). "Evaluating large language models in theory of mind tasks". Proceedings of the National Academy of Sciences 121 (45). doi:10.1073/pnas.2405460121. PMID 39471222. Bibcode: 2024PNAS..12105460K. 
  20. ↑ Davidson, Tim R.; Veselovsky, Veniamin; Kosinski, Michal; West, Robert (2024). "Evaluating Language Model Agency Through Negotiations". https://openreview.net/forum?id=3ZqKxMHcAg. 
  21. ↑ Cao, Xubo; Kosinski, Michal (2024). "Large language models know how the personality of public figures is perceived by the general public". Scientific Reports 14 (1). doi:10.1038/s41598-024-57271-z. PMID 38509191. Bibcode: 2024NatSR..14.6735C. 
  22. ↑ Cao, Xubo; Kosinski, Michal (2024). "Large language models and humans converge in judging public figures' personalities". PNAS Nexus 3 (10). doi:10.1093/pnasnexus/pgae418. PMID 39359393. 
  23. ↑ Kosinski, Michal; Matz, Sandra C.; Gosling, Samuel D.; Popov, Vesselin; Stillwell, David (2015). "Facebook as a research tool for the social sciences: Opportunities, challenges, ethical considerations, and practical guidelines". American Psychologist 70 (6): 543–556. doi:10.1037/a0039210. PMID 26348336. Bibcode: 2015AmPsy..70..543K. https://www.repository.cam.ac.uk/handle/1810/256072. 
  24. ↑ 24.0 24.1 24.2 "Oral evidence - Disinformation and 'fake news'". House of Commons Digital, Culture, Media and Sport Committee. 24 April 2018. https://committees.parliament.uk/oralevidence/7853/html/. 
  25. ↑ "Disinformation and 'fake news': Final Report". House of Commons Digital, Culture, Media and Sport Committee. 14 February 2019. https://publications.parliament.uk/pa/cm201719/cmselect/cmcumeds/1791/179104.htm. 
  26. ↑ Davies, Harry (11 December 2015). "Ted Cruz using firm that harvested data on millions of unwitting Facebook users". The Guardian. https://www.theguardian.com/us-news/2015/dec/11/senator-ted-cruz-president-campaign-facebook-user-data. 
  27. ↑ Levy, Steven (2020). Facebook: The Inside Story. Dutton. ISBN 978-0-7352-1315-9. 
  28. ↑ "Complaint for Permanent Injunction and Other Equitable Relief: Kogan and Nix". Federal Trade Commission. 2019. https://www.ftc.gov/system/files/documents/cases/182_3106_kogan-nix_complaint.pdf. 
  29. ↑ Wintroub, Michael (2020). "Author Correction: Sordid genealogies". Humanities and Social Sciences Communications (Nature Portfolio) 7 (1): 76. doi:10.1057/s41599-020-00568-x. https://www.nature.com/articles/s41599-020-00568-x. Retrieved 26 May 2026. 



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