Facial recognition algorithms can determine psychological traits from facial images even when controlling for demographics and self-presentation

  • Date:
  • Time: 16:00-17:00 ** NOTE LATER TIME **
  • Location: Online - book below



The widespread use of facial recognition leads to the dramatic decline of privacy and civil liberties. Ubiquitous CCTV cameras and giant databases of facial images, ranging from public social network profiles to national ID card registers, make it alarmingly easy to identify individuals, as well as track their location and social interactions. Moreover, unlike many other biometric systems, facial recognition can be used without subjects’ consent or knowledge. Yet, pervasive surveillance is not the only risk brought about by facial recognition. Apart from identifying individuals, the algorithms can identify individuals’ personal attributes, such as gender, age, ethnicity, and emotional state. Unfortunately, the list of personal attributes that can be inferred from the face extends well beyond those few obvious examples. In this talk, we will present evidence showing that widely used facial recognition algorithms are also sorting people based on intimate traits such as political or sexual orientation; describe particularly revealing facial features; and consider the implications of the progress in facial recognition for science, technology, and society.

The Speaker

Dr. Michal Kosinski an Associate Professor in Organizational Behaviour at Stanford University Graduate School of Business. He studies humans in a digital environment using cutting-edge computational methods, AI and Big Data. His research focuses on individual differences in behaviour, preferences, and performance. Specifically, he is interested in the mechanisms linking psychological traits (such as personality) with a broad range of organizational and social outcomes, including job performance, person-job fit, consumer preferences, and ideology, as well as the expression and recognition of psychological traits from behavioural residues, language, and facial features. He has co-authored Modern Psychometrics, a popular textbook, and published over 80 peer-reviewed papers in leading journals including Proceedings of the National Academy of Sciences, Nature Scientific Reports, Machine Learning, Psychological Science, and Journal of Personality and Social Psychology, that have been cited over 11,000 times. His research inspired a cover of The Economist, a 2014 theatre play “Privacy”, multiple TED talks, a video game, and was discussed in thousands of books, press articles, podcasts, and documentaries.