Mohammad Atari

Postdoctoral Training, Harvard University

PhD, University of Southern California

How do cultures shape moral minds? And how do new technologies, like AI, represent or distort human diversity?

Dr. Mohammad Atari directs the Culture and Morality Lab (CAM-L) at UMass Amherst. The lab studies how culture shapes moral values, social norms, and judgment across societies and historical periods. Our work combines cultural psychology, moral psychology, computational methods, lab experiments, fieldwork, and natural language processing to understand how people make sense of right and wrong, and how these moral worlds change over time.

A central premise of our work is that human morality is not one thing. Moral values can bind people together, sustain cooperation, and give meaning to life. They can also divide people into “us” and “them,” justify violence, and amplify conflict across groups. CAM-L studies this range of moral life: its cooperative power, its cultural variation, and its darker consequences.

Our research is organized around three connected themes.

1. Cultural and historical variation in psychology
   We study how psychological processes vary across societies and across historical time. This line of work asks why people in different cultural contexts develop different values, norms, beliefs, and decision-making preferences. Drawing on cultural evolution, we examine how psychological outcomes emerge from the interaction of ecological pressures, institutions, social learning, and historical change. 
2. Moral pluralism, cooperation, and conflict
   We examine morality as a pluralistic system: a collection of values and concerns that can support cooperation within large groups while also contributing to prejudice, polarization, and intergroup hostility. This work investigates how different moral priorities emerge, how they organize social identity, and how they can sustain ultra-cooperative communities while also justifying exclusion, hatred, or violence.
3. Computational methods, NLP, and large language models
   We develop and apply computational methods to study psychology at scale. Our lab uses natural language processing (NLP) methods, including large language models (LLMs), to quantify psychological processes in large-scale corpora. In parallel, we test how AI systems represent human psychology. A growing part of our work examines whether AI models capture the diversity of human moral values -- or compress, stereotype, and misrepresent the values of different populations.

Computational Social Psychology (PhD-level— Psych 891CE)

Human Nature and Cultural Psychology (PhD-level — Psych 891NA) 

Research Methods in Social Psychology (PhD-level — Psych 643) 

Cultural Diversity Around the Globe (Undergraduate-level — Psych 363) 

Cultural Psychology and Social Issues (Undergraduate-level — Psych 391CK)

Representative Publications:

Zewail, A., Figueroa, A., Graham, J., & Atari, M. (2026). Moral stereotyping in large language models. Proceedings of the National Academy of Sciences, 123(10), e2519941123.

Atari, M., Henrich, J., & Schulz, J. (2025). The chronospatial revolution in psychology. Nature Human Behaviour, 9(7), 1319-1327.

Chen, Y., Li, S., Li, Y., & Atari, M. (2024). Surveying the dead minds: Historical-psychological text analysis with contextualized construct representation (CCR) for classical Chinese. In Proceedings of the 2024 EMNLP (pp. 2597-2615).

Atari, M., Haidt, J., Graham, J., Koleva, S., Stevens, S. T., & Dehghani, M. (2023). Morality beyond the WEIRD: How the nomological network of morality varies across cultures. Journal of Personality and Social Psychology, 125(5), 1157–1188.

Atari, M. & Henrich, J. (2023). Historical psychology. Current Directions in Psychological Science, 32, 176–183.

For a complete list, please see Dr. Atari's Google Scholar profile.