Nature Reviews Psychology invited six researchers from cognitive science, clinical psychology, social psychology, language science and public health to share their perspectives on current and future uses of generative artificial intelligence, including its impacts on research and humankind.
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Monojit Choudhury is a Professor of Natural Language Processing at Mohamed Bin Zayed University of Artificial Intelligence, before which he was a Principal Researcher at Microsoft Research. His work focuses on fostering more inclusive language technologies, particularly for under-represented languages and cultures. His interests also extend to AI ethics and safety, and he has been an outspoken critic of the Western-centric bias that pervades much of AI and the AI alignment discourse.
Zohar Elyoseph is a licensed educational psychologist and Associate Professor (proposed rank) at the University of Haifa. An expert in AI in mental health, he researches aspects including basic capabilities, ethics and applications in treatment and training. He holds a BA in Psychology from the Open University, and an MA and PhD in Psychology from Tel Aviv University. He is also a visiting researcher at Imperial College London, Faculty of Medicine.
Nathanael J. Fast is an Associate Professor of Management and Organization and Director of the USC Neely Center for Ethical Leadership and Decision Making at the USC Marshall School of Business. He studies ethical power and leadership, examining how individuals change — and are changed by — social hierarchies, networks and AI-driven technologies. He earned his PhD in Organizational Behavior at Stanford University.
Desmond C. Ong is an Assistant Professor of Psychology at the University of Texas at Austin. He is a cognitive scientist and affective scientist whose expertise is in emotions, reasoning and AI (including natural language processing, probabilistic programming and affective computing). He is also interested in AI ethics especially with respect to emotion AI and led the introduction of Ethical Impact Statements for the IEEE Affective Computing and Intelligent Interaction conference.
Elaine O. Nsoesie is an Associate Professor and data scientist at Boston University’s School of Public Health. She has expertise in the application of data science methods including artificial intelligence to global health problems. Specifically, she develops approaches and tools that use data from non-traditional public health data sources (such as mobile phones, satellites and social media) for public health surveillance and to advance health equity. Her research has been published in major public health and medical journals, including The Lancet, JAMA and Nature family of journals.
Ellie Pavlick is an Associate Professor of Computer Science and Linguistics at Brown University. She studies computational models of language and is currently focused on understanding how LLMs work ‘under the hood’ and in how artificial intelligence resembles and differs from human intelligence. She earned her PhD in Computer and Information Science in 2017 from the University of Pennsylvania.
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Choudhury, M., Elyoseph, Z., Fast, N.J. et al. The promise and pitfalls of generative AI. Nat Rev Psychol 4, 75–80 (2025). https://doi.org/10.1038/s44159-024-00402-0
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DOI: https://doi.org/10.1038/s44159-024-00402-0
