M·M/A.I.
Photo of Janet Pauketat
Photo · Jo-Anne McArthur / We Animals
🇺🇸 Remote, USA

Janet Pauketat

Research Fellow · Sentience Institute
Researches Mental models of autonomy & sentience
Mind perceptionMoral consideration of AISentience & autonomySocial psychologyAnimal & AI ethics
About

Janet V. T. Pauketat is a Research Fellow at the Sentience Institute. She holds a PhD in Psychological & Brain Sciences from UC Santa Barbara and a Master of Research from the University of St Andrews, where she studied the psychology of socio-cultural context and morally-expanding capacities of global citizenship.

After her PhD she studied collective emotions in social movements as a postdoctoral research associate at Princeton University. She has worked with researchers at the University of St Andrews on moral values in social movements and at the National University of Singapore on values affecting immigration attitudes.

Her recent work, including a CHI 2026 paper with N = 2,702, disentangles the mental models of autonomy and sentience and shows how each independently shapes mind perception, moral consideration, and perceived threat from AI.

Affiliation: Sentience Institute · prev. UC Santa Barbara, Princeton.

Selected publications

Janet's prior work.

These papers are notsubmissions to the Mental Models of AI workshop. The workshop hasn't happened yet. They are the body of work Janet brings to the committee, verified against personal sites and Google Scholar.

7 entries · 20202026
20261 paper
2026CHI

Mental Models of Autonomy and Sentience Shape Reactions to AI

Janet V. T. Pauketat, Daniel B. Shank, Andrea Manoli, Jacy Reese Anthis
Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems

Three pilot studies and four pre-registered experiments (total N = 2,702) test how distinct mental models of AI shape downstream reactions. Activating sentience increases mind perception and moral consideration; activating autonomy increases perceived threat. Sentience changes reactions more than autonomy on average, and disentangling the two enables more precise human-AI interaction research.

Mind perception of AIDOI ↗PDF ↗
20254 papers
20221 paper
20201 paper