People increasingly treat AI systems as if they have minds. This project examines when and how people attribute minds to AI as an interaction of the perceiver's traits and specific behaviors by AI. In The Intentional Stance, Dennett (1987) argues that attributing beliefs and desires to a system is a predictive strategy, not a discovery about its interior. So rather than asking whether AI has a mind or sentience, the project studies which human traits and inference mechanisms lead to mind/sentience attribution and over-ascription of mental capacity. The work combines behavioral experiments and AI capability evaluation to ask why humans infer general cognitive competence from limited and inconsistent AI task success. It also studies how this depends on both traits of the perceiver (e.g., loneliness, need for cognition) and ontological assumptions about digital minds (e.g., life-AI continuity, evolution-AI continuity, extension vs autonomy, mind upload).
Microsoft Research NYC, USA
I’m currently studying perception of mind and human-AI interaction at Princeton University, where I use cognitive neuroscience techniques to investigate brain mechanisms supporting consciousness and perception of mind. Lately, my research has explored behavioral outcomes and how our brains respond when engaging with AI systems, as well as how AI works using mechanistic interpretability methods. Outside of the lab, I’ve been actively involved in projects that promote responsible AI development, driven by both enthusiasm for AI’s potential and a recognition of the ethical concerns it raises.
"I'm most excited by the opportunity to collaborate across philosophy, cognitive science, and machine learning, at a time where questions surrounding AI sentience are becoming increasingly urgent."