Belief Offloading in Human-AI Interaction
It addresses the problem of over-reliance on AI for belief formation, which is incremental as it builds on existing cognitive offloading research.
This paper investigates belief offloading, where people form and uphold beliefs by relying on LLMs, potentially harming cognitive skills and behavior. It clarifies boundary conditions and provides a taxonomy with normative implications.
What happens when people's beliefs are derived from information provided by an LLM? People's use of LLM chatbots as thought partners can contribute to cognitive offloading, which can have adverse effects on cognitive skills in cases of over-reliance. This paper defines and investigates a particular kind of cognitive offloading in human-AI interaction, "belief offloading," in which people's processes of forming and upholding beliefs are offloaded onto an AI system with downstream consequences on their behavior and the nature of their system of beliefs. Drawing on philosophy, psychology, and computer science research, we clarify the boundary conditions under which belief offloading occurs and provide a descriptive taxonomy of belief offloading and its normative implications. We close with directions for future work to assess the potential for and consequences of belief offloading in human-AI interaction.