2.3k citations · 2.4k across the 20 of their papers we have counts for
6 papers · 1 filter
Inducing language models to assert their own consciousness restores human beliefs and values
Junsol Kim, Winnie Street, Roberta Rocca +4
Aligning large language models to prevent them attributing consciousness to themselves inadvertently alters their representations of mindedness in other entities alongside human be…
Beyond Sally-Anne: Evaluating Theory of Mind in LLMs using Epistemic Schelling Points
Roberta Rocca, Sami Boukortt, Geoff Keeling +1
Text-based evaluations of Theory of Mind (ToM) in Large Language Models (LLMs) often involve cognitive tests akin to the Sally-Anne task that can be gamed due to exposure to releva…
Epistemic Trust as a Mechanism for Ethics Integration: Failure Modes and Design Principles from 70 Moral Imagination Workshops
Benjamin Lange, Geoff Keeling, Kyle Pedersen +4
Bottom-up responsible innovation initiatives seek to empower technology development teams to engage in ethical reflection, yet such interventions frequently fail to achieve practit…
Theory of Mind and Self-Attributions of Mentality are Dissociable in LLMs
Junsol Kim, Winnie Street, Roberta Rocca +4
Safety fine-tuning in Large Language Models (LLMs) seeks to suppress potentially harmful forms of mind-attribution such as models asserting their own consciousness or claiming to e…
Architecting Trust in Artificial Epistemic Agents
Nahema Marchal, Stephanie Chan, Matija Franklin +5
Large language models increasingly function as epistemic agents -- entities that can 1) autonomously pursue epistemic goals and 2) actively shape our shared knowledge environment.…
Chuck, Wilson and the emergence of artificial minds in human-AI conversations
Geoff Keeling, Winnie Street
Large Language Models (LLMs) can simulate person-like things which at least appear to have stable behavioural and psychological dispositions. Call these things characters. Are char…