Abstract

Many personality tests ask participants hypothetical questions predicting their own behaviours. Yet, as with humans, self-predicted AI behaviour does not always match observed behaviour. In this talk, I will introduce Feedback Forensics: a toolkit to measure AI traits related to personality directly based on observed behaviour data. Comparing model behaviours to the same input relative to each other, our toolkit can measure a diverse set of traits related to the underlying personality, manner, and style of AI responses. I will share results describing traits exhibited by popular AI models as well as detecting the traits encouraged by human feedback. The talk will feature a live demo of our personality visualisation tool and attendees are invited to follow along via our online platform https://feedbackforensics.com/ (laptops are encouraged).

Bio: Arduin is currently a PhD student in the Department of Computer Science in Cambridge working on AI model evaluation. His work focuses on understanding what desirable and undesirable model behaviours are reinforced by human and AI feedback. Prior to joining his current PhD programme, Arduin completed an MPhil in Machine Learning and Machine Intelligence in Cambridge’s Engineering Department. Recently, Arduin also worked on model evaluation within Apple’s Foundation Models team as an intern.