Topic: deception

Yoshua Bengio discusses risks arising when general-purpose AI agents autonomously pursue goals, including misuse, deception and loss of human control. He presents Scientist AI as a proposed non-agentic alternative combining a model that explains observations with question-answering inference. Explicit uncertainty is central to its design, with potential applications in scientific research and assessing other AI systems.

I my talk I will give an overview of recent research on deception and concealed information detection. I will start with a short introduction on the problems and shortcomings of traditional deception detection tools and why those still prevail in many recent approaches (e.g., in AI-based deception detection). I want to argue for the importance of more fundamental deception research and give some examples for insights gained therefrom. In the second part of the talk, I will introduce the Concealed Information Test (CIT), a promising paradigm for research and applied contexts to investigate whet