3 citations · 4 across the 5 of their papers we have counts for
5 papers · 1 filter
The Impossibility of Eliciting Latent Knowledge
Korbinian Friedl, Francis Rhys Ward, Paul Yushin Rapoport +2
Advanced AI systems have extensive knowledge of their environments; in fact, their knowledge may (far) exceed that of their developers or users. Consequently, a desirable property…
The Reasons that Agents Act: Intention and Instrumental Goals
Francis Rhys Ward, Matt MacDermott, Francesco Belardinelli +2
Intention is an important and challenging concept in AI. It is important because it underlies many other concepts we care about, such as agency, manipulation, legal responsibility,…
Honesty Is the Best Policy: Defining and Mitigating AI Deception
Francis Rhys Ward, Francesco Belardinelli, Francesca Toni +1
Deceptive agents are a challenge for the safety, trustworthiness, and cooperation of AI systems. We focus on the problem that agents might deceive in order to achieve their goals (…
Experiments with Detecting and Mitigating AI Deception
Ismail Sahbane, Francis Rhys Ward, C Henrik Åslund
How to detect and mitigate deceptive AI systems is an open problem for the field of safe and trustworthy AI. We analyse two algorithms for mitigating deception: The first is based…
Argumentative Reward Learning: Reasoning About Human Preferences
Francis Rhys Ward, Francesco Belardinelli, Francesca Toni
We define a novel neuro-symbolic framework, argumentative reward learning, which combines preference-based argumentation with existing approaches to reinforcement learning from hum…