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A Mechanism-Based Approach to Mitigating Harms from Persuasive Generative AI
This has led to growing concerns about harms from AI persuasion and how they can be mitigated, highlighting the need for a systematic study of AI persuasion.
An International Consortium for Evaluations of Societal-Scale Risks from Advanced AI
Given rapid progress toward advanced AI and risks from frontier AI systems (advanced AI systems pushing the boundaries of the AI capabilities frontier), the creation and implementation of AI governance and regulatory schemes deserves prioritization and substantial investment.
Strengthening the EU AI Act: Defining Key Terms on AI Manipulation
The European Union's Artificial Intelligence Act aims to regulate manipulative and harmful uses of AI, but lacks precise definitions for key concepts.
Concept Extrapolation: A Conceptual Primer
This article is a primer on concept extrapolation - the ability to take a concept, a feature, or a goal that is defined in one context and extrapolate it safely to a more general context.
The Influence of Explainable Artificial Intelligence: Nudging Behaviour or Boosting Capability?
This article aims to provide a theoretical account and corresponding paradigm for analysing how explainable artificial intelligence (XAI) influences people's behaviour and cognition.
Solutions to preference manipulation in recommender systems require knowledge of meta-preferences
Iterative machine learning algorithms used to power recommender systems often change people's preferences by trying to learn them.
Recognising the importance of preference change: A call for a coordinated multidisciplinary research effort in the age of AI
We operationalize preference to incorporate concepts from various disciplines, outlining the importance of meta-preferences and preference-change preferences, and proposing a preliminary framework for how preferences change.
