5 papers
Anthropomorphism in the age of Large Language Models: An overview of potential risks and mitigations
Ismael T. Freire, Marceau Nahon, Maud van Lier +6
Large Language Models (LLMs) and more broadly Artificial Intelligence (AI) systems are often described and understood in human-like terms, a phenomenon known as anthropomorphism. T…
Morality is Contextual: Learning Interpretable Moral Contexts from Human Data with Probabilistic Clustering and Large Language Models
Geoffroy Morlat, Marceau Nahon, Augustin Chartouny +3
A key question in current AI alignment research is how to make AI algorithms learn moral values. Because human morality is highly context-dependent, actions are judged not only by…
Semantic Deception: When Reasoning Models Can't Compute an Addition
Nathaniël de Leeuw, Marceau Nahon, Mathis Reymond +2
Large language models (LLMs) are increasingly used in situations where human values are at stake, such as decision-making tasks that involve reasoning when performed by humans. We…
Strong and weak alignment of large language models with human values
Mehdi Khamassi, Marceau Nahon, Raja Chatila
Minimizing negative impacts of Artificial Intelligent (AI) systems on human societies without human supervision requires them to be able to align with human values. However, most c…
Preliminaries to artificial consciousness: a multidimensional heuristic approach
K. Evers, M. Farisco, R. Chatila +6
The pursuit of artificial consciousness requires conceptual clarity to navigate its theoretical and empirical challenges. This paper introduces a composite, multilevel, and multidi…