5 papers
Automatic Causal Fairness Analysis with LLM-Generated Reporting
Alessia Berarducci, Eric Rossetto, Alessandro Antonucci +1
AutoML, intended as the process of automating the application of machine learning to real-world problems, is a key step for AI popularisation. Most AutoML frameworks are not accoun…
Why AI Safety Requires Uncertainty, Incomplete Preferences, and Non-Archimedean Utilities
Alessio Benavoli, Alessandro Facchini, Marco Zaffalon
How can we ensure that AI systems are aligned with human values and remain safe? We can study this problem through the frameworks of the AI assistance and the AI shutdown games. Th…
Connecting classical finite exchangeability to quantum theory
Alessio Benavoli, Alessandro Facchini, Marco Zaffalon
Exchangeability is a fundamental concept in probability theory and statistics. It allows to model situations where the order of observations does not matter. The classical de Finet…
The AI off-switch problem as a signalling game: bounded rationality and incomparability
Alessio Benavoli, Alessandro Facchini, Marco Zaffalon
The off-switch problem is a critical challenge in AI control: if an AI system resists being switched off, it poses a significant risk. In this paper, we model the off-switch proble…
dynoGP: Deep Gaussian Processes for dynamic system identification
Alessio Benavoli, Dario Piga, Marco Forgione +1
In this work, we present a novel approach to system identification for dynamical systems, based on a specific class of Deep Gaussian Processes (Deep GPs). These models are construc…