7 papers · 1 filter
FAIRGAME: a Framework for AI Agents Bias Recognition using Game Theory
Alessio Buscemi, Daniele Proverbio, Alessandro Di Stefano +3
Letting AI agents interact in multi-agent applications adds a layer of complexity to the interpretability and prediction of AI outcomes, with profound implications for their trustw…
Can Media Act as a Soft Regulator of Safe AI Development? A Game Theoretical Analysis
Henrique Correia da Fonseca, António Fernandes, Zhao Song +15
When developers of artificial intelligence (AI) products need to decide between profit and safety for the users, they likely choose profit. Untrustworthy AI technology must come pa…
KERAIA: An Adaptive and Explainable Framework for Dynamic Knowledge Representation and Reasoning
Stephen Richard Varey, Alessandro Di Stefano, The Anh Han
In this paper, we introduce KERAIA, a novel framework and software platform for symbolic knowledge engineering designed to address the persistent challenges of representing, reason…
Do LLMs trust AI regulation? Emerging behaviour of game-theoretic LLM agents
Alessio Buscemi, Daniele Proverbio, Paolo Bova +15
There is general agreement that fostering trust and cooperation within the AI development ecosystem is essential to promote the adoption of trustworthy AI systems. By embedding Lar…
Media and responsible AI governance: a game-theoretic and LLM analysis
Nataliya Balabanova, Adeela Bashir, Paolo Bova +15
This paper investigates the complex interplay between AI developers, regulators, users, and the media in fostering trustworthy AI systems. Using evolutionary game theory and large…
Enhancing Cancer Diagnosis with Explainable & Trustworthy Deep Learning Models
Badaru I. Olumuyiwa, The Anh Han, Zia U. Shamszaman
This research presents an innovative approach to cancer diagnosis and prediction using explainable Artificial Intelligence (XAI) and deep learning techniques. With cancer causing n…