4 papers
Information-thermodynamic principles unveil the response of complex networks to perturbations
Andrea Filippo Beretta, Manlio De Domenico
Understanding how complex networks respond to perturbations is key to uncovering their functional organization. We show that, for a maximum-entropy perturbation prior, standard dif…
Not All Explanations Are Sought: Information-Seeking Psychology for Human-Centered XAI
Andrea Beretta, Salvatore Rinzivillo
This position paper argues that human-centered explainable AI (HCXAI) should incorporate insights from the psychology of information seeking. Drawing on Sharot and Sunstein's frame…
Latent geometry emerging from network-driven processes
Andrea Filippo Beretta, Davide Zanchetta, Sebastiano Bontorin +1
Understanding network functionality requires integrating structure and dynamics, and emergent latent geometry induced by network-driven processes captures the low-dimensional space…
The explanation dialogues: an expert focus study to understand requirements towards explanations within the GDPR
Laura State, Alejandra Bringas Colmenarejo, Andrea Beretta +3
Explainable AI (XAI) provides methods to understand non-interpretable machine learning models. However, we have little knowledge about what legal experts expect from these explanat…