45 citations · 204 across the 11 of their papers we have counts for
11 papers
A Survey on Methods and Metrics for the Assessment of Explainability under the Proposed AI Act
Francesco Sovrano, Salvatore Sapienza, Monica Palmirani +1
This study discusses the interplay between metrics used to measure the explainability of the AI systems and the proposed EU Artificial Intelligence Act. A standardisation process i…
Making Things Explainable vs Explaining: Requirements and Challenges under the GDPR
Francesco Sovrano, Fabio Vitali, Monica Palmirani
The European Union (EU) through the High-Level Expert Group on Artificial Intelligence (AI-HLEG) and the General Data Protection Regulation (GDPR) has recently posed an interesting…
Generating User-Centred Explanations via Illocutionary Question Answering: From Philosophy to Interfaces
Francesco Sovrano, Fabio Vitali
We propose a new method for generating explanations with AI and a tool to test its expressive power within a user interface. In order to bridge the gap between philosophy and human…
From Philosophy to Interfaces: an Explanatory Method and a Tool Inspired by Achinstein's Theory of Explanation
Francesco Sovrano, Fabio Vitali
We propose a new method for explanations in Artificial Intelligence (AI) and a tool to test its expressive power within a user interface. In order to bridge the gap between philoso…
Modelling GDPR-Compliant Explanations for Trustworthy AI
Francesco Sovrano, Fabio Vitali, Monica Palmirani
Through the General Data Protection Regulation (GDPR), the European Union has set out its vision for Automated Decision- Making (ADM) and AI, which must be reliable and human-centr…
An Objective Metric for Explainable AI: How and Why to Estimate the Degree of Explainability
Francesco Sovrano, Fabio Vitali
Explainable AI was born as a pathway to allow humans to explore and understand the inner working of complex systems. However, establishing what is an explanation and objectively ev…