XAI - Science and technology for the explanation of AI decision making (DIT.AD004.097)
Area tematica
Ingegneria, ICT e tecnologie per l'energia e i trasporti
Area progettuale
Dati, Contenuti e Media (DIT.AD004)Struttura responsabile del progetto di ricerca
Istituto di scienza e tecnologie dell'informazione "Alessandro Faedo" (ISTI)
Altre strutture che collaborano al progetto di ricerca
Responsabile di progetto
FOSCA GIANNOTTI
Telefono: 0506212999
E-mail: fosca.giannotti@isti.cnr.it
Abstract
A wealthy friend of mine asks for a vacation credit card to his bank, to discover that the credit he is offered is very low. The bank teller cannot explain why. My stubborn friend continues his quest for explanation up to the bank executives, to discover that an algorithm lowered his credit score. Why? After a long investigation, it turns out that the reason is: bad credit by the former owner of my friend's house. Black box AI systems for automated decision making, often based on ML over (big) data, map a user's features into a class or a score without explaining why. This is problematic for lack of transparency, but also for possible biases inherited by the algorithms from human prejudices and collection artefacts hidden in the training data, which may lead to unfair or wrong decisions. I strive for solutions of the urgent challenge of how to construct meaningful explanations of opaque AI/ML systems, introducing the local-to-global framework for black box explanation, articulated along 3 lines: a) the language for explanations in terms of expressive logic rules, with statistical and causal interpretation; b) the inference of local explanations for revealing the decision rationale
Data inizio attività
01/10/2019
Parole chiave
Artificial intelligence, intelligent systems, multi agent systems, Machine learning,, statistical data processing and applications using signal processing
Ultimo aggiornamento: 09/09/2024