9 citations · 10 across the 6 of their papers we have counts for
3 papers · 1 filter
I-SAFE: Wasserstein Coherence Metrics for Structural Auditing of Scientific AI Models
Barbara Tarantino, Gennaro Auricchio, Paolo Giudici
Deep learning models are increasingly used in scientific prediction tasks where strong benchmark performance is often interpreted as evidence of scientifically meaningful behavior.…
ISAAC: Auditing Causal Reasoning in Deep Models for Drug-Target Interaction
Barbara Tarantino, Sun Kim, Yijingxiu Lu +1
Deep learning models for drug--target interaction (DTI) prediction often achieve strong benchmark performance without necessarily relying on mechanistically meaningful molecular fe…
A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms
Gavin Abercrombie, Djalel Benbouzid, Paolo Giudici +13
This paper introduces a collaborative, human-centred taxonomy of AI, algorithmic and automation harms. We argue that existing taxonomies, while valuable, can be narrow, unclear, ty…