most citedAddressing Social Misattributions of Large Language Models: An HCXAI-based Approach

3 citations · 3 across the 9 of their papers we have counts for

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cs.AI2026

Convex AI Compositionality and the Governance of AI System Populations

Andrea Ferrario

AI governance increasingly requires providers and public authorities to reason about multiple AI instantiations, alternative versions, and deployment configurations of multiple AI…

cs.AI2026

Tree-Based Formalization of Multi-Agent Complementarity in Human-AI Interactions

Andrea Ferrario

Complementarity is the case in which a human--AI interaction (HAI) outperforms the best prediction benchmark available among its members. Although this idea is central in HAI resea…

cs.AI2026

Epistemology gives a Future to Complementarity in Human-AI Interactions

Andrea Ferrario, Alessandro Facchini, Juan M. Durán

Human-AI complementarity is the claim that a human supported by an AI system can outperform either alone in a decision-making process. Since its introduction in the humanAI interac…

cs.AI2026

A Scoping Review of the Ethical Perspectives on Anthropomorphising Large Language Model-Based Conversational Agents

Andrea Ferrario, Rasita Vinay, Matteo Casserini +1

Anthropomorphisation -- the phenomenon whereby non-human entities are ascribed human-like qualities -- has become increasingly salient with the rise of large language model (LLM)-b…

cs.AI2024★ 3 cited

Addressing Social Misattributions of Large Language Models: An HCXAI-based Approach

Andrea Ferrario, Alberto Termine, Alessandro Facchini

Human-centered explainable AI (HCXAI) advocates for the integration of social aspects into AI explanations. Central to the HCXAI discourse is the Social Transparency (ST) framework…