Giacomo Zanotti
Biographic Data
| ID | 5995327 |
|---|---|
| NAME | Giacomo Zanotti |
| GIVEN NAMES | Giacomo |
| FAMILY NAME | Zanotti |
| SIGNATURE | ZANOTTI G |
| AFFILIATIONS | Politecnico di Milano |
| ORCID | 0000-0001-9898-4113 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 4 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
AI systems should be trustworthy, not trusted
Scientific and public debates on the ethical aspects of AI development and deployment often end up focusing on trust in AI systems, rather than on their trustworthiness. This paper argues that actual trust should not be the focus of the debate in AI ethics or the goal of the responsible design, deployment, and assessment of AI systems. The argument will insist on three distinct—although interrelated—points. First, I will argue that trust is a com…
Keep trusting! A plea for the notion of Trustworthy AI
A lot of attention has recently been devoted to the notion of Trustworthy AI (TAI). However, the very applicability of the notions of trust and trustworthiness to AI systems has been called into question. A purely epistemic account of trust can hardly ground the distinction between trustworthy and merely reliable AI, while it has been argued that insisting on the importance of the trustee’s motivations and goodwill makes the notion of TAI a categ…
AI-Related Risk
Risks connected with AI systems have become a recurrent topic in public and academic debates, and the European proposal for the AI Act explicitly adopts a risk-based tiered approach that associates different levels of regulation with different levels of risk. However, a comprehensive and general framework to think about AI-related risk is still lacking. In this work, we aim to provide an epistemological analysis of such risk building upon the exi…
Physicalism and the burden of parsimony
No prominent works on this page.
Physicalism and the burden of parsimony
Keep trusting! A plea for the notion of Trustworthy AI
A lot of attention has recently been devoted to the notion of Trustworthy AI (TAI). However, the very applicability of the notions of trust and trustworthiness to AI systems has been called into question. A purely epistemic account of trust can hardly ground the distinction between trustworthy and merely reliable AI, while it has been argued that insisting on the importance of the trustee’s motivations and goodwill makes the notion of TAI a categ…
AI-Related Risk
Risks connected with AI systems have become a recurrent topic in public and academic debates, and the European proposal for the AI Act explicitly adopts a risk-based tiered approach that associates different levels of regulation with different levels of risk. However, a comprehensive and general framework to think about AI-related risk is still lacking. In this work, we aim to provide an epistemological analysis of such risk building upon the exi…
AI systems should be trustworthy, not trusted
Scientific and public debates on the ethical aspects of AI development and deployment often end up focusing on trust in AI systems, rather than on their trustworthiness. This paper argues that actual trust should not be the focus of the debate in AI ethics or the goal of the responsible design, deployment, and assessment of AI systems. The argument will insist on three distinct—although interrelated—points. First, I will argue that trust is a com…
Adversarial Robustness in Machine Learning (3 works) · Computer Science (3 works) · Epistemology (3 works) · Philosophy (3 works) · Business (2 works) · Ethics and Social Impacts of AI (2 works) · Philosophy of science (2 works) · Trustworthiness (2 works) · Adversarial system (1 works) · Artificial Intelligence in Healthcare and Education (1 works)