Flavia Barsotti
Biographic Data
| ID | 9294093 |
|---|---|
| NAME | Flavia Barsotti |
| GIVEN NAMES | Flavia |
| FAMILY NAME | Barsotti |
| SIGNATURE | BARSOTTI F |
| AFFILIATIONS | ING Bank |
| ORCID | 0000-0002-7567-2640 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
MinMax fairness
This paper presents an intuitive explanation about why and how Rawlsian Theory of Justice (Rawls in A theory of justice, Harvard University Press, Harvard, 1971) provides the foundations to a solution for algorithmic bias. The contribution of the paper is to discuss and show why Rawlsian ideas in their original form (e.g. the veil of ignorance , original position , and allowing inequalities that serve the worst-off) are relevant to operationalize…
Ethical implications of fairness interventions
The importance of fairness in machine learning models is widely acknowledged, and ongoing academic debate revolves around how to determine the appropriate fairness definition, and how to tackle the trade-off between fairness and model performance. In this paper we argue that besides these concerns, there can be ethical implications behind seemingly purely technical choices in fairness interventions in a typical model development pipeline. As an e…
No prominent works on this page.
Ethical implications of fairness interventions
The importance of fairness in machine learning models is widely acknowledged, and ongoing academic debate revolves around how to determine the appropriate fairness definition, and how to tackle the trade-off between fairness and model performance. In this paper we argue that besides these concerns, there can be ethical implications behind seemingly purely technical choices in fairness interventions in a typical model development pipeline. As an e…
MinMax fairness
This paper presents an intuitive explanation about why and how Rawlsian Theory of Justice (Rawls in A theory of justice, Harvard University Press, Harvard, 1971) provides the foundations to a solution for algorithmic bias. The contribution of the paper is to discuss and show why Rawlsian ideas in their original form (e.g. the veil of ignorance , original position , and allowing inequalities that serve the worst-off) are relevant to operationalize…
Computer Science (2 works) · Economics (2 works) · Ethics and Social Impacts of AI (2 works) · Management science (2 works) · Adversarial Robustness in Machine Learning (1 work) · Artificial Intelligence (1 work) · Blockchain Technology Applications and Security (1 work) · Economic Justice (1 work) · Epistemology (1 work) · Explainable Artificial Intelligence (XAI (1 work)