Giovanni Sileno
Biographic Data
| ID | 6362113 |
|---|---|
| NAME | Giovanni Sileno |
| GIVEN NAMES | Giovanni |
| FAMILY NAME | Sileno |
| SIGNATURE | SILENO G |
| AFFILIATIONS | University of Amsterdam |
| ORCID | 0000-0001-5155-9021 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 5 |
| WORKS AS AUTHOR | 4 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 1 |
Analysing and organising human communications for AI fairness assessment
Algorithms used in the public sector, e.g., for allocating social benefits or predicting fraud, often require involvement from multiple stakeholders at various phases of the algorithm’s life-cycle. This paper focuses on the communication issues between diverse stakeholders that can lead to misinterpretation and misuse of algorithmic systems. Ethnographic research was conducted via 11 semi-structured interviews with practitioners working on algori…
On mapping values in AI Governance
We propose here a conceptual framework by which to analyze legal-regulatory problematics of algorithmic decision-making systems, focusing on mechanisms of value production in their design and deployment. An aim of our intervention is to develop an investigative model for application to algorithmic decision systems with regulatory effects, including predictive artificial intelligence applications and recommender systems that filter data and sugges…
Smart contracts
A smart contract is code deployed in a blockchain environment, or the source code from which such code was compiled
Mapping Value(s) in Ai
This paper presents a multidisciplinary approach (media studies, computer science, and legal scholarship) for the analysis of systems that rely on AI components as central components of their design. Taking recommender systems more generally and the one built by YouTube more specifically, we develop a methodology for conceptualizing and studying the broad array of “ideas”, “norms”, or “values” such systems mobilize. Instead of limiting ourselves …
On mapping values in AI Governance
We propose here a conceptual framework by which to analyze legal-regulatory problematics of algorithmic decision-making systems, focusing on mechanisms of value production in their design and deployment. An aim of our intervention is to develop an investigative model for application to algorithmic decision systems with regulatory effects, including predictive artificial intelligence applications and recommender systems that filter data and sugges…
Mapping Value(s) in Ai
This paper presents a multidisciplinary approach (media studies, computer science, and legal scholarship) for the analysis of systems that rely on AI components as central components of their design. Taking recommender systems more generally and the one built by YouTube more specifically, we develop a methodology for conceptualizing and studying the broad array of “ideas”, “norms”, or “values” such systems mobilize. Instead of limiting ourselves …
Smart contracts
A smart contract is code deployed in a blockchain environment, or the source code from which such code was compiled
On mapping values in AI Governance
We propose here a conceptual framework by which to analyze legal-regulatory problematics of algorithmic decision-making systems, focusing on mechanisms of value production in their design and deployment. An aim of our intervention is to develop an investigative model for application to algorithmic decision systems with regulatory effects, including predictive artificial intelligence applications and recommender systems that filter data and sugges…
Analysing and organising human communications for AI fairness assessment
Algorithms used in the public sector, e.g., for allocating social benefits or predicting fraud, often require involvement from multiple stakeholders at various phases of the algorithm’s life-cycle. This paper focuses on the communication issues between diverse stakeholders that can lead to misinterpretation and misuse of algorithmic systems. Ethnographic research was conducted via 11 semi-structured interviews with practitioners working on algori…
Computer Science (3 works) · Ethics and Social Impacts of AI (3 works) · Business (2 works) · Knowledge management (2 works) · Computer security (1 work) · Data science (1 work) · Digital Economy and Work Transformation (1 work) · Experiential learning (1 work) · FinTech, Crowdfunding, Digital Finance (1 work) · Insurance and Financial Risk Management (1 work)