Robert Gianni
Biographic Data
| ID | 6731334 |
|---|---|
| NAME | Robert Gianni |
| GIVEN NAMES | Robert |
| FAMILY NAME | Gianni |
| SIGNATURE | GIANNI R |
| AFFILIATIONS | Maastricht University |
| ORCID | 0000-0001-6192-0511 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 1 |
| FIRST PUBLICATION YEAR | 2016 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
AI ethics after generative AI: From consequences to effects
Large language model (LLM)-based applications are becoming increasingly integrated into everyday practices of communication, learning, and creativity. Their widespread adoption has intensified debates in AI ethics concerning how their societal significance should be understood and evaluated. Existing approaches to AI ethics have developed important concepts and governance frameworks for evaluating the consequences of AI systems, particularly in r…
Navigating many voices: Lessons for Elsa/RRI from the pragmatist perspective of Elsa-by-design
The societal uptake of AI has led to a proliferation of AI ethics guidelines that prescribe universal principles for ethical AI. However, these guidelines face limitations as the abstract nature of principles makes it difficult to translate them into practice and risks interpretations that allow for ethics-washing. Context sensitive frameworks, such as ELSA, RRI and VSD, are more attuned to the context-specificity required in AI development. Howe…
Responsible Research and Innovation: From Concepts to Practices
Responsibility and Freedom: The Ethical Realm of RRI
No prominent works on this page.
Responsibility and Freedom: The Ethical Realm of RRI
Responsible Research and Innovation: From Concepts to Practices
Navigating many voices: Lessons for Elsa/RRI from the pragmatist perspective of Elsa-by-design
The societal uptake of AI has led to a proliferation of AI ethics guidelines that prescribe universal principles for ethical AI. However, these guidelines face limitations as the abstract nature of principles makes it difficult to translate them into practice and risks interpretations that allow for ethics-washing. Context sensitive frameworks, such as ELSA, RRI and VSD, are more attuned to the context-specificity required in AI development. Howe…
AI ethics after generative AI: From consequences to effects
Large language model (LLM)-based applications are becoming increasingly integrated into everyday practices of communication, learning, and creativity. Their widespread adoption has intensified debates in AI ethics concerning how their societal significance should be understood and evaluated. Existing approaches to AI ethics have developed important concepts and governance frameworks for evaluating the consequences of AI systems, particularly in r…
Political science (2 works) · Pragmatism (2 works) · Research (2 works) · Action (physics) (1 works) · Art (1 works) · Artificial Intelligence in Healthcare and Education (1 works) · Biotechnology and Related Fields (1 works) · Business (1 works) · Computational and Text Analysis Methods (1 works) · Corporate governance (1 works)