Responsible AI in the Software Industry: A Practitioner-Centered Perspective
Fuente:
arXiv
Salvato in:
| Autori principali: | , , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2024
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866915057184538624 |
|---|---|
| author | Leça, Matheus de Morais Bento, Mariana Santos, Ronnie de Souza |
| author_facet | Leça, Matheus de Morais Bento, Mariana Santos, Ronnie de Souza |
| contents | Responsible AI principles provide ethical guidelines for developing AI systems, yet their practical implementation in software engineering lacks thorough investigation. Therefore, this study explores the practices and challenges faced by software practitioners in aligning with these principles. Through semi-structured interviews with 25 practitioners, we investigated their methods, concerns, and strategies for addressing Responsible AI in software development. Our findings reveal that while practitioners frequently address fairness, inclusiveness, and reliability, principles such as transparency and accountability receive comparatively less attention in their practices. This scenario highlights gaps in current strategies and the need for more comprehensive frameworks to fully operationalize Responsible AI principles in software engineering. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_07620 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Responsible AI in the Software Industry: A Practitioner-Centered Perspective Leça, Matheus de Morais Bento, Mariana Santos, Ronnie de Souza Software Engineering Responsible AI principles provide ethical guidelines for developing AI systems, yet their practical implementation in software engineering lacks thorough investigation. Therefore, this study explores the practices and challenges faced by software practitioners in aligning with these principles. Through semi-structured interviews with 25 practitioners, we investigated their methods, concerns, and strategies for addressing Responsible AI in software development. Our findings reveal that while practitioners frequently address fairness, inclusiveness, and reliability, principles such as transparency and accountability receive comparatively less attention in their practices. This scenario highlights gaps in current strategies and the need for more comprehensive frameworks to fully operationalize Responsible AI principles in software engineering. |
| title | Responsible AI in the Software Industry: A Practitioner-Centered Perspective |
| topic | Software Engineering |
| url | https://arxiv.org/abs/2412.07620 |