Responsible AI in the Software Industry: A Practitioner-Centered Perspective

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 21 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.

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Publication Details

Published
2025-04-29
DOI
https://doi.org/10.1109/raie66699.2025.00011
Citations
1
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
2.37

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article

Responsible AI in the Software Industry: A Practitioner-Centered Perspective

Matheus de Morais Leça, Ronnie de Souza Santos, Mariana Donato
1 citations
Ethics and Social Impacts of AI
2.37
article

Responsible AI in the Software Industry: A Practitioner-Centered Perspective

Matheus de Morais Leça, Ronnie de Souza Santos, Mariana Donato
article en
1 citations

Abstract

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 21 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.

University of Calgary (CA)
Natural Sciences and Engineering Research Council of Canada
Industry, innovation and infrastructure
Openalex Percentile: Top 11%
Ethics and Social Impacts of AI
2.37
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