Abstract
The rapid integration of AI techniques into software engineering introduces both opportunities and risks. This paper presents an empirical study examining the role of AI in software engineering processes, with a focus on responsibility, transparency, and reliability. We analyze practical challenges reported in industry and propose guidelines for building responsible AI-driven systems. Our results highlight the importance of explainability, ethical considerations, and robust evaluation metrics to ensure trust in AI-enabled software engineering practices.
CCS CONCEPTS
Software engineering → Empirical software engineering; • Computing methodologies → Artificial intelligence; • Social and professional topics → Computing / technology policy.
KEYWORDS
Responsible AI, Software Engineering, Empirical Study, Transparency, Ethics
1 INTRODUCTION
Artificial Intelligence (AI) is increasingly embedded in software engineering tasks such as code generation, defect detection, and requirements analysis. While offering productivity gains, these applications raise concerns around bias, reliability, and responsible use. This paper contributes to this discourse by synthesizing key empirical findings from recent studies, identifying challenges, and proposing actionable insights.
2 METHODOLOGY AND RESULTS
Our study builds on industrial case reports and controlled experiments analyzing the integration of AI into software engineering. Key findings indicate: (1) developers often struggle with opaque AI recommendations, (2) current evaluation metrics insufficiently capture ethical implications, and (3) responsible AI requires socio-technical alignment, including stakeholder engagement and continuous monitoring.
3 CONCLUSION
This paper emphasizes that responsible AI in software engineering is not optional but essential. By aligning empirical evidence with ethical guidelines, we outline a path towards sustainable and trustworthy adoption of AI in the software lifecycle. Future work includes developing standardized evaluation frameworks and exploring cross-disciplinary collaborations.
Biography
