Ethical Considerations in AI-Driven Software Development Life Cycle

Abstract

This chapter delves into the ethical challenges of incorporating AI technologies into the software development lifecycle (SDLC). As AI tools increasingly automate decisions from requirements analysis to deployment, developers and stakeholders face critical issues related to bias, fairness, accountability, transparency, and data privacy. It highlights ethical risks, such as biased algorithms and data misuse, while stressing the importance of maintaining a balance between automation and human oversight. The environmental impact of large-scale AI systems is also discussed, alongside strategies for sustainable development. Through case studies, the chapter showcases instances where ethical considerations were overlooked, resulting in negative outcomes. A comprehensive framework for ethical compliance is provided, emphasizing bias mitigation, transparency, privacy safeguards, and accountability. Ultimately, the chapter advocates for proactive ethical measures to ensure AI enhances software development while upholding societal values, individual rights, and environmental sustainability.

Ähnliche Arbeiten