Responsible Generative AI for Software Development Life Cycle

Software practitioners are driving a paradigm shift in software engineering practices by integrating generative AI technology into software development and lifecycle management. Integration of generative AI to plan, design, develop, test and maintain software brings productivity gains and enables rapid software releases, however it also presents ethical challenges. This paper examines strategies for developing software through integration of responsible Generative AI that endures, emphasizing primarily the ethical considerations, and the responsible use of Generative technology. It covers the benefits and challenges of collaborative development with responsible Generative AI technologies. The paper focuses on responsible use of generative AI considerations which are likely to induce software integrity and trust. The paper presents best practices, audits, assessments and benchmarking concepts for Gen AI integrated software development and lifecycle management. Subsequently, the paper highlights the importance of safeguarding the integrity of the software development lifecycle through incorporating responsible AI principles, mainly fairness, bias mitigation, privacy and data security, transparency and accountability. Lastly, presenting recommendation for built-in and add-on capabilities for responsible use of GenAI integration into SDLC which paves the way to the trusted ecosystem of GenAI integration for software practitioners.