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Ethics of Software Programming with Generative AI: Is Programming without Generative AI always radical?

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arxiv 2408.10554 v2 pith:UV5FGZCS submitted 2024-08-20 cs.SE

classification cs.SE
keywords genaisoftwarecodeethicalgenerativeprogrammingwritingapproach
verification ladder T0 review T1 audit T2 compute T3 formal
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This paper provides a comprehensive analysis of Generative AI (GenAI) potential to revolutionise software coding through increased efficiency and reduced time span for writing code. It acknowledges the transformative power of GenAI in software code generation, while also cautioning against the inherent risks of bias and errors if left unchecked. Emphasising the irreplaceable value of traditional programming, it posits that GenAI is not a replacement but a complementary tool for writing software code. Ethical considerations are paramount with the paper advocating for stringent ethical guidelines to ensure GenAI serves the greater good and does not compromise on accountability in writing software code. It suggests a balanced approach, combining human oversight with AI's capabilities, to mitigate risks and enhance reliability. The paper concludes by proposing guidelines for GenAI utilisation in coding, which will empower developers to navigate its complexities and employ it responsibly. This approach addresses current ethical concerns and sets a foundation for the judicious use of GenAI in the future, ensuring its benefits are harnessed effectively while maintaining moral integrity.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. The Effects of GitHub Copilot on Computing Students' Programming Effectiveness, Efficiency, and Processes in Brownfield Programming Tasks

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  2. Single Conversation Methodology: A Human-Centered Protocol for AI-Assisted Software Development

    cs.SE 2025-07 conditional novelty 5.0 of 10

    Proposes a structured protocol for LLM-assisted development that keeps requirements, code, and documentation inside a single persistent conversation to preserve human oversight and traceability.

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