Developer Perspectives on Licensing and Copyright Issues Arising from Generative AI for Software Development
Trevor Stalnaker, Nathan Wintersgill, Oscar Chaparro, Laura A. Heymann, Massimiliano Di Penta, Daniel M German, Denys Poshyvanyk

TL;DR
This study surveys 574 developers to understand their perspectives on licensing, copyright, and legal issues related to using Generative AI for coding, providing insights for future regulation.
Contribution
It offers the first comprehensive survey and analysis of developers' views on legal and licensing issues of GenAI in software development.
Findings
Developers see benefits in using GenAI for coding.
Many view AI-generated code as similar to existing code.
Concerns about data leakage and ownership rights are prevalent.
Abstract
Despite the utility that Generative AI (GenAI) tools provide for tasks such as writing code, the use of these tools raises important legal questions and potential risks, particularly those associated with copyright law. As lawmakers and regulators engage with those questions, the views of users can provide relevant perspectives. In this paper, we provide: (1) a survey of 574 developers on the licensing and copyright aspects of GenAI for coding, as well as follow-up interviews; (2) a snapshot of developers' views at a time when GenAI and perceptions of it are rapidly evolving; and (3) an analysis of developers' views, yielding insights and recommendations that can inform future regulatory decisions in this evolving field. Our results show the benefits developers derive from GenAI, how they view the use of AI-generated code as similar to using other existing code, the varied opinions they…
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Taxonomy
MethodsAttentive Walk-Aggregating Graph Neural Network
