"So what if I used GenAI?" -- Implications of Using Cloud-based GenAI in Software Engineering Research
Gouri Ginde
TL;DR
The paper investigates the legal and ethical implications of using cloud-based GenAI in software engineering research, focusing on data privacy and copyright concerns. It analyzes how GenAI usage intersects with researcher workflows, scholarly publishing policies, and licensing regimes. The authors propose the Generative AI Transparency & Accountability Evaluation (GATE) checklist to structure disclosure, data legality, ownership, licensing, and compliance. The checklist aims to improve transparency, reproducibility, and liability mitigation for GenAI-assisted research and to stimulate ongoing discussion. Overall, it provides a foundation for responsible adoption of GenAI in SE research and invites iterative refinement of governance practices.
Abstract
Generative Artificial Intelligence (GenAI) advances have led to new technologies capable of generating high-quality code, natural language, and images. The next step is to integrate GenAI technology into various aspects while conducting research or other related areas, a task typically conducted by researchers. Such research outcomes always come with a certain risk of liability. This paper sheds light on the various research aspects in which GenAI is used, thus raising awareness of its legal implications to novice and budding researchers. In particular, there are two risks: data protection and copyright. Both aspects are crucial for GenAI. We summarize key aspects regarding our current knowledge that every software researcher involved in using GenAI should be aware of to avoid critical mistakes that may expose them to liability claims and propose a checklist to guide such awareness.