作者
Madiha Zahrah Choksi, David Goedicke
发表日期
2023/4/6
期刊
The Second Workshop on Intelligent and Interactive Writing Assistants, ACM CHI Conference on Human Factors in Computing Systems 2023
出版商
arXiv preprint arXiv:2304.02839
简介
Intelligent or generative writing tools rely on large language models that recognize, summarize, translate, and predict content. This position paper probes the copyright interests of open data sets used to train large language models (LLMs). Our paper asks, how do LLMs trained on open data sets circumvent the copyright interests of the used data? We start by defining software copyright and tracing its history. We rely on GitHub Copilot as a modern case study challenging software copyright. Our conclusion outlines obstacles that generative writing assistants create for copyright, and offers a practical road map for copyright analysis for developers, software law experts, and general users to consider in the context of intelligent LLM-powered writing tools.
引用总数
学术搜索中的文章
MZ Choksi, D Goedicke - Intellectual Property, and Ethics. ArXiv abs/2304.02839, 2023