  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.
