Whose Text Is It Anyway? Exploring BigCode, Intellectual Property, and Ethics

Autor:	Choksi, Madiha Zahrah, Goedicke, David
Rok vydání:	2023
Předmět:	Computer Science - Computers and Society Computer Science - Artificial Intelligence K.4.1
Druh dokumentu:	Working Paper
Popis:	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. Comment: 3 pages, submitted to the Second Workshop on Intelligent and Interactive Writing Assistants co-located with the ACM CHI Conference on Human Factors in Computing Systems (CHI 2023)
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2304.02839 Zobrazit plný text záznamu View this record from Arxiv