  Language models may memorize more than just facts, including entire chunks of
texts seen during training. Fair use exemptions to copyright laws typically
allow for limited use of copyrighted material without permission from the
copyright holder, but typically for extraction of information from copyrighted
materials, rather than {\em verbatim} reproduction. This work explores the
issue of copyright violations and large language models through the lens of
verbatim memorization, focusing on possible redistribution of copyrighted text.
We present experiments with a range of language models over a collection of
popular books and coding problems, providing a conservative characterization of
the extent to which language models can redistribute these materials. Overall,
this research highlights the need for further examination and the potential
impact on future developments in natural language processing to ensure
adherence to copyright regulations. Code is at
\url{https://github.com/coastalcph/CopyrightLLMs}.
