6. Cross-cutting design questions 
The workshops brie ﬂy touched on several cross-cutting design questions. While most 
relevant for approaches that depend on limitations and exceptions, considerations of these 
questions may be relevant across both tracks. 
Would authors, publishers, and other relevant rightsholders 
and creators have any ability to exclude their works? 
One of the greatest sources of controversy in this area is the extent to which rightsholders of 
copyrighted works, as well as the original creators of such works (e.g., book authors in this 
context), should be able to prevent use of their works for AI training. 
While a system that required a ﬃrmative “opt-in” consent would limit utility signi ﬁcantly (as 
discussed above in the context of directly licensing works), a system that allowed some 
forms of “opt-out” could still be quite useful to some types of AI development. In the context 
of use cases like development of LLMs, the performance impact may not be so signi ﬁcant. 
Since most in-copyright books are not actively managed, the majority of books would remain 
in the corpus by default. The performance of LLMs can still be improved across various 
dimensions without including, for example, the most famous writers or those who continue 
to commercially exploit their works and may choose to exercise an opt-out. Perhaps the 
potential for licensing relationships (and revenue) may induce some rightsholders to come 
forward and begin actively managing their works. In such a case, uses that do require a 
license may once again become more feasible once the rightsholder can be reached.  
Workshop participants discussed different types of opt-outs that could be built. For example,  
opt-outs could be thought of not in blanket terms, but only as applied to certain uses, for 
example to commercial uses of the corpus, but not research uses. This could build on or 
mirror the approach that the EU has taken in its text and data mining exceptions to 
copyright.  Opt-outs might be more granular, by focusing on allowing or forbidding particular 38
uses or other categories of users, given that rights holders have many different sets of 
preferences. 
Another question is about who can opt-out particular works from the dataset. This could 
solely be an option for copyright holders, although authors might be allowed to exercise an 
opt-out for their books even if they don’t hold the copyrights. This might create challenges if 
the author and rightsholder disagree about whether to opt a particular book out of the 
corpus. Another related issue is that individual books, such as anthologies, may comprise 
works created (and rights held) by many different entities. The images in a book may have 
come from third-party sources, for instance, or a compendium of poetry might involve many 
 In fact, as noted above, to the extent an AI model developer intends for their model to abide by the 38
EU’s legal regime, they will have to abide by such opt-outs, at least if they are engaged in text and data 
mining for commercial uses and/or are users outside of the covered set of research and heritage 
institutions. A books data commons may incorporate opt-outs in particular to serve such EU-focused AI 
developers.
Towards a Books Data Commons for AI Training 17