Human-Content-to-Machine-Data_Final - Flipbook - Page 30
This does not mean the preferences of individual creators are unimportant. In many cases, a
content collection will include works by different contributors. There are different ways in
which stewards of content collections can use CC signals to give force to the expectations of
individual creators, and we9re eager to engage further about this as part of our public
consultation process. We9re observing efforts to understand and deûne community
preferences with keen interest, such as Holly Herndon and Mat Dryhurst9s recent work with
Serpentine Arts Technologies to bring groups of choirists together to determine how they9d
like their works to be used by generative AI models.101
Conceivably, stewards of content could enable individual contributors to select the signals
they want associated with their contributions, similar to the approach being taken by the
social media platform, Bluesky, to enable users to express their own preferences regarding
the reuse of their public posts.102 Using this approach, the full collection would then be
divisible into different datasets with different combinations of signals.
The Relationship between CC Signals, Copyright, and CC
Licenses
As previously stated, we are not conceiving of CC signals as copyright licenses.
As manners for machines, the signals are primarily designed to address the social layer of
data governance. However, when applied by a Declaring Party with copyright authority over
the content, CC signals are likely to have legal implications under copyright law. The precise
effect will depend on the jurisdiction. For example, in the EU, there is a copyright exception
for TDM, including AI training, which can be overridden if a rightsholder
