Filling the governance vacuum related to the use of information commons for AI training

More research is needed in this context to understand the relationship between research institutions and commercial entities, particularly in light of the excep -tions for non-commercial and research uses.

dealing with bad actors and reducing harm is not the same as in -centivizing good actors to establish best practices and good dataset governance.

There are con -cerns about the responsibilities of researchers and developers who use publicly available data to build AI. Copyright measures are not the best way to address these issues, and open licensing is not the best way to safeguard digital rights and uphold ethical behavior. To address the factors that contributed to the misuse of open cont... See more

In its opinion on the case from 2021 , Creative Commons acknowledged that “The legal uncertainty caused by ethical concerns around AI, the lack of transparency of AI algorithms, and the patterns of privatization and enclosure of AI outputs, all together constitute yet another obstacle to better sharing. 4

Specific AI system regulations, such as the European AI Act or the AI Bill of Rights in the United States (both of which have yet to be adopted), may include rules that govern the development and management of AI training datasets. Other laws are also applicable. The Digital Services Act, recently adopted in the European Union, requires platforms t... See more

cases of obvious harm should be distinguished from those in which there is a sense of potential harm, or the issue is one of the unexpected uses

An alternative process entails introducing additional rules and limits to reuse while adhering to the general vision of the commons. Such a more robust form of commons-based ordering has often not been considered a form of openness in the past 3 . It involves harnessing non-copyright-based tools, introducing other legal mechanisms, and considering ... See more

This awareness is well expressed by Creative Commons, in the organization’s 2020-2025 strategy is based on a vision of better sharing 1 : “In order to protect what we have achieved so far and to create the world we want to see, we must expand our focus beyond copyright licensing, because content sharing cannot be decoupled from economic or ethical ... See more

In one scenario, these conditions would be personalized by each entity sharing their works through tools that allow them to express motivations for sharing. This path is currently being explored by the new responsible AI licenses introduced in 2022, and their creators envision a proliferation of licensing conditions chosen by licensors 5