Balancing innovation with fairness: What transparency in AI means for copyright law

Artificial intelligence is increasingly the subject of costly litigation around the world, particularly in the realm of copyright and intellectual property. Copyright and AI — specifically generative AI — is usually framed as a battle between model developers seeking to innovate versus creatives and other rightsholders who are afraid of having their work exploited at their expense. Jurisdictions are reacting to the rapid rise of AI in this field by issuing guidance, publishing judicial opinions, and conducting public consultations to explore potential solutions, frequently highlighting the importance of increased transparency and traceability. But, in the realm of intellectual property, how can transparency be achieved without skewing the existing balance of competing interests between rightsholders and AI developers?

The U.S. National Institute of Standards and Technology defines transparency as "a property of openness and accountability throughout the supply chain." In the context of AI, NIST treats transparency as one of several properties that characterize a trustworthy, responsible system. These principles, which also include explainability, interpretability and accountability, work together to build trust and ensure fairness and lawfulness. In the context of copyright, transparency can promote a "fair and equitable sharing of benefits" for rightsholders, who want to be credited and compensated for their work, and developers, who rely on quality data for training purposes. But, as NIST's AI Risk Management Framework notes, the level of transparency and information availability will vary depending on the stage of the AI lifecycle in question.