Intellectual Property Office focuses on the impact of AI on the global IP framework
What happened: The Intellectual Property Office has published its 2019–20 plan and has included the impact of AI on the global IP framework as one of their yearly focuses.
They will explore how AI will affect IP rights both conceptually and in operational enforcement. They will do this through a conference with the World Intellectual Property Office, seminars with universities and industry across the UK, and utilising the Regulators’ Pioneer Fund to explore how AI can be used in the IP filling process.
They plan to publish a report setting out their understanding of AI’s impact of the IP framework, and their key questions and actions, by March 2020.
Why this matters: AI systems can already generate new works theoretically protectable by copyright, such as creating new artwork or music. For example, only this week OpenAI has released MuseNet. Under current UK copyright laws, the legal author of computer-generated literary, dramatic, musical or artistic works is the person “by whom the arrangements necessary for the creation of the work are undertaken.”
But who is this? If all the data and models are produced by a single individual or company, its pretty clear; but when different groups have generated the data, designed the model and trained the model, things become increasingly difficult to untangle. And at when systems can start to generate their own data and design their own architecture, at what point was a living human necessary for the creation of the work? This may make it difficult to monetise the output of sufficiently automated output generation under current rules, either through complex distribution of ownership or outright uncertainty whether the work can be attributed to any human author at all.
However, any new IP regulation needs to be mindful for the potential to entrench inequality. If IP rights for large-scale auto-generated content belong to the developers of the model, and they are able to generate vast amount of monetisable content compared to traditional content producers, then it risks exacerbating concentrations of wealth and capital in the creative fields. If copyright and patent were originally intended as incentives and rewards for the effort and skill required to produce outputs, but automate systems can produce vast amounts of novel content at relatively low unit costs, perhaps time-limited protections shouldn’t apply at all.