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Submission to the UK IPO: Artificial Intelligence and Performers' rights

Authors: Mathilde Pavis;

Submission to the UK IPO: Artificial Intelligence and Performers' rights

Abstract

This submission assesses the impact of Artificial Intelligence (AI) systems on performers’ rights under UK law, provided by the Copyright, Designs and Patents Act 1988. AI systems have introduced ground-breaking changes to the practice of performance synthetisation. Performance synthetisation refers to the manipulation of a performance or performer’s likeness. Performance synthetisation powered by AI (or AI-made performance synthetisation) utilises live or recorded performances protected by performers’ rights as source material. The Act does not protect performers and other stakeholders against AI-made performance synthetisation because the application of its provisions to this type of activity is unclear. Performers and other stakeholders are thus left exposed by the current intellectual property (IP) framework. This sector of the creative economy is ill-equipped to adapt to the changes brought by AI systems to their industry. Performance synthetisation created using AI systems raises novel legal questions on the subsistence and infringement framework for performers’ rights. Some of these questions are unique to performers’ rights (as opposed to copyright or other related rights). AI-made performance synthetisation challenges our intellectual property framework insofar as it is capable of reproducing performances without generating a ‘recording’ or a ‘copy’ of a recording. This technical distinction between the reproduction of a performance, the recording of a performance and the reproduction (or copy) of that recording is important. The Act does not grant protection against unauthorized reproductions of a performance. Instead, the Act controls the recording of a performance, and the copy of that recording. The current scope of the Act means that performers and other relevant stakeholders are left unprotected against the unauthorised synthetisation of their performances. Without the legal recognition of these rights, performers are also unable to form contracts to authorise the synthetisation of their performance or likeness. As a result, performers are unable to commercialise the synthetisation of their own performance effectively. The legal recognition of these rights is therefore paramount to supporting performers and other relevant stakeholders in adapting to the changes that AI systems will bring to their industry. For these reasons, UK policy-makers should review the impact of AI systems on performers’ rights, particularly in relation to performance synthetisation. Any review should aim to improve the legal protections for performers and others invested in the making of performances. This reform closes an existing gap in UK law. This reform is the opportunity to establish the UK as a forward-thinking global leader on the legal protection of performers. This submission was written by Dr Mathilde Pavis (University of Exeter, UK) in response to the call for views on Artificial Intelligence and Intellectual Property issued by UK Intellectual Property in September 2020.

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United Kingdom
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Keywords

340, performers' rights, synthetisation, Deep fakes, intellectual property, artificial intelligence, performance, Neural networks

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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