AI lab TL;DR | Derek Slater - What the Copyright Case Against Ed Sheeran Can Teach Us About AI

🔍 In this TL;DR episode, Derek Slater (Proteus Strategies) discusses his recent blog post on the Tech Policy Press website, titled “What the Copyright Case Against Ed Sheeran Can Teach Us About AI”, with the AI lab

📌 TL;DR Highlights

⏲️[00:00] Intro

⏲️[01:11] Q1 - Legal boundaries & creativity:

How to define the boundary between protectable expression and unprotectable building blocks in music & other creative fields?

What lessons does this offer for generative AI?

⏲️[05:13] Q2 - Consent vs. enclosure:

What is enclosure?

How can we balance it with consent in regulating AI tools?

What guiding principles should policymakers follow to not stifle innovation & creativity?

⏲️[09:35] Q3 - Technological impact on art:

What is the long-term impact of generative AI on music & artistic expression, as other technological advances ultimately revolutionised creative industries after an initial backlash?

⏲️[12:18] Wrap-up & Outro

💭 Q1 - Legal boundaries & creativity

🗣️ All creativity builds on the past. All songs are made up of a limited number of notes and chords available to the composers [and] to protect their combination would give Let’s Get It On an impermissible monopoly[, the judge said].

🗣️ Copyright has always allowed certain uses of existing content (...) by drawing lines between protectable expression and unprotectable ideas, facts, and other elements.

🗣️ Rightsholders can demand consent for some uses, but they are not allowed to enclose and cut off the basic building blocks of culture and knowledge.

🗣️ Generative AI: (...) it’s a big statistical analysis of lots and lots of texts to derive rules about syntax and how different concepts are related (...) For music, it’s analysing lots and lots of music to tease out those basic building blocks.

🗣️ [AI training] can’t be reduced to the simplicity of consent (...) because the question is: consent for what? (...) Deriving insights [and] uncopyrightable elements from protectable expression generally can be permissible.

💭 Q2 - Consent vs. enclosure

🗣️ We also recognise downsides to [copyright], (...) meaning the public can no longer freely build on and use it. (...) We’ve always had copyright protection but also limits so that enclosure (...) doesn’t go too far.

🗣️ When is it unethical to stop people from (...) using basic building block[s] of language or music? Because that information, that knowledge, those cultural artefacts, ought to belong to the public.

🗣️ I think from a copyright perspective, the first key principle is: is this protection necessary to encourage creativity (...)? If creativity is already booming, abundant, and would happen anyway (...) then there should not be an issue.

🗣️ When we think about generative AI, these are tools for productivity, for creativity, not for piracy (...). They’re not about simply reusing the works that they were trained on in the outputs. (...) That’s considered a bug, a failure (...) and something to be avoided.

🗣️ When somebody uses [an AI ] tool like Suno or Udio to create a new song, that’s in line with copyright’s purpose. (...) It crosses the line (...) where that output is directly substituting, reusing that communicative expression embodied in some specific work.

💭 Q3 - Technological impact on art

🗣️ One way to think about [AI] is sort of like the synthesizer, computer-generated graphics or Photoshop, where, at first, people said, this is not music, [or] art, and over time, it became integrated into artistic processes in a variety of ways.

🗣️ [2023] Oscar winner, ’Everything Everywhere All at Once’, used the generative AI tool Runway to edit one of its famous scenes. Nobody knew that was generative AI at the time. Nobody said ‘Oh, this is a generative AI movie’, but it was part of their artistic process.

🗣️ It’s acknowledged that generative AI is driving an abundance of creativity. (...) So that fundamentally is not at odds with (...) copyright. I think most of the concerns that people have are...