https://www.economist.com/business/2023/03/15/a-battle-royal-is-brewing-over-copyright-and-ai

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Business | Schumpeter

A battle royal is brewing over copyright and AI

Beware the Napster precedent

[20230318_W]
Mar 15th 2023
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Consider two approaches in the music industry to artificial
intelligence (AI). One is that of Giles Martin, son of Sir George
Martin, producer of the Beatles. Last year, in order to remix the Fab
Four's 1966 album "Revolver", he used AI to learn the sound of each
band member's instruments (eg, John Lennon's guitar) from a mono
master tape so that he could separate them and reverse engineer them
into stereo. The result is glorious. The other approach is not bad
either. It is the response of Nick Cave, a moody Australian
singer-songwriter, when reviewing lyrics written in his style by Chat
GPT, an AI tool developed by a startup called OpenAI. "This song
sucks," he wrote. "Writing a good song is not mimicry, or
replication, or pastiche, it is the opposite. It is an act of
self-murder that destroys all one has strived to produce in the
past."

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Mr Cave is unlikely to be impressed by the latest version of the
algorithm behind ChatGPT, dubbed GPT-4, which OpenAI unveiled on
March 14th. Mr Martin may find it useful. Michael Nash, chief digital
officer at Universal Music Group, the world's biggest label, cites
their examples as evidence of both excitement and fear about the AI
behind content-creating apps like ChatGPT (for text) or Stable
Diffusion (for images). It could help the creative process. It could
also destroy or usurp it. Yet for recorded music at large, the coming
of the bots brings to mind a seismic event in its history: the rapid
rise and fall of Napster, a platform for sharing mainly pirated songs
at the turn of the millennium. Napster was ultimately brought down by
copyright law. For aggressive bot providers accused of riding
roughshod over intellectual property (IP), Mr Nash has a simple
message that sounds, from a music-industry veteran of the Napster
era, like a threat. "Don't deploy in the market and beg for
forgiveness. That's the Napster approach."

The main issue here is not AI-made parodies of Mr Cave or
faux-Shakespearean sonnets. It is the oceans of copyrighted data the
bots have siphoned up while being trained to create humanlike
content. That information comes from everywhere: social-media feeds,
internet searches, digital libraries, television, radio, banks of
statistics and so on. Often, it is alleged, AI models plunder the
databases without permission. Those responsible for the source
material complain that their work is hoovered up without consent,
credit or compensation. In short, some AI platforms may be doing with
other media what Napster did with songs--ignoring copyright
altogether. The lawsuits have started to fly.

It is a legal minefield with implications that extend beyond the
creative industries to any business where machine-learning plays a
role, such as self-driving cars, medical diagnostics, factory
robotics and insurance-risk management. The European Union, true to
bureaucratic form, has a directive on copyright that refers to
data-mining (written before the recent bot boom). Experts say America
lacks case history specific to generative AI. Instead, it has
competing theories about whether or not data-mining without licences
is permissible under the "fair use" doctrine. Napster also tried to
deploy "fair use" as a defence in America--and failed. That is not to
say that the outcome will be the same this time.

The main arguments around "fair use" are fascinating. To borrow from
a masterclass on the topic by Mark Lemley and Bryan Casey in the
Texas Law Review, a journal, use of copyrighted works is considered
fair when it serves a valuable social purpose, the source material is
transformed from the original and it does not affect the copyright
owners' core market. Critics argue that AIs do not transform but
exploit the entirety of the databases they mine. They claim that the
firms behind machine learning abuse fair use to "free-ride" on the
work of individuals. And they contend that this threatens the
livelihoods of the creators, as well as society at large if the AI
promotes mass surveillance and the spread of misinformation. The
authors weigh these arguments against the fact that the more access
to training sets there is, the better AI will be, and that without
such access there may be no AI at all. In other words, the industry
might die in its infancy. They describe it as one of the most
important legal questions of the century: "Will copyright law allow
robots to learn?"

An early lawsuit attracting attention is from Getty Images. The
photography agency accuses Stability AI, which owns Stable Diffusion,
of infringing its copyright on millions of photos from its collection
in order to build an image-generating AI model that will compete with
Getty. Provided the case is not settled out of court, it could set a
precedent on fair use. An even more important verdict could come soon
from America's Supreme Court in a case involving the transformation
of copyrighted images of Prince, a pop idol, by the late Andy Warhol,
an artist. Daniel Gervais, an IP expert at Vanderbilt Law School in
Nashville, believes the justices may provide long-awaited guidance on
fair use in general.

Scraping copyrighted data is not the only legal issue generative AI
faces. In many jurisdictions copyright applies only to work created
by humans, hence the extent to which bots can claim IP protection for
the stuff they generate is another grey area. Outside the courtrooms
the biggest questions will be political, including whether or not
generative AI should enjoy the same liability protections for the
content it displays as social-media platforms do, and to what extent
it jeopardises data privacy.

The copyrighting is on the wall

Yet the IP battle will be a big one. Mr Nash says creative industries
should swiftly take a stand to ensure artists' output is licensed and
used ethically in training AI models. He urges AI firms to "document
and disclose" their sources. But, he acknowledges, it is a delicate
balance. Creative types do not want to sound like enemies of
progress. Many may benefit from AI in their work. The lesson from
Napster's "reality therapy", as Mr Nash calls it, is that it is
better to engage with new technologies than hope they go away. Maybe
this time it won't take 15 years of crumbling revenues to learn it. #

Read more from Schumpeter, our columnist on global business:
How to stop the commoditisation of container shipping (Mar 9th)
Lessons from Novo Nordisk on the stampede for obesity drugs (Mar 2nd)
It's time for Alphabet to spin off YouTube (Feb 23rd)

To stay on top of the biggest stories in business and technology,
sign up to the Bottom Line, our weekly subscriber-only newsletter.

This article appeared in the Business section of the print edition
under the headline "Napster, remixed"

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