US Supreme Court addresses AI’s copyright dilemma and fair use

Generative artificial intelligence models like OpenAI’s ChatGPT are trained by using vast amounts of data. But what happens when this data is copyrighted?

Defendants in several lawsuits claim that using copyrighted data infringes upon their copyright protections.

For instance, on February 3, a stock photo provider, Getty Images, sued artificial intelligence firm, Stability AI, alleging that the latter copied over 12 million photos from its collections to build a competing business. Getty Images claims that Stability AI has created an image-generating model called Stable Diffusion that uses artificial intelligence to deliver computer-synthesized images in response to text prompts.

While the European Commission and other regions are developing regulations to keep up with the rapid development of AI, the question of whether training AI models using copyrighted works classifies as an infringement may be decided in court cases like this one.

The question is a hot topic, and in a May 16 Senate Judiciary Committee hearing, United States Senator Marsha Blackburn grilled OpenAI CEO Sam Altman about the issue.

While Altman noted that “creators deserve control over how their creations are used,” he refrained from committing not to train ChatGPT to use copyrighted works without consent, instead suggesting that his firm was working with creators to ensure they are compensated in some way.

AI companies argue “transformative use”

AI companies generally argue that their models do not infringe on copyright laws because they transform the original work, therefore qualifying as fair use — at least under US laws.

“Fair use” is a doctrine in the US that allows for limited use of copyrighted data without the need to acquire permission from the copyright holder.

Some of the key factors considered when determining whether the use of copyrighted material classifies as fair use include the purpose of the use, particularly whether it’s being used for commercial gain, and whether it threatens the livelihood of the original creator by competing with their works.

The Supreme Court’s Warhol opinion

On May 18, the Supreme Court of the United States issued an opinion that may play a significant role in the future of generative AI. The ruling in Andy Warhol Foundation for the Visual Arts v. Goldsmith found that famous artist Andy Warhol’s 1984 work “Orange Prince” infringed on the rights of rock photographer Lynn Goldsmith as the work was intended to be used commercially and therefore could not be covered by the fair use exemption.

While the ruling doesn’t change copyright law, it does clarify how transformative use is defined.

Given that many AI companies are selling access to their AI models after training them using creators’ works, the argument that they are transforming the original works and therefore qualify for the fair use exemption may have been rendered ineffective by the decision.

It is worth noting that there is no clear consensus, however.

The legal question marks surrounding generative AI models trained using copyrighted works have prompted some firms to heavily restrict the data going into their models.

For example, on May 23, software firm Adobe announced the launch of a generative AI model called Generative Fill, which allows Photoshop users to “create extraordinary imagery from a simple text prompt.”

The Generative Fill AI model is similar to Stability AI’s Stable Diffusion, but it is trained using only stock photos from its own database. Adobe claims this helps ensure that the AI model does not generate content based on other people’s work, brands, or intellectual property.

Related: Microsoft urges lawmakers, companies to ‘step up’ with AI guardrails

Although this may be the safer legal path, AI models are only as good as the data they are trained on. Popular AI tools like ChatGPT would not be as accurate or useful as they are today if they had not scraped vast amounts of data from the web.

Creatives may be encouraged by the recent Warhol decision, but it is important to consider its broader impact. If generative AI models can only be trained using copyright-free data, what effect will this have on innovation and productivity growth?

Productivity growth is considered by many to be the most significant contributor to raising the standard of living for a country’s citizens. This is highlighted in a famous quote from prominent economist Paul Krugman in his 1994 book The Age of Diminished Expectations:

“Productivity isn’t everything, but in the long run it is almost everything. A country’s ability to improve its standard of living over time depends almost entirely on its ability to raise its output per worker.”

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