Why AI General Legal Battles Are Heating | Beats of AI

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This morning, Kevin Roose of the New York Times called what was an important week for artificial intelligence tool one”coming party [subscription required].

He detailed an actual party that, on Monday night, held a large funding round for stable AI, The startup behind Diffusion Stabilization, the world’s most popular image generation algorithm, went public only two months ago.

But this week is full of other important news around creative AI (which refers to the use of unsupervised learning algorithms to learn from existing text, audio, or images and create new content – and now includes popular tools including GPT-3, DALL-E 2 and Imagen as well as babies text to video options from OpenAI and Google).

Is there news that Microsoft will add DALL-E to its Office suite and Azure AIwhile Adobe planned to add generic AI tools to Photoshop and also committed to transparency in the use of general AI. Then, alongside the Stable Diffusion news, content generator Jasper also announced a massive $125 million funding round that reinforces VC’s interest in the creative AI space.


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There was also a lively online chat about GitHub user Matthew Butterick, who claimed GitHub Copilot, an aggregate AI tool that recommends computer code to developers, used his source code as data. training material. He is starting an investigation into Copilot with the intention of eventually starting a class-action lawsuit against GitHub and its parent company Microsoft.

This news fire (and I won’t even go into the whole “students are writing their papers According to Bradford Newman, head of machine learning and AI practices at global law firm Baker McKenzie, in the Palo Alto office, are leading legal battles far beyond GitHub Copilot.

Will questions of ‘fair use’ go to the Supreme Court?

I talked to Newman back in august around DALL-E image ownership issues – i.e. creative AI output. Now, he says, legal questions are fast-tracking and acrimonious around copyright and “fair use” of the input — that is, the training data that goes into general AI tools.

“Legally, right now, there is very little guidance,” he warned. “There are inevitable collective actions, but the net of it all is when you are using the huge datasets that these AI applications have and you sprinkle that on top of that open source license. [as in the GitHub Copilot example]the argument would be fair use versus violation. ”

He predicts that different courts will reach different conclusions. “Ultimately, I believe this will go to the Supreme Court.”

Newman isn’t the only one who thinks so: Legal scholar Andres Guadamuz, an intellectual property law reader at the University of Sussex in the UK who has researched the legal issues surrounding artificial intelligence, said much in a blog post this week — although he warned that the legal battles could drag on for years.

He said the GitHub Copilot case in the blog post, “starts like the first case specifically dealing with machine learning and legal use in the US.”

If it continues, it could be the first to test that theory, although he says he wouldn’t bet on an outcome. But one thing is clear, he stressed: “If this case continues, it will take years, any lower court decisions will be appealed, and appeals can go to the Supreme Court. USA. So we’re talking years and years of uncertainty. ”

Millions of images used for synthetic AI training data

McKenzie points out that some copyright issues related to artificial intelligence can be straightforward. For example, Greg Rutkowski, a Polish digital artist, is said to have become More popular reminders in Diffusion is more stable than Picasso. McKenzie says such a one-on-one situation could have a legal leg up against piracy.

But what if an AI or ML application is trained on millions of images, such as Paris? Some of those images are obviously copyrighted, but how can anyone prove that their image, even if it’s tagged in some way, leads directly to the AI ​​output?

“The law wasn’t really written for artificial intelligence,” Newman said. “Perhaps we will need new IP laws to cover AI, which I have been crying about for years – I believe we need new laws to solve these problems, which is about people wanting money for what machines do. ”

But Guadamuz, in his blog post, takes a similar view. “In principle, I agree that there is no direct case law dealing with fair use in training an AI,” he said. “However, there is a good argument to be made that training data is used properly and this includes Authors Association v Googleand the aforementioned Google v Oracle. It is true that this has not been decided, and as the first assumption, a court case could easily favor the claimants of copyright infringement, but I do not think that is a one-sided argument. by any imagination. ”

Just to make things even more interesting, Guadamuz points out that other countries have enacted laws stating that machine learning training is legal. Great Britain had a text and data mining exceptions copyright for research purposes since 2014, he writes, and the EU has approved Digital Single Market Directive in 2019, there is an exception for text and data mining “for any purpose as long as the author does not reserve their rights.”

“The practical outcome of the existence of these provisions is that while the litigation is ongoing in the US, most of the training and data mining activities will move to Europe and the US AI companies have can only license trained models,” he said. “The result will be to put the US at a disadvantage in the AI ​​arms race.”

The bottom line, Newman said, as with many enthusiasts on both sides of the general legal debate over AI, “no one knows the answers” to these complex questions. At the end of the day, he explained, “The courts will have to figure it out.”

Meanwhile, Steady Diffusion, and many others, will continue.

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