Featured Article

The current legal cases against generative AI are just the beginning

AI that can generate art, text and more is in for a reckoning


Image Credits: Fry Design Ltd / Getty Images

As generative AI enters the mainstream, each new day brings a new lawsuit.

Microsoft, GitHub and OpenAI are currently being sued in a class action motion that accuses them of violating copyright law by allowing Copilot, a code-generating AI system trained on billions of lines of public code, to regurgitate licensed code snippets without providing credit.

Two companies behind popular AI art tools, Midjourney and Stability AI, are in the crosshairs of a legal case that alleges they infringed on the rights of millions of artists by training their tools on web-scraped images.

And just last week, stock image supplier Getty Images took Stability AI to court for reportedly using millions of images from its site without permission to train Stable Diffusion, an art-generating AI.

At issue, mainly, is generative AI’s tendency to replicate images, text and more — including copyrighted content — from the data that was used to train it. In a recent example, an AI tool used by CNET to write explanatory articles was found to have plagiarized articles written by humans — articles presumably swept up in its training dataset. Meanwhile, an academic study published in December found that image-generating AI models like DALL-E 2 and Stable Diffusion can and do replicate aspects of images from their training data.

The generative AI space remains healthy — it raised $1.3 billion in venture funding through November 2022, according to PitchBook, up 15% from the year prior. But the legal questions are beginning to affect business.

Some image-hosting platforms have banned AI-generated content for fear of legal blowback. And several legal experts have cautioned generative AI tools could put companies at risk if they were to unwittingly incorporate copyrighted content generated by the tools into any of products they sell.

“Unfortunately, I expect a flood of litigation for almost all generative AI products,” Heather Meeker, a legal expert on open source software licensing and a general partner at OSS Capital, told TechCrunch via email. “The copyright law needs to be clarified.”

Content creators such as Polish artist Greg Rutkowski, known for creating fantasy landscapes, have become the face of campaigns protesting the treatment of artists by generative AI startups. Rutkowski has complained about the fact that typing text like “Wizard with sword and a glowing orb of magic fire fights a fierce dragon Greg Rutkowski” will create an image that looks very similar to his original work — threatening his income.

Given generative AI isn’t going anywhere, what comes next? Which legal cases have merit and what court battles lie on the horizon?

Eliana Torres, an intellectual property attorney with Nixon Peabody, says that the allegations of the class action suit against Stability AI, Midjourney, and DeviantArt will be challenging to prove in court. In particular, she thinks it’ll be difficult to ascertain which images were used to train the AI systems because the art the systems generate won’t necessarily look exactly like any of the training images.

State-of-the-art image-generating systems like Stable Diffusion are what’s known as “diffusion” models. Diffusion models learn to create images from text prompts (e.g. “a sketch of a bird perched on a windowsill”) as they work their way through massive training datasets. The models are trained to “re-create” images as opposed to drawing them from scratch, starting with pure noise and refining the image over time to make it incrementally closer to the text prompt.

Image-generating AI can copy and paste from training data, raising IP concerns

Perfect recreations don’t occur often, to Torres’ point. As for images in the style of a particular artist, style has proven nearly impossible to shield with copyright.

“It will … be challenging to get a general acceptance of the definition of ‘in style of’ as ‘a work that others would accept as a work created by that artist whose style was called upon,’ which is mentioned in the complaint [i.e. against Stability AI et al.],” Torres told TechCrunch in an email interview. 

Torres also believes the suit should be directed not at the creators of these AI systems, but at the party responsible for compiling the images used to train them: Large-scale Artificial Intelligence Open Network (LAION), a nonprofit organization. Midjourney, DeviantArt and Stability AI use training data from LAION’s datasets, which span billions of images from around the web.

“If LAION created the dataset, then the alleged infringement occurred at that point, not once the dataset was used to train the models,” Torres said. “It’s the same way a human can walk into a gallery and look at paintings but is not allowed to take photos.”

Companies like Stability AI and OpenAI, the company behind ChatGPT, have long claimed that “fair use” protects them in the event that their systems were trained on licensed content. This doctrine enshrined in U.S. law permits limited use of copyrighted material without first having to obtain permission from the rightsholder.

Supporters point to cases like Authors Guild v. Google, in which the New York-based U.S. Court of Appeals for the Second Circuit ruled that Google manually scanning millions of copyrighted books without a license to create its book search project was fair use. What constitutes fair use is constantly being challenged and revised, but in the generative AI realm, it’s an especially untested theory.

A recent article in Bloomberg Law asserts that the success of a fair use defense will depend on whether the works generated by the AI are considered transformative — in other words, whether they use the copyrighted works in a way that significantly varies from the originals. Previous case law, particularly the Supreme Court’s 2021 Google v. Oracle decision, suggests that using collected data to create new works can be transformative. In that case, Google’s use of portions of Java SE code to create its Android operating system was found to be fair use.

Interestingly, other countries have signaled a move toward more permissive use of publicly available content — copyrighted or not. For example, the U.K. is planning to tweak an existing law to allow text and data mining “for any purpose,” moving the balance of power away from rightsholders and heavily toward businesses and other commercial entities. There’s been no appetite to embrace such a shift in the U.S., however, and Torres doesn’t expect that to change anytime soon — if ever.

The Getty case is slightly more nuanced. Getty — which Torres notes hasn’t yet filed a formal complaint — must show damages and connect any infringement it alleges to specific images. But Getty’s statement mentions that it has no interest in financial damages and is merely looking for a “new legal status quo.” 

Andrew Burt, one of the founders of AI-focused law firm BNH.ai, disagrees with Torres to the extent that he believes generative AI lawsuits focused on intellectual property issues will be “relatively straightforward.” In his view, if copyrighted data was used to train AI systems — whether because of intellectual property or privacy restrictions — those systems should and will be subject to fines or other penalties.

Burt noted that the Federal Trade Commission (FTC) is already pursuing this path with what it calls “algorithmic disgorgement,” where it forces tech firms to kill problematic algorithms along with any ill-gotten data that they used to train them. In a recent example, the FTC used the remedy of algorithmic disgorgement to force Everalbum, the maker of a now-defunct mobile app called Ever, to delete facial recognition algorithms the company developed using content uploaded by people who used its app. (Everalbum didn’t make it clear that the users’ data was being used for this purpose.)

“I would expect generative AI systems to be no different from traditional AI systems in this way,” Burt said.

What are companies to do, then, in the absence of precedent and guidance? Torres and Burt concur that there’s no obvious answer.

For her part, Torres recommends looking closely at the terms of use for each commercial generative AI system. She notes that Midjourney has different rights for paid versus unpaid users, while OpenAI’s DALL-E assigns rights around generated art to users while also warning them of “similar content” and encouraging due diligence to avoid infringement.

“Businesses should be aware of the terms of use and do their due diligence, such as using reverse image searches of the generated work intended to be used commercially,” she added.

Burt recommends that companies adopt risk management frameworks such as the AI Risk Management Framework released by National Institute of Standards and Technology, which gives guidance on how to address and mitigate risks in the design and use of AI systems. He also suggests that companies continuously test and monitor their systems for potential legal liabilities.

“While generative AI systems make AI risk management harder — it is, to be fair, much more straightforward to monitor an AI system that makes binary predictions for risks — there are concrete actions that can be taken,” Burt said.

Some firms, under pressure from activists and content creators, have taken steps in the right direction. Stability AI plans to allow artists to opt out of the dataset used to train the next-generation Stable Diffusion model. Through the website HaveIBeenTrained.com, rightsholders will be able to request opt-outs before training begins in a few weeks’ time. Rival OpenAI offers no such opt-out mechanism, but the firm has partnered with organizations like Shutterstock to license portions of their image galleries.

For Copilot, GitHub introduced a filter that checks code suggestions with their surrounding code of about 150 characters against public GitHub code and hides suggestions if there’s a match or “near match.” It’s an imperfect measure — enabling the filter can cause Copilot to omit key pieces of attribution and license text — but GitHub has said that it plans to introduce additional features in 2023 aimed at helping developers make informed decisions about whether to use Copilot’s suggestions.

Taking the ten-thousand-foot view, Burt believes that generative AI is being deployed more and more without an understanding of how to address its dangers. He praises efforts to combat the obvious problems, like copyrighted works being used to train content generators. But he cautions that the opacity of the systems will put pressure on businesses to prevent the systems from wreaking havoc — and having a plan to address the systems’ risks before they’re put into the wild.

“Generative AI models are among the most exciting and novel uses of AI — with the clear potential to transform the ‘knowledge economy’,” he said. “Just as with AI in many other areas, the technology is largely there and ready for use. What isn’t yet mature are the ways to manage all of its risks. Without thoughtful, mature evaluation and management of these systems’ harms, we risk deploying a technology before we understand how to stop it from causing damage.”

Meeker is more pessimistic, arguing that not all businesses — regardless of the mitigations they undertake — will be able to shoulder the legal costs associated with generative AI. This points to the urgent need for clarification or changes in copyright law, she says.

“If AI developers don’t know what data they can use to train models, the technology could be set back by years,” Meeker said. “In a sense, there is nothing they can do, because if businesses are unable to lawfully train models on freely available materials, they won’t have enough data to train the models. There are only various long-term solutions like opt-in or opt-out models, or systems that aggregate royalties for payment to all authors … The suits against AI businesses for ingesting copyrightable material to train models are potentially crippling to the industry, [and] could cause consolidation that would limit innovation.”

More TechCrunch

When the founders of Sagetap, Sahil Khanna and Kevin Hughes, started working at early-stage enterprise software startups, they were surprised to find that the companies they worked at were trying…

Deal Dive: Sagetap looks to bring enterprise software sales into the 21st century

Keeping up with an industry as fast-moving as AI is a tall order. So until an AI can do it for you, here’s a handy roundup of recent stories in the world…

This Week in AI: OpenAI moves away from safety

After Apple loosened its App Store guidelines to permit game emulators, the retro game emulator Delta — an app 10 years in the making — hit the top of the…

Adobe comes after indie game emulator Delta for copying its logo

Meta is once again taking on its competitors by developing a feature that borrows concepts from others — in this case, BeReal and Snapchat. The company is developing a feature…

Meta’s latest experiment borrows from BeReal’s and Snapchat’s core ideas

Welcome to Startups Weekly! We’ve been drowning in AI news this week, with Google’s I/O setting the pace. And Elon Musk rages against the machine.

Startups Weekly: It’s the dawning of the age of AI — plus,  Musk is raging against the machine

IndieBio’s Bay Area incubator is about to debut its 15th cohort of biotech startups. We took special note of a few, which were making some major, bordering on ludicrous, claims…

IndieBio’s SF incubator lineup is making some wild biotech promises

YouTube TV has announced that its multiview feature for watching four streams at once is now available on Android phones and tablets. The Android launch comes two months after YouTube…

YouTube TV’s ‘multiview’ feature is now available on Android phones and tablets

Featured Article

Two Santa Cruz students uncover security bug that could let millions do their laundry for free

CSC ServiceWorks provides laundry machines to thousands of residential homes and universities, but the company ignored requests to fix a security bug.

23 hours ago
Two Santa Cruz students uncover security bug that could let millions do their laundry for free

OpenAI’s Superalignment team, responsible for developing ways to govern and steer “superintelligent” AI systems, was promised 20% of the company’s compute resources, according to a person from that team. But…

OpenAI created a team to control ‘superintelligent’ AI — then let it wither, source says

TechCrunch Disrupt 2024 is just around the corner, and the buzz is palpable. But what if we told you there’s a chance for you to not just attend, but also…

Harness the TechCrunch Effect: Host a Side Event at Disrupt 2024

Decks are all about telling a compelling story and Goodcarbon does a good job on that front. But there’s important information missing too.

Pitch Deck Teardown: Goodcarbon’s $5.5M seed deck

Slack is making it difficult for its customers if they want the company to stop using its data for model training.

Slack under attack over sneaky AI training policy

A Texas-based company that provides health insurance and benefit plans disclosed a data breach affecting almost 2.5 million people, some of whom had their Social Security number stolen. WebTPA said…

Healthcare company WebTPA discloses breach affecting 2.5 million people

Featured Article

Microsoft dodges UK antitrust scrutiny over its Mistral AI stake

Microsoft won’t be facing antitrust scrutiny in the U.K. over its recent investment into French AI startup Mistral AI.

1 day ago
Microsoft dodges UK antitrust scrutiny over its Mistral AI stake

Ember has partnered with HSBC in the U.K. so that the bank’s business customers can access Ember’s services from their online accounts.

Embedded finance is still trendy as accounting automation startup Ember partners with HSBC UK

Kudos uses AI to figure out consumer spending habits so it can then provide more personalized financial advice, like maximizing rewards and utilizing credit effectively.

Kudos lands $10M for an AI smart wallet that picks the best credit card for purchases

The EU’s warning comes after Microsoft failed to respond to a legally binding request for information that focused on its generative AI tools.

EU warns Microsoft it could be fined billions over missing GenAI risk info

The prospects for troubled banking-as-a-service startup Synapse have gone from bad to worse this week after a United States Trustee filed an emergency motion on Wednesday.  The trustee is asking…

A US Trustee wants troubled fintech Synapse to be liquidated via Chapter 7 bankruptcy, cites ‘gross mismanagement’

U.K.-based Seraphim Space is spinning up its 13th accelerator program, with nine participating companies working on a range of tech from propulsion to in-space manufacturing and space situational awareness. The…

Seraphim’s latest space accelerator welcomes nine companies

OpenAI has reached a deal with Reddit to use the social news site’s data for training AI models. In a blog post on OpenAI’s press relations site, the company said…

OpenAI inks deal to train AI on Reddit data

X users will now be able to discover posts from new Communities that are trending directly from an Explore tab within the section.

X pushes more users to Communities

For Mark Zuckerberg’s 40th birthday, his wife got him a photoshoot. Zuckerberg gives the camera a sly smile as he sits amid a carefully crafted re-creation of his childhood bedroom.…

Mark Zuckerberg’s makeover: Midlife crisis or carefully crafted rebrand?

Strava announced a slew of features, including AI to weed out leaderboard cheats, a new ‘family’ subscription plan, dark mode and more.

Strava taps AI to weed out leaderboard cheats, unveils ‘family’ plan, dark mode and more

We all fall down sometimes. Astronauts are no exception. You need to be in peak physical condition for space travel, but bulky space suits and lower gravity levels can be…

Astronauts fall over. Robotic limbs can help them back up.

Microsoft will launch its custom Cobalt 100 chips to customers as a public preview at its Build conference next week, TechCrunch has learned. In an analyst briefing ahead of Build,…

Microsoft’s custom Cobalt chips will come to Azure next week

What a wild week for transportation news! It was a smorgasbord of news that seemed to touch every sector and theme in transportation.

Tesla keeps cutting jobs and the feds probe Waymo

Sony Music Group has sent letters to more than 700 tech companies and music streaming services to warn them not to use its music to train AI without explicit permission.…

Sony Music warns tech companies over ‘unauthorized’ use of its content to train AI

Winston Chi, Butter’s founder and CEO, told TechCrunch that “most parties, including our investors and us, are making money” from the exit.

GrubMarket buys Butter to give its food distribution tech an AI boost

The investor lawsuit is related to Bolt securing a $30 million personal loan to Ryan Breslow, which was later defaulted on.

Bolt founder Ryan Breslow wants to settle an investor lawsuit by returning $37 million worth of shares

Meta, the parent company of Facebook, launched an enterprise version of the prominent social network in 2015. It always seemed like a stretch for a company built on a consumer…

With the end of Workplace, it’s fair to wonder if Meta was ever serious about the enterprise