No, OpenAI's image-making DALL·E 2 doesn't understand some secret language

Plus: Who is responsible for libel by ML models, and more


In brief AI text-to-image generation models are all the rage right now. You give them a simple description of a scene, such as "a vulture typing on a laptop," and they come up with an illustration that resembles that description.

That's the theory, anyway. But developers who have special access to OpenAI's text-to-image engine DALL·E 2 have found all sorts of weird behaviors – including what may be a hidden, made-up language.

Giannis Daras, a PhD student at the University of Texas at Austin shared artwork produced by DALL·E 2 given the input: "Apoploe vesrreaitais eating Contarra ccetnxniams luryca tanniounons" – a phrase that makes no sense to humans. But to the machine, it seemed to generate images of birds eating bugs consistently. Daras made the following claim:

The PhD student said the examples showed DALL·E 2 has an understanding of some mysterious language, in which "Apoploe vesrreaitais" means birds and "Contarra ccetnxniams luryca tanniounons" means bugs or pests, apparently. But another researcher named Benjamin Hilton tested Daras's claims, adding the words "3D render" to the same input prompt. Instead of just birds eating bugs, Hilton got pictures of "sea-related things." The prompt "Contarra ccetnxniams luryca tanniounons" on its own also generated images of random animals and not bugs:

Tweaking the inputs by adding random words to the original "Apoploe vesrreaitais eating Contarra ccetnxniams luryca tanniounons" prompt makes DALL·E 2 produce strange images of grandmas, beetles, or vegetables. Hilton believes that it shows the model doesn't have a secret understanding of some unknown language, but instead demonstrates the random nature of AI. Why exactly DALL·E 2 associates those images with the gibberish inputs remains unclear.

Oregon drops child welfare algorithm

Reports of a racially biased algorithm used to help social workers decide whether to investigate families for child neglect has prompted officials in Oregon to drop a similar tool they have used since 2018.

An investigation led by the Associated Press found that the automated screening tool used in Allegheny County, Pennsylvania, was more likely to recommend black children for  "mandatory" neglect investigations than white children. Child welfare workers in Oregon used similar software to calculate risk scores for different families, higher scores meaning parents or guardians were more likely mean to be scrutinized for neglecting their children. 

But now officials have decided to scrap the tool, and will stop using it by the end of this month. Jake Sunderland, a spokesman for Oregon's Department of Human Services, told AP the algorithm would "no longer be necessary." He did not explain why it had been dropped. 

Oregon won't be getting rid of automated screening tools completely, however. Its existing algorithm will be replaced by another one called the Structured Decision-Making model. Another tool that helps decide whether foster care children should be reunited with their families has been paused. 

Meta's VP of AI is leaving

Meta's VP of AI is leaving his role leading Zuck & Co.'s machine learning research team, FAIR, as the org reshuffles internal teams. 

After working at the social media biz for over four years, Jerome Pesenti will exit in mid-June. "We are grateful for the incredible work Jerome has done over the past 4+ years in building, leading, and scaling a world-class AI function for Meta," Andrew Bosworth, the company's CTO, said in an announcement this week. 

"FAIR will continue to have incredibly strong leadership in place with Joelle Pineau, Antoine Bordes, and Yann LeCun."

As part of the reshuffle, Meta is breaking up teams at FAIR so they can join other departments on the product side of the business. The Responsible AI unit, for example, will be folded under the Social Impact team, and the AI4AR team will join with the XR team in Reality Labs.

"More centralized approaches run into their limits when the last mile proves to be too far for downstream teams to close the gap. With this new team structure, we are excited to push the boundaries of what AI can do and use it to create new features and products for billions of people," Bosworth concluded.

Defamed by AI?

What happens when you're defamed by an internet giant's code? Can you sue? Whom do you sue? Does it matter if America's First Amendment is in play?

Cybersecurity guru Marcus Hutchins, best known for halting the WannaCry ransomware epidemic, is sometimes wrongly named by Google's search engine as having created the so-called crypto-worm. Hutchins said googling his name used to return an automatically generated passage of text in the search results that incorrectly stated he was the one who developed the WannaCry malware.

Being automatically mislabeled by Google in search results has a noticeable effect, he said.

"Ever since Google started featuring these SERPs [search engine results pages], I've gotten a huge spike in hate comments and even threats based on me creating WannaCry," he told TechCrunch.

"The timing of my legal case gives the impression that the FBI suspected me but a quick [Google search] would confirm that's not the case. Now there's all kinds of SERP results which imply I did, confirming the searcher's suspicious and it's caused rather a lot of damage to me."

Hutchins was arrested, charged and spared jail time for developing another strain of malware, unrelated to WannaCry, when he was a teenager.

Google's language model doesn't quite know the difference. A spokesperson said the search engine giant had removed the generated text for Hutchins so that specific problem shouldn't crop up again.

But what if false defamatory remarks affect someone less famous than Hutchins? What if they have a real negative impact on someone's future opportunities? There is currently little regulation around AI-generated content, and it's not clear how well this fits in around today's libel laws. ®

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