Yet this assumes that you can get hold of that training data, says Kautz. He and his colleagues at Nvidia have come up with a different way to expose private data, including images of faces and other objects, medical data, and more, that does not require access to training data at all.
Instead, they developed an algorithm that can re-create the data that a trained model has been exposed to by reversing the steps that the model goes through when processing that data. Take a trained image-recognition network: to identify what’s in an image, the network passes it through a series of layers of artificial neurons. Each layer extracts different levels of information, from edges to shapes to more recognizable features.
Kautz’s team found that they could interrupt a model in the middle of these steps and reverse its direction, re-creating the input image from the internal data of the model. They tested the technique on a variety of common image-recognition models and GANs. In one test, they showed that they could accurately re-create images from ImageNet, one of the best known image recognition data sets.
As in Webster’s work, the re-created images closely resemble the real ones. “We were surprised by the final quality,” says Kautz.
The researchers argue that this kind of attack is not simply hypothetical. Smartphones and other small devices are starting to use more AI. Because of battery and memory constraints, models are sometimes only half-processed on the device itself and sent to the cloud for the final computing crunch, an approach known as split computing. Most researchers assume that split computing won’t reveal any private data from a person’s phone because only the model is shared, says Kautz. But his attack shows that this isn’t the case.
Kautz and his colleagues are now working to come up with ways to prevent models from leaking private data. We wanted to understand the risks so we can minimize vulnerabilities, he says.
Even though they use very different techniques, he thinks that his work and Webster’s complement each other well. Webster’s team showed that private data could be found in the output of a model; Kautz’s team showed that private data could be revealed by going in reverse, re-creating the input. “Exploring both directions is important to come up with a better understanding of how to prevent attacks,” says Kautz.
A bot that watched 70,000 hours of Minecraft could unlock AI’s next big thing
The researchers claim that their approach could be used to train AI to carry out other tasks. To begin with, it could be used to for bots that use a keyboard and mouse to navigate websites, book flights or buy groceries online. But in theory it could be used to train robots to carry out physical, real-world tasks by copying first-person video of people doing those things. “It’s plausible,” says Stone.
Matthew Gudzial at the University of Alberta, Canada, who has used videos to teach AI the rules of games like Super Mario Bros, does not think it will happen any time soon, however. Actions in games like Minecraft and Super Mario Bros. are performed by pressing buttons. Actions in the physical world are far more complicated and harder for a machine to learn. “It unlocks a whole mess of new research problems,” says Gudzial.
“This work is another testament to the power of scaling up models and training on massive datasets to get good performance,” says Natasha Jaques, who works on multi-agent reinforcement learning at Google and the University of California, Berkeley.
Large internet-sized data sets will certainly unlock new capabilities for AI, says Jaques. “We’ve seen that over and over again, and it’s a great approach.” But OpenAI places a lot of faith in the power of large data sets alone, she says: “Personally, I’m a little more skeptical that data can solve any problem.”
Still, Baker and his colleagues think that collecting more than a million hours of Minecraft videos will make their AI even better. It’s probably the best Minecraft-playing bot yet, says Baker: “But with more data and bigger models I would expect it to feel like you’re watching a human playing the game, as opposed to a baby AI trying to mimic a human.”
The Download: AI conquers Minecraft, and babies after death
+ Scientists have found a way to mature eggs from transgender men in the lab. It could offer them new ways to start a family—without the need for distressing IVF procedures. Read the full story. + How reproductive technology is changing what it means to be a parent. Advances could lead to babies with four or more biological parents—forcing us to reconsider parenthood. Read the full story.
I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.
1 Elon Musk wants to reinstate banned Twitter accounts
It’s an incredibly dangerous decision with widespread repercussions. (WP $)
+ Recent departures have hit Twitter’s policy and safety divisions hard. (WSJ $)
+ It looks like Musk’s promise of no further layoffs was premature. (Insider $)
+ Meanwhile, Twitter Blue is still reportedly launching next week. (Reuters)
+ Imagine simply transferring your followers to another platform. (FT $)
+ Twitter’s potential collapse could wipe out vast records of recent human history. (MIT Technology Review)
2 Russia’s energy withdrawal could kill tens of thousands in Europe
High fuel costs could result in more deaths this winter than the war in Ukraine. (Economist $)
+ Higher gas prices will also hit Americans as the weather worsens. (Vox)
+ Ukraine’s invasion underscores Europe’s deep reliance on Russian fossil fuels. (MIT Technology Review)
3 FTX is unable to honor the grants it promised various organizations
Many of them are having to seek emergency funding to plug the gaps. (WSJ $)
+ Bahamians aren’t thrilled about what its collapse could mean for them. (WP $)
5 The UK is curbing its use of Chinese surveillance systems
But only on “sensitive” government sites. (FT $)
+ The world’s biggest surveillance company you’ve never heard of. (MIT Technology Review)
7 San Francisco’s police is considering letting robots use deadly force
The force has 12 remotely piloted robots that could, in theory, kill someone. (The Verge)
8 Human hibernation could be the key to getting us to Mars
It could be the closest we can get to time travel. (Wired $)
9 Why TikTok is suddenly so obsessed with dabloons
It’s a form of choose-your-own-adventure fun. (The Guardian)
10 We can’t stop trying to reinvent mousetraps 🧀
There are thousands of versions out there, yet we keep coming up with new designs. (New Yorker $)
We can now use cells from dead people to create new life. But who gets to decide?
His parents told a court that they wanted to keep the possibility of using the sperm to eventually have children that would be genetically related to Peter. The court approved their wishes, and Peter’s sperm was retrieved from his body and stored in a local sperm bank.
We have the technology to use sperm, and potentially eggs, from dead people to make embryos, and eventually babies. And there are millions of eggs and embryos—and even more sperm—in storage and ready to be used. When the person who provided those cells dies, like Peter, who gets to decide what to do with them?
That was the question raised at an online event held by the Progress Educational Trust, a UK charity for people with infertility and genetic conditions, that I attended on Wednesday. The panel included a clinician and two lawyers, who addressed plenty of tricky questions, but provided few concrete answers.
In theory, the decision should be made by the person who provided the eggs, sperm or embryos. In some cases, the person’s wishes might be quite clear. Someone who might be trying for a baby with their partner may store their sex cells or embryos and sign a form stating that they are happy for their partner to use these cells if they die, for example.
But in other cases, it’s less clear. Partners and family members who want to use the cells might have to collect evidence to convince a court the deceased person really did want to have children. And not only that, but that they wanted to continue their family line without necessarily becoming a parent themselves.
Sex cells and embryos aren’t property—they don’t fall under property law and can’t be inherited by family members. But there is some degree of legal ownership for the people who provided the cells. It is complicated to define that ownership, however, Robert Gilmour, a family law specialist based in Scotland, said at the event. “The law in this area makes my head hurt,” he said.
The law varies depending on where you are, too. Posthumous reproduction is not allowed in some countries, and is unregulated in many others. In the US, laws vary by state. Some states won’t legally recognize a child conceived after a person’s death as that person’s offspring, according to the American Society for Reproductive Medicine (ASRM). “We do not have any national rules or policies,” Gwendolyn Quinn, a bioethicist at New York University, tells me.
Societies like ASRM have put together guidance for clinics in the meantime. But this can also vary slightly between regions. Guidance by the European Society for Human Reproduction and Embryology, for example, recommends that parents and other relatives should not be able to request the sex cells or embryos of the person who died. That would apply to Peter Zhu’s parents. The concern is that these relatives might be hoping for a “commemorative child” or as “a symbolic replacement of the deceased.”