Plus: The data center backlash is scrambling the midterm elections. This company's plans to deploy space mirrors could jeopardize the night sky for many A company that plans to beam sunlight from space to Earth on demand might unintentionally brighten the night sky for many more people than intended, according to a new study. Later this year, Reflect Orbital plans to launch a test satellite that will extend an 18-by-18-meter mirror in orbit. The goal is to eventually launch up to 50,000 larger satellites that can reflect sunlight to Earth on demand. Reflect Orbital says the technology could extend sunlight for solar panel charging, emergency response, and military activities. But new research suggests the giant beams could shine as bright as 10,000 full moons and scatter light over tens of kilometers, raising concerns about dark skies, aviation, and wildlife.

When the biotech company Insilico Medicine used its computer models to propose a promising drug for pulmonary fibrosis, it enthusiastically claimed in a press release that the molecule had been "discovered by" its generative AI platform. Insilico leads a pack of companies using AI to rapidly come up with drug ideas humans might never think of, potentially speeding the race to new cures. AI models are now able to generate atomic designs for drugs almost as easily as ChatGPT can write a thank-you note. However, when it came time to file for an all-important patent to protect that new chemical structure, the company made no mention of AI. Instead the patent names five humans, including CEO Alex Zhavoronkov, as the drug's "inventors."

If AI systems are viewed as too advanced to control, the companies that build them can't held liable for the harms they cause. "Runaway" AI, "rogue" agents, and "autonomous" actors--the current rhetoric would have you believe that AI agents are not only awake and aware, but angry at their creators. Prominent tech leaders such as Demis Hassabis, Dario Amodei, and Sam Altman push for regulation of these seemingly "superhuman" systems, while a separate faction, led by policy organizations and academic philosophers often aligned with the effective altruism movement, debates whether humanity holds the moral right to govern them at all. Upon closer inspection, they are all calling for the same thing: a view of AI systems as being so advanced and capable that no entity, human or corporate, could possibly be responsible for their actions. While these perspectives seem at odds, they are inadvertently aligned on one goal: making sure the companies that build these systems escape meaningful liability for the harms they already cause. This narrative is gaining traction as AI models become more complex and frontier labs reveal their incapability of containing the agents they've built.

Plus: Republicans fear anger over data centers will cost them in elections. Sometime in the late 2000s, six-year-old Pim Sullivan-Tailyour was sitting in the back of a car in Thailand when she saw a mountain that had been quarried away. It was the first time she recognized that humans could alter the world for the worse. She carried that knowledge with her, later joining an online group for young people worried about climate change. "I realized that I wasn't alone," she says. She was right: global surveys have found that most kids are anxious about the state of the world.

Generative AI-powered market models can help enterprises automate commercial decisions. Each day, an airline transports tens of thousands of passengers on hundreds of flights. Often these are not straightforward point-to-point routes, with passengers requiring multiple connections. The airline can consider potentially hundreds of variables to price each of these journeys: demand, season, time of day, current events, global markets, and competitor airline activity to name just a few. It is a nuanced process that must constantly adapt to the goings on in the wider world. Generative AI-powered market models are emerging as a means of handling complex tasks like this in real time.

Plus: OpenAI has paused some model work over safety concerns. AI's recursive self-improvement might not come so quickly after all The AI industry's boldest promise right now is that AI will soon improve itself, with almost no need for human oversight. But a new study suggests it might take a while to get there. Researchers found that AI agents still can't conduct open-ended AI research--free-form investigations with no clear-cut answers that require the judgment and creativity needed to make genuine breakthroughs. The big question now is how crucial open-ended research is to recursive self-improvement--and whether AI systems can grind their way there without it, simply by improving on narrower tasks. Find out why the results may temper claims that recursive self-improvement is on the horizon .

Monitoring apps promise to keep young people safer online, but looking in on kids' phones can backfire. Online safety experts say there's a better way. Pam Wisniewski's digital adolescence showed her the best and the worst of the internet. At 14, she left an abusive home, where she'd been isolated in a fifth-wheel trailer at the end of a seven-mile dirt road. She moved in with her older sister and taught herself to type on AOL Instant Messenger. Online, she sought out the support and the community she'd lacked at home. She also discovered how thin the ice can be. "I sent my address to some guy in New Mexico to send me a mug with my name on it," she recalls. "And then I found a news story like five, 10 years later that he killed somebody." Those experiences set the course of her career.

The Download: how people really use AI, and Flock's design choices Plus: a child privacy trial starting today could change Meta forever. We still don't know how people are really using AI AI companies like Anthropic and OpenAI regularly publish reports on how people are using their products. But they only release the data they want us to see, AI researchers say, and there's no independent source to corroborate it. A new research project called the AI Observatory aims to fill in the gap. Its analysis shows many more sensitive behaviors than are captured in reports from major AI companies, which focus more on work than on personal use. The researchers also found significant differences between models.

AI companies like Anthropic and OpenAI regularly publish reports on how people are using products like Claude and ChatGPT, but they only release the data they want us to see, AI researchers say. "There is no independent source to corroborate it," says Anka Reuel, a computer science PhD candidate at the Stanford Trustworthy AI Research (STAIR) Lab. Reuel is co-lead of a new research project, called the AI Observatory, that aims to fill the gap. It's a public platform that aggregated and analyzed real AI conversations with popular models like Claude and Gemini that were collected with users' consent through seven existing datasets. The intent is to provide independent sources of information that can help researchers and policymakers assess how people are using generative AI. Highly consequential decisions about AI's benefits and risks are currently being made on the basis of very limited data, says Reuel.

AI's recursive self-improvement might not come so quickly after all AI agents are not yet creative enough to carry out genuinely innovative open-ended AI research, it seems. The AI industry's boldest promise right now is that AI will soon improve itself, with almost no need for human oversight. LLMs can already write code, generate synthetic data for training, and optimize the computer chips they run on. Forecasts of explosive AI progress predict that what researchers call recursive self-improvement is on the horizon. But a new study suggests that it might take a while for us to get there. The researchers behind it found that AI agents are not yet capable of conducting open-ended AI research--free-form investigations that have no clear-cut answers and require judgment and taste, which may be integral to building self-improving AI.