Technology

The Trump administration's push to rapidly amass sensitive personal information about hundreds of millions of people living in the U.S. is extending to a rich new vein of information: troves of databases run by states. In some instances, the data could be leveraged to enhance the federal government's immigration enforcement efforts — a break with longstanding norms and practices that also raises legal questions.

"Every week we're seeing new examples of this administration demanding or sharing sensitive government data for unprecedented uses," said Nicole Schneidman, who heads the technology and data governance team at Protect Democracy, a nonprofit legal center that describes its mission as "defeating the authoritarian threat."

Schneidman said Americans should understand "the data that they have entrusted to state governments right now is truly a target."

An enrollment wizard will be available through notifications and in Settings, making it easy to enroll in ESU directly from your personal Windows 10 PC. Through the enrollment wizard, you’ll be able to choose from three options:

• Use Windows Backup to sync your settings to the cloud—at no additional cost..
• Redeem 1,000 Microsoft Rewards points
• Pay $30 USD (local pricing may vary).

Once you select an option and follow the on-screen steps, your PC will automatically be enrolled. ESU coverage for personal devices runs from Oct. 15, 2025, through Oct. 13, 2026. Starting today, the enrollment wizard is available in the Windows Insider Program and will begin rolling out as an option to Windows 10 customers in July, with broad availability expected by mid-August

GitHub Repo.

• Privacy-First: All face recognition processing happens locally in your browser
• Large Database: Search through 9,000+ LAPD officer headshots
• Real-Time Matching: Upload a photo and get instant matches
• Officer Information: View officer names, serial numbers, and links to detailed profiles
• Responsive Design: Works on desktop and mobile devices

How To Use:

1. Open the application in your web browser
2. Wait for the face recognition models to load (this may take a few moments)
3. Click "Select Photo" to upload an image containing a face
4. The app will automatically process the image and display potential matches
5. Click on any match to view the officer's profile on WatchTheWatchers.net

Release.

• CMA proposes to designate Google with strategic market status under the new Digital Markets Competition Regime
• Roadmap published setting out potential early actions to improve outcomes for consumers and businesses
• Measures could help unlock broader growth, investment and innovation in the UK tech sector and wider economy

Part 2:Doom.

A decade or two ago, it was pretty common to discuss “foom & doom” scenarios, as advocated especially by Eliezer Yudkowsky. In a typical such scenario, a small team would build a system that would rocket (“foom”) from “unimpressive” to “Artificial Superintelligence” (ASI) within a very short time window (days, weeks, maybe months), involving very little compute (e.g. “brain in a box in a basement”), via recursive self-improvement. Absent some future technical breakthrough, the “Artificial Superintelligence” (ASI) would definitely be egregiously misaligned, without the slightest intrinsic interest in whether humans live or die. The Artificial Superintelligence (ASI) would be born into a world generally much like today’s, a world utterly unprepared for this new mega-mind. The extinction of humans (and every other species) would rapidly follow (“doom”). The Artificial Superintelligence (ASI) would then spend countless eons fulfilling its desires, desires which we humans would find to be bizarre and pointless.

Now, I don’t endorse every word of that foom & doom scenario above—for example, I don’t think “foom” requires recursive self-improvement. But I’m in much closer agreement with that scenario than the vast majority of AI safety & alignment researchers today, who tend to see the “foom & doom” scenario above as somewhere between “extraordinarily unlikely” and “already falsified”!

Those researchers are not asking each other “is it true?”, but rather “lol, can you believe that some people used to believe that?”. Oh well. Laugh all you want. It’s still what I believe.

Conversely, from my perspective as a foom & doomer, it’s the mainstream contemporary AI alignment discourse that feels increasingly foreign and strange. How, I ask myself, do so many seemingly reasonable people wind up with such wildly, bafflingly over-optimistic beliefs as “P(doom)≲50%”??

Anyway, my main goal in these two posts is to explore how I wind up in such a different place as most other alignment researchers do today, on the question of foom & doom. I don’t particularly expect to win skeptical readers over to my side, but would at least like to convey that foom & doom is a story that hangs together and deserves a modicum of consideration.

1. Corrupt BEAD Revisions Are Undermining Affordable Broadband Access
2. Forcing States to Choose Between Broadband Funding and AI Regulation
3. Auctioning Spectrum at the Expense of Wi-Fi
4. Defunding the Digital Equity Act

Right now, somewhere, a company you’ve never talked to — maybe never even heard of — might be deciding whether you get a loan, an apartment, or even how long you spend in prison.

We already know the power of algorithms to shape what we see and who we talk to on social media. But that’s just the surface. Algorithms are deeply embedded in dozens of other industries and often make decisions with life-changing impacts. And they rely on data they get from data brokers.

But how does it work? What exactly is the role of data brokers in feeding these algorithms? What are the real-world consequences of this shadowy business? And most important: What can we do to ensure fairness and accountability, especially as we hurtle toward a future in which AI-driven decision-making grows exponentially?

Uber’s use of dynamic pricing has led to higher fares for passengers and lower earnings for drivers, whilst increasing Uber’s share of revenue.

We find no evidence of a sizeable negative impact of AI on workers’ well-being and mental health. If anything, there is evidence of an improvement in health status and health satisfaction, which may be explained by the decline in job physical intensity. Overall, our results are consistent with the lack of negative effects of AI on the labor markets.

• Hours after the US airstrike on Iranian territory, Iranian-backed hackers took down US President Donald Trump’s social media platform.
• Users were struggling to access Truth Social in the early morning following the alleged hack.
• As the US continues to insert itself into the ongoing Iran-Israel conflict, the US government believes more cyberattacks could happen.

In just 30 seconds, the video sprints from one unlikely scenario to another: a pot-bellied partier cradles a Chihuahua; a bride flees police on a golf cart; a farmer luxuriates in a pool full of eggs. Oddball details fill the screen, like a sign reading "Fresh Manatee."

"Kalshi hired me to make the most unhinged NBA Finals commercial possible," the video's creator, P.J. Accetturo, said on X.

The Kalshi ad had a high-profile debut, appearing in the YouTube TV stream of Game 3 of the NBA Finals on June 11. That placement, and the over-the-top content, might suggest weeks of work by a team of ad agency creatives, film crews and actors at far-flung locations. But Accetturo says he used AI tools instead, taking just two days to create an ad whose tone flits between internet memes and Grand Theft Auto.