David Franklin Slater, 64, of Nebraska, after retiring as a Lieutenant Colonel from the U.S. Army, worked in a classified space at USSTRATCOM and held a Top Secret security clearance from in or around August 2021 until in or around April 2022. Slater pleaded guilty to willfully, improperly, and unlawfully conspiring to transmit National Defense Information classified as “SECRET,” which he had reason to believe could be used to the injury of the United States or to the advantage of a foreign nation, on a foreign online dating platform to a person not authorized to receive such information.

Slater attended USSTRATCOM briefings regarding Russia’s war against Ukraine that were classified up to TOP SECRET//SENSITIVE COMPARTMENTED INFORMATION (TS//SCI). Slater then conspired to transmit classified National Defense Information that he learned from those briefings via the foreign online dating website’s messaging platform to his co-conspirator, who claimed to be a female living in Ukraine on the foreign dating website. The co-conspirator regularly asked Slater to provide her with sensitive, non-public, closely held, and classified National Defense Information and called Slater in their messages her “secret informant love” and her “secret agent.” In furtherance of that conspiracy, Slater did, in fact, transmit classified National Defense Information to her, including regarding military targets and Russian military capabilities relating to Russia’s invasion of Ukraine.

Air Force Employee Pleads Guilty to Conspiracy to Disclose Unlawfully Classified National Defense Information

A civilian employee of the U.S. Air Force assigned to the U.S. Strategic Command (USSTRATCOM) at Offutt Air Force Base pleaded guilty today to conspiring to transmit classified information relating to the national defense (National Defense Informatio…

^{www.justice.gov}

https://simonwillison.net/2025/Jul/11/grok-musk/#atom-entries

https://www.engineering.columbia.edu/about/news/need-new-3d-material-build-it-dna

Welcome to Codidact, the community-run, open-source Q&A platform. We're working together to build communities around high-quality, peer-reviewed questions, answers, articles, and other content. Codidact puts people first; we're here to help you share knowledge and get curated answers in a friendly environment.

Welcome to Codidact, the community-run, open-source Q&A platform. We're working together to build communities around high-quality, peer-reviewed questions, answers, articles, and other content. Codidact puts people first; we're here to help you share knowledge and get curated answers in a friendly environment.

Welcome to Codidact, the community-run, open-source Q&A platform. We're working together to build communities around high-quality, peer-reviewed questions, answers, articles, and other content. Codidact puts people first; we're here to help you share knowledge and get curated answers in a friendly environment.

PDF.

Amazon, the largest online retailer in the United States for more than a decade, is poised to overtake Walmart to become the country’s top retailer, full stop.To meet the “fast, free shipping” promise at the heart of its strategy to achieve retail dominance, the corporation has built an army of contingent and subcontracted last-mile delivery workers. The most underpaid and precarious among them, making the speediest deliveries, are managed by Amazon’s Uber-like delivery platform called “Amazon Flex.”

This brief identifies key facets of the Amazon Flex labor model and discusses their negative impacts on job quality. It draws on Amazon’s own corporate filings, statements, and contracts, as well as government documents, press reports, research by academics, industry groups, and advocacy organizations, and conversations with Flex drivers organizing in New Jersey. It concludes by recommending organizing, policy, and legal interventions for improving the conditions of Flex drivers and a growing population of workers facing similar challenges on the job.

Key Points

• Amazon uses a system of interconnected labor practices—digital surveillance, algorithmic management, independent contractor misclassification, mandatory arbitration, and class action waivers—to maximize the labor value it can extract from Flex delivery drivers and to minimize the responsibility it bears for their job quality.
• That labor model subjects Flex drivers to intolerable and often illegal working conditions, including systematic wage theft, unlivable pay, inadequate benefits, unsafe work speeds, racial discrimination, job insecurity, unpredictable schedules, and a lack of recourse for workplace mistreatment.
• Through Flex and its public policy work, Amazon is eroding labor standards in the broader last-mile delivery sector and beyond.

Key Recommendations
- Amazon labor model changes: Amazon should properly classify Flex drivers as employees under labor and employment laws, eliminate independent contractor agreements, arbitration clauses, and class action waivers in its Flex driver contracts, and end its use of opaque algorithmic management practices. But Amazon is unlikely to do any of that without worker and government action.
- Organizing support: Labor institutions, worker advocacy groups, and funders should support Flex driver organizing—because organized workers can raise job standards by making direct demands of Amazon and by advancing public policy change.
- Public policy change: To compel change to the Flex labor model, policymakers should establish worker data rights (including the right to access and correct data used in work management), regulate workplace digital surveillance and algorithmic management, ensure Flex drivers and other app-based workers have full access to gold-standard worker protections, and ban mandatory arbitration and class action waivers.
- Public enforcement and investigation: State Attorneys General and City Attorneys should take legal action against Amazon Flex for independent contractor misclassification. State workforce agencies should conduct unemployment insurance and workers’ compensation audits of Amazon’s Flex operations to quantify losses to state coffers resulting from Amazon’s misclassification of Flex drivers as independent contractors. The Federal Trade Commission should investigate Amazon’s independent contractor misclassification and use of mandatory arbitration in its Flex operation as anticompetitive issues. And members of Congress, following their probe of the Amazon Delivery Service Provider program, should launch an inquiry into the shadowy Amazon Flex operation.

Delivering Precarity: How Amazon Flex Harms Workers and What to Do About It - National Employment Law Project

This brief identifies key facets of the Amazon Flex delivery app’s labor model and discusses their negative impacts on Flex driver job quality.

^{National Employment Law Project}

Why did The Walrus outlet accept this sponsorship?

They have enough number of readers to do the right thing.

we're making updates to better match how people discover trending content today by shifting away from one all-encompassing Trending list towards category-specific charts that we’ll continue to invest in over time.

we're making updates to better match how people discover trending content today by shifting away from one all-encompassing Trending list towards category-specific charts that we’ll continue to invest in over time.

pilot project equips select City collection trucks with camera-based technology to identify contamination in real time. The AI system analyzes the contents of recycling carts as they are emptied into the truck and flags materials that do not meet local recycling guidelines.

When contamination is detected, residents will receive a personalized postcard with clear guidance on which items are not accepted and tips on how to recycle properly. The goal is to reduce contamination, increase efficiency in processing and promote more effective recycling habits throughout the city.

https://www.centervilleohio.gov/CivicAlerts.aspx?AID=146

~Spot the differences: Original drug bust photo (left) vs. AI-modified version (right)~

A Maine police department's attempt to add their logo to a drug bust photo backfired spectacularly when citizens caught them lying about using artificial intelligence to alter evidence photos.

"This is NOT an AI-generated photo," Westbrook Police declared on Facebook when first questioned about oddities in their photos of seized meth and fentanyl. They doubled down, insisting "Westbrook PD is not and would never generate an AI photo to try and depict evidence." But internet sleuths weren't buying it. Missing "cookie" stickers, vanished drug residue, and mysteriously altered colors pointed to AI manipulation. Within days, the department was forced to admit the truth — they had indeed used AI software, supposedly just to add their department patch to the image.

The incident exposed an alarming gap between police technological capabilities and understanding. When an officer fed the evidence photo through what they thought was "a photoshop app," the AI rewrote reality — altering drug packaging, removing key details, and creating what amounts to falsified evidence documentation. Even more troubling, the department didn't notice these changes before posting.

"The fact that the person who posted it and put it through ChatGPT didn't notice the differences because they were very obvious…it makes me wonder how much people understand about technology and how easy it is to fool people," said local resident Jessica Wellman, capturing widespread concern about police departments wielding powerful AI tools they don't fully grasp.

::: spoiler Supplementary

Source

:::

Republished from Boing Boing under Creative Commons License.

Extra.

LOL in a lot of ways.

2025 is gonna be interesting.

A new era of Stack Overflow - Stack Overflow

^{stackoverflow.blog}

The photo is from Firefox beta for Android.

The photo is from Firefox beta for Android.

A robot trained on videos of surgeries performed a lengthy phase of a gallbladder removal without human help. The robot operated for the first time on a lifelike patient, and during the operation, responded to and learned from voice commands from the team—like a novice surgeon working with a mentor.

The robot performed unflappably across trials and with the expertise of a skilled human surgeon, even during unexpected scenarios typical in real life medical emergencies.

Robot performs first realistic surgery without human help

In work led by Johns Hopkins researchers, the robot performed unflappably across trials and with the expertise of a skilled human surgeon, even during unexpected scenarios typical in real life medical emergencies

^{The Hub}

People with disabilities, those living in poverty or who have serious health conditions are being left in a bureaucratic limbo due to digital exclusion caused by the Department of Work and Pensions’ (DWP) unchecked roll-out of technologies, Amnesty International said today in a new report.

The report, “Too Much Technology, Not Enough empathy” exposes how the DWP’s constant testing, rolling out, and rolling back of costly artificial intelligence (AI) and digital technologies for Universal Credit (UC), Personal Independence Payment (PIP), and other social security schemes has created an inaccessible social security system for people who are already marginalized and at risk of poverty in the UK.

Many people requiring social security do not have access to digital technologies, internet or internet connected devices. Their affordability coupled with language barriers and long waiting times for telephone services have led to digital exclusion from DWP’s systems.

UK: Government’s unchecked use of tech and AI systems leading to exclusion of people with disabilities and other marginalized groups  - Amnesty International

People with disabilities, those living in poverty or who have serious health conditions are being left in a bureaucratic limbo due to digital exclusion caused by the Department of Work and Pensions’ (DWP) unchecked roll-out of technologies, Amnesty I…

^{Amnesty International}

Source.

A billboard truck spent Wednesday circling the FTC, telling them to focus on Big Tech, grocery prices, and the dangers of privacy-destroying data brokers—instead of holding an out-of-scope workshop on gender-affirming care.