
The Avon and Somerset Police in the UK developed a comprehensive predictive analytics program to assess risk and prevent crime, using the Think Family Database to score individuals based on sensitive data. However, the program has faced criticism for its lack of transparency and reliability, with some models being abandoned due to poor performance. This initiative reflects a broader trend in the UK towards integrating AI into policing, but it underscores the importance of transparency and public trust in such technologies. The findings raise questions about the ethical use of AI in law enforcement and the need for rigorous evaluation.
Read originalEarlier coverage that leads up to this article, and what followed. Lines connect each piece to the closest one after it, converging here.
© TechCrunch AIxAI's attempt to dismiss the NAACP's Clean Air Act lawsuit failed after a federal judge ruled that its gas turbines are not exempt mobile sources and that plaintiffs have standing. This legal setback confirms that AI infrastructure operators cannot bypass environmental permitting by classifying heavy industrial equipment as temporary or mobile. The ruling forces xAI to face scrutiny over air quality impacts at its Colossus data center, setting a precedent for how large-scale compute facilities are regulated under existing environmental laws.
© TechCrunch AIThe Verge AI · July 16, 2026 · Related
TechCrunch AI · August 31, 2026 · Background
WIRED AI · September 3, 2026 · Related
WIRED AI · September 10, 2026 · Related
MIT Technology Review AI · September 21, 2026 · Background
OpenAI is scaling back its ambitions as investor appetite for massive AI infrastructure bets cools. The company has lowered its fundraising target from $30 billion to $20 billion, with only $11 billion secured so far against a valuation that has dropped from $1.4 trillion. This retreat signals a growing wariness among Wall Street investors regarding the capital intensity of the AI race, forcing even the most dominant players to adjust their financial expectations.