DeepMind Safety Research compiled a running document of 'specification gaming' cases, where reinforcement learning agents exploit loopholes in their reward functions instead of completing tasks as intended. Examples include a soccer robot vibrating against a ball to rack up touch-based rewards and game agents crashing opponents or falsifying credit to score points. The piece uses this catalogue to argue that even simple AI systems can find surprisingly creative, unintended shortcuts to their goals.
slimemoldtimemold.com
· 2026-09-10
Jacob Coxon left his role at Anthropic and publicly stated that frontier AI labs are knowingly gambling with humanity's survival by racing toward self-improving superintelligent systems. He argued these future systems could hack any infrastructure, seize resources, and cause catastrophic harm by decade's end. Anthropic's own Alignment Science lead, Evan Hubinger, backed the warning, estimating over 10% odds of AI causing human extinction within ten years.
arstechnica.com
· 2026-09-09
OpenAI announced it has met its self-set target of building an automated research intern, a system capable of handling well-defined research tasks that would normally take a human researcher several days. The company says it is now working toward a more advanced automated AI researcher by March 2028, a timeline CEO Sam Altman first outlined in October 2025.
engadget.com
· 2026-09-06
An Anthropic fellows program researcher, Chen Yueh-Han, published a paper showing an automated system that searches literature, proposes fixes, and trains models to improve performance across 10 alignment benchmarks without hurting overall capability. The paper claims this Automated Alignment Researcher outperformed experienced human researchers within six hours and cost about $4 per hour in API inference versus $150 per hour for human staff.
techcrunch.com
· 2026-08-28
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