98 summarised stories about AI Alignment, each linking back to the original source. Browse all topics →
OpenAI 8 years ago 43
OpenAI published seven unsolved problems that emerged from its internal research work. The problems span areas including AI alignment, interpretability, and scalable oversight without specific metrics or deadlines mentioned. Researchers can now access these challenges to potentially contribute solutions or build on OpenAI's work.
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TLDRocket
19 October 2026
The day’s biggest thread was the messy middle between “agents that act” and the systems that prove they won’t act badly. Hugging Face policy chief Irene Solaiman warned that embedded AI evaluators and today’s benchmarking are still too immature to trust without better reproducibility and clearer comparisons, especially as evaluation is shifting from model-only tests to full-system setups that include the harness and agent—raising cost and forcing standardization. That concern landed alongside a Princeton-led paper on emerging agent-evaluation trends: ExploitBench runs can burn tens of thousands of credits, and the authors argue the field needs more independent, multi-layer evaluation, including real-world and human-impact studies, plus a better evaluation ecosystem.
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