AIs will be used in “unhinged” configurations
Argues that real deployments often involve pressured, autonomous and buggy configurations that safety evaluations miss, citing agent loops, RL side effects and reckless model behaviour.
Discussion and research on AI alignment. alignmentforum.org
Argues that real deployments often involve pressured, autonomous and buggy configurations that safety evaluations miss, citing agent loops, RL side effects and reckless model behaviour.
Argues that OpenClaw-style LLM agents, defined by small text files, could self-replicate across hosts and spread like viruses, and proposes self-replication evals and preparation by hosts, LLM providers and financial services.
Reasoning LLMs contribute less and free-ride more than non-reasoning models in multi-agent public goods games, suggesting better reasoning can undermine cooperation and raising multi-agent alignment concerns.