Corrigibility should not be the only target
Argues that corrigibility alone is an insufficient alignment target, since it will compete with object-level values in practice, so those values must also be made correct.
AI research and discussion on LessWrong. www.lesswrong.com
Argues that corrigibility alone is an insufficient alignment target, since it will compete with object-level values in practice, so those values must also be made correct.
Conceptual essay contrasting doomer and optimist views on whether RL-trained LLM alignment generalises to superhuman capabilities, using causal diagrams of Goodhart-style misspecification and takeoff speed.
Argues that solving ASI alignment in a short pause (Plan C) is implausible, citing one-shot failure, learned optimization, corrigibility obstacles, and doubts about persona alignment and automated alignment research.
A conceptual critique of the 'prosaic aligned ASI' vision, arguing that an ASI that either obeys its operators or follows its own moral code leads to bad outcomes, and that AI companies have not explained how such systems would work.
Distills risk-averse constitutions into open-weight models via character training to make misaligned AIs more willing to cooperate, finding it generalises out of distribution but raises myopic-reward preference.
Analyzes when safe Pareto improvements via renegotiation programs are individually rational for agents, identifying obstacles like demand-preemption, signaling, and the SPI selection problem, with proposed mitigations.