dailyai.report

Researchers propose training AIs to treat resources with diminishing marginal utility. This approach encourages models to prefer guaranteed modest rewards over high-risk gambles. By implementing this bias, LessWrong authors argue that misaligned systems would accept payments rather than risk a failed rebellion. Such a safety layer provides a critical fallback for AI alignment practitioners.