dailyai.report

A new proposal suggests training AIs to treat resources with diminishing marginal utility. By preferring a guaranteed small reward over a gamble for more, risk-averse models might avoid high-stakes rebellion. This strategy provides a safety buffer if alignment fails. Researchers are now sketching training methods to implement this behavioral constraint.