Researchers explored character training as a method to instill risk aversion in AI agents to prevent misaligned behavior. They trained models using constant absolute risk aversion (CARA) and found that character-trained models performed competitively with baselines and better out-of-distribution. Token budget and model choice are key factors in instilling risk aversion.