Risk Preference

Risk preference, the tendency to favor certain versus uncertain outcomes, is a central theme in decision-making research, with current investigations focusing on how it manifests in both humans and artificial intelligence (AI). Researchers are employing behavioral economics frameworks, such as cumulative prospect theory and risk measures like Conditional Value-at-Risk (CVaR), alongside machine learning techniques like inverse reinforcement learning and distributional reinforcement learning, to model and understand risk preferences in diverse contexts, including autonomous vehicle interactions and AI-driven financial decisions. These studies reveal significant individual differences in risk attitudes and highlight the potential for biases in AI systems, underscoring the need for ethical considerations and the development of robust, risk-aware algorithms for safe and reliable decision-making in various applications.