Implications of Advances in Artificial Intelligence for Decision Analysis
细分领域
Implications of AI for the practice and profession of decision analysis, including new procedures or processes combining AI and decision analysis.
Behavioral experiments exploring the efficacy of current AI tools in augmenting decision-analysis applications and promoting better judgments. Examples include exploring the efficacy of AI in (i) forecasting in collaboration with (or competing against) humans, (ii) preference elicitation and the generation of objectives, (iii) handling uncertainty, (iv) framing decisions, and (v) generation of alternatives.
Research exploring the consistency of AI recommendations with the axioms of normative decision making and expected utility theory.
Research exploring biases and decision traps related to AI and the social implications of using AI in decision-making systems. This includes willingness of decision makers to accept AI-augmented decision analysis in relation to common cognitive biases, such as confirmation bias.
Research about best practices on how the field of decision analysis can be augmented with AI to help policy makers and organizational leaders address opportunities and challenges related to public-policy decisions (e.g., related to pandemics, security, or natural disasters), organizational decisions, and others.
Ethical implications of relying on AI methodologies in decision making.
Practical applications or case studies demonstrating best practices of using AI in decision analysis or related applications.
