Lily Hu - Do causal diagram assume a can opener (Day5: Social foundations of stats/ ML)

The current decision-theoretic foundations of statistics and machine learning are insufficient for addressing some of the key challenges facing science and society today. First, there are pressing concerns about the social impact of artificial intelligence and machine learning, regarding issues such as fairness, inequality, and value alignment. Single-agent decision theory is insufficient for conceptualizing the underlying conflicts of interest between different agents, or the value alignment issues resulting from divergent objectives.
Second, there is a perceived replication crisis of empirical research, which might be due to p-hacking or publication bias. This crisis has motivated proposed solutions such as pre-registration of statistical analyses and reforms of the publication system. Single-agent statistical decision theory again cannot make sense of these problems and solutions, as it does not allow for conflicts of interest between different parties, private information, or dynamic inconsistency.