Ten Hard Problems in Artificial Intelligence We Must Get Right
This work provides a comprehensive review of key problems for AI researchers, policymakers, and society, but it is incremental as it synthesizes existing literature rather than introducing novel solutions.
The paper identifies and outlines ten critical challenges in artificial intelligence that must be addressed to realize its promise and mitigate risks, including issues like general capabilities, alignment, and governance, without presenting new experimental results or numerical data.
We explore the AI2050 "hard problems" that block the promise of AI and cause AI risks: (1) developing general capabilities of the systems; (2) assuring the performance of AI systems and their training processes; (3) aligning system goals with human goals; (4) enabling great applications of AI in real life; (5) addressing economic disruptions; (6) ensuring the participation of all; (7) at the same time ensuring socially responsible deployment; (8) addressing any geopolitical disruptions that AI causes; (9) promoting sound governance of the technology; and (10) managing the philosophical disruptions for humans living in the age of AI. For each problem, we outline the area, identify significant recent work, and suggest ways forward. [Note: this paper reviews literature through January 2023.]