Ten Hard Problems in Artificial Intelligence We Must Get Right

Gavin Leech, Simson Garfinkel, Misha Yagudin, Alexander Briand, Aleksandr Zhuravlev
2/6/2024
cs.AIcs.CY

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Abstract

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.]

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Cite this paper

@article{leech2024hard,
  title  = {Ten Hard Problems in Artificial Intelligence We Must Get Right},
  author = {Gavin Leech and Simson Garfinkel and Misha Yagudin and Alexander Briand and Aleksandr Zhuravlev},
  year   = {2024},
  eprint = {2402.04464},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2402.04464v2}
}

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