# Ten Hard Problems in Artificial Intelligence We Must Get Right

arXiv: https://arxiv.org/abs/2402.04464 · HTML: https://mlsanity.com/paper/2402.04464/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Feb 2024.

## Built on by (most cited first, 1 of 1)

- [Questionable practices in machine learning](https://mlsanity.com/paper/2407.12220/) (2024)

## Abstract (arXiv)

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.]