Summary of Ten Hard Problems in Artificial Intelligence We Must Get Right, by Gavin Leech and Simson Garfinkel and Misha Yagudin and Alexander Briand and Aleksandr Zhuravlev
Ten Hard Problems in Artificial Intelligence We Must Get Right
by Gavin Leech, Simson Garfinkel, Misha Yagudin, Alexander Briand, Aleksandr Zhuravlev
First submitted to arxiv on: 6 Feb 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computers and Society (cs.CY)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A new research paper tackles the pressing “hard problems” obstructing the potential benefits of Artificial Intelligence (AI) while posing risks to society. The study identifies ten key challenges hindering AI’s widespread adoption, including developing general capabilities, ensuring system performance and training processes, aligning goals with human objectives, and promoting socially responsible deployment. To address these issues, researchers outline relevant areas, highlight recent advancements, and propose ways forward for each problem. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper explores the biggest obstacles to harnessing AI’s potential, such as developing general capabilities, ensuring system performance, and aligning AI goals with human values. It also looks at how to ensure socially responsible deployment, address economic disruptions, and promote sound governance of the technology. The study reviews recent literature up to January 2023. |
