Summary of Taking Training Seriously: Human Guidance and Management-based Regulation Of Artificial Intelligence, by Cary Coglianese and Colton R. Crum
Taking Training Seriously: Human Guidance and Management-Based Regulation of Artificial Intelligence
by Cary Coglianese, Colton R. Crum
First submitted to arxiv on: 13 Feb 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computer Vision and Pattern Recognition (cs.CV)
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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 The paper presents a management-based approach to regulating artificial intelligence (AI), which has gained popularity globally due to concerns about AI-related harms. This approach emphasizes human oversight during the development and training of AI tools. The authors argue that refinements in human-guided training techniques are necessary to align with this emerging regulatory paradigm. They highlight the benefits of human-guided training, including improved AI performance, fairness, and explainability. The paper discusses the connection between management-based regulatory frameworks and the need for human oversight during training. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary AI is getting a bad rap because it’s not being governed well. To fix this, people are proposing a new way to regulate AI called “management-based.” This means humans will have more control over how AI tools are developed and trained. The authors think that making AI training more human-led will make AI better, fairer, and easier to understand. |
