Summary of Towards Leveraging News Media to Support Impact Assessment Of Ai Technologies, by Mowafak Allaham et al.
Towards Leveraging News Media to Support Impact Assessment of AI Technologies
by Mowafak Allaham, Kimon Kieslich, Nicholas Diakopoulos
First submitted to arxiv on: 4 Nov 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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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 research explores the potential of fine-tuning large language models (LLMs) to incorporate diversity into impact assessments (IAs) of AI technologies. The study highlights the effectiveness of fine-tuned LLMs, particularly Mistral-7B, in generating high-quality negative impacts across four qualitative dimensions: coherence, structure, relevance, and plausibility. This approach can support IAs by providing a wider range of categories of impacts that were previously overlooked. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary AI technology has the potential to impact society, policy, and culture in various ways. Researchers are working on fine-tuning large language models (LLMs) to better understand these effects. The goal is to create more accurate assessments of AI’s impact by considering diverse perspectives from around the world. This could lead to a more complete picture of how AI affects us. |
Keywords
» Artificial intelligence » Fine tuning
