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Towards Leveraging News Media to Support Impact Assessment of AI Technologies
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Expert-driven frameworks for impact assessments (IAs) may inadvertently overlook the effects of AI technologies on the public's social behavior, policy, and the cultural and geographical contexts shaping the perception of AI and the impacts around its use. This research explores the potentials of fine-tuning LLMs on negative impacts of AI reported in a diverse sample of articles from 266 news domains spanning 30 countries around the world to incorporate more diversity into IAs. Our findings highlight (1) the potential of fine-tuned open-source LLMs in supporting IA of AI technologies by generating high-quality negative impacts across four qualitative dimensions: coherence, structure, relevance, and plausibility, and (2) the efficacy of small open-source LLM (Mistral-7B) fine-tuned on impacts from news media in capturing a wider range of categories of impacts that GPT-4 had gaps in covering.
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Cited by 1 Pith paper
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Informing AI Risk Assessment with News Media: Analyzing National and Political Variation in the Coverage of AI Risks
AI risk coverage in the news varies by country and by U.S. outlet political bias, with right-leaning outlets emphasizing malicious actors and political-culture risks.
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