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Using Scenario-Writing for Identifying and Mitigating Impacts of Generative AI
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Impact assessments have emerged as a common way to identify the negative and positive implications of AI deployment, with the goal of avoiding the downsides of its use. It is undeniable that impact assessments are important - especially in the case of rapidly proliferating technologies such as generative AI. But it is also essential to critically interrogate the current literature and practice on impact assessment, to identify its shortcomings, and to develop new approaches that are responsive to these limitations. In this provocation, we do just that by first critiquing the current impact assessment literature and then proposing a novel approach that addresses our concerns: Scenario-Based Sociotechnical Envisioning.
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Cited by 2 Pith papers
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Envisioning Stakeholder-Action Pairs to Mitigate Negative Impacts of AI: A Participatory Approach to Inform Policy Making
A two-survey participatory pipeline turns laypeople's brainstormed stakeholder-action pairs for generative AI harms in the news environment into prioritized, LLM-generated policy fact sheets.
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Global Perspectives of AI Risks and Harms: Analyzing the Negative Impacts of AI Technologies as Prioritized by News Media
In 42,853 news articles from 27 countries, societal and legal risks dominate AI coverage, while environmental risks are almost absent, and outlet political bias shifts the emphasis.
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