General purpose AI, such as ChatGPT, seems to have lowered the barriers for the public to use AI and harness its power. However, the governance and development of AI still remain in the hands of a few, and the pace of development is accelerating without a comprehensive assessment of risks. As a first step towards democratic risk assessment and design of general purpose AI, we introduce PARTICIP-AI, a carefully designed framework for laypeople to speculate and assess AI use cases and their impacts. Our framework allows us to study more nuanced and detailed public opinions on AI through collecting use cases, surfacing diverse harms through risk assessment under alternate scenarios (i.e., developing and not developing a use case), and illuminating tensions over AI development through making a concluding choice on its development. To showcase the promise of our framework towards informing democratic AI development, we run a medium-scale study with inputs from 295 demographically diverse participants. Our analyses show that participants' responses emphasize applications for personal life and society, contrasting with most current AI development's business focus. We also surface diverse set of envisioned harms such as distrust in AI and institutions, complementary to those defined by experts. Furthermore, we found that perceived impact of not developing use cases significantly predicted participants' judgements of whether AI use cases should be developed, and highlighted lay users' concerns of techno-solutionism. We conclude with a discussion on how frameworks like PARTICIP-AI can further guide democratic AI development and governance.

翻译：通用人工智能（如ChatGPT）似乎降低了公众使用并利用AI能力的门槛。然而，AI的治理与发展仍掌握在少数人手中，其发展速度不断加快却缺乏全面的风险评估。作为实现通用人工智能民主化风险评估与设计的第一步，我们提出了PARTICIP-AI——一个精心设计的框架，使非专业人士能够系统推演和评估AI应用场景及其潜在影响。该框架通过以下方式帮助我们获取更细致入微的公众意见：收集具体应用案例，在不同情境（即开发或不开发某应用场景）下进行风险评估以揭示多元危害，并通过最终是否开发的决策来凸显AI发展中的矛盾张力。为验证本框架对民主化AI发展的启示价值，我们开展了中等规模研究，收集了295名人口统计学背景多元的参与者的反馈。分析表明：参与者更关注AI在个人生活与社会层面的应用，这与当前以商业为导向的AI开发形成鲜明对比。我们还发现了专家定义之外的多种潜在危害，例如对AI及机构信任的侵蚀。进一步研究发现，参与者对"不开发应用场景所产生影响"的感知，能显著预测其是否支持开发该AI应用的判断，这凸显了普通用户对技术万能论的担忧。最后，我们探讨了PARTICIP-AI类框架如何进一步引导民主化的AI发展与治理。