Artificial Intelligence (AI) is increasingly used to analyze large amounts of data in various practices, such as object recognition. We are specifically interested in using AI-powered systems to engage local communities in developing plans or solutions for pressing societal and environmental concerns. Such local contexts often involve multiple stakeholders with different and even contradictory agendas, resulting in mismatched expectations of these systems' behaviors and desired outcomes. There is a need to investigate if AI models and pipelines can work as expected in different contexts through co-creation and field deployment. Based on case studies in co-creating AI-powered systems with local people, we explain challenges that require more attention and provide viable paths to bridge AI research with citizen needs. We advocate for developing new collaboration approaches and mindsets that are needed to co-create AI-powered systems in multi-stakeholder contexts to address local concerns.
翻译:人工智能(AI)越来越多地用于分析各种实践中的大量数据,例如物体识别; 我们特别有兴趣利用人工智能动力系统,让地方社区参与制定计划或解决方案,解决紧迫的社会和环境问题; 这种本地环境往往涉及多个利益攸关方,其议程不同,甚至相互矛盾,导致对这些系统行为和预期结果的期望不相称; 有必要调查人工智能模型和管道能否在不同情况下通过共同创建和实地部署而发挥预期的作用; 根据与当地人民共同创建AI动力系统的案例研究,我们解释需要更多关注的挑战,并提供可行的途径,将AI研究与公民需要联系起来; 我们倡导制定新的合作方式和心态,以便在多个利益攸关方背景下共同创建AI动力系统,以解决当地关切的问题。