  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.
