mlsanityData to 7 Oct 2026

Empowering Local Communities Using Artificial Intelligence

arXiv 2110.02007 ↗First posted 5 Oct 2021cs.AI cs.HCcited by 7

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Abstract (arXiv)

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.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 9 of its 58 references that are in the map. First posted on arXiv 5 Oct 2021.

Builds on

9 of 58 references.

References · 9

  1. 2017Towards A Rigorous Science of Interpretable Machine Learningcited by 1,400
  2. 2017Explanation in Artificial Intelligence: Insights from the Social Sciencescited by 1,201
  3. 2020Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scanscited by 158
  4. 2020Participation is not a Design Fix for Machine Learningcited by 110
  5. 2021Envisioning Communities: A Participatory Approach Towards AI for Social Goodcited by 29
  6. 2020Project RISE: Recognizing Industrial Smoke Emissionscited by 5
  7. 2018Community-Empowered Air Quality Monitoring Systemcited by 2
  8. 2019When Human-Computer Interaction Meets Community Citizen Sciencecited by 1
  9. 2019Smell Pittsburgh: Engaging Community Citizen Science for Air Qualitycited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 3; 2023: 2; 2024: 1; 2025: 0; 2026: 1.

7 papers.