Funding AI for Good: A Call for Meaningful Engagement

2025-09-15

AI Summary

This study identifies a fundamental misalignment between technocentric tendencies and social impact objectives in AI4SG (Artificial Intelligence for Social Good) practice: funding agendas overemphasize technical capability while neglecting community engagement, contextual understanding, and long-term sustainability—resulting in limited real-world social benefit, particularly in public health. Method: Through qualitative analysis of 35 funding documents (totaling ~$410 million), the study examines prevailing funding frameworks and their institutional constraints. Contribution/Results: It reveals systemic underinvestment in localized co-design mechanisms and sustained community empowerment. The paper introduces the “dual-track funding design” framework, advocating that funders simultaneously strengthen technical feasibility and socio-contextual alignment, while institutionalizing cross-disciplinary collaboration among AI4SG practitioners, HCI researchers, and community development professionals. This framework offers an actionable governance pathway to enhance the authenticity, equity, and sustainability of AI’s societal deployment.

Technology Category

• Philosophy and Ethics of AI: Societal Impact of AI
• Humans and AI: Other Foundations of Human Computation & AI
• Application Domains: Humanities & Computational Social Science

Application Category

• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

Artificial Intelligence for Social Good (AI4SG) is a growing area exploring AI's potential to address social issues like public health. Yet prior work has shown limited evidence of its tangible benefits for intended communities, and projects frequently face inadequate community engagement and sustainability challenges. Funding agendas play a crucial role in framing AI4SG initiatives and shaping their approaches. Through a qualitative analysis of 35 funding documents -- representing about $410 million USD in total investments, we reveal dissonances between AI4SG's stated intentions for positive social impact and the techno-centric approaches that some funding agendas promoted. Drawing on our findings, we offer recommendations for funders to scaffold approaches that balance both contextual understanding and technical capacities in future funding call designs. We call for greater engagement between AI4SG funders and the HCI community to support community engagement work in the funding program design process.

Problem

• Analyzes funding agendas' role in AI4SG initiatives
• Reveals dissonance between social impact goals and techno-centric approaches
• Examines inadequate community engagement in AI4SG projects

Innovation

• Analyzed funding documents for AI4SG
• Revealed techno-centric versus social impact dissonances
• Recommended balanced contextual and technical approaches