The Next Wave of AI for Social Impact: Challenges and Opportunities

The burgeoning field of artificial intelligence for social impact (AI4SI) represents a significant evolution in artificial intelligence, prioritizing measurable positive impact for vulnerable and under-resourced populations. This article examines the historical context and recent surge in AI4SI, driven by technological advancements and a growing awareness of societal challenges. It highlights the crucial role of interdisciplinary collaboration, ethical considerations, and the potential of emerging AI trends in addressing issues such as poverty, health, and environmental sustainability. Furthermore, the article delves into key research questions and challenges facing the field, including the need for contextually relevant AI design, overcoming data limitations, ensuring scalable and sustainable deployments in resource-constrained environments, and establishing robust evaluation frameworks. Realizing the full potential of AI to address pressing societal needs in the coming decade and beyond will hinge on effectively navigating these challenges and fostering a deeply impact-driven approach to research and development.

Authors

Institutions

Publication Details

Journal
IEEE Intelligent Systems
Published
2025-05-01
DOI
https://doi.org/10.1109/mis.2025.3565829
Citations
1
Primary Topic
Impact of Light on Environment and Health
Type
article
Field-Weighted Citation Impact
1.11
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Next Wave of AI for Social Impact: Challenges and Opportunities

Milind Tambe, Andrew Perrault, Fei Fang, Bryan Wilder
1 citations
IEEE Intelligent Systems
Impact of Light on Environment and Health
1.11
article

The Next Wave of AI for Social Impact: Challenges and Opportunities

Milind Tambe, Andrew Perrault, Fei Fang, Bryan Wilder
article en
1 citations

Abstract

The burgeoning field of artificial intelligence for social impact (AI4SI) represents a significant evolution in artificial intelligence, prioritizing measurable positive impact for vulnerable and under-resourced populations. This article examines the historical context and recent surge in AI4SI, driven by technological advancements and a growing awareness of societal challenges. It highlights the crucial role of interdisciplinary collaboration, ethical considerations, and the potential of emerging AI trends in addressing issues such as poverty, health, and environmental sustainability. Furthermore, the article delves into key research questions and challenges facing the field, including the need for contextually relevant AI design, overcoming data limitations, ensuring scalable and sustainable deployments in resource-constrained environments, and establishing robust evaluation frameworks. Realizing the full potential of AI to address pressing societal needs in the coming decade and beyond will hinge on effectively navigating these challenges and fostering a deeply impact-driven approach to research and development.

IEEE Intelligent SystemsVol. 40(3)
Harvard University Press (US), The Ohio State University (US), Carnegie Mellon University (US)
Reduced inequalities
Openalex Percentile: Top 23%
Impact of Light on Environment and Health
1.11
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

The Next Wave of AI for Social Impact: Challenges and Opportunities — Milind Tambe, Andrew Perrault, et al. · IEEE Intelligent Systems (2025) | TGRS Research Map | TGRS