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AI Developed to Locate Slums Worldwide... Wins Best Paper Award at AAAI 2026
<(From Left) Sumin Lee, Sungwon Park, Prof. Jihee Kim, Prof. Meeyoung Cha, Prof. Jeasurk Yang>
"Cities don't even know where their slums (impoverished areas) are located."
In many developing nations, the most vulnerable citizens are invisible to the state simply because their homes don't appear on any official map. Today, a breakthrough using Artificial Intelligence (AI) is changing that.
A joint research team from KAIST and Chonnam National University in South Korea and MPI-SP in Germany has developed an AI technology that autonomously identifies slum areas using nothing but satellite imagery. This technology is expected to fundamentally transform urban policy-making and public resource allocation in developing countries where data is scarce and has won the Best Paper Award in the ‘AI for Social Impact’ category at the AAAI 2026 (Association for the Advancement of Artificial Intelligence), the world's premiermost prestigious AI academic conference.
Why it Matters
While previous studies struggle to recognize slums across countries due to varying architectural styles, the team introduced a "Mixture-of-Experts (MoE)" structure. In this system, multiple AI models learn different regional characteristics; when a new city is inputted, the system automatically selects the most appropriate model.
<Figure1. Overview of the Mixture-of-Experts(MoE) structure to identify slum areas>
The core of this research is "Test-Time Adaptation (TTA)" technology. Even if humans do not pre-mark slum locations in a new city, the AI reduces its own errors by comparing and verifying the prediction results of multiple models, trusting only the areas where they commonly agree. This ensures stable performance even in regions with insufficient data.
The research team applied this technology to major cities such as Kampala (Uganda) and Maputo (Mozambique) and confirmed that it distinguishes slum areas more precisely than existing state-of-the-art technologies.
This technology is expected to be utilized in various policy fields, including:
Establishing urban infrastructure expansion plans for developing countries.
Identifying areas vulnerable to disasters and infectious diseases in advance.
Selecting targets for housing environment improvement projects.
Monitoring the implementation of UN Sustainable Development Goals (SDGs).
<Figure2. Slum segmentation results in Kampala in 2015 (yellow) and 2023 (red). Over the eight-year period, the slum ratio in the city increased from 8.4% to 8.6%>
Meeyoung Cha, an AI researcher and author, stated, "This research proves that AI is no longer just a tool for analysis. It is a tool for action. Our technology can bridge the data gap to solve the world’s most pressing social challenges." Jihee Kim, an economist and author, added, "It will complement costly field surveys and help effectively allocate limited resources to the areas that need them most."
The research results were presented at AAAI 2026 in Singapore on January 25th.
Paper Title: Generalizable Slum Detection from Satellite Imagery with Mixture-of-Experts
Paper Link: https://aaai.org/about-aaai/aaai-awards/aaai-conference-paper-awards-and-recognition/
This research was supported by the National Research Foundation of Korea (NRF) through the Mid-career Researcher Support Program and the Data Science Convergence Human Resources Training Program.
2026.03.08 View 1067 -
Professor Jihee Kim Wins the Lucas Prize for Her Income Inequality Theory
Professor Jihee Kim from the School of Business and Technology Management at KAIST was announced as one of two winners of the 2021 Robert E. Lucas Jr. Prize. Professor Kim was recognized for having provided an empirical analysis on engines of income growth, sources of income inequality, and their rich interplay in her paper published in the Journal of Political Economy (JPE) in October 2018. The co-author of this study, Professor Charles I. Jones at Stanford University, was honored to be another awardee of this year’s Lucas Prize.
The Robert E. Lucas Jr. Prize, simply known as the Lucas Prize, is awarded biannually for the most interesting paper in the area of Dynamic Economics published in the leading economics journal JPE in the preceding two years. The prize was established in 2016 in celebration of the 1995 Nobel Prize in Economics Laureate Dr. Lucas’s seminal contributions to economics. The two former prizes were presented in 2019 and 2017 respectively.
Professor Kim and Professor Jones, in their award-winning paper titled 'A Schumpeterian Model of Top Income Inequality', observed that top income inequality was relatively low and stable between 1960 and 1980, but then rose sharply in some countries, including the United States and the United Kingdom.
The authors focused on entrepreneurial activities and the resulting income as the driving force of income inequality. They assumed that the forces that increased the efforts of fast-growing entrepreneurs to improve their products or increased productivity of their efforts could increase income inequality. On the other hand, the forces that enhanced creative destruction or that raised the rate at which high-growth entrepreneurs lost that status could decrease income inequality, according to the authors’ theory.
Professor Kim explained, “Various economic forces due to globalization, the advancement in AI and IT technologies, taxes, and policies related to innovation blocking may explain the varied patterns in income inequality.”
“Through follow-up research, I will continue developing economic theory models that can analyze the impact of changes such as income tax rates and salary negotiations on income inequality,” she added.
Professor Kim received her bachelor’s degree from the KAIST School of Computing in 2005 and pursued her graduates studies at Stanford University, acquiring a master’s degree in economics in 2011 and a doctoral degree in management science and engineering in 2013.
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2021.03.26 View 12235