Foundational models like large language models (LLMs) have recently commanded widespread public attention—and caution—given their transformational potential for both our economy and society. Naturally, questions loom about how these AI innovations will impact the global development research and policy landscape. If used properly by the right actors, these tools might unlock enormous troves of data and create new opportunities to improve lives around the world.
The World Bank's Development Impact (DIME) department and Development Data Group (DECDG), the Center for Effective Global Action (CEGA), and the development community at the University of Chicago are excited to explore this topic at our tenth annual Measuring Development (MeasureDev) Conference, “AI, The Next Generation.”
MeasureDev 2024 will feature presentations on AI that span the measurement ecosystem: from efforts to improve and expand responsible data infrastructure in low- and middle-income countries (LMICs) and facilitate the development of a new generation of AI tools, to analysis tailoring foundational models to optimize generative AI (GenAI) including LLMs for social impact. The event will feature speakers who are shaping the way these new tools will be adopted and regulated.
Featured Speakers
- ORGANIZERS
- AGENDA
- RELATED
The World Bank's Development Impact (DIME) department generates high-quality and operationally relevant data and research to transform development policy, help reduce extreme poverty, and secure shared prosperity.
The Development Data Group (DECDG) is the World Bank's center of excellence on data and statistics, involved in the entire life cycle of data: from its collection, curation, and management through its analysis, visualization, dissemination, as well as enabling its use by policymakers and citizens.
The Center for Effective Global Action (CEGA) is a research hub at the University of California, Berkeley that generates evidence decision-makers use to reduce global poverty.
The development community at the University of Chicago uses the tools of economics to identify, test, refine, and scale innovations with the potential to benefit millions of people. 
| 8:30 AM | Registration and Coffee | |
9:00 AM |
Opening Remarks Arianna Legovini (World Bank), Carson Christiano (CEGA) and Leah Rosenzweig (DIL) |
|
| 9:15 AM | Keynote 1 Dan Bjorkegren (Columbia University) |
|
| 9:45 AM | Tools Demo 1 for (Semi-)Automated Evidence Aggregation ImpactAI: Impact Evaluation Insights Using Generative AI Leveraging LLM-powered Text-to-SQL Tools for Democratizing Data Analytics AI for Data: Exploring AI Applications Across the Data Lifecycle Evaluating the Quality of Automatic Speech Recognition (ASR) Models in Improving Transcription in Qualitative Research |
|
| 10:25 AM | Coffee Break | |
| 10:45 AM |
Research Session I: Integrating Generative AI into the Scientific Process Crowdsourcing Safety: The Value of Passenger Feedback for Measuring Driving Safety Automated Social Science: A Structural Causal Model-Based Approach Advancing Foundation Models for Geospatial Applications with Scarce Reference Data Productionizing Geospatial Foundation Models (GeoFMs) for Development: Forecasting |
|
| 11:45 AM |
Keynote II: Guardrails for the New Frontier in Global Development: Building AI Solutions that Center Equity and Inclusion Uyi Stewart (data.org) |
|
| 12:15 PM | Lunch | |
| 1:00 PM | Panel | Unlocking AI's Economic Potential for Shared Prosperity: A Pragmatic Policy Agenda
|
|
| 1:50 PM | Research Session II | AI-Informed Safety and Algorithmic Bias Please Take a Second Look: Improving Labeling Quality for Toxic Content using Nudges Hate Speech Detection in Limited Data Contexts Using Synthetic Data Generation Detecting and Reducing Harmful Online Content at Scale Using Large Language Models |
|
| 2:50 PM | Lightning Talks: Transparency and Accountability in AI Design Deon: An ethics checklist for data science Document Before You Deploy: A Proposal for Accountability in Generative AI Decision-Making |
|
| 3:05 PM | Coffee Break | |
| 3:20 PM | Research Session III | LLM-enabled Behavioral Insights Early Experimental Evidence on the Behavioral Dynamics of Prompt Engineering The Uneven Impact of Generative AI on Entrepreneurial Performance Gamified and Narrative Chatbot for Infant Nutrition and Perinatal Depression Critical Thinking and Storytelling |
|
| 4:20 PM | Lightning Talks: Reasoning with LLMs ClimateX: Do LLMs Accurately Assess Human Expert Confidence in Climate Statements? Using Large Language Models for Qualitative Analysis can Introduce Serious Bias |
|
| 4:35 PM | Tools Demo II | Structuring, Verifying, and Extending LLM-informed Research LLM Knowledge Hubs: A Transformative Leap for Development Data Leveraging Text Data and Generative AI in Complex Thematic Evaluations Agrifood Data Lab: Using AI to Facilitate Access to Agricultural Data and Use Cases Democratizing AI Maintaining Human Oversight and Agency in AI-assisted Development Research: Instrument Evaluation as Case Study |
|
| 5.25 PM | Closing & Acknowledgements Sean Luna McAdams (CEGA) & Maria Ruth Jones (World Bank) |
|
| 5:30 PM |
Reception |
Learn more about the annual Measuring Development Conference
Measuring Development 2023: Mitigating the Risks and Impacts of Climate Change
Measuring Development 2022: The Role of Mobile Data in Global Development Research
Measuring Development 2021: Emerging Data and Methods in Global Health Research
Measuring Development 2020: Data Integration and Data Fusion
Measuring Development 2019: Crisis Preparedness and Response
Conference round-up: the role of mobile data in global development research
Date: May 02, 2024
Time: 09:00 AM - 07:00 PM ET
Location: Washington, DC