Past Event

Measuring Development 2024: AI, the Next Generation

The annual Measuring Development Conference co-hosted with the Center for Effective Global Action (CEGA) and the University of Chicago Center for the Economics of Innovation and Development (CEID) will focus on the theme of AI.

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

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
Karim Lasri (World Bank)

Leveraging LLM-powered Text-to-SQL Tools for Democratizing Data Analytics
Jahnavi Meher (IDinsight)

AI for Data: Exploring AI Applications Across the Data Lifecycle
Aivin Solario (World Bank)

Evaluating the Quality of Automatic Speech Recognition (ASR) Models in Improving Transcription in Qualitative Research
Dunstan Matekenya (World Bank)

 
10:25 AM Coffee Break  
10:45 AM

Research Session I: Integrating Generative AI into the Scientific Process
Chair: Haishan Fu (World Bank)

Crowdsourcing Safety: The Value of Passenger Feedback for Measuring Driving Safety
Sveta Milusheva (World Bank)

Automated Social Science: A Structural Causal Model-Based Approach
Benjamin Manning (MIT)

Advancing Foundation Models for Geospatial Applications with Scarce Reference Data
Hamed Alemohammad (Clark University)

Productionizing Geospatial Foundation Models (GeoFMs) for Development: Forecasting
Vivek Sakhrani (Atlas AI)

 
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

  • Han Sheng Chia (CGD, USAID) - Moderator
  • Sayash Kapoor (Princeton University)
  • Alex Nawar (OpenAI)
  • Arianna Legovini (World Bank)
  • Mike Pisa (Google)
 
1:50 PM

Research Session II | AI-Informed Safety and Algorithmic Bias
Chair: Charles Mberi (African Institute of Mathematical Sciences)

Using Controlled Image Synthesis to Measure Social Bias in Vision-language Models
Carina Ines Hausladen (ETH Zurich)

Please Take a Second Look: Improving Labeling Quality for Toxic Content using Nudges
Sung Hyun (SK) Kwon (University of Maryland)

Hate Speech Detection in Limited Data Contexts Using Synthetic Data Generation
Daniel Nkemelu (Georgia Institute of Technology)

Detecting and Reducing Harmful Online Content at Scale Using Large Language Models
Samiel Fraiberger and Philipp Zimmer (World Bank)

 
2:50 PM

Lightning Talks: Transparency and Accountability in AI Design

Deon: An ethics checklist for data science
Katie Wetstone (Driven Data)

Document Before You Deploy: A Proposal for Accountability in Generative AI Decision-Making
Taylor Lynn Curtis (MIT)

 
3:05 PM Coffee Break  
3:20 PM

Research Session III | LLM-enabled Behavioral Insights
Chair: Vice minister Jessica Niño (Ministry of Development and Social Inclusion, Republic of Peru)

Early Experimental Evidence on the Behavioral Dynamics of Prompt Engineering
Hong-Yi TuYe (MIT)

The Uneven Impact of Generative AI on Entrepreneurial Performance
Rem Koning (Harvard Business School) 

Gamified and Narrative Chatbot for Infant Nutrition and Perinatal Depression
Paloma Bellatin (The Behavioural Insights Team)

Critical Thinking and Storytelling
Brian Jabarian (University of Chicago)

 
4:20 PM

Lightning Talks: Reasoning with LLMs

ClimateX: Do LLMs Accurately Assess Human Expert Confidence in Climate Statements?
Edmond Dilworth(Stanford University)

Using Large Language Models for Qualitative Analysis can Introduce Serious Bias
Julian Ashwin (Maastricht University)

Strategy for Institutional AI Adoption
Rweyemamu Barongo (Bank of Tanzania)

 
4:35 PM

Tools Demo II | Structuring, Verifying, and Extending LLM-informed Research

LLM Knowledge Hubs: A Transformative Leap for Development Data
Dimitri Stoelinga (Laterite) 

Leveraging Text Data and Generative AI in Complex Thematic Evaluations
Virginia Ziulu (Independent Evaluation Group-IEG)

Agrifood Data Lab: Using AI to Facilitate Access to Agricultural Data and Use Cases
Michael Norton (World Bank)

Democratizing AI
Jude Mwenda (Fastagger Inc.)

Maintaining Human Oversight and Agency in AI-assisted Development Research: Instrument Evaluation as Case Study
Chris Robert (Higher Bar AI, PBC)

 
5.25 PM Closing & Acknowledgements
Sean Luna McAdams (CEGA) & Maria Ruth Jones (World Bank)
 
5:30 PM
Reception  

Date: May 02, 2024

Time: 09:00 AM - 07:00 PM ET

Location: Washington, DC