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PBL
Bloomberg Project
AI and Economics: Decision-Making with Language Models
Simulate economic decision-making with large language models (LLMs) acting as consumers, firms, policymakers, or loan officers,.
Project
Bloomberg Project
Location
Online
Duration
8 Weeks
Upcoming Sessions
May 25 - July 24, 2026
Outcomes
AI Experimentation for policy and market simulations
Algorithmic Fairness analysis in lending decisions
Credit Risk Modeling using AI loan evaluation systems
Text Data Processing for economic narrative insights
Sentiment Analysis from news and social media data
You Will Get
Industry Guidance
Work directly with our project leads—experts and top researchers—who bring their real-world insights and expertise straight to your learning experience.
Research Experience
Collaborate with teammates and the project lead in a multi-week project to pursue novel questions in your research field.
Peer Networks
Engage with our PBL participants from all over the world. Collaborate with new peers and learn about their own research endeavours.
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A Strong Portfolio
Put your best foot forward in the PBL with a standout project and receive a PBL Evaluation Report that can be used as a recommendation letter for employers and grad schools.
Expert Guidance
Get personalized feedback to grow your research and innovation skills.
Deliverables
Real projects, lasting connections, and new opportunities beyond your program.
Project Deliverables
The final presentation of your 8 weeks could be a poster, written report, or a slide deck, all of which can be expanded on.
Research Extension
Utilize up to 5 additional meeting times with the project lead after the project’s conclusion to build your work out for publication or conference presentation.
Industry Network
Meet peers in your projects and participate in a global talent community both online and in-person.
Industry Application
Bloomberg is a global leader in financial data, economic intelligence, and market analytics. Through platforms like the Bloomberg Terminal, the company aggregates massive datasets—from macroeconomic indicators to market sentiment—to help investors, policymakers, and institutions make informed decisions. This PBL mirrors those real-world workflows by using AI and language models to simulate markets, analyze economic narratives, and model financial decisions. Learners gain experience applying AI to economic data, sentiment analysis, and policy evaluation, similar to how Bloomberg develops tools that transform complex economic information into actionable insights for governments, banks, and financial professionals.
Popular Industry Positions
Policy & Economic Research Analyst
Applies data analytics and AI tools to evaluate macroeconomic trends and policy outcomes.
Financial AI Analyst
Uses machine learning and data tools to interpret market sentiment and investment signals.
Economic Data Scientist
Builds AI models to analyze economic indicators, market behavior, and policy impacts.
Tracks
Track 1
Simulated Markets with LLM Agents
Learners will build a virtual marketplace where large language model agents act as consumers and generate demand behavior under different market conditions.
Define AI consumer personas with budgets and preferences
Use LLMs to simulate purchasing decisions from product menus
Analyze price sensitivity and demand elasticity
Observe substitution effects when prices or products change
Evaluate how nudges influence consumer behavior
Track 2
AI as the Central Bank
Learners will simulate monetary policy decision-making by using LLMs to analyze economic indicators and determine interest-rate strategies.
Analyze macroeconomic indicators such as inflation and unemployment
Prompt LLMs to propose interest-rate decisions
Evaluate tradeoffs between price stability and employment
Compare AI-generated policies with traditional economic models
Interpret and explain the reasoning behind policy responses
Track 3
Measuring Economic Sentiment with AI
Learners will build a sentiment analysis system using LLMs to measure economic mood from news, social media, and public discussions.
Collect economic text data from news and social media
Use LLMs to classify sentiment such as optimism or uncertainty
Visualize sentiment trends across time
Compare AI sentiment with consumer confidence indicators
Analyze how narratives influence markets and expectations
Track 4
The AI Loan Officer
Learners will simulate AI-driven lending decisions to understand how financial institutions evaluate borrower risk and creditworthiness.
Create borrower profiles with diverse financial characteristics
Prompt LLMs to approve or reject loan applications
Identify which borrower attributes influence credit decisions
Test how additional signals such as credit scores change outcomes
Evaluate bias, transparency, and fairness in AI lending systems
PBL Journey
Online PBL Projects meet once a week for 8 weeks, and follow the research project format. Participants will meet the project lead, learn the conventions of the field and familiarize themselves with the tracks, then spend the middle portion of their time collaborating to develop their research.
At the end, participants will present their final project and receive feedback, with the opportunity to extend their timeline and develop the project in greater depth.
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Project Team
Our Academic Team plays a vital role in your PBL journey at Blended Learning. We are dedicated to enhancing your learning experience and ensuring your academic success. Our team consists of three distinct roles, each with a specific focus to support your Research Guidance, Project Progress, and Personal Growth.
Project Lead
Providing Industry and Research Guidance
Research Scientist, Stanford Digital Economy Lab
She is a Research Scientist at the Stanford Digital Economy Lab within the Stanford Institute for Human-Centered AI (HAI), where her work focuses on how artificial intelligence and machine learning shape macro-finance and the digital economy. She previously spent seven years at the Federal Reserve Bank of Richmond as a financial economist and quantitative analyst, specializing in banking supervision, regulatory policy, and financial risk modeling. She holds a Ph.D. in Economics from the University of Houston and a B.A. from Tel Aviv University. Her research spans AI in central banking, behavioral finance, and alternative data, with publications in leading economics and machine learning journals.
Academic Advisor
Tracking Your Project Development
The Academic Advisor is dedicated to your project completion success. They manage the progress of your PBL, guiding team formation, facilitating group discussions, and resolving conflicts. Additionally, the Academic Advisor ensures team member contributions are on track and provides logistical support, including attendance tracking, hosting recitation sessions, managing research support requests, and conducting student evaluations at the end of the PBL.
From Our Students
"After a night spent debugging, I suddenly discovered the program running perfectly. In that triumphant moment, you realize your true capability and success. The exhaustion fades, replaced by the thrill of knowing your skills and persistence led to this achievement, reaffirming your potential."
Nicole Y.
National University of Singapore
B.S. Economics
FAQs
What is the learning format of a PBL?
All PBLs are offered in an 8-week online format that begins with an orientation followed by subject setup overview of the different tracks. The majority of the session time is dedicated to project development, with a final presentation at the culmination of the 8 weeks. Many PBLs are also offered bi-annually in an on-campus format that consists of daily in-person meetings.
How long does each PBL cohort last？
One round of the Online PBL cohort lasts 8 weeks, preceded bys a pre-PBL orientation week. Each On-Campus PBL usually has 8 in person meetings, with intensive classroom education and collaboration. This means the biggest difference between online and on-campus PBLs is time participants have in between meetings.
How can I be more academically prepared before the PBL starts?
Review the Blended Learning Insights sent by the Academic Advisor and familiarize yourself with the project topic and pre-learning materials. Ensure you have all necessary softwares and other resources needed for the PBL.
For each PBL cohort, will I work in teams? Are PBL team members self-selected or assigned?
Yes, you will work in teams for each round of the PBL Cohort. Each team has 3 to 6 participants, organized by the Academic Team. The Academic Advisor will organize groupings based on students' backgrounds, preferred track, and skills.
Can I work with the Project Lead on my project after the PBL ends?
Yes, with your AI + X Research Plan, you may request up to five PBL Research Extension meetings, where you work with the project lead to develop your project into a working manuscript. To schedule a PBL Research Extension meeting, talk to your Academic Advisor at the conclusion of your PBL.
What do I receive at the end of the PBL?
At the conclusion of the PBL cohort, you can request a PBL Evaluation Report which summarizes the PBL content, the hours you spent, the track you chose, and includes a recommendation letter from the Project Lead (for eligible participants who completed the project successfully).
Is attendance mandatory for PBL Live Sessions and Recitation Sessions?
Yes, attendance is mandatory for both PBL Live Sessions and Recitation Sessions. Participants with three or more unexcused absences forfeit their eligibility for a PBL Evaluation Report.
Do I need to have my camera on during online PBL Live Sessions?
Yes, you must have your camera on during online PBL Live Sessions. Participants with cameras off will be marked as absent. This is meant to encourage active engagement and participation in meetings.
