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Digital Economy

Economics of Artificial Intelligence

Specialize in Artificial Intelligence and its impact on the economy.

10h (5 days)

€675 - €1,175

Face-to-face

English

Program date: June 30 - July 4, 2025

Application deadline: June 23, 2025

Learn more

Economics of Artificial Intelligence

Applications for 2025 Summer School programs are now open!

Summer school

Digital Economy

Economics of Artificial Intelligence

Course Overview

Artificial Intelligence (AI) algorithms are increasingly crowding our markets and, more broadly, shaping our societies. The impact of learning algorithms on competition in “digital” markets is an issue of great importance in policy circles and increasingly studied in academic work.

This short course will bring students to the frontier of research on the Economics of Artificial Intelligence with particular emphasis on competition policy. We will focus on some of the topics that will pose imminent and relevant challenges in this rapidly evolving area for economic research and policymakers.

This course is particularly suitable to advanced graduate students looking for a dissertation topic as well as practitioners and legal scholars seeking to catch up with the state-of-the-art academic research on digital markets.

Faculty

Learning algorithms' impact on digital market competition is crucial for policy and academia

This course would be ideal for:

Advanced graduate students looking for a dissertation topic
Practitioners seeking to catch up with state-of-the-art academic research on digital markets

Develop insights into the evolving landscape of AI and its economic implications

By the end of this course, participants will have:

Understood the frontier of research on the Economics of Artificial Intelligence
Analyzed the impact of AI and learning algorithms on competition in digital markets
Explored competition policy in the context of AI developments
Identified and discussed imminent challenges in AI for economic research and policymakers
Critically evaluate current academic and policy approaches to AI economics

Program Syllabus for Economics of AI

What is AI?

Economics in AI
Economics of AI
Technical session: Reinforcement Learning algorithms

Policies and Value Functions

Dynamic programming and Montecarlo methods
Temporal difference learning
Application: Pricing algorithms

Introduction to Pricing Algorithms

Experimental evidence of Algorithmic collusion
Empirical evidence of algorithmic collusion
More theories of harm and evidence

Recommender Systems and Collaborative Filtering

Introduction and the Spectrum of Applications

Do algorithms affect consumption? Evidence
Case Study: Spotify
Theories of biased advice
Experimental evidence of recommendation bias
Technical Session: Collaborative filtering algorithms

Neighborhood-Based Collaborative Filtering

Model Based Collaborative Filtering (latent factor models)

Foundation Models / LLMs

Distinctive Product and Industry Characteristics

Competition issues in the vertical stack

Algorithmic Harm Via Choice Manipulation

Public Policy

Why is AI Different?

The policy landscape: AI act, DMA, DSA
Application: Tackling algorithmic bias
Application: Tackling Collusion

Why join our Summer School?

All BSE Summer courses are taught to the same high standard as our Master’s programs. Join us to:

1

Network with like-minded peers

2

Study in vibrant Barcelona

3

Learn from world-renowned faculty

Admissions and Requirements

Please make sure you meet the following admissions criteria before you apply.

Program date: June 30 - July 4, 2025

Application deadline: June 23, 2025

Requirements

A strong background in Economics or a field closely related to the course topic (Statistics, Law, etc.)
Postgraduate degree or current Master’s/PhD studies related to the course topic
Relevant professional experience

Schedule

Here is your schedule for this edition of BSE Digital Economy Summer School, Economics of Artificial Intelligence course.

Time

30

mon

1

tue

2

wed

3

thu

4

fri

09:00 - 11:00

Lecture

Credit Transfers (ECTS)

To be eligible for credit transfer, students must complete a final project.

Students will deliver a short final project one week after the summer school finishes. It will consist in solving a final problem that will include the practical and empirical issues worked on in class.

Consult the Summer School Admissions page for more information about this option.

Certificate of Attendance

Participants who attend more than 80% of the course will receive a Certificate of Attendance, free of charge.

Fees

Multiple course discounts are available, consult our fees and discounts to learn more. Fees for courses in other Summer School programs may vary.

Course

The Economics of Artificial Intelligence

Platform Pricing: Strategy and Regulation

Understanding Digital Business Models, Platform Markets and Digital Strategies

Digital Empirical Methods for Cartel and Corruption Screening in Procurement

Modality

Face-to-face

Total Hours

10

ECTS

1

Regular Fee

1,175€

Reduced Fee*

675€

* Reduced Fee applies for PhD or Master’s students, Alumni of BSE Master’s programs, and participants who are unemployed.

FAQ

Need more information? Check out our most commonly asked questions.

Can I see the full Summer School calendar?

You can view the full Summer School calendar here.

Is accommodation included in the course fee?

Unfortunately, accommodation is not included in the course fee. Participants are responsible for finding accommodation.

Are the sessions recorded?

Sessions will NOT be recorded; however, the materials provided by the professor will be available for a month after the course has finished.

How much does each Summer School course cost?

Fees for each course may vary. Please consult each course page for accurate information.

Are there any discounts available?

Yes, BSE offers a variety of discounts on its Summer School courses. See more information about available discounts or request a personalized discount quote by email.