The digital revolution is gradually changing our daily life, as well as the economy. The Digital Economy Summer School will deal with some of the challenges that regulators and policymakers face due to this technological revolution.
The courses will be taught by leading experts in different areas of the digital economy, and we will emphasize practical applications and discussion of policy relevant problems.
This year we offer a course that provides fundamental tools to understand and contribute to the digital economy. Emilio Calvano will teach the latest developments in artificial intelligence, how basic algorithms work and how they will affect the functioning of markets.
Course list for 2023
Week of June 26 - 30, 2023 (Face-to-face)
- Economics of Artificial Intelligence
Instructor: Emilio Calvano (University of Rome - Tor Vergata, TSE and CEPR)
Program director
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Fees and discounts
Fees vary by course. You may be eligible for one or more available Summer School discounts. Our staff can provide a personalized quote for you.
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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 seeking to catch up with state-of-the-art academic research on digital markets.
Course Outline
- What is AI? Concepts and tools
- Economics of AI: a helicopter tour:
a) AI as a general purpose technology
b) Effect of automation and the labor share
c) AI and marketplaces - Competing and colluding pricing algorithms:
a) Theoretical and experimental results
b) Pricing algorithms in the wild - Shaping consumer choices: the economics of recommender systems
a) Case study: Spotify playlists - Automating bidding in auctions
a) Collusion
b) Optimal Auction design - Algorithms and public policy
a) The EU initiatives
b) How can Economics inform the regulatory debate?
c) Algorithmic discrimination
About the Instructor
Emilio Calvano (PhD, Toulouse School of Economics, 2008) is a full professor of Economics at the University of Rome - Tor Vergata, associate faculty at the Toulouse School of Economics and research fellow of the Centre for Economic Policy Research in London (CEPR). He is an applied theoretical economist whose research mainly focuses on the theory of Industrial Organization.
He has published in top international peer-reviewed outlets such as Science Magazine, American Economic Review, Management Science, American Economic Journal: Microeconomics, Economic Journal and International Journal of Industrial Organization and is associate editor at the Journal of Industrial Economics.
His research interests include the economics of artificial intelligence, the economics of platforms, information economics and competition policy. His recent work studies the impact of AI powered algorithms (such as pricing software and recommender systems) on digital markets.
Who will benefit from this program?
The program targets advanced undergraduate and graduate students, researchers and practitioners that want to understand how the so-called new economy works.
Entry requirements
Applicants to all Summer School programs should meet the basic entry requirements.
Credit transfers (ECTS)
Students will deliver a short research proposal one week after the summer school finishes. It will consist of 3-4 pages, 1.5 spaced, font size 11, with a clear research question, a motivation (introduce the question and its policy relevance), a discussion of the existing literature and how your paper relates to that, and an explanation on how you would approach the questions (empirical strategy and/or theoretical model).
Consult the Credit Transfer Page for more information about this option.
Certificate of attendance
Participants not interested in credit transfer will instead receive a Certificate of Attendance, stating the courses and number of hours completed. These students will be neither evaluated nor graded. There is no fee for the certificate.
Fees
The price of each course includes all lecture hours and practical hours. Multiple course discounts are available. Fees for courses in other Summer School programs may vary.
Multiple course discounts are available. Fees for courses in other Summer School programs may vary.
| Course | Modality | Lecture Hours | ECTS | Regular Fee | Reduced Fee* |
|---|---|---|---|---|---|
| Economics of Artificial Intelligence | Face-to-face | 10 | 1 | 1125€ | 625€ |
* Reduced Fee applies for PhD or Master's students, Alumni of BSE Master's programs, and participants who are unemployed.
** Flexible cancelation policy: cancelations made on or before June 1, 2023, will receive a 100% refund.
See more information about available discounts or request a personalized discount quote by email.
Course schedule
The schedule is designed to allow students to participate in both courses. Courses can also be taken individually or in combination with courses in other BSE Summer School programs, schedule permitting.
| Day / Time | Mon | Tue | Wed | Thu | Fri |
|---|---|---|---|---|---|
| 9:00 - 11:00 | Economics of Artificial Intelligence | ||||
Mix and match your summer courses!
Remember that you can combine Digital Economy courses with courses in any of the other BSE Summer School programs (schedule permitting).