Call for Grant Proposals on the Economics of Digital Services

Penn's Center for Technology, Innovation and Competition and Warren Center recently announced that they will fund grants to support research on the economics of digital services. The grant program encompasses research examining the issues raised by the economics of digital services from either an economic or legal perspective.

• Economics
• Law

Penn Researchers Join NSF-Simons Foundation Collaboration on the ‘Foundations of Deep Learning’

Warren Center faculty affiliates Alejandro Ribeiro, Robert Ghrist, and Edgar Dobriban will partner with an interdisciplinary team led by researchers at Johns Hopkins University in a project called Transferable, Hierarchical, Expressive, Optimal, Robust, & Interpretable NETworks (THEORINET).

• Electrical and Systems Engineering
• Mathematics
• Statistics

Leveraging Analytics Today and Tomorrow: Test and Learn

In this Wharton@Work article, Raghu Iyengar discusses customer behavior in today’s pandemic world, and in the post-pandemic future. "Companies that were already digital have a lot of data, but to successfully harness the power of analytics, new competencies have to be built."

• Marketing

Blockchain: The Last, Best Hope for Open Data

In Kevin Werbach's winning essay in the Nesta Decentralized Future Prize essay contest, he argues that blockchain will see mass adoption ‘behind the scenes’ in the infrastructural foundations of digital identity and hardware, and big tech will participate in the new decentralised data economy because it provides benefits for them.

• Legal Studies & Business Ethics

The Ethical Algorithm

Algorithms have evolved into powerful engines of financial technology. But they don’t always live up to the hype, as algorithmic models fail to take account of basic societal concerns like fairness, privacy and bias. Fintech Beat sits down with Michael Kearns to find out what can be done to make algorithms “ethical.”

• Computer and Information Science

Workshop on Equivariance and Data Augmentation

Recently, there has been a great deal of progress to develop improved equivariant and invariant learning architectures, as well as improved data augmentation methods. View the recorded talks from this recent workshop, organized by Edgar Dobriban and Kostas Daniilidis.

• Computer and Information Science
• Statistics

Creating Inclusive Public Policies: Guidelines for Compassionate Regulators

Why are some government policies more inclusive than others, striving to benefit all citizens and not just a select few? “We believe that a policy’s success largely rests on how well inclusion is embedded in its blueprints,” write Santosh K. Misra and Raghuram Iyengar in this opinion piece.

• Marketing

Estimating COVID Intervention Effectiveness with ‘Censored’ Testing

In its COVID-19 Rapid-Response research project, Hamsa Bastani's team focused on the use of proxy methods to generate more accurate infection estimates. She explains how her team calculated that Pennsylvania's COVID-19 positive test rate is actually about 60% higher than is publicly reported.

• Operations Information and Decisions

Behind the Buzzwords- Big Data

The first academic reference to Big Data came in a paper written in 2003 by Francis Diebold. He explains how he was inspired by George Orwell’s Big Brother when he first used the term, as the data we now generate is being collected with every click we make.

• Economics
• Finance
• Statistics

Kristian Lum on ACM ByteCast

Kristian Lum discusses her transition from math and statistics into computer science, and how her lab work in bioinformatics expanded her interest into social issues on this episode of ACM ByteCast..