The Issues

  • Artificial Intelligence
  • Competition Policy and Antitrust
  • Innovation and Economic Growth
  • Intellectual Property
  • Interoperability
  • Networks, the Internet, and Cloud Computing
  • Privacy and Security

TAP Highlights

Digital Dystopia

In “Digital Dystopia,” economist Jean Tirole explores factors that strengthen states’ ability to use social credit to suppress dissent. He concludes that societies with strong social ties are more resistant to the abuse of social scoring, and recommends that scoring systems avoid using “guilt by association.”

The Illusion That Data Is Neutral

In her multi-year ethnographic study of the U.S. census, Dr. danah boyd, Microsoft Researcher, learned that some people pretend the use of data allows for neutral decision-making; however, data are never neutral. For example, the choice of which data to collect and how to collect it reveals ideological differences.

In the EU, an Algorithmic Decision-Making System Was Taken to Court

The Court’s findings of the Dutch government’s use of a big-data analysis system aimed at combatting fraud “exemplifies the relevance of three regulatory frameworks governing algorithmic systems, namely data protection, human rights law, and algorithmic accountability.” - Dr. Mando Rachovitsa, University of Groningen

What Is the Connection Between Inequality, Innovation, and Patents?

“In 2020, over 50% of new U.S. patents went to the top 1% of patentees, and more than 50% of all patents of U.S. origin were generated by just five states, all coastal. Less than 13% of inventors were women.” – from “The Inequality of Innovation” by Santa Clara law professor Colleen Chien

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New TAP Blog Posts

danah boyd Advocates for Responsible Data Science

Posted on November 29, 2022
Microsoft Partner Researcher danah boyd shared insights from her multi-year ethnographic study of the U.S. census. She discussed how the U.S. Census Bureau’s decision to embrace differential privacy as part of its system to protect statistical confidentiality upended what people imagined the work of data to be.

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