WASHINGTON, Feb. 19, 2021 — The American Bar Association Antitrust Law Section has released a white paper titled, “Artificial Intelligence & Machine Learning: Emerging Legal and Self-Regulatory Considerations, Part Two. Competition Implications of Big Data and
Artificial Intelligence/Machine Learning.” The document is a report of the section’s Big Data Task Force.
Part Two of the Big Data: Law and Impact Study Task Force’s two-part series summarizes U.S. and international jurisprudence, regulatory guidance and studies about competition issues arising from artificial intelligence and machine learning technologies and related business models. The report examines how antitrust law and economics approach questions surrounding big data and AI/ML. It also surveys litigation and enforcement actions that have touched on these issues, including in the United States, Europe and other jurisdictions. Finally, the report summarizes various international reports that have analyzed similar big data and AI/ML issues and their recommendations.
The report is organized into two sections: Antitrust Analysis Involving Big Data and AI/ML and Government and Non-Government Enforcement. Topics covered include:
- Economic models for competition law analysis
- Market definition and market power theories
- Tensions between competition and consumer protection law
- Monopolization and abuse of dominance
- Mergers and acquisitions
- Multi-firm conduct
- International reports on digital competition
The views expressed in the report represent the opinions of the authors. They have not been approved by the ABA House of Delegates or the Board of Governors and should not be construed as representing the policy of the American Bar Association.
The complete report, dated February 2021, is available for review online.
Part One of the report, which was published in 2019, analyzed the consumer protection implications of big data and AI/ML.
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