By American Bar Association
The Next Generation of Antitrust, Data Privacy and Data Protection Scholars Conference will be held Jan. 22-23 at the University of Southern California Gould School of Law in Los Angeles.
Co-sponsored by the American Bar Association Antitrust Law Section, New York University School of Law, USC Gould School of Law and USC Marshall School of Business, the conference provides an opportunity for professors in law, economics, accounting, finance, management, information system, operations management and marketing who began their full-time tenure-track career in or after 2018 to present their latest research.
Senior scholars and practitioners in the field will comment on the papers. The day-and-a-half 9th Biennial Next Generation Conference is complimentary.
Among the sessions are:
“Competition Policy I” will explore multifaceted challenges of competition policy and antitrust law in digital markets, focusing on issues of structural market power, the efficacy of regulatory remedies and the specialized judicial expertise required for effective enforcement.
“Competition Policy II” will examine the evolving landscape of market power by connecting firm strategies, regulatory interventions and the broader consequences of industry concentration. The session includes discussion of platform self-preferencing, serial acquisitions in the tech sector, price transparency on Airbnb and linking economic consolidation to political influence.
“Privacy I” will investigate the complex interplay between regulatory frameworks, firm innovation and consumer responses in the data-driven economy. The session will examine how the California Consumer Privacy Act reshapes the trajectory of AI innovation. Complementing this macro-view, the second paper explores the micro-incentives of privacy as a competitive tool.
“Competition, Privacy and Data Issues” will investigate the complex interplay between algorithmic decision-making, firm incentives and consumer welfare across diverse digital environments and explore the prevalence of tacit collusion among deep Q-learning algorithms in first-price advertising auctions, the "transparency paradox" in privacy regulation, ad quality improvements from stronger competition could benefit consumers.
(https://www.americanbar.org/news/abanews/aba-news-archives/2026/01/antitrust-section-to-cohost-data-privacy-conference/)
The Next Generation of Antitrust, Data Privacy and Data Protection Scholars Conference will be held Jan. 22-23 at the University of Southern California Gould School of Law in Los Angeles.
Co-sponsored by the American Bar Association Antitrust Law Section, New York University School of Law, USC Gould School of Law and USC Marshall School of Business, the conference provides an opportunity for professors in law, economics, accounting, finance, management, information system, operations management and marketing who began their full-time tenure-track career in or after 2018 to present their latest research.
Senior scholars and practitioners in the field will comment on the papers. The day-and-a-half 9th Biennial Next Generation Conference is complimentary.
Among the sessions are:
“Competition Policy I” will explore multifaceted challenges of competition policy and antitrust law in digital markets, focusing on issues of structural market power, the efficacy of regulatory remedies and the specialized judicial expertise required for effective enforcement.
“Competition Policy II” will examine the evolving landscape of market power by connecting firm strategies, regulatory interventions and the broader consequences of industry concentration. The session includes discussion of platform self-preferencing, serial acquisitions in the tech sector, price transparency on Airbnb and linking economic consolidation to political influence.
“Privacy I” will investigate the complex interplay between regulatory frameworks, firm innovation and consumer responses in the data-driven economy. The session will examine how the California Consumer Privacy Act reshapes the trajectory of AI innovation. Complementing this macro-view, the second paper explores the micro-incentives of privacy as a competitive tool.
“Competition, Privacy and Data Issues” will investigate the complex interplay between algorithmic decision-making, firm incentives and consumer welfare across diverse digital environments and explore the prevalence of tacit collusion among deep Q-learning algorithms in first-price advertising auctions, the "transparency paradox" in privacy regulation, ad quality improvements from stronger competition could benefit consumers.
(https://www.americanbar.org/news/abanews/aba-news-archives/2026/01/antitrust-section-to-cohost-data-privacy-conference/)
