No. 114: Regulating Online Algorithmic Pricing: A Comparative Study of Privacy and Data Protection Laws in the EU and US

Details

Author(s):
  • Zihao Li
Publish Date:
May 17, 2024
Publication Title:
TTLF Working Papers
Publisher:
Stanford Law School
Format:
Working Paper
Citation(s):
  • Zihao Li, Regulating Online Algorithmic Pricing: A Comparative Study of Privacy and Data Protection Laws in the EU and US, TTLF Working Papers No. 114, Stanford-Vienna Transatlantic Technology Law Forum (2024).
Related Organization(s):

Abstract

The emergence of big data, AI and machine learning has allowed sellers and online platforms to tailor pricing for customers in real-time. While online algorithmic pricing can increase efficiency, market welfare, and optimize pricing strategies for sellers and companies, it poses a threat to the fundamental values of privacy, digital autonomy, and non-discrimination, raising legal and ethical concerns. On both sides of the Atlantic, legislators have endeavored to regulate online algorithmic pricing in different ways in the context of privacy and personal data protection. Represented by the GDPR, the EU adopts an omnibus approach to regulate algorithmic pricing and is supplemented by the Digital Service Act and the Digital Market Act. The US combines federal and state laws to regulate online algorithmic pricing and focuses on industrial regulations. Therefore, a comparative analysis of these legal frameworks is necessary to ascertain the effectiveness of these approaches.
Taking a comparative approach, this working paper aims to explore how EU and US respective data protection and privacy laws address the issues posed by online algorithmic pricing. The paper evaluates whether the current legal regime is effective in protecting individuals against the perils of online algorithmic pricing in the EU and the US. It particularly analyses the new EU regulatory paradigm, the Digital Service Act (DSA) and the Digital Market Act (DMA), as supplementary mechanisms to the EU data protection law, in order to draw lessons for US privacy law and vice versa.