Taking the Person Seriously: Ethically Aware IS Research in the Era of Reinforcement Learning-based Personalization

Travis Greene, Galit Shmueli, Soumya Ray

Research output: Contribution to journalJournal articleResearchpeer-review

135 Downloads (Pure)

Abstract

Advances in reinforcement learning and implicit data collection on large-scale commercial platforms mark the beginning of a new era of personalization aimed at the adaptive control of human user environments. We present five emergent features of this new paradigm of personalization that endanger persons and societies at scale and analyze their potential to reduce personal autonomy, destabilize social and political systems, and facilitate mass surveillance and social control, among other concerns. We argue that current data protection laws, most notably the European Union’s General Data Protection Regulation, are limited in their ability to adequately address many of these issues. Nevertheless, we believe that IS researchers are well-situated to engage with and investigate this new era of personalization. We propose three distinct directions for ethically aware reinforcement learning-based personalization research uniquely suited to the strengths of IS researchers across the sociotechnical spectrum.
Original languageEnglish
Article number6
JournalJournal of the Association for Information Systems
Volume24
Issue number6
Pages (from-to)1527-1561
Number of pages35
ISSN1558-3457
DOIs
Publication statusPublished - Nov 2023

Keywords

  • Personalization
  • Reinforcement learning
  • Sociotechnical
  • Data protection
  • AI ethics
  • Digital platforms

Cite this