Beyond Automation: Machine Learning-Based Systems and Human Behavior in the Personalization Economy

Abstract

Personalization has long been a feature of online services, shaping targeted advertisement and online manipulation. Corporations now seek to exploit the enormous economic potential of personalization beyond the confinements of the online space. In recent years, the proliferation of machine learning-based decision-making has led to personalization in all spheres of life. Corporations rely on machine learning-based systems to decide if and under what conditions they contract with individuals. They determine who is invited for job interviews and who is eligible for loans. They shape how we are perceived and tailor the way in which we are treated. The implications of these systems are already immense, and they foreshadow a larger transformation. Over the course of the 21st century, ubiquitous, machine learning-based personalization will likely permeate the economy and become a fundamental condition of human existence. The shape of this transformation is still uncertain; before it concretizes, we have the opportunity to guide its direction by articulating concepts that allow us to describe and critically examine it.

Details

Publisher:
Stanford University Stanford, California
Citation(s):
  • 25 STAN. TECH. L. REV. 1 (2021)

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