The Role of Machine Learning (ML) in Predicting Consumer Behaviour: Innovation or Violation?

Abstract

This paper explores the dual role of Machine Learning (ML) in predicting consumer behavior within e-commerce. ML technologies have driven innovation by enabling personalized recommendations, targeted marketing, dynamic pricing, inventory optimization, and fraud detection—enhancing both customer experience and operational efficiency. At the same time, these advancements raise critical ethical concerns, including privacy invasion, manipulation of consumer choices, algorithmic bias, and lack of transparency. As a Commentary / Opinion Article, this work examines how these risks intersect with the growing reliance on predictive algorithms in digital marketplaces. It argues that while ML offers immense opportunities for growth and innovation, its implementation must be guided by robust ethical frameworks and regulatory oversight. The discussion emphasizes responsible data use, algorithmic transparency, and consumer empowerment to ensure that ML remains a tool for innovation rather than exploitation.