AI-washing: The Asymmetric Effects of Its Two Types on Consumer Moral Judgments

TL;DR

This study investigates how false claims about AI usage, either overstated or understated, influence consumer moral judgments and trust, revealing asymmetric effects that impact attitudes and purchase intentions.

Contribution

It introduces the concept of AI-washing, distinguishing between deceptive boasting and denial, and empirically examines their asymmetric effects on consumers.

Findings

Deceptive denial leads to more negative moral judgments than honest denial.

Deceptive boasting does not significantly affect moral judgments.

Perceived betrayal mediates the relationship between AI-washing and consumer attitudes.

Abstract

As AI hype continues to grow, organizations face pressure to broadcast or downplay purported AI initiatives - even when contrary to truth. This paper introduces AI-washing as overstating (deceptive boasting) or understating (deceptive denial) a company's real AI usage. A 2x2 experiment (N = 401) examines how these false claims affect consumer attitudes and purchase intentions. Results reveal a pronounced asymmetry: deceptive denial evokes more negative moral judgments than honest negation, while deceptive boasting has no effects. We show that perceived betrayal mediates these outcomes. By clarifying how AI-washing erodes trust, the study highlights clear ethical implications for policymakers, marketers, and researchers striving for transparency.