Algorithm Aversion

Algorithm aversion is the consumer tendency, described by Colleen Kirk in Is "made by humans" the new premium label?, to distrust or discount algorithmic or AI-created work when people believe the task should involve human emotion, judgment, or care. In the episode, it helps explain why AI-generated labels can reduce purchase intent and perceived authenticity.

The source treats algorithm aversion as context-dependent. Consumers may not care much if AI helped design a highly utilitarian item, but they can object when the product or message touches identity, self-expression, art, or emotional connection. The aversion can also be softened when AI is framed as an assistant to a human rather than as the author.

Key Claims

• Consumer resistance to AI is stronger when the task is expected to be human or emotional.
• The same AI involvement can be read differently depending on whether AI is author, editor, assistant, or back-end tool.
• Algorithm aversion can affect trust, authenticity, purchase intent, and word of mouth.
• Utilitarian product categories may face weaker aversion than identity-linked categories.
• The concept helps explain why Human Authorship Premium can become commercially meaningful as AI-generated content becomes common.

Connections

• Colleen Kirk and New York Institute of Technology - source speaker and affiliation.
• Human Authorship Premium and AI Authorship Presence - adjacent authorship-trust concepts.
• AI-Generated Advertising, AI Content Devaluation, and AI Content Provenance - marketing and disclosure contexts where aversion can appear.
• AI Assistant Augmentation and Human Judgment Under AI - tool-use frames that can reduce or clarify aversion.