What Happens If AI Makes Things Too Easy for Us?

2026-03-22 · Source: IEEE Spectrum · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Emerging Technologies & Innovation, AI Ethics & Human Impact · Depth: Intermediate, medium

Summary

A commentary titled "Against Frictionless AI," published in *Communications Psychology* on February 24 by University of Toronto psychologists, argues that the excessive removal of effort by AI tools can have significant, unexpected costs. Lead author Emily Zohar and coauthors Paul Bloom and Michael Inzlicht contend that "friction"—defined as difficulty, struggle, and discomfort—is crucial for learning, motivation, and finding meaning. While AI streamlines tasks like summarizing documents or generating code, it bypasses the "desirable difficulties" that deepen understanding and strengthen memory. Unlike past technologies that reduced physical effort from mundane tasks, AI is now removing cognitive and creative friction, which is integral to human development, skill acquisition, and relationship building. The authors express concern that this trend could lead to long-term detrimental impacts, particularly for adolescents, by eroding critical thinking and social interaction skills.

Key takeaway

For AI scientists and product developers designing new systems, you should prioritize integrating "productive friction" into AI workflows. Instead of defaulting to instant solutions, consider models that encourage collaborative problem-solving and guided learning. This approach, while potentially facing initial user resistance, can foster deeper engagement, skill development, and long-term user benefit by preserving the effortful processes crucial for human cognition and meaning-making.

Key insights

Excessive AI-driven friction removal can hinder human learning, motivation, and meaning-making.

Principles

• Friction is essential for learning and motivation.
• Productive friction balances effort and achievability.
• AI removes friction from cognitive, not just physical, tasks.

Method

Design AI to incorporate "productive friction" by making the default a collaborative process model that guides users through problem-solving rather than instantly providing answers, fostering critical thinking and engagement.

In practice

• Implement AI that guides users through steps.
• Avoid AI that instantly provides complete answers.
• Consider AI's impact on adolescent development.

Topics

• AI Ethics
• Human-AI Interaction
• Cognitive Psychology
• Learning and Development
• AI Design

Best for: AI Scientist, Research Scientist, AI Researcher, AI Ethicist, AI Product Manager

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Editorial summary, takeaway, and curation by AIssential. Original article published by IEEE Spectrum.