Counter-design practices for deliberate AI engagement¶

Strategy · All strategies
Evidence · no claims cited

Description¶

Drawing on the counter-design literature, PAUSE recommends concrete practices users can adopt to keep their own capacities engaged: "Structured prompting, deliberate verification, alternation between AI-assisted and AI-free work, and exposure to diverse outputs can mitigate or reverse offloading effects". Recommendations are branched by role and domain, e.g. brain-only literature reading sessions for researchers, AI-free first drafts and journal-based ideation for creatives, and source-reading exercises for learners. They are presented as practices to consider, not prescriptions.

Design Implications¶

Context¶

Requirements¶

• Practices should match the domain where offloading is highest and the respondent's self-identified role

Constraints¶

• Presented as practices to consider, not claims tested on the individual respondent
• The aim is conscious engagement, not abstinence from AI tools

Target Learners¶

• Adult LLM users across research, creative, student, and knowledge-work roles

Target Learning Goals¶

• Preserving critical thinking, creativity, deep learning, and human communication while using AI

Related Strategies¶

• Checking Your Blind Spot
• Describe AI instructional role and learner–AI interaction design in detail (prompts, scaffolds, modality, dialogue structures)
• Design AI configurations that preserve generative work: feedback-only audiences, generate-then-compare, and calibrated teaching interactions

Examples¶

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Key Sources¶

• Mahbub Ul Alam. (2026). PAUSE: A Privacy-Preserving Self-Reflection Tool for AI-Associated Cognitive Offloading. arXiv. https://arxiv.org/abs/2609.13155