AI as Extraherics: Fostering Higher-order Thinking Skills in Human-AI Interaction
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Abstract (arXiv)
As artificial intelligence (AI) technologies, including generative AI, continue to evolve, concerns have arisen about over-reliance on AI, which may lead to human deskilling and diminished cognitive engagement. Over-reliance on AI can also lead users to accept information given by AI without performing critical examinations, causing negative consequences, such as misleading users with hallucinated contents. This paper introduces extraheric AI, a human-AI interaction conceptual framework that fosters users' higher-order thinking skills, such as creativity, critical thinking, and problem-solving, during task completion. Unlike existing human-AI interaction designs, which replace or augment human cognition, extraheric AI fosters cognitive engagement by posing questions or providing alternative perspectives to users, rather than direct answers. We discuss interaction strategies, evaluation methods aligned with cognitive load theory and Bloom's taxonomy, and future research directions to ensure that human cognitive skills remain a crucial element in AI-integrated environments, promoting a balanced partnership between humans and AI.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Sep 2024.
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Citing papers per year: 2025: 3; 2026: 1.
4 papers.
- 2025When Models Know More Than They Can Explain: Quantifying Knowledge Transfer in Human-AI Collaborationcited by 4
- 2025The Variance Paradox: How AI Reduces Diversity but Increases Noveltycited by 1
- 2025AnimAgents: Coordinating Multi-Stage Animation Pre-Production with Human-Multi-Agent Collaborationcited by 1
- 2026Orality: A Semantic Canvas for Externalizing and Clarifying Thoughts with Speechcited by 0
- 2026Orality: A Semantic Canvas for Externalizing and Clarifying Thoughts with Speech3 Mar 2026
- 2025AnimAgents: Coordinating Multi-Stage Animation Pre-Production with Human-Multi-Agent Collaboration22 Nov 2025
- 2025The Variance Paradox: How AI Reduces Diversity but Increases Novelty20 Aug 2025
- 2025When Models Know More Than They Can Explain: Quantifying Knowledge Transfer in Human-AI Collaboration5 Jun 2025