Knowledge Resource · Open access
AI-Augmented Inquiry and Regulation in Hybrid Systems: A Control Allocation Architecture for Preserving Epistemic Agency in Hybrid Human-AI Cognition
- Author
- Aziz Shuaib Ausi
- Published
- 7 September 2026
- Reading time
- 1 min
- Publication type
- Knowledge Resource
- Availability
- Open access
The increasing integration of generative artificial intelligence (genAI) into critical epistemic processes, including hypothesis generation and decision-making, presents a complex challenge. While genAI systems can enhance performance, there is growing evidence of a 'metacognitive dilemma' where reliance on external AI capabilities may lead to a decline in human internal monitoring, calibration, and cognitive engagement. This shift in cognitive control within human-AI systems goes beyond simple automation bias. The proposed AIRIS framework aims to analyze this dilemma and identify areas for regulatory intervention to mitigate these effects.
Why it matters
This development highlights a critical challenge in the effective and ethical integration of advanced AI: ensuring human cognitive agency is preserved rather than eroded. Organizations must strategically address how AI augments, rather than diminishes, human intellectual capabilities to maintain robust decision-making and innovation processes. Understanding this dilemma is crucial for designing future human-AI systems and policies that foster collaborative intelligence.
Key insights
- Generative AI (genAI) is becoming fundamental to epistemic processes such as hypothesis generation, explanation construction, and decision-making.
- GenAI reliably enhances performance in these cognitive tasks.
- A 'metacognitive dilemma' is emerging: as external genAI capacity increases, human internal monitoring, calibration, and cognitive engagement may decrease.
- This phenomenon represents a redistribution of cognitive control in human-AI systems, distinct from mere automation bias or algorithm reliance.
- The AIRIS (AI-Augmented Inquiry and Regulation in Hybrid Systems) framework is introduced to analyze this dilemma and pinpoint effective regulatory intervention points.
Source
arXiv — Computers and Society — https://arxiv.org/abs/2608.21618
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Citation
Cite this publication (APA 7)
Aziz Shuaib Ausi (2026). AI-Augmented Inquiry and Regulation in Hybrid Systems: A Control Allocation Architecture for Preserving Epistemic Agency in Hybrid Human-AI Cognition. Knowledge Resource. Aziz Shuaib Ausi. https://www.azizshuaib.com/verify/ASA-EXE-2026-00124
Verification
This is an authenticated institutional record.
- Verification ID
- ASA-EXE-2026-00124
- Version
- v1.0 · r0
- Issued
- 7 September 2026
- Publisher
- Aziz Shuaib Ausi
- Licence
- All rights reserved. Reproduction requires written permission.