Research
Research Interests
Human-AI Interaction, AI-Augmented Cognition
AI-Assisted Decision-Making, Organizational Design
Publications & Working Papers
Abhari, K., & Peine, T. (2026).
Cognitive Extension or Erosion? A Calibration Theory of Cognitive Well-Being under Generative AI.
Information Technology & People
Special Issue: People, Robots and AI at Work
Under review.
This paper develops a mechanism-level account of how knowledge workers regulate sustained generative AI use and what that regulation means for professional wellbeing. Drawing on an informed grounded theory study of twenty-five experienced GenAI users, it identifies five regulatory mechanisms operating across a calibration spectrum. Under-calibration and over-calibration emerge as paired failure modes, producing dependency and skill erosion on one end, with vigilance fatigue and efficiency reversal on the other. Productive wellbeing follows not from AI use itself, but from calibration proportional to actual cognitive need.
Abhari, K., & Peine, T. (2026).
How Generative AI Reshapes Cognition: Empirical Grounding of the Augmented Cognitive Extension Model.
International Conference on Information Systems (ICIS 2026).
Under review.
This paper empirically grounds the ACE model through an informed grounded theory study of fifteen experienced GenAI users. It identifies a three-stage developmental trajectory and a stabilization–destabilization spectrum showing that productive cognitive extension and problematic dependency emerge from the same regulatory mechanisms, often within the same individual.
Peine, T., & Abhari, K., & (2026).
Agentic AI and Delegation Paradox: An Augmented Cognitive Extension Perspective.
Americas Conference on Information Systems (AMCIS 2026).
Accepted for presentation.
This paper examines the delegation paradox in agentic AI: how offloading cognitive labor can simultaneously expand capacity and erode disciplined reasoning. We propose a dual-pathway model explaining how similar AI systems produce either cognitive extension or cognitive atrophy depending on regulatory patterns.
Abhari, K., & Peine, T. (2026).
How Generative AI Changes the Way We Think: The Case for Augmented Cognitive Extension.
European Conference on Information Systems (ECIS 2026).
Accepted for presentation.
This paper introduces the Augmented Cognitive Extension (ACE) framework, a process theory explaining how generative AI becomes internalized within everyday thinking and triggers shifts in attention, trust, and decision-making.
Peine, T., & Abhari, K. (2026).
How AI Companion Changes Your Mind: Toward a Theory of Augmented Cognitive Extension.
International Conference on Human-Computer
Interaction (HCII 2026).
Accepted for presentation.
This paper extends the ACE framework by articulating five regulatory mechanisms that govern whether sustained AI use strengthens or destabilizes cognitive agency: attentional synchronization, epistemic calibration, affective attunement, risk construal, and narrative preservation.
Research Mentorship
Digital Innovation Lab, San Diego State University Advisor: Dr. Kaveh Abhari
September 2025 – Present