Research
Research Interests
Human-AI Interaction, AI-Augmented Cognition
AI-Assisted Decision-Making, Organizational Design
Publications & Working Papers
Peine, T., & Abhari, K. (2026).
The Team Delegation Paradox: Augmented Cognitive Extension in Hybrid Human-AI Teams
Industrial Management & Data Systems
Special Issue: Artificial Intelligence and Team Dynamics
Under review.
Conceptually extends ACE to hybrid human-AI teams, theorizing why delegation to agentic teammates strengthens collective intelligence in some teams and erodes it in others.
Peine, T., & Abhari, K. (2026).
The Calibration Gap: How Cognitive Regulation Converts Generative AI Adoption into Organizational Performance
Hawaii International Conference on System Sciences (HICSS 2027).
Under review.
Empirically argues that organizational returns on GenAI track how workers regulate cognitive coupling rather than how much they use the system, and links calibration states to observable performance signals.
[Read on ResearchGate →]
Peine, T., & Abhari, K. (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.
Develops a calibration theory of cognitive well-being, showing how the regulatory mechanisms that let GenAI extend cognition can also erode it through dependency or exhaust it through hypervigilance.
Peine, T., & Abhari, K. (2026).
How Generative AI Reshapes Cognition: Empirical Grounding of the Augmented Cognitive Extension Model.
International Conference on Information Systems (ICIS 2026).
Conditionally accepted.
Empirically grounds the ACE model through an informed grounded theory study of fifteen experienced GenAI users. 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.
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.
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.
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
August 2025 – Present