Research
Research Interests
Human–AI interaction and cognitive regulation, Organizational AI adoption and implementation, Responsible and ethical AI system design, AI governance and accountability in professional settings, Augmented cognition and extended mind theory
Publications & Working Papers
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.
As first author, I drafted this manuscript with limited faculty revision, articulating five regulatory mechanisms that govern whether AI strengthens or destabilizes agency: attentional synchronization, epistemic calibration, affective attunement, risk construal, and narrative preservation. This paper advances the Augmented Cognitive Extension (ACE) framework by examining how these mechanisms shift across stages of sustained AI use.
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 manuscript introduces the Augmented Cognitive Extension (ACE) framework, a process theory explaining how generative AI becomes internalized within everyday thinking. I conducted the full literature review, wrote the initial draft, and integrated prior research into the theoretical model. ACE identifies how sustained AI interaction triggers systematic shifts in attention, trust, and decision-making patterns.
Abhari, K., & Peine, T. (2026).
Agentic AI and Delegation Paradox: An Augmented Cognitive Extension Perspective
Americas Conference on Information Systems (AMCIS 2026).
Under review
This manuscript introduces the delegation paradox: delegating cognitive labor to agentic AI simultaneously expands bandwidth and attenuates productive friction, weakening epistemic vigilance and disciplined reasoning. We theorize three cognitive states (entanglement, cognitive extension, and cognitive atrophy) governed by Calibration & Negotiation, a central regulatory mechanism enacted through five interdependent capacities. The paper presents a dual-pathway process model explaining how delegation stabilizes into competing equilibria: a competence-reinforcing pathway producing cognitive extension through regulated reliance, or a competence-depleting pathway producing cognitive atrophy through unregulated offloading. Self-reinforcing feedback loops explain why structurally similar agentic systems yield divergent cognitive outcomes.
Current Projects
- Mixed-methods Qualtrics study examining how cognitive regulation patterns shift across stages of sustained AI use, combining structured measures of trust, attention, and authorship with narrative prompts capturing users' retrospective experiences (deployed via Prolific)
- Deepening of the Augmented Cognitive Extension (ACE) framework to address agentic AI systems, formalizing developmental stages and regulatory mechanisms that govern long-term trajectories of cognitive augmentation or atrophy (manuscript in preparation for AMCIS 2026)
Future Directions
- Longitudinal field research examining AI adoption and cognitive regulation in organizational settings, with focus on professional services and knowledge work environments where AI mediates consequential decision-making
Research Mentorship
Digital Innovation Lab, San Diego State University Advisor: Dr. Kaveh Abhari
September 2024 – Present