EXPLORING THE COGNITIVE IMPACT OF CONTINUOUS AI COLLABORATION

In an era of AI augmentation, where human intelligence intersects with machine learning capabilities, this research delves into the evolving dynamics of human cognition as individuals increasingly rely on intelligent systems. Drawing on the Theory of Technology Dominance (TTD2), we investigate the short-term and long-term effects of continuous collaboration with machine learning AI on professionals' cognitive capabilities. The study explores facets such as adaptive collaboration, skill layoffs, transparency, and the use of unexplainable AI techniques, aiming to uncover the nuanced interplay between humans and AI. In this research-in-progress proposal, we investigate this impact and create a research model along with a set of hypotheses we aim to test over time due to the temporal nature of the study. Our findings should provide in-depth insights, theoretical contributions, and practical implications for organizations navigating the landscape of AI-augmented decision-making.

Publication Details

Journal
Journal of the Association for Information Systems
Published
2025-04-01
Primary Topic
Magnetic Field Sensors Techniques
Type
article
Field-Weighted Citation Impact
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article

EXPLORING THE COGNITIVE IMPACT OF CONTINUOUS AI COLLABORATION

Journal of the Association for Information Systems
Magnetic Field Sensors Techniques
article

EXPLORING THE COGNITIVE IMPACT OF CONTINUOUS AI COLLABORATION

article en

Abstract

In an era of AI augmentation, where human intelligence intersects with machine learning capabilities, this research delves into the evolving dynamics of human cognition as individuals increasingly rely on intelligent systems. Drawing on the Theory of Technology Dominance (TTD2), we investigate the short-term and long-term effects of continuous collaboration with machine learning AI on professionals' cognitive capabilities. The study explores facets such as adaptive collaboration, skill layoffs, transparency, and the use of unexplainable AI techniques, aiming to uncover the nuanced interplay between humans and AI. In this research-in-progress proposal, we investigate this impact and create a research model along with a set of hypotheses we aim to test over time due to the temporal nature of the study. Our findings should provide in-depth insights, theoretical contributions, and practical implications for organizations navigating the landscape of AI-augmented decision-making.

Journal of the Association for Information Systems
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Magnetic Field Sensors Techniques
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