The Impact of Artificial Intelligent Tools on Decision Making Behavioral and Neural Dynamics

Edmundo Molina-Perez, Pedro Cortes, Isaac Molina, Fernanda Sobrino, Mario Tellez, Yessica Orozco, Mitzi Castellón, Steven Popper and Luis Serra
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Edmundo Molina-Perez: School of Government and Public Transformation, Tecnológico de Monterrey
Pedro Cortes: Tecnológico de Monterrey
Isaac Molina: Tecnológico de Monterrey
Fernanda Sobrino: Tecnológico de Monterrey
Mario Tellez: Tecnológico de Monterrey
Yessica Orozco: Tecnológico de Monterrey
Mitzi Castellón: Tecnológico de Monterrey
Steven Popper: Tecnológico de Monterrey
Luis Serra: Tecnológico de Monterrey

No 8, Working Paper Series of the School of Government and Public Transformation from School of Government and Public Transformation, Tecnológico de Monterrey

Abstract: Decision-making is a multifaceted cognitive process influenced by task complexity, information availability, individual cognitive strategies, and environmental settings. Yet, the neural mechanisms guiding everyday choices remain incompletely understood. This gap intensifies when integrating real-time aids, such as artificial intelligence tools (AIT), as cognitive decisionsupport especially for complex and ambiguous problems. This study explores the neural mechanisms of decision-making and examines how AIT influences these processes. Combining behavioral assessments and neurophysiological measurements, we investigate the dynamic interplay between human cognition and AIT through behavioral execution and electroencephalogram (EEG) activity. Experimental data from 54 participants suggest that in low-complexity decision-making, AIT is largely ignored in favor of heuristics. In high-complexity contexts, AIT positively influences decision-making outcomes while also increasing capacity for engagement with a challenging task as registered by EEG cortical activity. This suggests a non-linear effect of AIT in decision-making strategies highlighting its role as a complement to —rather than a replacement of—human cognitive processes.

Keywords: artificial intelligence; decision-making; EEG; neuroeconomics; cognitive support tools (search for similar items in EconPapers)
JEL-codes: C91 D83 D89 (search for similar items in EconPapers)
Pages: 22 pages
Date: 2025-08
New Economics Papers: this item is included in nep-ain, nep-exp and nep-neu
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