Exploring collaborative decision-making: A quasi-experimental study of human and Generative AI interaction

Xinyue Hao, Emrah Demir and Daniel Eyers

Technology in Society, 2024, vol. 78, issue C

Abstract: This paper explores the effects of integrating Generative Artificial Intelligence (GAI) into decision-making processes within organizations, employing a quasi-experimental pretest-posttest design. The study examines the synergistic interaction between Human Intelligence (HI) and GAI across four group decision-making scenarios within three global organizations renowned for their cutting-edge operational techniques. The research progresses through several phases: identifying research problems, collecting baseline data on decision-making, implementing AI interventions, and evaluating the outcomes post-intervention to identify shifts in performance. The results demonstrate that GAI effectively reduces human cognitive burdens and mitigates heuristic biases by offering data-driven support and predictive analytics, grounded in System 2 reasoning. This is particularly valuable in complex situations characterized by unfamiliarity and information overload, where intuitive, System 1 thinking is less effective. However, the study also uncovers challenges related to GAI integration, such as potential over-reliance on technology, intrinsic biases particularly ‘out-of-the-box’ thinking without contextual creativity. To address these issues, this paper proposes an innovative strategic framework for HI-GAI collaboration that emphasizes transparency, accountability, and inclusiveness.

Keywords: ChatGPT; Artificial intelligence; Human intuition; Decision-making; Cognitive biases (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0160791X24002100
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:teinso:v:78:y:2024:i:c:s0160791x24002100

DOI: 10.1016/j.techsoc.2024.102662

Access Statistics for this article

Technology in Society is currently edited by Charla Griffy-Brown

More articles in Technology in Society from Elsevier
Bibliographic data for series maintained by Catherine Liu ().