ABSTRACT. The present study systematically reviews the existing research on computer-based teamwork simulations, movement tracking sensors, and wearable augmented reality devices in 3D immersive spaces. The findings indicate that immersive interconnected virtual experiences can be attained by use of virtual reality-based job training, data-driven cognitive and affective processes, and interoperable digital avatars. The contribution to the literature is by clarifying that robust job and productivity growth, qualified skilled labor, and virtual workspaces and meetings can necessitate generative artificial intelligence and simulation modeling algorithms. Throughout July 2023, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “generative artificial intelligence and workplace tracking systems” + “synthetic training data,” “computer-based teamwork simulations,” and “3D immersive spaces.” As research published in 2023 was inspected, only 169 articles satisfied the eligibility criteria, and 50 mainly empirical sources were selected. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Dedoose, Distiller SR, and SRDR.

Keywords: generative artificial intelligence; workplace tracking; synthetic training data; computer-based teamwork simulation; immersive

How to cite: Nica, E., Androniceanu, A., Sabie, O.-M., and Mișa, A. (2023). “Generative Artificial Intelligence and Workplace Tracking Systems, Synthetic Training Data, and Computer-based Teamwork Simulations in 3D Immersive Spaces,” Analysis and Metaphysics 22: 24–42. doi: 10.22381/am2220232.

Received 18 August 2023 • Received in revised form 17 December 2023
Accepted 22 December 2023 • Available online 30 December 2023