ABSTRACT. The purpose of this study is to examine generative artificial intelligence and spatial data mining algorithms transforming employment, tasks, and jobs, enabling staff reskilling, and optimizing promotion operations in virtual work environments. Throughout August 2023, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “generative artificial intelligence and multi-sensory augmented reality systems” + “spatial data mining and image processing computational algorithms,” “productivity software and emotional state prediction tools,” and “virtual work settings.” As research published in 2023 was inspected, only 171 articles satisfied the eligibility criteria, and 49 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: AXIS, Dedoose, MMAT, and SRDR.

Keywords: spatial data mining; image processing computational algorithms; generative artificial intelligence; multi-sensory augmented reality systems; productivity software; emotional state prediction tools; virtual work

How to cite: Kucera, J., Kovacova, M., Stevens, A., and Pattak, D. C. (2023). “Spatial Data Mining and Image Processing Computational Algorithms, Generative Artificial Intelligence and Multi-Sensory Augmented Reality Systems, and Productivity Software and Emotional State Prediction Tools in Virtual Work Settings,” Analysis and Metaphysics 22: 159–177. doi: 10.22381/am2220239.

Received 18 September 2023 • Received in revised form 19 December 2023
Accepted 22 December 2023 • Available online 30 December 2023