Exploring Human–AI–Mobile Collaboration for Enhanced Decision Making in Complex Environments
DOI:
https://doi.org/10.64882/ijrt.v14.i3.1579Keywords:
Human AI Collaboration; Artificial Intelligence; Mobile Technology; Collaborative Intelligence; Decision Support Systems; Context Aware Computing; Explainable AI; Mobile Intelligence; Human Centered AI; Complex Decision Making.Abstract
In contemporary decision making environment, intelligent systems must be used to aid the decision process as it requires adaptive, precise and quick decision making. Although advanced methods and models for analysis and forecasting such as artificial intelligence (AI) are used to aid the process, the inputs of the decision makers which help the system understand the situation are equally important. Moreover, mobile technology also aids the decision making process through real time information collection and situational awareness. This research intends to look into the integration of human intelligence, AI and mobile technology in Human AI Mobile Decision Framework. The Human AI Mobile Decision Framework includes context aware mobile intelligence, explainable AI, trust management and adaptive feedback mechanisms. This includes decision process which can be structured, decision scoring model and learning capabilities that make the system more adaptable. It is applied in various fields such as healthcare, emergency response, transportation, disaster management, business intelligence and risk assessment. The findings indicate that collaborative models for decision making are superior to both the human centric and the AI centric models since they assist in ensuring an appropriate balance between context knowledge, analytical knowledge, transparency and responsiveness. This study offers the basis for collaborative intelligence.
References
Saha, G. C., Kumar, S., Kumar, A., Saha, H., Lakshmi, T., & Bhat, N. (2023). Human-AI collaboration: Exploring interfaces for interactive machine learning. Tuijin Jishu/Journal of Propulsion Technology, 44(2), 2023.
Xu, B., Song, X., Cai, Z., Lim, E., Tan, C. W., & Yu, J. (2020). Artificial intelligence or augmented intelligence: A case study of human-AI collaboration in operational decision making.
Alam, S., & Khan, M. F. (2024). Enhancing AI-human collaborative decision-making in Industry 4.0 management practices. IEEE Access, 12, 119433-119444.
Bader, V., & Kaiser, S. (2019). Algorithmic decision-making? The user interface and its role for human involvement in decisions supported by artificial intelligence. Organization, 26(5), 655-672.
Kim, J., Davis, T., & Hong, L. (2022). Augmented intelligence: enhancing human decision making. In Bridging Human Intelligence and Artificial Intelligence (pp. 151-170). Cham: Springer International Publishing.
Kase, S. E., Hung, C. P., Krayzman, T., Hare, J. Z., Rinderspacher, B. C., & Su, S. M. (2022). The future of collaborative human-artificial intelligence decision-making for mission planning. Frontiers in Psychology, 13, 850628.
Etuk, E. A., & Omankwu, O. C. B. (2025). Human-AI collaboration: Enhancing decision-making in critical sectors. Communication In Physical Sciences, 12(2), 426-433.
Ren, M., Chen, N., & Qiu, H. (2023). Human-machine collaborative decision-making: An evolutionary roadmap based on cognitive intelligence. International Journal of Social Robotics, 15(7), 1101-1114.
Alix, C., Lafond, D., Mattioli, J., De Heer, J., Chattington, M., & Robic, P. O. (2021, June). Empowering adaptive human autonomy collaboration with artificial intelligence. In 2021 16th International Conference of System of Systems Engineering (SoSE) (pp. 126-131). IEEE.
Sarker, I. H., Khan, A. I., Abushark, Y. B., & Alsolami, F. (2021). Mobile expert system: exploring context-aware machine learning rules for personalized decision-making in mobile applications. Symmetry, 13(10), 1975.
Luo, G., Yuan, Q., Li, J., Wang, S., & Yang, F. (2022). Artificial intelligence powered mobile networks: From cognition to decision. IEEE Network, 36(3), 136-144.
Mondal, S., & Mukherjee, N. (2016, December). Mobile-assisted remote healthcare delivery. In 2016 Fourth International Conference on Parallel, Distributed and Grid Computing (PDGC) (pp. 630-635). IEEE.
Molina, D. A., Kharlov, V., & Chen, J. S. (2024, August). Towards effective human-AI collaboration in decision-making: A comprehensive review and conceptual framework. In 2024 Portland International Conference on Management of Engineering and Technology (PICMET) (pp. 1-6). IEEE.
Raisch, S., & Fomina, K. (2025). Combining human and artificial intelligence: Hybrid problem-solving in organizations. Academy of Management Review, 50(2), 441-464.
Li, H., & Tian, F. (2025). Advancing decision-making through AI-human collaboration: A systematic review and conceptual framework.
Downloads
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
