AGI-Powered Human-Machine Systems for Social Computing: Technologies, Infrastructure, Applications, Challenges, and Future Directions
Adamu Gaston Philipo, Doreen Sebastian Sarwatt, Huansheng Ning, Feifei Shi, Mahmoud Daneshmand, Jianguo Ding · 2025
AGI-powered human-machine systems for social computing offer significant benefits, including enhanced functionality, improved performance, increased time efficiency, and reduced computational costs in the digital society's social computing sectors. This study provides a systematic review of AGIpowered human-machine systems, examining the employed technologies and infrastructure, while highlighting their applications in social computing. The findings reveal that many of these systems rely heavily on natural language processing technologies, which are applied across various fields, demonstrating their versatility. However, the limitations of existing AGI-powered humanmachine systems present valuable opportunities for innovation. Designing, developing, and implementing secure, robust, and ethical systems can address these challenges, promoting growth and ensuring sustainability in the digital society.