Parallel Intelligence
Parallel Intelligence in distributed AI systems allows multiple agents to work concurrently on a problem, enhancing the speed and efficacy of the solution.
Background
Parallel Intelligence (PI) is constructed from the interactions and entanglement between actual systems and artificial systems. This chapter summarizes the research on PI and CPHS over the past 20 years. After a brief description of the history and framework, various applications are presented along eight aspects: parallel control and intelligent control, parallel robotics and parallel manufacturing, parallel management and intelligent organizations, parallel medicine and smart healthcare, parallel ecology and parallel societies, parallel economic systems and social computing, parallel military systems, and parallel cognition and parallel philosophy. Finally, the technical support and future direction for CPHS development are addressed.
Applications
The origin of artificial intelligence is investigated, based on which the concepts of hybrid intelligence and parallel intelligence are presented. The paradigm shift in Intelligence indicates the "new normal" of cyber-social-physical systems (CPSS), in which the system behaviors are guided by Merton's Laws. Thus, the ACP-based parallel intelligence consisting of Artificial societies, Computational experiments and Parallel execution are introduced to bridge the big modeling gap in CPSS.
Challenges and Ethical Considerations
While Parallel Intelligence holds significant promise, it also poses challenges and raises ethical considerations. One challenge is the effective coordination and integration of different intelligent entities, as each may have its own goals, biases, and limitations. Ensuring seamless collaboration and avoiding conflicts among these entities requires careful design and engineering.
Ethical considerations in Parallel Intelligence include issues related to accountability, transparency, and fairness. When human and AI systems collaborate, questions arise regarding who bears responsibility for the decisions made and the consequences that follow. It is crucial to establish clear frameworks for accountability and to ensure that decisions made are explainable and fair.
See also
References
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