Emergence of Collective Behavior and Networks from Individual Choices

 

The rapid growth in artificial intelligence (AI) brings to life the possibility that individual and team performance could one day exhibit a level of collective intelligence never seen before. However, our current approaches to team science and technology development lead to conceptual fragmentation that undercuts the possibilities for the synergistic gains we seek. If each area (cognitive and network sciences) continues to progress in isolation, we will continue to develop AI that fails to be tuned to the needs and communications of human users. In my current work I seek to propel team science and AI forward by integrating existing work on individual and team cognition into a socio-cognitive architecture that will enable further integration with developing work on Machine Theory of Mind (M-ToM) to yield an Integrated Theory of Human-Machine Teaming. I will present the current status of this work drawing together the literature on individual and team cognition and identifying the qualities necessary for synthetic teammates to scaffold cognition for individuals (M-ToM).  These inputs are used to develop computational representations of the cognitive processes involved in individual dynamic decision making and collective problem solving tasks.