Functional Modeling and General Collective Intelligence as the Basis for Pervasive Healthcare

Abstract

General Collective Intelligence has the potential to combine individuals into a single collective collective intelligence with general problem-solving ability (intelligence) that might be exponentially greater than that of any individual. In every software domain, including health and wellness, General Collective Intelligence and functional modeling have the potential to enable the definition of pervasive cognitive computing applications and platforms. In such cognitive apps, intelligent agents might provide services to the user that optimize their outcomes by independently executing functional operations in each software domain on whatever software best implements those operations, and independently incorporating any possible data available to the user in the best way available. And at the same time in such cognitive computing platforms, a GCI might orchestrate the process of gathering data from all such individual uses in order to optimize collective outcomes such as significantly increasing healthcare and wellness. And these models of individual and collective cognition suggest that such optimization might not be reliably achievable otherwise. For both of these cognitive computing approaches functional modeling is required to provide a universal mechanism for representing data and processes. Therefore, to achieve significantly increased healthcare and wellness outcomes both functional modeling and GCI might be required. Functional modeling has the potential to overcome the lack of consistency in type and format of data gathered and the lack of a mechanism for universally comparing and combining that data. This paper explores why functional modeling might not only be of critical importance to pervasive healthcare, but why it also might be critical to significantly improving capacity to diagnose and to make interventions.