The beauty of AI is that it can enhance itself. This means that even if we are in the time of domain-specific AI growth, AI will generalize itself and evolve into a cross-domain interdisciplinary functionality, which means AI will power ultra-smart agents and become what we loosely refer to as Web 4.0. Building a generalized AI is like building a master algo or in other words finding something that is very simple and hence powerful and all-encompassing. Such a general AI does not have to be invented, it has to be discovered.
All policies and regulation should be thought around such a future. A future where AI processes can be easily measured, validated, secured, enhanced and distributed. In this future, data privacy is not a challenge as the AI processes are no more concerned with the content of the data and can operate in its context. Such an ecosystem will require data referencing as intelligent extracting bots will continue to cross-reference the dynamic data focussing on data as a group rather the data’s source. This world of general AI will not have any privacy concerns but will seamless collaboration and objective reward systems. The convergence of many of these new technologies is the infrastructure where a general AI can thrive and live up to its potential.
This is why we should promote nascent convergence technologies that work in a domain agnostic environment, are universal in behavior, and work on data context (group) rather than data content (source).