Data Connectivity and the Free Energy Principle
Why Your Main AI Strategy Should Be Data Connectivity: in the rapidly evolving landscape of AI, the ability to remain distinct and competitive hinges on an unexpected factor: how interconnected your data is.
Think of your organisation as a living entity—its survival depends on a well-defined information boundary, which functions like a semi-permeable membrane. Karl Friston's Free Energy Principle (FEP) models this boundary as a Markov Blanket and says that to sustain itself, a system must minimise its free energy. Free energy is essentially a measure of surprise or uncertainty, and minimising it equates to maintaining a state of low internal entropy. A system achieves this by forming accurate predictions about the external environment and updating its internal states accordingly, thus allowing for a dynamic yet stable interaction with its surroundings. All of this is only possible because the Markov Blanket delineates a boundary between internal and external systems.
The versatility of the FEP is remarkable, spanning various scales. Chris Fields' application to quantum mechanics, suggests that an entangled quantum system maintains a distinct information boundary, that is only loosely coupled to its environment. An entangled quantum system is a distinct system. The implication is potent: the more interconnected the system's components, the stronger the boundary and thus the more pronounced its individual identity.
⚡The degree of your internal connectivity equates to how distinct you are⚡
Upon scaling this concept to an organisational level, we face a sobering reality. Often, our data is siloed and disconnected, lacking any unifying structure, common vocabulary, or shared semantics. Disconnected systems signal weak boundaries. The lower the data connectivity, the less distinct you are as a whole. Your organisation will unintentionally leak subtle information across its boundary. This did not matter before, but advanced AIs, with their ever-increasing sophistication, will penetrate these overly porous boundaries, and your organisation will begin to dissipate.
The good news is that we all possess the means to reinforce our data connectivity. Shared ontologies and URLs as universal identifiers are ready to be deployed, and AI itself can be leveraged to manage the formidable task of achieving comprehensive organisational data integration.
The progress in AI is not just hype; it is very real, but amidst the dazzle of new AI algorithms, I propose a strategic pivot—focus on the unglamorous yet critical task of data integration. Use shared semantics and URLs to make your data cohesive and thus protect your independent identity. The best time to begin integrating your data this way was two decades ago—but the next best time is now!
