This paper is effectively subtitled “Considerations of Requirements for Programmable Laws of Probabilistic Higher Order Logical Thought”. Why such a need? Issues such as privacy, security, bandwidth, and computational power demand not a central analyzing agency, but roaming agents to analyze the global explosion of medical data in many hundreds of petabytes distributed across many sites. They will send back only the conclusions, not the source data. But how will they reach those conclusions? This future pressing need will driving workers to consider Best Practice in inference. Right now, there are diverse approaches to inference, and it is not clear how to unify them into a self-consistent system. For example, there is not even universal agreement on how to treat probabilistic higher order logic. Quantum mechanics is held by many to be a universal system, but produces bizarre predictions for the everyday world of human experience. However, by rotation of the imaginary number i = of quantum mechanics to the split complex number h such that hh=+1, quantum mechanics becomes an inference system for higher order probabilistic logic. And the system has interesting emergent properties which may shed light on the nature of thought.