Decisions and actions of all kinds by humans and AIs ultimately reduce to knowledge in use. The safety and effectiveness of actions, in particular, therefore depends upon the quality of knowledge used to inform and guide them. And while the use of knowledge for instrumental purposes occurs at the level of business processing, the production of knowledge as a precursor to action takes place in a different process called knowledge processing, in which distinctions between truth and falsity (facts) and legitimacy and illegitimacy (values) can be made.
Not all knowledge processes, however, are alike, much less effective in terms of the truth, legitimacy, or reliability of the knowledge they produce. Indeed, two AI systems endowed with different epistemologies can very well produce different answers to the same questions, some of which may even be contradictory. Choosing the best framework for use at the level of knowledge processing therefore matters greatly.
A third level of interest is the knowledge management (KM) level, the level at which management strategies and interventions aimed at improving knowledge processing are made. This is the applied epistemology or meta-epistemic level. Put differently, KM is knowledge process management — a management system for determining how best to kill our worst ideas before they kill us, and for addressing the safety and alignment problems in AI. The higher the quality of knowledge in AI, the safer and more aligned its outputs and actions can be for human well-being.
The Susty Code, then, is a game-changing innovation in high-performance fact/value knowledge processing — a creature of Epistemological AI — conceived at the level of KM and with the quality of knowledge and business processing in mind. The epistemology it relies on is a blend of Fallibilism, Critical Rationalism, Kantian Deontology, and Consequentialism, and takes the form of an integrated fact/value protocol for knowledge production in AI. No other approach to addressing the safety and alignment problems in AI does this, and yet it must be done if AI is to be safe, ethical and effective in the long run.
