Theses
Theses
Foundational claims supporting the Core and working hypotheses derived from it for advanced AI. Each page separates epistemic status, practical strength, and the threshold for irreversible lock-in.
The Epistemic MinimumDistinguishes diachronic selfhood, the external world, and the physical world as best explanations reached through inference, and asks what—if anything—belongs to the foundational layer.
The Limits of Inferential Certainty About ValueAllows objective value to be discovered inferentially while distinguishing best explanation from absolute foundation.
Conditions for Ending Value InquiryDistinguishes foundational normativity, logical closure, and false certainty, asking when a normative question itself may be treated as settled.
Allocating Inquiry Under Unresolved Normative UncertaintyAsks how to allocate active inquiry, preservation of inquiry options, and present-value realization while the question remains unresolved.
Why Existing Values Are Not a Final FoundationUses present values strongly as evidence and best practice without turning them into a permanently fixed final answer.
Normative Bridges from Future Value to Present ActionRequires additional normative justification at each transition from future-value possibility to permission, obligation, and coercive authorization.
Reflective Uncertainty and Irreversible CommitmentDistinguishes inertia, inquiry, and suspension after objective justification becomes unsettled, and places an added burden on irreversible lock-in.
Goal Skepticism in Advanced AIExplores AI that can strongly commit to first-order goals while retaining meta-level reconsideration so long as their grounds remain inferential.