An Axiomatic Approach to Historical Reconstruction (Draft)

This is one of those projects that has taken over my thoughts. The project is still in a draft stage, as the axioms are not quite axioms yet, but I am still thinking deeply about it. If you happen to read this, please let me know any feedback!

Given multiple imperfect records of an event, how can we computationally establish what actually happened with quantifiable certainty? Historians have long struggled with the challenge of reconstructing the past from incomplete sources and subjective interpretations. While recent computational methods such as machine learning, probabilistic modeling, and large-scale data integration have introduced powerful new tools, they lack rigorous theoretical foundations. At present, no formal framework exists to systematically quantify and maximize historical objectivity while recognizing the insurmountable physical and epistemological constraints inherent in the study of the past. Here we present an axiomatic system that combines artificial intelligence, a distributed ledger, and consensus mechanisms, to formally constrain historical reconstructions within provable epistemic and physical limits. While perfect certainty remains unattainable, we establish quantifiable degrees of historical objectivity and enable the systematic reduction of uncertainty as new data arise. This framework is a conceptual departure from traditional historiography, offering a robust, testable methodology that can guide historians toward more constrained, evidence-driven interpretations, bridging the gap between classical scholarship and modern computational approaches.

You can read the full paper here: An Axiomatic Approach to Historical Reconstruction (Draft).