Amanda Hicks

We outline initial work aligning the Basic Formal Ontology (BFO) and the Information Exchange Standard (IES), illustrating how key design patterns and content structures can be connected across the two frameworks. Our analysis highlights points of ontological convergence and divergence, guided by scenarios and supported by formal modeling. The study contributes to methodologies for mapping between upper-level ontologies and standards-based models while providing insights for communities aiming to improve semantic interoperability.

The field of AI has undergone a series of transformations, each marking a new phase of development. The initial phase emphasized curation of symbolic models which excelled in capturing reasoning but were fragile and not scalable. The next phase was characterized by machine learning models—most recently large language models (LLMs)—which were more robust and easier to scale but struggled with reasoning. Now, we are witnessing a return to symbolic models as complementing machine learning. Successes of LLMs contrast with their inscrutability, inaccuracy, and hallucinations, which underwrite concerns over the reliability and trustworthiness of these systems, motivating investigations into commonsense reasoning, AI explainability, and formal verification techniques. Moreover, proper assessments of hybrid machine learning/symbolic systems require novel strategies to facilitate comparisons of performance and guide future AI progress. The EDGeS AAAI 2023 Spring symposium brought together researchers focusing on novel assessments and benchmarks for evaluating hybrid and artificial general intelligence (AGI) systems. This symposium revealed what was already suspected: research concerning evaluation of machine learning/symbolic hybrids and AGI is, unfortunately, lacking. Even so, the discussion was fruitful.

For Kant one of the goals of any critique of pure reason is to answer the question, how are a priori synthetic propositions possible? Because rationalists such as Eberhard and Wolff took the principle of sufficient reason (hereafter, the PSR) as the principle of all a priori synthetic judgments, understanding both the various formulations of this principle and arguments in favor of its use as an axiom in metaphysical reasoning provides an interesting back door to understanding The Critique of Pure Reason. Despite his statements in the First Critique rejecting the PSR as a principle of judgment1, I argue that Kant was actually more sympathetic to the PSR than these passages alone would suggest. The Kant-Eberhard Controversy suggests that, even though Kant explicitly denies that the PSR can guide metaphysical reasoning, he actually presupposes its truth. I show that Kant’s position is tenable because, like the rationalists, Kant accepts the assumption that real essences exist and that they ground real possibility2; this leads him to accept the truth of all clear statements of the PSR. Unlike the rationalists, however, he does not accept the assumption that human understanding is isomorphic with real essences. As a result, Kant rejects only the use of the PSR to determine a priori the existence or properties of a thing. In this paper I hope to illuminate this position. I will begin with a survey of the various formulations of the PSR that have been put forward by Kant and his predecessors: Leibniz, Eberhard, and Wolff. Then I will examine Wolff and Eberhard’s arguments in favor of the PSR along with Kant’s criticisms of these arguments. Lastly, I will show why Kant rejected the very possibility of justifying this use of the PSR while presupposing its truth.