Francesco Franda

Since the 1970s, the metaphysics of dispositions and causal powers has been a flourishing field, providing accounts of the identity of properties, modality, laws of nature, and causation. In parallel, social ontology is undergoing a “power turn,” seeking to move beyond frameworks built around collective intentionality to capture the variety of power dynamics that structure the social world. This collection brings these two traditions into dialogue through three original contributions. Joel Cox examines a tension internal to Aristotle’s system: if only substances can bear active powers and social entities such as cities or families do not figure among his examples of substance, how can Aristotle nevertheless appear to ascribe such powers to them? Tobias Hansson Wahlberg tackles the puzzle of retroactive institutional declarations in Searle’s framework, proposing an account in terms of modal mere Cambridge change. Finally, Theodore Locke defends the existence of a social modality irreducible to metaphysical modality, grounded in the distribution of social powers, with implications for understanding a form of modal injustice.

Although the last decade has seen a proliferation of ontological approaches to arguments, many of them employ ad hoc solutions to representing arguments, lack interoperability with other ontologies, or cover arguments only as part of a broader approach to evidence. To provide a better ontological representation of arguments, we present the Arguments Ontology (ArgO), a small ontology for arguments that is designed to be imported and easily extended by researchers who work in different upper-level ontology frameworks, different logics, and different approaches to argument evaluation. Unlike most ontological approaches to arguments, ArgO utilizes Basic Formal Ontology (BFO) as an upper-level ontology, and may be used alongside other commonly used ontologies in the BFO framework, including boththe Information Artifact Ontology (IAO), and the Information Entity Ontology (INFO). Critically, our proposal is principled, based on rigorous definitions and formal axioms out of which characterizations of arguments naturally fall. It is our hope that ArgO may assist researchers in many projects, including: integrating heterogeneous sources of evidence, structuring the content of semantic wikis, and enhancing semantic reasoning.

Proponents of technical monism argue that artistic functions are technical functions, and that therefore artworks and technical artifacts may be unified under the same theoretical framework. We hold that this view fails because it does not account for the phenomenon of technical malfunction: if artistic functions were technical functions, then artistic malfunctions would be technical malfunctions too. We argue that artistic malfunctions are not technical malfunctions because they cannot meet all the following four criteria: (1) malfunctioning attribution to a technical artifact entails negative evaluation and a reason to avoid use; (2) technical malfunction is caused by a failure of the artifact itself rather than failing circumstances; (3) a malfunctioning technical artifact remains a member of its artifactual kind; (4) malfunctioning technical artifacts are sometimes repaired. Since artistic malfunction cannot meet all these conditions, we claim that artworks and technical artifacts do not share the same type of function and, as such, unification theories based on technical function are untenable. We conclude by suggesting that our account raises broader challenges not only for technical-function-based unification theories, but also for other theories that seek to unify artworks and technical artifacts through a shared notion of function, as well as for accounts of artifact function more broadly.

The explosion of interest in large language models (LLMs) has been accompanied by concerns over the extent to which generated outputs can be trusted, owing to the prevalence of bias, hallucinations, and so forth. Accordingly, there is a growing interest in the use of ontologies and knowledge graphs to make LLMs more trustworthy. This rests on the long history of ontologies and knowledge graphs in constructing human-comprehensible justification for model outputs as well as traceability concerning the impact of evidence on other evidence. Understanding the nature of arguments and argumentation is critical to each, especially when LLM output conflicts with what is expected by users. The central contribution of this article is to extend the Arguments Ontology (ARGO) - an ontology specific to the domain of argumentation and evidence broadly construed - into the space of LLM fact-checking in the interest of promoting justification and traceability research through the use of ARGO-based ‘blueprints’.