Abstract
The ethics of artificial intelligence (AI) is a research topic with both theoretical and practical significance. However, the ethical and moral aspects of conceptual, ontological, semantic, and knowledge modeling, more specifically, and which are sometimes found in AI applications, is not being given sufficient attention. I argue that it should. Whether considering using or developing these meaning-focused models, there are ethical aspects. This paper offers a preliminary outline about this potentially new research field, discussing: some questions and areas of concern, their significance; scenarios of ethical import, and initial ethical guidelines. A focus area, potential case study, and lens through which to see the ethical significance at hand, is ontologies, with emphasis on the most abstract ontologies (so-called generic, foundational, top-level or upper ontologies). This would aim to show the ethical import of highly abstract (often philosophical) ontological choices, assumptions, and their effects on data, developers, users, and society. In particular, I stress the need for critical examination of such models, their content, their intended meanings, assumptions, ideologies, as well as the development process. Both the ethics of, and ethics in, these activities are, therefore, of interest. Topics in the ethics of AI that are relevant include: transparency, bias, data-sharing, privacy, control over data, etc. This paper thereby contributes to the ethics of AI, as well as the ethics of information, of knowledge managment and relevant topics by developing and discussing the ethics of ontology (and similar systems). Future development will refine and add to the ideas expressed in this paper.
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Notes
I declare this term to directly express the shared emphasis on meaning, and semantics and indirectly express the claim that this aspect calls for ethical awareness.
Abstract theories about the generic nature of how the world truly is, what sorts of things exist, what is real, what is not real, what are fundamental categories to classify things, what it is to exist etc.
Symbol-structures, such as so-called classes, classifiers, properties, relations, entities, named individuals, etc., in some computable formalisms.
I.e., topic areas, scientific disciplines, broad human activities, a set of concepts of interest, the content of a particular database, a business or enterprise, etc.
Ethical aspects of the former call for being informed, and critically examining all assumptions (e.g., imported content at all degrees of abstraction). The latter calls for a self-reflective grasp of any assumptions (ideological or otherwise).
A logical (and technical) commitment, for instance, may be to certain rules of reasoning, or to a computable logic-based formalism.
They are sometimes described as being domain-neutral, domain-independent, applicable to any domain, which itself may be controversial.
Questions, often found in philosophical ontology and metaphysics, such as what is personhood? What is the nature of the mind and its relationship to the body? What are the basic categories of the world? Is X real? What is the nature of X?
Ideology, broadly construed for brevity to include the assumed worldviews, philosophical theories, metaphysical accounts, ontological commitments.
E.g., so-called knowledge representation languages, schema languages, ontology languages, etc.
We should ask: to what extent does meaning truly get encoded? Meaning is at least a mind-internal phenomena. Perhaps it is not actually encoded, but rather—in developing these models we are simply replacing one symbol system for another, always needing the observing mind to comprehend.
A couple of exceptions may be: a requirement being imposed by a decision-making authority (e.g., management, funding source, etc.); or sensitive (proprietary, private, etc.) information.
The use of ‘baggage’ is to emphasize that the added content and complexity may be incorrect, inaccurate, undesired, misrepresentative, etc. It is also to emphasize that the computational context is not the most appropriate one for metaphysical claims.
As an ethical side note: if a user does not care about those details, that disinterest should not be taken as allowance to add details or to justify hiding them from the user.
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Thanks to anonymous reviewers for their helpful input. Thanks also to Stefano Borgo, Paul Brandt, Michael DeBellis, Heinrich Herre, Elisa Kendall, and Adam Pease for their comments.
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Rovetto, R.J. The ethics of conceptual, ontological, semantic and knowledge modeling. AI & Soc (2023). https://doi.org/10.1007/s00146-022-01563-3
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DOI: https://doi.org/10.1007/s00146-022-01563-3