Ethical Aspects of Ontology Development & Use

Research and development into ethical, moral and social aspects of ontologies, ontology development and use.

Contact the author to purchase content (see the Works sections below), to hire for lectures, to formally sponsor or support this research, or to discuss. Actively open to formal work collaborations, a study opportunity, etc.

Goals

• To explore the ethics of ontology in philosophical and computational contexts
• To explore application of contemporary ethics of AI and digital ethics topics, and the application of distinct ethical and moral theories
• A set of ethical guidelines/principles for ontology development.
• To correct misinformation and myths and distinguish facts from fictions of ontology development and use.
• To increase moral awareness and responsibility in relevant communities and projects.
• To increase user awareness of the semantics and underlying viewpoints within ontologies they (users) may use
• To ensure fairness, equal opportunity among ontologies in the community.
• To identify ethical and moral implications, if any, of ontology development and use.
• To innovate and contribute to ideas to topics of digital ethics, ethics of AI (artifiical intelligence), data ethics, metadata ethics, and ethics general.

Works

• “Ethics in Ontology”, 2013-present, PhilPapers
• “Ethics of Semantics” in US2TS 2022 (accepted poster), Purchase the poster here
• “The Ethics of Conceptual, Ontological, Semantic and Knowledge modeling”, Rovetto, R.J., in AI & Society, 2023 View online.
• “The Ethics of Ontology”, poster presented at OntoCommons 2nd Global Workshop (June 2023).
• “Ethics of Vocabulary Development and Use”, PPT presentation at AU Vocabulary Symposium by Australian Research Data Commons (Nov 2023)
• “Ethical Aspects of Ontology Development and Use”, submitted (but rejected) to IJCKG 2021 - Purchase here
• “Ethical aspects of Knowledge Engineering - Toward the Ethics of Ontology”, submitted (but rejected) to EKAW2022.
• “The Ethics of Ontology - An Overview”, Presentation and Paper at 1st WISDOMS Workshop at Extended Semantic Web Conference, 27 May 2024.

Noteworthy Reviews

• “The paper provides a comprehensive overview of the ethical considerations surrounding ontology, particularly in the context of AI and data ethics. It delves into different topics such as transparency, pitfalls, myths, and the implications of philosophical assumptions in ontology development. The author’s interdisciplinary approach is commendable, as it bridges philosophical, computational, and ethical perspectives.” (Reviewers of 2024 Workshop)
• ” The paper effectively integrates philosophical concepts with computational ontology, providing a holistic view of the subject matter. This interdisciplinary approach enriches the discussion and enhances its relevance to both philosophical and practical domains. The paper covers a wide range of ethical considerations related to ontology, including transparency, pitfalls, ethical implications of philosophical assumptions, and common myths. This breadth of coverage ensures that different aspects of the topic are addressed, offering valuable insights to readers. The author critically evaluates the ethical implications of ontology development and application, raising thought-provoking questions about the potential consequences for users, developers, and society at large. This analytical approach stimulates further reflection and discussion on the subject.” (Reviewers of 2024 Workshop)

Preliminary Points

• Historically, but also in modernity, the original and non-computaitonal sense of ‘ontology’ is the generic study of existence. As such, various philosophical or otherwise sepeculative ontological theories/accounts have been posited. As such, they often make fundamental and profound claims about the nature of the world.
• Therefore, one fundamental idea for what I call the ethics of ontology (and the ethics of semantics and the ethics of knowledge organization systems more broadly)– i.e., for inquiry into the ethical and moral aspets of computational ontologies, their development, and their use– is that if any aspect of that endeavor (and its metaphysical questions) transfers to contemporary computational activities involving personal and societal data, then there is a necessary moral imperative to understand the implications thereof. More specifically, there is a moral imperative to understand what computational ontologies are claiming about the world, and how they are classifying and describing your data, your content, your knowledge, and other things.
• It is taken for granted knowledge that many ontological or semntic models, many classifications, are possible. For these reasons, a recommnedation and conclusion is that it is more ethical to not use a computational ontology that imposes a metaphysical worlview or specifical metaphysical committments (e.g., exprssed via definitions and labels that annotate and describe your data accordingly, i.e., according to that worldview).
• If ontologies are, in part, about stating the things that are either of interest (perhaps remaining neutral or perhaps ignoring the philosophical ontology aspect) or things that are presumed to exist, then you should be informed whether a given ontology is inclusive of what you, your data, or your organnization believes to exist. Be aware whether an ontology accepts, or miscategorizes/micharacterizes the things you want to include in an ontology. Hence, another basic idea of this research is that of transparency (and active research to be informed) by ontology creators/developers (and potential users).
• Your mental model should not be forced under, or changed into, that of another ontology or it’s developers…at least not without your consent.
• Broader, meta-level, methodological and philosophical question worth exploring are:
  • is raw data empty of inherent semantics?
  • is all raw data open to semantic interpretation?
  • do we ascribe semantics to datasets and individual data elements? One working claim of this research is: If datasets or data elements collected from some source that do not have any inherent or unique semantics, then it would be ethical to not exclusively associate a single semantics (e.g., a metadata set, or an ontology annotating that data) to that data.
  • For a given dataset, what is a good (by what criteria is good?) ontology to annotate it? What is a good semantic model for tha data?
• One ethical area of concern is about an often-stated aspect of ontologies: consensus/aggrement. Ontologies are often described as being examples of common agreement (of a vocabulary, its definitions; of a worldview, of a model of the target domain of interest, etc.); or as aiming to reach consensus.
  • We must ask and determine: is there, actually, agreement/consensus? was it reached? if so, how?

Support

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As an unfunded personal project to date, formal support (such as funding, work opportunnities, formal collaborations, etc.) is needed to continue and sustain development.

Attribution

If you find value or use in any of the content or work here, please give attribution by referencing/citing this or the above-mentioned works. Citation style may be: “Rovetto, Robert J. “The Ethics of Ontology Development and Use”, https://github.com/rrovetto/Ethics-of-Ontology-Development-and-Use/

Copyright

© 2017-2023, Robert John Rovetto. All right reserved. Not authorized for commercial use unless explicitly negotiated with the author. No warranty. Presented “AS IS”. Author and copyright holder is not liable. All content, work and products are subject to revision. No claims to completeness or complete accuracy. Citation/attribution required. If you use any content from these Github pages, then you must cite them.