Digital Ethics and Digital Epistemology


Published: February 14, 2023 by Dr. Norman Mooradian

My current research has two central tracks, digital ethics, and digital epistemology.  The label digital ethics includes traditional information ethics[1], but also encompasses ethical issues arising from emerging technologies, for example, the ethics of artificial intelligence and virtual reality. Digital epistemology includes areas such as knowledge management and representation, as well as the application of theories of knowledge to computing and information science generally.

During the fall 2022 semester, I wrote an article entitled, “Automation versus Augmentation:  Knowledge Management as a Framework for Human Enabling AI”. The paper connects digital ethics and epistemology, focusing on the conflicting potentials of AI to both devalue and enhance human knowledge and knowledge work. The main argument of the paper is that knowledge management provides a social-technical framework for integrating artificial intelligence into platforms and processes in ways that enhance knowledge work as opposed to replacing it. I am currently reviewing candidate journals to which to submit the article.

During this same semester, I joined an international team of subject matter experts in knowledge management to write a book with the title of Knowledge Ethics in the Knowledge Economy. The book will be published by Emerald Publishing as part of its series, Working Knowledge.  Its unifying theme is how ethics underwrites and promotes the generation and dissemination of knowledge within society and organizations.

During this same time period I began two article projects on the topic of AI and data privacy. The first project consists of an article I am writing with the title, “Regulating Inference:  AI and the GDPR.” The thesis of the paper is that AI increases privacy risks over traditional technologies in two respects: (a) its dependence on data and (b) its inferential capabilities. However, the conceptual resources of the GDPR, which is the most comprehensive and influential legal framework, only partially address the inferential capabilities of AI. In particular, its conceptual resources address data and data subjects robustly, but are much less developed to address privacy in relation to inference and model subjects. In addition to this project, I am co-writing a paper with Dr. Franks (Professor Emerita, iSchool) and an industry colleague, , the working title of which is: “Artificial Intelligence and Data Privacy: Issues, Risks, and Technology Trends Influencing Ethics in Information Governance.”

Lastly, another area of research currently underway is part of the InterPARES Trust AI initiative. I joined the working group, WG4 – RP04 – Preserving AI techniques as Paradata, during the fall. The working group is chaired by Dr. Franks and is investigating documentation techniques for the capture of records of AI models and model instances. Different members are collaborating on article projects as deliverables of the project. I am conducting research with the objective of publishing as part of this effort.

[1] Information ethics can be characterized in terms of its focus on the use information in the context of technologies such as databases and the internet. See Mooradian, N. (2018) Ethics for Records and Information Management, ALA.


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