About
The London AI and Humanity Project is a unique collaboration between academic philosophers and cognitive scientists, AI practitioners, UK government policymakers, and industry experts, formed with a mission to improve the quality of academic and public debate on AI.
AI raises complex ethical and policy questions. Matters are complicated further by the lack of a common terminology between AI researchers, lawyers, policymakers, industry, philosophers, media, and the public.
It is hard to know what to make of claims like “LLMs are intelligent”, “we have reached AGI”, or “AI’s outputs are biased” without a grasp of the definitions of the terms ‘intelligent’, ‘AGI’, and ‘bias’. And yet, many do just this. Interdisciplinary debate would be easier and more fruitful if a common set of working definitions were used. This glossary aims to contribute to that end.
How to Cite this Glossary
We recommend the bibliographic format below, which you may need to adapt to meet your own requirements. Overtime, entries may undergo changes/updates and so it is important to note the time at which you accessed material. Earlier iterations of entries will be archived.
Author(s) name, “Title of Glossary Entry”, The Philosophical Glossary for AI, Alex Grzankowski and Benjamin Henke (eds.), URL =<https://www.aiglossary.co.uk/index/…>, accessed on day, month, year.
Our Process and Approach
The criteria for glossary entries are:
Accuracy: Entries should reflect the breadth and key content of relevant academic literature in philosophy and empirical sciences at time of writing.
Accessibility: All of our content is free and open access. Entries are aimed at an intelligent lay audience. Entries are short and pithy, with minimal use of jargon unless helpful, and free from academic baggage (references and bibliographies).
Interest: We prioritise content with real-world practical import, be that where a definitional issue is relevant to a live political debate, or a technical debate among AI researchers. We avoid covering purely technical computer science terms over which there is less definitional debate, e.g. ‘Neural network’ or ‘megabyte’.
To meet these criteria the glossary is underpinned by a rigorous editorial process. To ensure accuracy:
Entries are written by suitably qualified academics and practitioners with relevant expertise.
All entries are peer-reviewed by The Glossary’s editorial team, composed of internationally recognised researchers with earlier career academics.
Entries are often also reviewed by a wider network calling on leaders in specific fields.
To ensure accessibility and interest entries and format are regularly tested on different audience groups such as policymakers, lawyers, and journalists at stakeholder events.
We rely on the generosity of individual authors, members of the editorial team, and our wider support network, all of whom work pro bono and have generously donated their time to make this project possible. We are grateful to everyone involved for supporting our aim of improving public discourse on crucial questions around AI.
Edited by
Editor-in-Chief:
Dr Alex Grzankowski (Institute of Philosophy and Birkbeck College, University of London)
Managing Editor:
Dr Benjamin Henke (Department of Computing, Imperial College London)
Associate Editors:
Prof Emma Borg (Institute of Philosophy, School of Advanced Study, University of London)
Prof Herman Cappelen (University of Hong Kong)
Prof Anandi Hattangadi (Stockholm University, Institute for Futures Studies, Stockholm)
Jackie Kay (Centre for Artificial Intelligence, University College London)
Prof Nicholas Shea (Institute of Philosophy, School of Advanced Study, University of London)
Prof Barry Smith (Institute of Philosophy, School of Advanced Study, University of London)
Dr Ben Steyn (UK Department for Science, Innovation and Technology)
