Bauer, Martin W. and Schiele, Bernard, eds. (2024) AI and common sense: ambitions and frictions. Routledge Studies in Science, Technology and Society. Routledge, Abingdon, UK. ISBN 9781032626185
Full text not available from this repository.Abstract
Common sense is the endless frontier in the development of artificial intelligence, but what exactly is common sense, can we replicate it in algorithmic form, and if we can – should we? Bauer, Schiele and their contributors from a range of disciplines analyse the nature of common sense, and the consequent challenges of incorporating into artificial intelligence models. They look at different ways we might understand common sense and which of these ways are simulated within computer algorithms. These include sensory integration, self-evident truths, rhetorical common places, and mutuality and intentionality of actors within a moral community. How far are these possible features within and of machines? Approaching from a range of perspectives including Sociology, Political Science, Media and Culture, Psychology and Computer Science, the contributors lay out key questions, practical challenges and "common sense" concerns underlying the incorporation of common sense within machine learning algorithms for simulating intelligence, socialising robots, self-driving vehicles, personnel selection, reading, automatic text analysis, and text production. A valuable resource for students and scholars of Science–Technology–Society Studies, Sociologists, Psychologists, Media and Culture Studies, human–computer interaction with an interest in the post-human, and programmers tackling the contextual questions of machine learning.
| Item Type: | Book |
|---|---|
| Official URL: | https://www.routledge.com/AI-and-Common-Sense-Ambi... |
| Additional Information: | © 2024 selection and editorial matter, the editors; individual chapters, the contributors |
| Divisions: | Psychological and Behavioural Science |
| Subjects: | Q Science > Q Science (General) |
| Date Deposited: | 18 Jul 2024 09:54 |
| Last Modified: | 15 Nov 2024 06:39 |
| URI: | http://eprints.lse.ac.uk/id/eprint/124281 |
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