The Method of Critical AI Studies, A Propaedeutic
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arXiv
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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866915210690822144 |
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| author | Offert, Fabian Dhaliwal, Ranjodh Singh |
| author_facet | Offert, Fabian Dhaliwal, Ranjodh Singh |
| contents | We outline some common methodological issues in the field of critical AI studies, including a tendency to overestimate the explanatory power of individual samples (the benchmark casuistry), a dependency on theoretical frameworks derived from earlier conceptualizations of computation (the black box casuistry), and a preoccupation with a cause-and-effect model of algorithmic harm (the stack casuistry). In the face of these issues, we call for, and point towards, a future set of methodologies that might take into account existing strengths in the humanistic close analysis of cultural objects. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_18833 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | The Method of Critical AI Studies, A Propaedeutic Offert, Fabian Dhaliwal, Ranjodh Singh Computers and Society We outline some common methodological issues in the field of critical AI studies, including a tendency to overestimate the explanatory power of individual samples (the benchmark casuistry), a dependency on theoretical frameworks derived from earlier conceptualizations of computation (the black box casuistry), and a preoccupation with a cause-and-effect model of algorithmic harm (the stack casuistry). In the face of these issues, we call for, and point towards, a future set of methodologies that might take into account existing strengths in the humanistic close analysis of cultural objects. |
| title | The Method of Critical AI Studies, A Propaedeutic |
| topic | Computers and Society |
| url | https://arxiv.org/abs/2411.18833 |