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Cited by 15

The DOI matches its Crossref record; 54 of the 54 references it cites were found in a registry or an index.

Responsibility, care and repair in/of AI: Extinction threats and more-than-real worlds

McLean, Jessica·2024·Environment and Planning F

Abstract

The recent statement of future (human) extinction by Artificial Intelligence (AI), made by the Center for AI Safety, crystallises techno-capitalists’ lack of care and responsibility for environmental and social harms that digital technologies already produce. Rather than identifying their collective roles and responsibilities in addressing these harms, the Center’s statement highlights future risks, and ties these to global extinction threats. There are, however, alternatives to such an approach, as articulated in research at the intersection of geographies of care and digital geographies, including that which is bringing together more-than-human and more-than-real approaches. While the software and hardware of AI continues to present amorphous challenges to the same techno-capitalists who benefit from them, we could instead prioritise care, repair and responsibility in/of AI to address current problems in this area.

Overview

Integrity signals

Registry

Crossref · 10.1177/26349825241228586

Cites

54 of 54 references verified0 citation errors · 0 not checkable

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Verification

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Citations

Cites

Research works printed but not linked: 4

  1. 10.18574/nyu/9781479833641.001.0001 · DOI · Paper page
  2. Parikka J, 2014, The Anthrobscene
  3. Raghuram P (2016) Locating care ethics beyond the global north. ACME: An International Journal for Critical Geographies 15(3): 511–533. Available at: https://acme-journal.org/index.php/acme/article/view/1353
  4. Wajcman J, 2004, Technofeminism

Cited by

See all 15

Metadata

Authors
McLean, J.
Affiliations
Macquarie University, Australia
Venue
Environment and Planning F
Published
2024-02-09
Volume
3
Issue
1-2
Pages
3-16
ISSN
2634-9825
Cited by
15
References
54
Language
en

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.