Artificial Canaries: Early Warning Signs for Anticipatory and Democratic Governance of AI
We propose a method for identifying early warning signs of transformative progress in artificial intelligence (AI), and discuss how these can support the anticipatory and democratic governance of AI. We call these early warning signs ‘canaries’, based on the use of canaries to provide early warnings...
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Universidad Internacional de La Rioja (UNIR)
2021-03-01
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doaj-95310df4ec5d42178f75f3c03e6565122021-03-03T22:41:37ZengUniversidad Internacional de La Rioja (UNIR)International Journal of Interactive Multimedia and Artificial Intelligence1989-16601989-16602021-03-016510010910.9781/ijimai.2021.02.011ijimai.2021.02.011Artificial Canaries: Early Warning Signs for Anticipatory and Democratic Governance of AICarla Zoe CremerJess WhittlestoneWe propose a method for identifying early warning signs of transformative progress in artificial intelligence (AI), and discuss how these can support the anticipatory and democratic governance of AI. We call these early warning signs ‘canaries’, based on the use of canaries to provide early warnings of unsafe air pollution in coal mines. Our method combines expert elicitation and collaborative causal graphs to identify key milestones and identify the relationships between them. We present two illustrations of how this method could be used: to identify early warnings of harmful impacts of language models; and of progress towards high-level machine intelligence. Identifying early warning signs of transformative applications can support more efficient monitoring and timely regulation of progress in AI: as AI advances, its impacts on society may be too great to be governed retrospectively. It is essential that those impacted by AI have a say in how it is governed. Early warnings can give the public time and focus to influence emerging technologies using democratic, participatory technology assessments. We discuss the challenges in identifying early warning signals and propose directions for future work.https://www.ijimai.org/journal/bibcite/reference/2905ai governanceforecastinganticipatory governanceparticipatory technology |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Carla Zoe Cremer Jess Whittlestone |
spellingShingle |
Carla Zoe Cremer Jess Whittlestone Artificial Canaries: Early Warning Signs for Anticipatory and Democratic Governance of AI International Journal of Interactive Multimedia and Artificial Intelligence ai governance forecasting anticipatory governance participatory technology |
author_facet |
Carla Zoe Cremer Jess Whittlestone |
author_sort |
Carla Zoe Cremer |
title |
Artificial Canaries: Early Warning Signs for Anticipatory and Democratic Governance of AI |
title_short |
Artificial Canaries: Early Warning Signs for Anticipatory and Democratic Governance of AI |
title_full |
Artificial Canaries: Early Warning Signs for Anticipatory and Democratic Governance of AI |
title_fullStr |
Artificial Canaries: Early Warning Signs for Anticipatory and Democratic Governance of AI |
title_full_unstemmed |
Artificial Canaries: Early Warning Signs for Anticipatory and Democratic Governance of AI |
title_sort |
artificial canaries: early warning signs for anticipatory and democratic governance of ai |
publisher |
Universidad Internacional de La Rioja (UNIR) |
series |
International Journal of Interactive Multimedia and Artificial Intelligence |
issn |
1989-1660 1989-1660 |
publishDate |
2021-03-01 |
description |
We propose a method for identifying early warning signs of transformative progress in artificial intelligence (AI), and discuss how these can support the anticipatory and democratic governance of AI. We call these early warning signs ‘canaries’, based on the use of canaries to provide early warnings of unsafe air pollution in coal mines. Our method combines expert elicitation and collaborative causal graphs to identify key milestones and identify the relationships between them. We present two illustrations of how this method could be used: to identify early warnings of harmful impacts of language models; and of progress towards high-level machine intelligence. Identifying early warning signs of transformative applications can support more efficient monitoring and timely regulation of progress in AI: as AI advances, its impacts on society may be too great to be governed retrospectively. It is essential that those impacted by AI have a say in how it is governed. Early warnings can give the public time and focus to influence emerging technologies using democratic, participatory technology assessments. We discuss the challenges in identifying early warning signals and propose directions for future work. |
topic |
ai governance forecasting anticipatory governance participatory technology |
url |
https://www.ijimai.org/journal/bibcite/reference/2905 |
work_keys_str_mv |
AT carlazoecremer artificialcanariesearlywarningsignsforanticipatoryanddemocraticgovernanceofai AT jesswhittlestone artificialcanariesearlywarningsignsforanticipatoryanddemocraticgovernanceofai |
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