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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Main Authors: Carla Zoe Cremer, Jess Whittlestone
Format: Article
Language:English
Published: Universidad Internacional de La Rioja (UNIR) 2021-03-01
Series:International Journal of Interactive Multimedia and Artificial Intelligence
Subjects:
Online Access:https://www.ijimai.org/journal/bibcite/reference/2905
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spelling 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
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