Ethics and Governance of Artificial Intelligence: Evidence from a Survey of Machine Learning Researchers
Machine learning (ML) and artificial intelligence (AI) researchers play an important role in the ethics and governance of AI, including through their work, advocacy, and choice of employment. Nevertheless, this influential group's attitudes are not well understood, undermining our ability to di...
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description | Machine learning (ML) and artificial intelligence (AI) researchers play an important role in the ethics and governance of AI, including through their work, advocacy, and choice of employment. Nevertheless, this influential group's attitudes are not well understood, undermining our ability to discern consensuses or disagreements between AI/ML researchers. To examine these researchers' views, we conducted a survey of those who published in two top AI/ML conferences (N = 524). We compare these results with those from a 2016 survey of AI/ML researchers (Grace et al., 2018) and a 2018 survey of the US public (Zhang & Dafoe, 2020). We find that AI/ML researchers place high levels of trust in international organizations and scientific organizations to shape the development and use of AI in the public interest; moderate trust in most Western tech companies; and low trust in national militaries, Chinese tech companies, and Facebook. While the respondents were overwhelmingly opposed to AI/ML researchers working on lethal autonomous weapons, they are less opposed to researchers working on other military applications of AI, particularly logistics algorithms. A strong majority of respondents think that AI safety research should be prioritized and that ML institutions should conduct pre-publication review to assess potential harms. Being closer to the technology itself, AI/ML researchers are well placed to highlight new risks and develop technical solutions, so this novel attempt to measure their attitudes has broad relevance. The findings should help to improve how researchers, private sector executives, and policymakers think about regulations, governance frameworks, guiding principles, and national and international governance strategies for AI.
This article appears in the special track on AI & Society. |
doi_str_mv | 10.1613/jair.1.12895 |
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This article appears in the special track on AI & Society.</description><subject>Algorithms</subject><subject>Artificial intelligence</subject><subject>Attitudes</subject><subject>Ethics</subject><subject>International organizations</subject><subject>Logistics</subject><subject>Machine learning</subject><subject>Military applications</subject><subject>Researchers</subject><issn>1076-9757</issn><issn>1076-9757</issn><issn>1943-5037</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNpNkE1Lw0AQhhdRsFZv_oAFr6Zmkk028VZKWwsVwY_zMtmPZku6qbtpof_exHrwNA_MOwPvQ8g9xBPIIX3aovUTmEBSlNkFGUHM86jkGb_8x9fkJoRtHEPJkmJE6nlXWxkoOkWX7VF7h05q2ho69Z01Vlps6Mp1umnsRverZzo_WjUQNb7dUaQfB3_Up-HkFWVtnaZrjd5Zt6HvOvQoa-3DLbky2AR99zfH5Gsx_5y9ROu35Wo2XUcSeNFFClhSJSWYQsm0UgWCSRF030gh47JSqCCJJecMMsUY01ixKoUMU2lUyfJ0TB7Of_e-_T7o0Ilte-hbNUEkWc4LAMh4n3o8p6RvQ_DaiL23O_QnAbEYXIrBpQDx6zL9AWooaKU</recordid><startdate>2021</startdate><enddate>2021</enddate><creator>Zhang, Baobao</creator><creator>Anderljung, Markus</creator><creator>Kahn, Lauren</creator><creator>Dreksler, Noemi</creator><creator>Horowitz, Michael C.</creator><creator>Dafoe, Allan</creator><general>AI Access Foundation</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>COVID</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope></search><sort><creationdate>2021</creationdate><title>Ethics and Governance of Artificial Intelligence: Evidence from a Survey of Machine Learning Researchers</title><author>Zhang, Baobao ; Anderljung, Markus ; Kahn, Lauren ; Dreksler, Noemi ; Horowitz, Michael C. ; Dafoe, Allan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c178t-d142b291f8dc3bd8a1f3a1e289da47cbdad120c77415d444eab4b315a3cfd9463</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Algorithms</topic><topic>Artificial intelligence</topic><topic>Attitudes</topic><topic>Ethics</topic><topic>International organizations</topic><topic>Logistics</topic><topic>Machine learning</topic><topic>Military applications</topic><topic>Researchers</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhang, Baobao</creatorcontrib><creatorcontrib>Anderljung, Markus</creatorcontrib><creatorcontrib>Kahn, Lauren</creatorcontrib><creatorcontrib>Dreksler, Noemi</creatorcontrib><creatorcontrib>Horowitz, Michael C.</creatorcontrib><creatorcontrib>Dafoe, Allan</creatorcontrib><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>Coronavirus Research Database</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><jtitle>The Journal of artificial intelligence research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhang, Baobao</au><au>Anderljung, Markus</au><au>Kahn, Lauren</au><au>Dreksler, Noemi</au><au>Horowitz, Michael C.</au><au>Dafoe, Allan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Ethics and Governance of Artificial Intelligence: Evidence from a Survey of Machine Learning Researchers</atitle><jtitle>The Journal of artificial intelligence research</jtitle><date>2021</date><risdate>2021</risdate><volume>71</volume><spage>591</spage><pages>591-</pages><issn>1076-9757</issn><eissn>1076-9757</eissn><eissn>1943-5037</eissn><abstract>Machine learning (ML) and artificial intelligence (AI) researchers play an important role in the ethics and governance of AI, including through their work, advocacy, and choice of employment. Nevertheless, this influential group's attitudes are not well understood, undermining our ability to discern consensuses or disagreements between AI/ML researchers. To examine these researchers' views, we conducted a survey of those who published in two top AI/ML conferences (N = 524). We compare these results with those from a 2016 survey of AI/ML researchers (Grace et al., 2018) and a 2018 survey of the US public (Zhang & Dafoe, 2020). We find that AI/ML researchers place high levels of trust in international organizations and scientific organizations to shape the development and use of AI in the public interest; moderate trust in most Western tech companies; and low trust in national militaries, Chinese tech companies, and Facebook. While the respondents were overwhelmingly opposed to AI/ML researchers working on lethal autonomous weapons, they are less opposed to researchers working on other military applications of AI, particularly logistics algorithms. A strong majority of respondents think that AI safety research should be prioritized and that ML institutions should conduct pre-publication review to assess potential harms. Being closer to the technology itself, AI/ML researchers are well placed to highlight new risks and develop technical solutions, so this novel attempt to measure their attitudes has broad relevance. The findings should help to improve how researchers, private sector executives, and policymakers think about regulations, governance frameworks, guiding principles, and national and international governance strategies for AI.
This article appears in the special track on AI & Society.</abstract><cop>San Francisco</cop><pub>AI Access Foundation</pub><doi>10.1613/jair.1.12895</doi><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Artificial intelligence Attitudes Ethics International organizations Logistics Machine learning Military applications Researchers |
title | Ethics and Governance of Artificial Intelligence: Evidence from a Survey of Machine Learning Researchers |
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