Ethics and Governance of Artificial Intelligence: Evidence from a Survey of Machine Learning Researchers
Ethics and Governance of Artificial Intelligence: Evidence from a Survey of Machine Learning Researchers
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人工智能的伦理与治理：来自机器学习研究人员调查的证据
DOI：
10.1613/jair.1.12895
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发表时间：
2021
期刊：
影响因子：
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通讯作者：
A. Dafoe
中科院分区：
文献类型：
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作者：
Baobao Zhang;Markus Anderljung;L. Kahn;Noemi Dreksler;Michael C. Horowitz;A. Dafoe
机器学习 (ML) 和人工智能 (AI) 研究人员在人工智能的道德和治理中发挥着重要作用，包括通过他们的工作、宣传和就业选择。然而，这个有影响力的群体的态度并没有得到很好的理解，这削弱了我们辨别人工智能/机器学习研究人员之间共识或分歧的能力。为了检验这些研究人员的观点，我们对在两个顶级 AI/ML 会议上发表文章的研究人员进行了调查 (N = 524)。我们将这些结果与 2016 年 AI/ML 研究人员调查（Grace 等人，2018）和 2018 年美国公众调查（Zhang 和 Dafoe，2020）的结果进行了比较。我们发现人工智能/机器学习研究人员对国际组织和科学组织高度信任，以促进人工智能的开发和使用以符合公共利益；对大多数西方科技公司有中等信任度；对国家军队、中国科技公司和 Facebook 的信任度较低。虽然受访者绝大多数反对人工智能/机器学习研究人员研究致命自主武器，但他们不太反对研究人工智能其他军事应用，特别是物流算法。绝大多数受访者认为人工智能安全研究应优先考虑，机器学习机构应进行发表前审查以评估潜在危害。由于更接近技术本身，人工智能/机器学习研究人员能够很好地突出新风险并开发技术解决方案，因此这种衡量他们态度的新颖尝试具有广泛的相关性。研究结果应有助于改善研究人员、私营部门高管和政策制定者对人工智能法规、治理框架、指导原则以及国家和国际治理战略的思考。
本文出现在人工智能与社会的特别轨道上。
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.
权威制裁：促进公众对人工智能的信任
DOI：
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发表时间：
2021
期刊：
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影响因子：
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作者：
Bran Knowles
通讯作者：
Bran Knowles