Ethics and AI Startups

James Bessen, Stephen Michael Impink, Lydia Reichensperger, Robert C. Seamans
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引用次数: 2

Abstract

Artificial Intelligence (AI) startups use training data as direct inputs in product development. These firms must balance numerous trade-offs between ethical issues and data access without substantive guidance from regulators or existing judicial precedence. We survey these startups to determine what actions they have taken to address these ethical issues and the consequences of those actions. We find that 58% of these startups have established a set of AI principles. Startups with data-sharing relationships with large high-technology firms (i.e., Amazon, Google, Microsoft), that were negatively impacted by privacy regulations, or with prior (non-seed) funding from institutional investors are more likely to establish ethical AI principles. Lastly, startups with data-sharing relationships with large high-technology firms and prior regulatory experience with GDPR are more likely to incur negative business outcomes, like dropping training data or turning down business, to adhere to their ethical AI policies.
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伦理与人工智能创业
人工智能(AI)初创公司将培训数据作为产品开发的直接输入。这些公司必须在没有监管机构的实质性指导或现有司法先例的情况下,在道德问题和数据访问之间进行大量权衡。我们调查了这些初创公司,以确定他们采取了哪些行动来解决这些道德问题,以及这些行动的后果。我们发现,58%的初创公司已经建立了一套人工智能原则。与大型高科技公司(如亚马逊、bb0、微软)有数据共享关系的初创公司,受到隐私法规的负面影响,或者从机构投资者那里获得事先(非种子期)资金,更有可能建立道德的人工智能原则。最后,与大型高科技公司有数据共享关系、之前有GDPR监管经验的初创公司更有可能产生负面的业务结果,比如放弃培训数据或拒绝业务,以遵守他们的道德人工智能政策。
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