The range of application of artificial intelligence (AI) is vast, as is the potential for harm. Growing awareness of potential risks from AI systems has spurred action to address those risks, while eroding confidence in AI systems and the organizations that develop them. A 2019 study found over 80 organizations that published and adopted "AI ethics principles'', and more have joined since. But the principles often leave a gap between the "what" and the "how" of trustworthy AI development. Such gaps have enabled questionable or ethically dubious behavior, which casts doubts on the trustworthiness of specific organizations, and the field more broadly. There is thus an urgent need for concrete methods that both enable AI developers to prevent harm and allow them to demonstrate their trustworthiness through verifiable behavior. Below, we explore mechanisms (drawn from arXiv:2004.07213) for creating an ecosystem where AI developers can earn trust - if they are trustworthy. Better assessment of developer trustworthiness could inform user choice, employee actions, investment decisions, legal recourse, and emerging governance regimes.
翻译:2019年的一项研究发现,有80多个组织公布和采纳了“AI道德原则”,此后又有更多的组织加入。但这些原则往往在可信赖的AI发展的“什么”和“如何”之间留下差距。这些差距导致令人怀疑或伦理上可疑的行为,这使人对特定组织的信誉以及更广泛的领域产生怀疑。因此迫切需要采用具体方法,使AI开发商能够预防伤害,并允许他们通过可核查的行为展示其可信赖性。下文,我们探索各种机制(从ArXiv:2004.07213中绘制),以便创建AI开发商能够赢得信任的生态系统,如果它们可以信赖的话。更好地评估开发者的信誉可以为用户的选择、雇员行动、投资决定、法律追索权以及新兴的治理制度提供信息。