Artificial intelligence (AI) continues to find more numerous and more critical applications in the financial services industry, giving rise to fair and ethical AI as an industry-wide objective. While many ethical principles and guidelines have been published in recent years, they fall short of addressing the serious challenges that model developers face when building ethical AI solutions. We survey the practical and overarching issues surrounding model development, from design and implementation complexities, to the shortage of tools, and the lack of organizational constructs. We show how practical considerations reveal the gaps between high-level principles and concrete, deployed AI applications, with the aim of starting industry-wide conversations toward solution approaches.
翻译:人工智能(AI)在金融服务业中继续发现更多和更关键的应用,从而产生了公平和道德的人工智能,作为整个行业的一个目标。尽管近年来公布了许多道德原则和准则,但这些原则和准则还不足以应对模型开发者在建立道德的人工智能解决方案时所面临的严重挑战。我们调查了围绕模型开发的实际和总体问题,从设计和实施的复杂性,到工具短缺,以及缺乏组织结构。我们展示了实际考虑如何揭示了高层次原则与具体、部署的人工智能应用程序之间的差距,目的是启动全行业对话,找到解决办法。