论文标题
在人工智能中设计人权
Designing for Human Rights in AI
论文作者
论文摘要
在大数据时代,公司和政府越来越多地使用算法来告知招聘决策,员工管理,警务,信用评分,保险定价以及我们生活的更多方面。 AI系统可以帮助我们做出证据驱动的,有效的决策,但也可以与我们不合理的,歧视性的决策与我们面对不合理的决定是准确的,因为它们是自动和定量做出的。这些技术发展对人们的基本人权而言是显而易见的。尽管近年来对这些紧急挑战的关注越来越多,但对于这些复杂的社会伦理问题的技术解决方案通常是在没有经验研究的社会背景和受到该技术影响的社会利益相关者的关键投入的情况下开发的。另一方面,要求更符合道德和社会意识的AI通常无法为如何进行透明度,解释性和公平性的重要性提供答案。弥合这些社会技术差距以及抽象价值语言和设计要求之间的深层鸿沟对于促进细微的,与上下文有关的设计选择,这些选择将支持道德和社会价值。在本文中,我们借助了价值设计的设计框架,利用价值敏感设计和参与式设计的方法,为主动吸引社会利益相关者提供了路线图,以通过结构性,包容性和透明的过程将基本人权转化为背景依赖性设计需求。
In the age of big data, companies and governments are increasingly using algorithms to inform hiring decisions, employee management, policing, credit scoring, insurance pricing, and many more aspects of our lives. AI systems can help us make evidence-driven, efficient decisions, but can also confront us with unjustified, discriminatory decisions wrongly assumed to be accurate because they are made automatically and quantitatively. It is becoming evident that these technological developments are consequential to people's fundamental human rights. Despite increasing attention to these urgent challenges in recent years, technical solutions to these complex socio-ethical problems are often developed without empirical study of societal context and the critical input of societal stakeholders who are impacted by the technology. On the other hand, calls for more ethically- and socially-aware AI often fail to provide answers for how to proceed beyond stressing the importance of transparency, explainability, and fairness. Bridging these socio-technical gaps and the deep divide between abstract value language and design requirements is essential to facilitate nuanced, context-dependent design choices that will support moral and social values. In this paper, we bridge this divide through the framework of Design for Values, drawing on methodologies of Value Sensitive Design and Participatory Design to present a roadmap for proactively engaging societal stakeholders to translate fundamental human rights into context-dependent design requirements through a structured, inclusive, and transparent process.