As concerns about unfairness and discrimination in "black box" machine
learning systems rise, a legal "right to an explanation" has emerged as a
compellingly attractive approach for challenge and redress. We outline recent
debates on the limited provisions in European data protection law, and
introduce and analyze newer explanation rights in French administrative law and
the draft modernized Council of Europe Convention 108. While individual rights
can be useful, in privacy law they have historically unreasonably burdened the
average data subject. "Meaningful information" about algorithmic logics is more
technically possible than commonly thought, but this exacerbates a new
"transparency fallacy"---an illusion of remedy rather than anything
substantively helpful. While rights-based approaches deserve a firm place in
the toolbox, other forms of governance, such as impact assessments, "soft law,"
judicial review, and model repositories deserve more attention, alongside
catalyzing agencies acting for users to control algorithmic system design.

机器学习系统中不公正和歧视的问题引起了对 “解释权” 的关注。该研究对欧洲数据保护法的规定、法国行政法和欧洲理事会 108 号公约草案中的新的解释权进行了分析。虽然个人权利在隐私法中具有一定的作用，但与之相对应的透明度似乎仅仅是治标不治本的手段，因此其他形式的治理手段如影响评估、软性法律、司法审查和模型资源库等应该得到更多的关注，同时，推动代理机构为用户控制算法系统设计也应得到重视。