论文

研究表明，机器学习在公共部门的成功，将更少依赖模型准确率的突破，而更多依赖机构能否构建出透明、可复现、可问责且受公民信任的数据基础设施。It is shown that the success of machine learning in the public sector will depend less on breakthroughs in model accuracy and more on the ability of institutions to engineer transparent, reproducible, and accountable data infrastructures that citizens can trust.