Mapping Artificial Intelligence Use in the Government of Canada

Paul Daly
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Abstract

On the one hand, technological advances and their enthusiastic uptake by government entities are seen as a push toward a Canadian dystopic state, with friendly bureaucrats being replaced by impassive machines. On the other hand, embracing technology is considered a confident move of the Canadian administrative state toward an utopian low-cost, high-impact decision making process. I will suggest in this paper that the truth—for the moment, at least—lies somewhere between the extremes of dystopia and utopia. In the federal public administration, technology is being deployed in a variety of areas, but rarely, if ever, displacing human decision making. Indeed, technology tends to be leveraged in areas of public policy that don’t involve any settling of benefits, statuses, licenses, and so on. We are still a long way from sophisticated machine learning tools deciding whether marriages are genuine, whether taxpayers are compliant or whether nuclear facilities are safe. The reality is more down to earth. In this paper, I map out the uses of algorithms and machine learning in the federal public administration in Canada. I will briefly explain my methodology in Part I; in Part II, I identify seven different use cases, which I describe with the aid of representative examples, and offer some critical reflections.
绘制人工智能在加拿大政府中的应用
一方面,技术进步和政府机构对技术的热情吸收被视为推动加拿大成为一个反乌托邦国家,友好的官僚被冷漠的机器所取代。另一方面,拥抱技术被认为是加拿大行政国家走向乌托邦式低成本、高影响力决策过程的自信之举。我将在本文中提出,真相——至少就目前而言——介于反乌托邦和乌托邦的极端之间。在联邦公共管理中,技术被部署在各种领域,但很少,如果有的话,取代人类的决策。实际上,技术往往被用于公共政策领域,而这些领域不涉及任何利益、地位、许可等问题的解决。从复杂的机器学习工具来判断婚姻是否真实,纳税人是否合规,或者核设施是否安全,我们还有很长的路要走。现实更接地气。在本文中,我描绘了算法和机器学习在加拿大联邦公共管理中的应用。我将在第一部分简要解释我的方法;在第2部分中,我确定了7个不同的用例,我用代表性的例子来描述它们,并提供了一些批判性的思考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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