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For most citizens in liberal democracies, life is dependent on the provision of good-quality public services in education, health care, retirement, policing, taxation, and the courts—to name but a few. These valuable public services are becoming extremely costly over time, contributing to the swelling of government deficits and the ballooning of national debts. Bad demographics make this trend worse, as many liberal democracies are trapped in a vicious circle of ever-diminishing tax receipts, due to the scarcity of young, taxable workers, and an aging population demanding more public services. This situation is clearly unsustainable. Artificial intelligence is a technology that could help alleviate some of these imbalances—for example, by optimizing the distribution of scarce public resources, improving decision-making based on intelligent predictions, and preventing tax fraud. Shouldn’t we therefore welcome the computer automation of government and public services using AI?
The relationship between computers and governments goes back a long way. In The Government Machine, historian Jon Agar argues that the ideological roots of computers are found in public administration. According to Agar, the mechanization of government started in the late eighteenth century when the public administration of the United Kingdom, trusted with running a global empire, invested in efficient operations, as well as in the collection and processing of information from across the world. In a liberal system of government, where civil servants run everyday government affairs, the computer is a reflection of a technocratic vision for efficiency and process management. As Agar says, “The general purpose computer is the apotheosis of the civil service.” Until recently, computer systems were acting as the “peripheral nervous system” of government organizations: automating some processes, collecting data, and using simple interfaces to serve citizens over the web. Extending the brain metaphor, the “central nervous system” of government has remained the cabal of top-level human administrators; the departmental directors, directors general, and ministers. For it is at that level where the ultimate responsibility for decision-making and action still resides. Nevertheless, complex government decisions require not just data and information fed upward by administration processes but expert advice too. Indeed, the rise of expert advisors in public administration—such as statisticians, health scientists, economists, and so on—is absolutely necessary for “evidence-based” politics, or what the German philosopher Jürgen Habermas calls the “scientization of politics.”
Enter AI, which can potentially automate the central nervous system of government, as well, and deliver an efficient, mechanized “organizational brain” that can make complex decisions autonomously by accessing vast amounts of diverse knowledge and data. By replacing human decision makers in public administration with informational processes controlled by AI algorithms, one could get the perfect government: impartial, efficient, and effective. But what would be the consequences of transforming the metaphorical “government machine” into a reality?
