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Artificial Intelligence And The End Of Government

Even as artificial intelligence (AI) is forecast to exceed human capabilities across a range of industries it is also predicted to augment human labor. In finance, AI is already helping financial advisors augment financial planning while enhancing investment strategy. And in medicine, AI diagnostics systems have proven to be far more accurate than doctors in diagnosing heart disease and cancerous growths. In fact, McKinsey lists some 400 use cases representing $6 trillion in value across 19 industries in which AI will augment human work.

But what about government? What will the impact of AI be on the nature of government?

Waking Government to AI

Not surprisingly much of the public sector has already begun experimenting with AI-driven technologies. At the federal level many agencies are beginning to deploy AI-powered interfaces for customer service, alongside an expanding use of software to update legacy-systems and automate simple tasks. Growing investments in infrastructure planning, legal adjudication, fraud detection, and citizen response systems represent the first phase in the ongoing digitization of government.

Notwithstanding these investments however, government remains far behind the private sector in deploying and integrating AI. As Silicon Valley’s Tim O’Reilly has suggested, augmenting government through AI is critical to modernizing the public sector. AI-based applications could potentially reduce backlogs and free workers from mundane tasks while cutting costs. According to Deloitte, documenting and recording information alone consumes a half-billion staff hours each year, at a cost of more than $16 billion in wages. Add to this an additional $15 billion in the procuring and processing of information and the value of AI in transforming government bureaucracy becomes clear.

Some now argue that the affordances of technology are critical to remaking government for the 21st century. Advancing democracies into the era of Big Data could go a long way towards reducing systemic dysfunction within the public sector. Using sensor technologies and machine learning systems to reinforce government oversight could begin to reduce regulation while actually increasing the amount of oversight. Coining the term “algorithmic regulation” for example, O’Reilly suggests that government regulations should be regarded as algorithms (i.e. a set of rules) that can be adjusted based on fresh data.

The most recent advancement in AI— deep learning— represents a revolution in the use of machines for supporting decision-management, forecasting, data classification and the synthesis of information. Building on deep learning tools, AI could mean significantly improving service delivery for citizens and elevating the work of public service professionals while also inspiring a new generation of technocrats to enter government. Alternatively, AI could also mean remaking government altogether.


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