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Risk Management in the AI Era: Navigating the Opportunities and Challenges of AI Tools in the Public Sector : IBM Center for The Business of Government , 2020

2020

IBM Center for The Business of Government

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From the document: "Machine Learning (ML) continues to play an integral role in advancing this AI revolution. ML systems can “learn” and adapt in ways that the old expert systems that made up earlier forms of AI could not. There have been significant improvements in video and natural language recognition that seemed impossible only a few years ago. These ML techniques apply statistical inference to large input datasets, taking advantage of declining cost of computing power, to make predictions, create and analyze large data, and automate tasks that were either previously completed by humans or that were not even possible. The success of ML techniques enabled it to quickly spread throughout industries, including governments and the work of government agencies. Numerous reports highlight surveys of industry experts demonstrating the current and continued expected impact of AI tools, such as ML, natural language processing (NLP), robotic process automation (RPA), or artificial neural networks, in disrupting how private firms conduct their business. AI tools are also augmenting and automating the work of governments. Private industry faces its own challenges with adopting AI tools to make companies more profitable, but many more challenges are faced by government leaders and public managers. Those doing the work of government not only have to go about achieving their objectives and doing so in an efficient manner, but also they face concerns of equity, accountability, transparency, and others that must be factored into the overall risk management strategy associated with the adoption of AI tools to improve overall governance. It is to this challenge faced by government leaders and public managers that this report seeks to assist.

Authors - Bullock, Justin B., Young, Matthew M.

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Authors

Bullock, Justin B., Young, Matthew M.

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IBM Center for The Business of Government

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