Governments face at least four fundamental challenges in decision making: making a large number of decisions; making policy-consistent decisions; making procedurally fair decisions; and learning from the outcomes of decisions. AI and machine learning have the potential to make major advances on all these challenges. Decisions which can be automated, or which can move to a recommendation more rapidly can allow for faster decision making. Similarly, automating decision processes has the potential to bring to bear data and other information that are chosen because of their consistency with policy goals. At the same time, we can eliminate the influence of irrelevant and potentially biased/biasing sources of information. Because machines do not get tired and are not naturally biased, they can under some circumstances make choices which are procedurally fairer. Automated decision making can incorporate much more information into any retrospection or audit. Learning is easier. There are, however, major risks to be considered, among them principal-agent problems, problems of biased data inputs, problems of explainability and black-boxing, and problems of consent and procedural unfairness, where citizens will not accept a decision made without a human in the loop. This talk presents a short framework for understanding how a policy or administrative might be a good candidate to implement AI or a machine learning process.
Speaker: Peter Loewen, Director, Munk School of Global Affairs & Public Policy, University of Toronto; Associate Director, Schwartz Reisman Institute.
About this series:
Artificial intelligence is constantly evolving, playing an increasingly larger role in our lives, and transforming every sector from medicine to finance to law and far beyond. We often read about both the great promise of AI and its negative consequences. But what really is AI? How can AI advance human welfare by improving health, education, sustainability, equality and inclusion, access to justice, and more? What do we need to do to ensure that AI is built for public benefit, and how can we mitigate the harm AI can cause? To respond to these questions, the Schwartz Reisman Institute for Technology and Society partnered with Canada School of Public Service to present “Artificial Intelligence is Here,” an eight-part series designed to explain what AI is, where it’s headed, and what workers in the public sector need to know about it.