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In partnership with Campaign for Social Science, Social Research Association, and UK Evaluation Society. Artificial Intelligence (AI) is accelerating change in the economy and society. But while AI has the potential to be transformative, not all uses of AI will be a game changer – or be the positive force we want it to be. How do we cut through the noise and find out what AI will actually do for us? In this talk, Oliver Hauser will discuss how policy-makers, researchers and evaluators should think about evaluating the causal effects of AI in policy-making and business. He will begin by introducing key principles around AI and machine learning (ML) – a brief primer for those new to the technology or the terminology - and then an example in practice by showcasing a large-scale field experiment in a public sector organisation where we evaluate the causal effects of ML and behavioural interventions, and demonstrate where there are (or are not) benefits of each, and why we should care. Oliver will describe a framework for how we might think about evaluating AI, especially where our traditional approaches need tweaking to keep up with the fast pace, the ‘self-learning’ nature and the feedback loop of the technology. He will conclude with a challenge—and a moral appeal—highlighting the importance of “test, learn, adapt” more than ever, for an age where AI promises to be able to do anything and everything for us – but where we need the best policy-makers, researchers and evaluators to hold us (and the technology) accountable, making sure we figure out what actually works. Presented By: Professor Oliver Hauser Oliver Hauser is Professor of Economics and Deputy Director at the Institute for Data Science & Artificial Intelligence at the University of Exeter, Faculty Affiliate at Harvard University, Senior Specialist Advisor in the Evaluation Task Force in the UK Cabinet Office, and an advisor to several multinational firms, start-ups and charities.