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Managing Risk in AI (6/6)

As the importance of knowing the internal details of machine learning algorithms diminishes, the importance of understanding how to apply machine learning appropriately rises. This series of videos explores the issues that you need to consider when making data driven decisions, such as: when machine learning is appropriate, sources of bias, validations, and explains ability of models and decision-making criteria.

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Managing Risk in AI: Part 6 - Ethical Decisions

The final video of the series touches on extra ethical considerations for humans and machines working together to make decisions, including respect for privacy and where human responsibilities lie.

Mon 2 Mar 2020
Jon McLoone
56 mins
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Managing Risk in AI: Part 5 - Explainability

This video discusses the limits of trying to understand and explain how the 'black box' of AI is making its decisions and alternative approaches to make sure you can respond to challenges to your AI-driven decisions.

Mon 2 Mar 2020
Jon McLoone
56 mins
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Managing Risk in AI: Part 4 - Making Decisions

This video explores how applications for decision-making are informed by AI models and, more importantly, when those predictions should be used as a basis for decisions.

Mon 2 Mar 2020
Jon McLoone
56 mins
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Managing Risk in AI: Part 3 - Validation

This video discusses how you can measure the performance of your AI tools and make sure they are making useful predictions.

Mon 2 Mar 2020
Jon McLoone
56 mins
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Managing Risk in AI: Part 2 - Managing Bias

This video explores different sources of problematic data and the interpretation that can cause unexpected bias in AI-driven decisions.

Mon 2 Mar 2020
Jon McLoone
56 mins
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Managing Risk in AI Part 1: Uses of AI

This video explains what kinds of tasks modern AI is capable of and its inherent limitations, and provides a rough guide for when you should turn to AI as a solution.

Mon 2 Mar 2020
Jon McLoone
56 mins