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Machine Learning Curve

Probably approximately ethical

Making AI work in the enterprise requires more than talented scientists and large data sets. AI is as powerful and popular as it is because it can automate tasks for which precise rules are too hard to describe. But loosening this constraint also introduces new trade-offs executives need to understand to manage AI projects successfully. This talk from senior director of product and business development at Borealis AI Kathryn introduces the trade-offs around accuracy, error, explainability, privacy, and fairness that executives need to understand to guide technology teams and manage the risks of applying AI in real-world applications.

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  • Kathryn Hume

    Kathryn leads product and business development for Borealis AI.

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Machine Learning Curve