Donti: Average-Case ML Fails on Grids Without Physical Boundary Guardrails
Priya Donti · How AI is being used in energy, right now · Jun 22, 2023 · at 11:55
MIT assistant professor Priya Donti explains the operational hazards of deploying standard machine learning models into complex physical power systems without engineering constraints.
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“The fact that you can get a machine learning algorithm that learns to do something nuanced from data and does it right most of the time doesn't help you in those times when it does something wrong that one time that really blacks out your grid. So this is where kind of machine learning can help you find the predominant patterns, help you figure out what to do in the average case when things are going as usual, but in these extremal cases or kind of, you know, anomalous cases that may only show up You know, little or not at all in your underlying data. That's when you need often to put guardrails to make sure that your algorithm is not kind of crossing some physical boundary.”
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