Innovation-July-August-2023

F E A T U R E

“As a general rule, we’re very cautious of models that change over time. It’s not appropriate to rely on them in a safety related context.” One of the ways Diemert tests his models is by coming up with “challenge cases” and choosing a genuinely tricky task for the model to handle within that operating domain. Then he exercises the model over variants of those challenges. In his work with cars, for example, AI sometimes struggles to detect specific pedestrians, such as someone wearing odd attire or an exceptionally tall person. They’ll run the model through numerous tests along those lines to find its limitations. Diemert says it’s important to differentiate between using AI to find solutions and using it to verify or produce dependable solutions. In drug development, for example, many initiatives are using AI to produce solutions, but they still go through the established process for drug trials. “One framework could be that perhaps we view these tools as ways of inspiring our work and coming up with new approaches,” he says.

I llustration : AI creation

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