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Thought this was interesting. Across 160 teams of researchers, just about all failed to make good life outcome predictions on things like GPA, evictions, layoffs, and others. Data followed 4.5k families across 15 years, with 13k features (varied over time). Haven't looked at it directly yet, but will be turning the docs and data inside out... In the meantime, authors claim this as showing the limits of ML. Oh, and it's published in PNAS, so you know there's some big publication energy there.
https://www.pnas.org/content/117/15/8398
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I am curious to which group you are in...I have seen a few new leaders get hired in to KPMG and they are...lets just say organizations they leave, usually try to hire back the folks that left under said leader.
I’d raise it as a problem as see if your organization takes it seriously and addresses it. If not, or if you don’t feel comfortable raising the issue, I’d leave.
I was in that situation once. Left after 1.5 years since it wasn’t taken seriously. A year later the entire management team (up to senior VP) was let go.
Technical or not, I think it’s important that any manager understands own limitations, e.g. when to challenge their team and when to trust their team is more knowledgeable and/or more into the project that they are able to make the best decisions.