4 Comments

The gender / income data was interesting. Is there really much value in the data when using total averages, and not even specific to industries or roles? I can say I’ve never had a hiring budget large enough to hire a minority female in finance, but white men are very cheap in comparison. I’d be interested to see how much this gap changes by industry / role.

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I’ve learned something new again. If you could what would be the top diseases or conditions you would look to solve for ?

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Hmm, there are so many choices! Antibiotic resistant tuberculosis ranks among the top though or the other top causes of death listed here: https://ourworldindata.org/causes-of-death

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TB and AMR, would be up there for me, for sure. I was interested because some areas like Alzh, dementia are very high impact, but currently not easily tractable. Some of the infectious diseases, or clean water areas, are high impact, and maybe somewhat tractable. And maybe you had thought about what the better areas were triangulating money, ease, impact etc. I've also wondered about alchohol which tends to always be a risk factor, but the underlying is complicated. Thanks!

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