I’ll add the one additional caveat that mid and high level professionals need to realize this is not just an entry-level or low-skilled-worker issue. In fact, as people are deciding where to invest machine learning and “AI” research resources, we’ll likely see those investments being made in positions where the average cost of human replacement is much higher.
If I’m running a hospital, for example, I don’t care nearly as much about lowering costs by automating the front desk staff as I do about reducing the number of doctors I need. Yes, it may be technically easier to automate or scale via remote work the tasks being executed at the front desk, but since every application of “AI” still requires heavy training and customization the more valuable way to apply it would be in basic diagnosis or research synthesis etc. that makes what doctors I do keep able to do 10X the work.
Great article Janessa, and very important that we keep talking about this now. The human race has historically had a difficult time adapting to changes over decades or centuries (e.g. industrialization), but this is a change that’s going to happen much faster.
I love this gif that shows the pace of computational progress. It seems very slow — until it isn’t:
