Enough to reason about what the thing does in a basic manner and potential pros and cons? That seems like a straightforward heuristic but maybe I'm an optimist

Enough to reason about what the thing does in a basic manner and potential pros and cons? That seems like a straightforward heuristic but maybe I'm an optimist haha. You don't need to know the ins and outs of the mathematics to understand what encryption does, but you should be able to reason about how data is encrypted and what is necessary to decrypt, and what law provides you to request decryption. You sure as hell should also be able to grasp that, like the atomic bomb, once out in the world it's there to stay and you can't really prevent it from being used. As for economic impact - I find that measure does not really get ahead of the problem. In the case of machine learning if you're regulating economic impact you're decades late. The first-movers already have the data sets, the training has occurred and now you're living in their world. I think it's important to understand a bit more upstream so that you can get ahead of these kinds of issues. Furthermore, a baseline understanding of these algorithms and their potential biases / impacts of misclassification is important to understand to ensure we don't compromise society by their mis-use, or shift scales in a terrible way unintentionally. The earlier the better, and economic impacts are probably a lagging indicator, or even worse considered a huge boon for those areas that have companies doing this work but using labor from elsewhere to train their models.