Why do people think any kind of “x for people with no knowledge of x” tool is a worthwhile idea? It reminds me of various cloud vendor ML offerings too. With ML

Why do people think any kind of “x for people with no knowledge of x” tool is a worthwhile idea? It reminds me of various cloud vendor ML offerings too. With ML, you _always_ need ML domain knowledge to (at minimum) understand the performance characteristics of the black box you’re using, and (more often) also how to re-train/fine-tune/incrementally update as your use case’s data distribution changes over time or your required performance characteristics change over time. Like with AWS Rekognition where you’re billed on raw usage, which makes no sense when what matters is going to be the precision & recall & false detection rate on your data distribution (not whatever Amazon’s team trains it on). How many true positives / false positives / etc. will you get on your data? ML is uniquely poorly suited to be treated as just some API or just some black box library. I really wish people would stop popularizing footgun approaches to this!