Assuming you selectively quoted me in good faith before asking "who is harmed", you should read the whole SEP entry on the ethics of manipulation, and then you should review the works it references.
https://plato.stanford.edu/entries/ethics-manipulation/
But to answer you directly:
- Whoever hires the author for their software engineering or data science expertise in part because of this blog post will pay for substandard work.
- By deceiving their audience as to the accuracy and precision of the demonstrated techniques, the author undermines the audience's ability to make good decisions about when to use or how to reason from the results of machine learning algorithms.
- The author disrespects their audience when they misrepresent themself, their work, and their results.
Who is harmed by carrying around a mistaken number for this, especially if they notice the 40% confidence?
As to the rest, I read it as an application of tools for an interesting question, not a comprehensive or authoritative how-to. It’s scaled napkin math, and napkin math is very useful.