| We are not talking about the level of professional mathematicians or ML theory researchers you mentioned [1]. An average person, in the overall population, is unlikely to pass or possess the prerequisites (e.g. two semesters of college calculus) to attend the linear algebra course in the first place [2] [3]. For simple, routine applications, one can call machine learning APIs without deep understanding of the math behind them. In most real world applications, however, input data tend to be messy and there are many complications and constraints to satisfy. For the foreseeable future, applying machine learning in the real world requires input from humans who understand the why's and the how's behind an API. For more advanced work, reading papers is necessary and most of the recent machine learning papers contain substantial math (from the viewpoint of an average person, not a professional mathematician). In addition, math skills, at the basic level that PISA measures, are highly correlated with logical thinking, which will be relevant for AI engineering for a long time to come. [1] There are perhaps fewer than 100,000 professional mathematicians in the US out of over 100 million knowledge workers there. https://mathoverflow.net/questions/5485/how-many-mathematici... [2] https://www.noodle.com/articles/the-problem-with-college-cal... [3] http://hechingerreport.org/high-failure-rates-spur-universit... |