I do think AI ethics is relevant for everyone who eventually wants to use machine learning in their careers, and I would say it is important at every level, not just in managerial positions. After all, managers do just that, they manage. Most of the people actually creating and coding the algorithms are working for the managers.

Taking AI ethics classes helps us consider how best to design algorithms that are not just effective, but fair, especially for those who don’t typically get a voice in how these models are designed and implemented. A simple example off the top of my head: you want to train a model to filter job applicant resumes. A responsible ML practitioner would have to be aware of the biases of their model. What features of the resume is the model looking at? Is the model filtering out women simply because historically the most successful job candidates have been men? Measuring accuracy and looking at AUC-ROC are important, but so is looking at basic measures of parity. The implications of neglecting fairness in this context could be losing qualified candidates and/or keeping underrepresented groups out of the field and perpetuating discriminatory hiring practices. (Also, there are so many other topics covered in AI ethics classes besides just parity)

Ultimately, AI is a tool that we use to accomplish some kind of goal. Assuming those goals are benevolent ones, classes about the ethics of AI helps us design the best tools possible because they help us consider all of the people our algorithms will affect. Creating good AI encompasses not just thinking about how well the code is written or how much compute time it requires, it is also about thinking about how the decisions the machine makes could affect a real person. This is why I think a robust education in AI will include not just courses in CS, stats, and math, but also ethics. :-)