I just read all of this. I think the whole course -- which is actually pretty short, like an hour or two of reading sans exercises, and for the most part clearly written -- would be a good assignment for a single day of a first-year university computer science course. It does offer a reasonable, albeit almost entirely nontechnical, overview of why people should care about AI ethics, and what caring about it "means".
As for my reaction to it, I'll borrow a useful distinction the course makes near the beginning about three types of ethics:
> 1) Meta-ethics studies the meaning of ethical concepts, the existence of ethical entities (ontology) and the possibility of ethical knowledge (epistemology). 2) Normative ethics concerns the practical means of determining a moral (or ethically correct) course of action. 3) Applied ethics concerns what a moral agent (defined as someone who can judge what is right and wrong and be held accountable) is obligated or permitted to do in a specific situation or a particular domain of action.
In this language, the course is almost entirely about 1) with a few gestures in the direction of 2) and 3) near the end. I'm not totally unsympathetic to this; there are still people out there who are not convinced AI (or algorithmic) ethics is a "thing" (response: any apparatus that makes choices that matter involves ethics!), so I get why justifying the topic itself seems necessary.
But in the other direction, I think people sometimes conflate "ethicist" with "person who will know what to do" -- that is, someone with expertise in 2) and 3) above. In my limited experience, ethicists seem to "work on" mostly 1). I hope there will be more work on the 2) and 3) parts of AI ethics in the near future.
By the way, if you want a more technical look at this topic (albeit framed more narrowly as "fairness and machine learning"), there is a nice draft textbook on the topic [1]. It probably has enough material for a semester-long upper-level computer science course.
As for my reaction to it, I'll borrow a useful distinction the course makes near the beginning about three types of ethics:
> 1) Meta-ethics studies the meaning of ethical concepts, the existence of ethical entities (ontology) and the possibility of ethical knowledge (epistemology). 2) Normative ethics concerns the practical means of determining a moral (or ethically correct) course of action. 3) Applied ethics concerns what a moral agent (defined as someone who can judge what is right and wrong and be held accountable) is obligated or permitted to do in a specific situation or a particular domain of action.
In this language, the course is almost entirely about 1) with a few gestures in the direction of 2) and 3) near the end. I'm not totally unsympathetic to this; there are still people out there who are not convinced AI (or algorithmic) ethics is a "thing" (response: any apparatus that makes choices that matter involves ethics!), so I get why justifying the topic itself seems necessary.
But in the other direction, I think people sometimes conflate "ethicist" with "person who will know what to do" -- that is, someone with expertise in 2) and 3) above. In my limited experience, ethicists seem to "work on" mostly 1). I hope there will be more work on the 2) and 3) parts of AI ethics in the near future.
By the way, if you want a more technical look at this topic (albeit framed more narrowly as "fairness and machine learning"), there is a nice draft textbook on the topic [1]. It probably has enough material for a semester-long upper-level computer science course.
[1] https://fairmlbook.org/