This couse presented some interesting case studies, but never presented a real ethical system. In particular, the instructor frequently equated ethical behavior with socially acceptable behavior (this activity by corporation x was unethical because it resulted in public outcry). Someone with a background in ethics really should have been consulted in course developement.

On a purely practical matter, the ta did not seem to have any training in ethics at all. He just responded to every comment in the discussion area with a "what about" statement that sounded like it came straight from a late night dorm room bs session.

I've been disappointed with the course overall. it's a very interesting topic, one that's relevant to the times we live in. But I feel that many of the big questions are neither asked nor answered in the course.

The presenter's background is in engineering, not philosophy. This isn't a fundamental problem in itself, but it does mean that concepts are left very vaguely defined. So 'ethics' is, at one point, defined more or less as 'what's socially agreed-up'. But in the questions as well as the videos, the terminology shifts between 'ethically right/wrong', 'appropriate', 'have to do something,' 'by rights', 'legally', and lots more besides. So it's far from clear what the right or wrong position might be in many of the thought-experiments described in the quiz questions. What's more, if an action isn't in itself ethically right, that doesn't entail that it must be ethically wrong: it could be neither. There's virtually no input from other voices, too: no discussions with, say, experts in the field of data ethics, or moral philosophers, or whatever.

At one point in week 1, the presenter correctly points out that ''data ownership is really complex''. So it'd be useful to have a MOOC that makes it less complex: that asks hard questions, and critically examines the range of possible answers. Unfortunately, this MOOC isn't it.

Good course. Challenging and thought provoking. The professor was very good, but, even if you complete all assignments, your certification and grade depends upon having others in the course go in and review your assignment. Even if you review more than you are required to review, if others don't review yours, you don't pass or get your certification. So, be aware of that if you are attending a class in the hopes of obtaining a certification. It is not guaranteed even if you do all of the work.

The instructor really explained everything well and in detailed manner. I appreciate all the videos and case studies. Those tools help me to understand the subject in a deeper manner.

The course content is actually quite good and thought provoking, but the final submission requires peer review which appears to be practically impossible to get. Looking through the course chat there are months-to-years-old posts pleading for reviews by poor souls who cannot get their certificates because they have yet to receive the required four reviews.

This one-star review is not for the content or presentation or quizzes, which are otherwise five-star, but for the simple fact that the evidenciary certificate that so many of us came here to get is locked behind a poorly planned and ironically unethical peer review system that was clearly not thought out before it was implemented.

TO,

RESPECTED H.V. JAGDISH SIR

THANK YOU SIR FOR GIVING US KNOWLEDGE ABOUT DATA PRIVACY, OWNERSHIP, PROTECTION AND USER CONTROLTO MANIPULATE DATA.

YOURS SINCERELY

HARSH MOHAN

I doesn't received any certificate

This is really a great course. It is a starting point for anyone who want to get deeper into Data Science Ethics. Even if I feel that I am fairly familiar with the topic, I learned a lot and particular the case studies were really great. It should be a must for anyone in Data Science.

I really enjoyed the material and the way it was presented. Even though I am not new to the topic, still more avenues and perspectives were supported with very good examples. Very refreshing.

Absolutely delightful to have Professor Jagadish walking us through the course. The course was informative and very stimulating. Opens up to a new world of data science ethics. Thank you!

Very good course with excellent examples and a balanced approach. My only issue was that the pace of the presentation was a little too slow at times. Content-wise, excellent.

As I expected, the course provided me a lot of food for thought.

The aspect that I appreciated most was the necessity, as an Italian legal privacy counsel, to put aside my legal and GDPR background, and to think in a “more ethic manner”. This kind of approach permitted me to view the EU General Data Protection Regulation with new eyes, finding some aspects about that Regulation that I think could be improved.

Very interesting course. The explanation has been made very easy with examples and references and the quizzes to test one's understanding at the end of each topic.

This course is short, slow, and easy, but I ranked it five stars because the content is important in today's growing reliance on data science.

Very enjoyable and useful course. Modules are easy to follow and the concepts are useful in the workplace and wider society.

Good course to learn

This is a good intro to the topic for data scientists with no prior background in ethics. As someone who has studied the philosophy of ethics (even if you've only taken one course in it) you'll likely be disappointed in the limited level of depth in terms of considering ethical theories. To be fair, the instructor does state this at the beginning of the course. My other issue I had with this course is that the assessment quizzes use true or false questions - which in my opinion represents a VAST simplification of the complexities of ethical questions. This kind of simplified black and white thinking is exactly what we do NOT want in the people creating and controlling our technology, so I was disappointed to see the assessment style encouraging it.

The examples used and discussion points were interesting to me and encouraged me to learn more, thank you.

Presenter did not vary tone, was not engaging and made it very difficult to follow.

This course is interesting, but not very complex. It does offer numerous case studies. You can explore pretty much the same material in a shorter period of time by reading "Weapons of Math Destruction" or "Calling Bulls&*t" which focus more on the specifics of how statistics and data science / machine learning can be either intentionally manipulated or inadvertently so. They cover p-hacking in more depth, visualizations that can be misleading, and many of the more deep ethical issues covered here.