Data Science Ethics

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 course provides a good insight into some of the issues with the ethics of data science. Perhaps there is too much focus on data validity and not enough on ethics. This course shows that there is a need for systematic ethical enquiry into this subject.

This is a good course, it is applicable to a wide range of fields. I found it very helpful in my career. Ethics is key in ever aspect of our life.Thanks.

A good overview of privacy, ethics, informational consent etc.The numerous case studies were very informative, relevant and helpful for the daily work in Data Science.

I really enjoy ethics courses and I liked that this related to something so ingrained in our daily lives: data. I think, in general, ethics lessons are undervalued so I am glad to see this one offered.The professor was knowledgeable and did a good job. I would watch other courses with him teaching.My only criticism would be that these ethics were mostly presented from one point of view. Ethics rules can be very subjective depending on who is applying them, so I think hearing from other professors as well as the one who taught it would be good.

Good overview of topics regarding ethics in data science.

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.

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

Great materials. Very original. But I think the lecturer needs to smile and put more energy in his talk. Hope you're having a good day!

Good introductory course into the topic. Great lecturer. Think needs more deep dive into each topic with more diverse examples.

Nice, introductory course to ethics in data science. It is a good starting point for ethics considerations in this area.