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Data Science Ethics – Course Preview

Living in the age of big data, we need to think about the ethics of data science.
The age of big data dawned a few years ago and now, of course, we live in a world today that people couldn’t have imagined a generation ago. I’m a data scientist and what this project is about is having other data scientist think about the ethics of our field. If I take a picture of you, who owns that picture? In terms of law and in terms of our general understanding, that picture is a picture of you, but I took that picture. I own it. What are ways in rechecking to use that picture, and whether I can use that picture in ways that could hurt you? Now take this to data.
If I have some data about you, is that your data or is that my data because I collected it? Just trying to understand what’s my ownership of this versus what’s your ownership, and what’s the obligation one has to the other is not so straightforward. If you don’t even know what one might be doing wrong, you can’t even begin to fix things. If you don’t even agree on what is right and what is wrong, then we don’t even have a motivation of something to fix. What one needs to have first is a societal agreement on what is right and what’s wrong. I think that in the case of data science, we really haven’t had that kind of broad discussion.
And then, flowing from that, a framework to think about how they could practice their data science differently so that they do the right thing. Doing this right can actually allow one to have guarantees of fairness. Your firm is at the forefront of educating the leaders of tomorrow in almost any field. And having an ethics component to that data science training at your firm is the right thing for your firm to do. If you’re doing things with data, you got to remember that you have a great deal of power. And with a great deal of power, comes a great deal of responsibility. This course is going to teach you how to be responsible in that exercise of power.
Data scientist who have had ethical training will be result in better more ethical practice of data science, and I think that this is good for data science and this is good for society at large.

Speaker: H. V. Jagadish

H. V. Jagadish is Bernard A Galler Collegiate Professor of Electrical Engineering and Computer Science at the University of Michigan in Ann Arbor. Prior to 1999, he was Head of the Database Research Department at AT&T Labs, Florham Park, NJ.

Professor Jagadish is well known for his broad-ranging research on information management, and has approximately 200 major papers and 37 patents. He is a fellow of the ACM, “The First Society in Computing,” (since 2003) and serves on the board of the Computing Research Association (since 2009). He has been an Associate Editor for the ACM Transactions on Database Systems (1992-1995), Program Chair of the ACM SIGMOD annual conference (1996), Program Chair of the ISMB conference (2005), a trustee of the VLDB (Very Large DataBase) foundation (2004-2009), Founding Editor-in-Chief of the Proceedings of the VLDB Endowment (2008-2014), and Program Chair of the VLDB Conference (2014).Ê Since 2016, he is Editor of the Morgan & Claypool Synthesis Lecture Series on Data Management. Among his many awards, he won the ACM SIGMOD Contributions Award in 2013 and the David E Liddle Research Excellence Award (at the University of Michigan) in 2008.

At the age of big data, we need to think about the ethics of data science.

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Data Science Ethics

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