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初級レベル

約16時間で修了

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英語

字幕:英語

100%オンライン

自分のスケジュールですぐに学習を始めてください。

柔軟性のある期限

スケジュールに従って期限をリセットします。

初級レベル

約16時間で修了

推奨:4 weeks, 3-4 hours/week...

英語

字幕:英語

シラバス - 本コースの学習内容

1
1時間で修了

What are Ethics?

Module 1 of this course establishes a basic foundation in the notion of simple utilitarian ethics we use for this course. The lecture material and the quiz questions are designed to get most people to come to an agreement about right and wrong, using the utilitarian framework taught here. If you bring your own moral sense to bear, or think hard about possible counter-arguments, it is likely that you can arrive at a different conclusion. But that discussion is not what this course is about. So resist that temptation, so that we can jointly lay a common foundation for the rest of this course.

...
4件のビデオ (合計21分), 4 readings, 1 quiz
4件のビデオ
What are Ethics?9 分
Data Science Needs Ethics3 分
Case Study: Spam (not the meat)4 分
4件の学習用教材
Course Syllabus10 分
Welcome Announcement10 分
Help us learn more about you!10 分
What are Ethics? - Introduction10 分
1の練習問題
Module 1 Quiz20 分
1時間で修了

History, Concept of Informed Consent

Early experiments on human subjects were by scientists intent on advancing medicine, to the benefit of all humanity, disregard for welfare of individual human subjects. Often these were performed by white scientists, on black subject. In this module we will talk about the laws that govern the Principle of Informed Consent. We will also discuss why informed consent doesn’t work well for retrospective studies, or for the customers of electronic businesses.

...
4件のビデオ (合計33分), 1 quiz
4件のビデオ
Human Subjects Research and Informed Consent: Part 28 分
Limitations of Informed Consent9 分
Case Study: It's Not OKCupid6 分
1の練習問題
Module 2 Quiz20 分
1時間で修了

Data Ownership

Who owns data about you? We'll explore that question in this module. A few examples of personal data include copyrights for biographies; ownership of photos posted online, Yelp, Trip Advisor, public data capture, and data sale. We'll also explore the limits on recording and use of data.

...
5件のビデオ (合計28分), 1 quiz
5件のビデオ
Limits on Recording and Use7 分
Data Ownership Finale3 分
Case Study: Rate My Professor3 分
Case Study: Privacy After Bankruptcy2 分
1の練習問題
Module 3 Quiz20 分
2
2時間で修了

Privacy

Privacy is a basic human need. Privacy means the ability to control information about yourself, not necessarily the ability to hide things. We have seen the rise different value systems with regards to privacy. Kids today are more likely to share personal information on social media, for example. So while values are changing, this doesn’t remove the fundamental need to be able to control personal information. In this module we'll examine the relationship between the services we are provided and the data we provide in exchange: for example, the location for a cell phone. We'll also compare and contrast "data" against "metadata".

...
7件のビデオ (合計53分), 2 readings, 1 quiz
7件のビデオ
Privacy3 分
History of Privacy15 分
Degrees of Privacy10 分
Modern Privacy Risks12 分
Case Study: Targeted Ads3 分
Case Study: The Naked Mile2 分
Case Study: Sneaky Mobile Apps5 分
2件の学習用教材
Privacy - Introduction10 分
Module 4 Discussion Prompt References10 分
1の練習問題
Module 4 Quiz20 分
1時間で修了

Anonymity

Certain transactions can be performed anonymously. But many cannot, including where there is physical delivery of product. Two examples related to anonymous transactions we'll look at are "block chains" and "bitcoin". We'll also look at some of the drawbacks that come with anonymity.

...
4件のビデオ (合計26分), 1 quiz
4件のビデオ
De-identification Has Limited Value: Part 17 分
De-identification Has Limited Value: Part 210 分
Case Study: Credit Card Statements2 分
1の練習問題
Module 5 Quiz20 分
3
2時間で修了

Data Validity

Data validity is not a new concern. All too often, we see the inappropriate use of Data Science methods leading to erroneous conclusions. This module points out common errors, in language suited for a student with limited exposure to statistics. We'll focus on the notion of representative sample: opinionated customers, for example, are not necessarily representative of all customers.

...
10件のビデオ (合計60分), 1 reading, 1 quiz
10件のビデオ
Choice of Attributes and Measures6 分
Errors in Data Processing8 分
Errors in Model Design8 分
Managing Change5 分
Case Study: Three Blind Mice4 分
Case Study: Algorithms and Race3 分
Case Study: Algorithms in the Office3 分
Case Study: GermanWings Crash5 分
Case Study: Google Flu5 分
1件の学習用教材
Data Validity - Introduction10 分
1の練習問題
Module 6 Quiz20 分
1時間で修了

Algorithmic Fairness

What could be fairer than a data-driven analysis? Surely the dumb computer cannot harbor prejudice or stereotypes. While indeed the analysis technique may be completely neutral, given the assumptions, the model, the training data, and so forth, all of these boundary conditions are set by humans, who may reflect their biases in the analysis result, possibly without even intending to do so. Only recently have people begun to think about how algorithmic decisions can be unfair. Consider this article, published in the New York Times. This module discusses this cutting edge issue.

...
6件のビデオ (合計50分), 1 reading, 1 quiz
6件のビデオ
Correct But Misleading Results12 分
P Hacking10 分
Case Study: High Throughput Biology3 分
Case Study: Geopricing2 分
Case Study: Your Safety Is My Lost Income10 分
1件の学習用教材
Algorithmic Fairness - Introduction10 分
1の練習問題
Module 7 Quiz20 分
4
1時間で修了

Societal Consequences

In Module 8, we consider societal consequences of Data Science that we should be concerned about even if there are no issues with fairness, validity, anonymity, privacy, ownership or human subjects research. These “systemic” concerns are often the hardest to address, yet just as important as other issues discussed before. For example, we consider ossification, or the tendency of algorithmic methods to learn and codify the current state of the world and thereby make it harder to change. Information asymmetry has long been exploited for the advantage of some, to the disadvantage of others. Information technology makes spread of information easier, and hence generally decreases asymmetry. However, Big Data sets and sophisticated analyses increase asymmetry in favor of those with ability to acquire/access.

...
5件のビデオ (合計46分), 1 reading, 1 quiz
5件のビデオ
Ossification7 分
Surveillance4 分
Case Study: Social Credit Scores7 分
Case Study: Predictive Policing8 分
1件の学習用教材
Societal Consequences - Introduction10 分
1の練習問題
Module 8 Quiz20 分
3時間で修了

Code of Ethics

Finally, in Module 9, we tie all the issues we have considered together into a simple, two-point code of ethics for the practitioner.

...
3件のビデオ (合計16分), 1 reading, 2 quizzes
3件のビデオ
Wrap Up2 分
Case Study: Algorithms and Facial Recognition4 分
1件の学習用教材
Post-Course Survey10 分
1の練習問題
Module 9 Quiz10 分
1時間で修了

Attributions

This module contains lists of attributions for the external audio-visual resources used throughout the course.

...
4 readings
4件の学習用教材
Week 1 Attributions10 分
Week 2 Attributions10 分
Week 3 Attributions10 分
Week 4 Attributions10 分
4.6
36件のレビューChevron Right

Data Science Ethics からの人気レビュー

by LAJun 27th 2019

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.

by AYMar 18th 2019

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!

講師

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H.V. Jagadish

Bernard A Galler Collegiate Professor
Electrical Engineering and Computer Science

ミシガン大学(University of Michigan)について

The mission of the University of Michigan is to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values, and in developing leaders and citizens who will challenge the present and enrich the future....

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