课程信息
4.6
53 个评分
24 个审阅
100% 在线

100% 在线

立即开始,按照自己的计划学习。
可灵活调整截止日期

可灵活调整截止日期

根据您的日程表重置截止日期。
初级

初级

完成时间(小时)

完成时间大约为15 小时

建议:4 weeks, 3-4 hours/week...
可选语言

英语(English)

字幕:英语(English)
100% 在线

100% 在线

立即开始,按照自己的计划学习。
可灵活调整截止日期

可灵活调整截止日期

根据您的日程表重置截止日期。
初级

初级

完成时间(小时)

完成时间大约为15 小时

建议:4 weeks, 3-4 hours/week...
可选语言

英语(English)

字幕:英语(English)

教学大纲 - 您将从这门课程中学到什么

1
完成时间(小时)
完成时间为 1 小时

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....
Reading
4 个视频 (总计 21 分钟), 4 个阅读材料, 1 个测验
Video4 个视频
What are Ethics?9分钟
Data Science Needs Ethics3分钟
Case Study: Spam (not the meat)4分钟
Reading4 个阅读材料
Course Syllabus10分钟
Welcome Announcement10分钟
Help us learn more about you!10分钟
What are Ethics? - Introduction10分钟
Quiz1 个练习
Module 1 Quiz20分钟
完成时间(小时)
完成时间为 1 小时

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....
Reading
4 个视频 (总计 33 分钟), 1 个测验
Video4 个视频
Human Subjects Research and Informed Consent: Part 28分钟
Limitations of Informed Consent9分钟
Case Study: It's Not OKCupid6分钟
Quiz1 个练习
Module 2 Quiz20分钟
完成时间(小时)
完成时间为 1 小时

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. ...
Reading
5 个视频 (总计 28 分钟), 1 个测验
Video5 个视频
Limits on Recording and Use7分钟
Data Ownership Finale3分钟
Case Study: Rate My Professor3分钟
Case Study: Privacy After Bankruptcy2分钟
Quiz1 个练习
Module 3 Quiz20分钟
2
完成时间(小时)
完成时间为 2 小时

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"....
Reading
7 个视频 (总计 53 分钟), 2 个阅读材料, 1 个测验
Video7 个视频
Privacy3分钟
History of Privacy15分钟
Degrees of Privacy10分钟
Modern Privacy Risks12分钟
Case Study: Targeted Ads3分钟
Case Study: The Naked Mile2分钟
Case Study: Sneaky Mobile Apps5分钟
Reading2 个阅读材料
Privacy - Introduction10分钟
Module 4 Discussion Prompt References10分钟
Quiz1 个练习
Module 4 Quiz20分钟
完成时间(小时)
完成时间为 1 小时

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....
Reading
4 个视频 (总计 26 分钟), 1 个测验
Video4 个视频
Anonymity5分钟
De-identification Has Limited Value: Part 17分钟
De-identification Has Limited Value: Part 210分钟
Case Study: Credit Card Statements2分钟
Quiz1 个练习
Module 5 Quiz20分钟
3
完成时间(小时)
完成时间为 2 小时

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....
Reading
10 个视频 (总计 60 分钟), 1 个阅读材料, 1 个测验
Video10 个视频
Validity9分钟
Choice of Attributes and Measures6分钟
Errors in Data Processing8分钟
Errors in Model Design8分钟
Managing Change5分钟
Case Study: Three Blind Mice4分钟
Case Study: Algorithms and Race3分钟
Case Study: Algorithms in the Office3分钟
Case Study: GermanWings Crash5分钟
Case Study: Google Flu5分钟
Reading1 个阅读材料
Data Validity - Introduction10分钟
Quiz1 个练习
Module 6 Quiz20分钟
完成时间(小时)
完成时间为 1 小时

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....
Reading
6 个视频 (总计 50 分钟), 1 个阅读材料, 1 个测验
Video6 个视频
Correct But Misleading Results12分钟
P Hacking10分钟
Case Study: High Throughput Biology3分钟
Case Study: Geopricing2分钟
Case Study: Your Safety Is My Lost Income10分钟
Reading1 个阅读材料
Algorithmic Fairness - Introduction10分钟
Quiz1 个练习
Module 7 Quiz20分钟
4
完成时间(小时)
完成时间为 1 小时

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. ...
Reading
5 个视频 (总计 46 分钟), 1 个阅读材料, 1 个测验
Video5 个视频
Ossification7分钟
Surveillance4分钟
Case Study: Social Credit Scores7分钟
Case Study: Predictive Policing8分钟
Reading1 个阅读材料
Societal Consequences - Introduction10分钟
Quiz1 个练习
Module 8 Quiz20分钟
完成时间(小时)
完成时间为 3 小时

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....
Reading
3 个视频 (总计 16 分钟), 1 个阅读材料, 2 个测验
Video3 个视频
Wrap Up2分钟
Case Study: Algorithms and Facial Recognition4分钟
Reading1 个阅读材料
Post-Course Survey10分钟
Quiz1 个练习
Module 9 Quiz10分钟
完成时间(小时)
完成时间为 1 小时

Attributions

This module contains lists of attributions for the external audio-visual resources used throughout the course....
Reading
4 个阅读材料
Reading4 个阅读材料
Week 1 Attributions10分钟
Week 2 Attributions10分钟
Week 3 Attributions10分钟
Week 4 Attributions10分钟
4.6
24 个审阅Chevron Right

热门审阅

创建者 JMJul 1st 2018

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.

创建者 SMMay 15th 2018

Excellent Course. Gives interesting and detailed perspectives on ethical matters related to how data can be used and should be used.

讲师

Avatar

H.V. Jagadish

Bernard A Galler Collegiate Professor
Electrical Engineering and Computer Science

关于 University of Michigan

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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