About this Course

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What are the ethical considerations regarding the privacy and control of consumer information and big data, especially in the aftermath of recent large-scale data breaches?
This course provides a framework to analyze these concerns as you examine the ethical and privacy implications of collecting and managing big data. Explore the broader impact of the data science field on modern society and the principles of fairness, accountability and transparency as you gain a deeper understanding of the importance of a shared set of ethical values. You will examine the need for voluntary disclosure when leveraging metadata to inform basic algorithms and/or complex artificial intelligence systems while also learning best practices for responsible data management, understanding the significance of the Fair Information Practices Principles Act and the laws concerning the "right to be forgotten."

This course will help you answer questions such as who owns data, how do we value privacy, how to receive informed consent and what it means to be fair.

Data scientists and anyone beginning to use or expand their use of data will benefit from this course. No particular previous knowledge needed.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

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Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

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Beginner Level

Approx. 14 hours to complete

English

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Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Beginner Level

Approx. 14 hours to complete

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructor

Instructor rating

4.76/5 (187 Ratings)

H.V. Jagadish

Bernard A Galler Collegiate Professor

Electrical Engineering and Computer Science

31,989 Learners

1 Course

Syllabus - What you will learn from this course

Content Rating95%(3,604 ratings)

Week1

Week 1

2 hours to complete

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.

2 hours to complete

4 videos (Total 21 min), 4 readings, 1 quiz

1 hour to complete

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.

1 hour to complete

4 videos (Total 33 min)

1 hour to complete

Data Ownership

1 hour to complete

5 videos (Total 28 min)

Week2

Week 2

2 hours to complete

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".

2 hours to complete

7 videos (Total 53 min), 2 readings, 1 quiz

1 hour to complete

Anonymity

1 hour to complete

4 videos (Total 26 min)

Week3

Week 3

2 hours to complete

Data Validity

2 hours to complete

10 videos (Total 60 min), 1 reading, 1 quiz

2 hours to complete

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.

2 hours to complete

6 videos (Total 50 min), 1 reading, 1 quiz

Week4

Week 4

2 hours to complete

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.

2 hours to complete

5 videos (Total 46 min), 1 reading, 1 quiz

2 hours to complete

Code of Ethics

2 hours to complete

3 videos (Total 16 min), 1 reading, 2 quizzes

1 hour to complete

Attributions

1 hour to complete

5 readings

Reviews

4.8

214 reviews

5 stars
82.07%
4 stars
14.28%
3 stars
2.07%
2 stars
0.90%
1 star
0.64%

TOP REVIEWS FROM DATA SCIENCE ETHICS

by KGSep 15, 2021

I enrolled on the course due to my curiosity. The instructor made the course interesting all through out. I will apply the things I have learned here on my job as a Safety personnel.

by MPOct 3, 2021

This course is very helpful about the ethics to be followed in data capturing, data sharing and data usage etc. Over all it's very useful for me to get understanding on Data ethics.

by JJMar 29, 2019

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!

by DDJun 19, 2021

Awesome course that is being carefully prepared. The case studies are classic hence it is rather easy to correlate with the identified problem being introduced throughout the course.

View all reviews

Frequently Asked Questions

When will I have access to the lectures and assignments?
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The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I purchase the Certificate?
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

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Data Science Ethics

Data Science Ethics

About this Course