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Data Science Ethics
  • Level Foundation
  • Duration 15 hours
  • Course by University of Michigan
  • Offered by

About

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.

Modules

What are Ethics?

    • 4 Videos
    • 4 Readings
    • 1 Discussion
    • 1 Assignment
Show info about module content

1 Assignment

  • Module 1 Quiz

1 Discussions

  • Module 1 Discussion

4 Videos

  • Data Science Ethics - Course Preview
  • What are Ethics?
  • Data Science Needs Ethics
  • Case Study: Spam (not the meat)

4 Readings

  • Course Syllabus
  • Welcome Announcement
  • Help us learn more about you!
  • What are Ethics? - Introduction

History, Concept of Informed Consent

    • 4 Videos
    • 1 Discussion
    • 1 Assignment
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1 Assignment

  • Module 2 Quiz

1 Discussions

  • Module 2 Discussion

4 Videos

  • Human Subjects Research and Informed Consent: Part 1
  • Human Subjects Research and Informed Consent: Part 2
  • Limitations of Informed Consent
  • Case Study: It's Not OKCupid

Data Ownership

    • 5 Videos
    • 1 Discussion
    • 1 Assignment
Show info about module content

1 Assignment

  • Module 3 Quiz

1 Discussions

  • Module 3 Discussion

5 Videos

  • Data Ownership
  • Limits on Recording and Use
  • Data Ownership Finale
  • Case Study: Rate My Professor
  • Case Study: Privacy After Bankruptcy

Privacy

    • 7 Videos
    • 2 Readings
    • 1 Discussion
    • 1 Assignment
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1 Assignment

  • Module 4 Quiz

1 Discussions

  • Module 4 Discussion

7 Videos

  • Privacy
  • History of Privacy
  • Degrees of Privacy
  • Modern Privacy Risks
  • Case Study: Targeted Ads
  • Case Study: The Naked Mile
  • Case Study: Sneaky Mobile Apps

2 Readings

  • Privacy - Introduction
  • Module 4 Discussion Prompt References

Anonymity

    • 4 Videos
    • 1 Discussion
    • 1 Assignment
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1 Assignment

  • Module 5 Quiz

1 Discussions

  • Module 5 Discussion

4 Videos

  • Anonymity
  • De-identification Has Limited Value: Part 1
  • De-identification Has Limited Value: Part 2
  • Case Study: Credit Card Statements

Data Validity

    • 10 Videos
    • 1 Readings
    • 1 Discussion
    • 1 Assignment
Show info about module content

1 Assignment

  • Module 6 Quiz

1 Discussions

  • Module 6 Discussion

10 Videos

  • Validity
  • Choice of Attributes and Measures
  • Errors in Data Processing
  • Errors in Model Design
  • Managing Change
  • Case Study: Three Blind Mice
  • Case Study: Algorithms and Race
  • Case Study: Algorithms in the Office
  • Case Study: GermanWings Crash
  • Case Study: Google Flu

1 Readings

  • Data Validity - Introduction

Algorithmic Fairness

    • 6 Videos
    • 1 Readings
    • 1 Discussion
    • 1 Assignment
Show info about module content

1 Assignment

  • Module 7 Quiz

1 Discussions

  • Module 7 Discussion

6 Videos

  • Algorithmic Fairness
  • Correct But Misleading Results
  • P Hacking
  • Case Study: High Throughput Biology
  • Case Study: Geopricing
  • Case Study: Your Safety Is My Lost Income

1 Readings

  • Algorithmic Fairness - Introduction

Societal Consequences

    • 5 Videos
    • 1 Readings
    • 1 Discussion
    • 1 Assignment
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1 Assignment

  • Module 8 Quiz

1 Discussions

  • Module 8 Discussion

5 Videos

  • Societal Impact
  • Ossification
  • Surveillance
  • Case Study: Social Credit Scores
  • Case Study: Predictive Policing

1 Readings

  • Societal Consequences - Introduction

Code of Ethics

    • 3 Videos
    • 1 Readings
    • 1 PeerReview
    • 1 Assignment
Show info about module content

1 Assignment

  • Module 9 Quiz

1 Peer Review

  • Data Ethics Case Study

3 Videos

  • Code of Ethics
  • Wrap Up
  • Case Study: Algorithms and Facial Recognition

1 Readings

  • Post-Course Survey

Attributions

    • 5 Readings
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5 Readings

  • Week 1 Attributions
  • Week 2 Attributions
  • Week 3 Attributions
  • Week 4 Attributions
  • Keep Learning with Michigan Online

Auto Summary

"Data Science Ethics" by Coursera is a foundational course in Data Science & AI, led by expert instructors. It delves into ethical considerations around privacy, control of consumer information, and big data management. Learners will explore the principles of fairness, accountability, and transparency, and understand the importance of ethical values in data science. The course also covers best practices for responsible data management, voluntary disclosure, and relevant laws like the Fair Information Practices Principles Act. Ideal for data scientists and beginners, it requires no prior knowledge and offers a 900-minute duration with a Starter subscription.

H.V. Jagadish
Instructor

H.V. Jagadish