AI Ethics research is an emerging field, and to prove our skills, we need to demonstrate our critical thinking and analytical ability. Since it's not reasonable to jump into a full research paper with our newly founded skills, we will instead work on 3 projects that will demonstrate your ability to analyze ethical AI across a variety of topics and situations. These projects include all the skills you've learned in this AI Ethics Specialization.
Artificial Intelligence Ethics in Action
Artificial Intelligence Ethics in Action
This course is part of Ethics in the Age of AI Specialization
Instructor: Brent Summers
Sponsored by Coursera Learning Team
11,648 already enrolled
Gain insight into a topic and learn the fundamentals.
4.6
(236 reviews)
Intermediate level
Some related experience required
5 hours to complete
3 weeks at 1 hour a week
Flexible schedule
Learn at your own pace
Skills you'll gain
Details to know
Shareable certificate
Add to your LinkedIn profile
Assessments
3 assignments
Taught in English
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This course is part of the Ethics in the Age of AI Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 4 modules in this course
Welcome to the capstone! Get to know a little bit about the projects we will be tackling in this section
What's included
1 video
Examining bias in a predictive text model
What's included
1 reading1 assignment
Understanding fairness issues with sensitive predictions
What's included
1 reading1 assignment
Predicting ethical issues before they arise in model theory
What's included
1 reading1 assignment
Instructor
Instructor ratings
4.5 (88 ratings)Offered by
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5
Reviewed on Jan 28, 2024
AI ethics often involve considerations such as fairness, transparency, accountability, privacy, bias mitigation, and the impact of AI on society.
ET
4
Reviewed on Feb 3, 2025
Insightful course with practical use cases for analysis.
Recommended if you're interested in Data Science
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