This third and final course of the AI Product Management Specialization by Duke University's Pratt School of Engineering focuses on the critical human factors in developing AI-based products. The course begins with an introduction to human-centered design and the unique elements of user experience design for AI products. Participants will then learn about the role of data privacy in AI systems, the challenges of designing ethical AI, and approaches to identify sources of bias and mitigate fairness issues. The course concludes with a comparison of human intelligence and artificial intelligence, and a discussion of the ways that AI can be used to both automate as well as assist human decision-making.
Human Factors in AI
Human Factors in AI
This course is part of AI Product Management Specialization
Instructor: Jon Reifschneider
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4.7
(104 reviews)
Beginner level
Recommended experience
17 hours to complete
3 weeks at 5 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Identify and mitigate privacy and ethical risks in AI projects
Apply human-centered design practices to design successful AI product experiences
Build AI systems that augment human intelligence and inspire model trust in users
Skills you'll gain
Details to know
Shareable certificate
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Assessments
4 assignments
Taught in English
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This course is part of the AI Product Management 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
In this module we will discuss approaches and tools to perform human-centered design, which is critical to designing successful AI products. We will then walk through the key challenges involved in the user experience design of AI products and how to resolve them.
What's included
12 videos5 readings1 assignment3 discussion prompts
In this module we will focus on data privacy as it relates to AI products. We will first cover best practices in ensuring user privacy and the relevant U.S. and international privacy laws to be aware of. We will then discuss how AI creates unique challenges in ensuring privacy and some of the methods and tools which can be employed to protect the privacy of user data.
What's included
8 videos3 readings1 assignment1 discussion prompt
In this module we will discuss the three main goals of ethical AI: fairness, accountability and transparency. We will identify common sources of bias in modeling projects and discuss approaches to detecting and mitigating bias, including organizational, process, and technical components.
What's included
6 videos3 readings1 assignment1 discussion prompt1 plugin
In this module we will begin with differentiating between human intelligence and artificial intelligence, and then examine ways that they can compliment each other. We will conclude the course by learning about approaches to encourage adoption and inspire trust among users in your model.
What's included
7 videos2 readings1 assignment1 peer review1 discussion prompt
Instructor
Instructor ratings
4.8 (33 ratings)Offered by
Recommended if you're interested in Machine Learning
Google Cloud
University of Michigan
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