Duke University

Human Factors in AI

This course is part of AI Product Management Specialization

Taught in English

Some content may not be translated

Jon Reifschneider

Instructor: Jon Reifschneider

9,015 already enrolled

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Course

Gain insight into a topic and learn the fundamentals

4.7

(66 reviews)

Beginner level

Recommended experience

17 hours (approximately)
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

Details to know

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Assessments

4 quizzes

Course

Gain insight into a topic and learn the fundamentals

4.7

(66 reviews)

Beginner level

Recommended experience

17 hours (approximately)
Flexible schedule
Learn at your own pace

See how employees at top companies are mastering in-demand skills

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Build your subject-matter expertise

This course is part of the AI Product Management Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate
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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 quiz3 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 quiz1 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 quiz1 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 quiz1 peer review1 discussion prompt

Instructor

Instructor ratings
4.8 (23 ratings)
Jon Reifschneider
Duke University
3 Courses40,621 learners

Offered by

Duke University

Recommended if you're interested in Machine Learning

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4.7

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