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January 28, 2025
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This course is part of AI Product Management Specialization
Instructor: Jon Reifschneider
13,950 already enrolled
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(112 reviews)
Recommended experience
Beginner level
No prior experience in AI or programming required
(112 reviews)
Recommended experience
Beginner level
No prior experience in AI or programming required
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
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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.
At the conclusion of this course, you should be able to: 1) Identify and mitigate privacy and ethical risks in AI projects 2) Apply human-centered design practices to design successful AI product experiences 3) Build AI systems that augment human intelligence and inspire model trust in users
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.
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.
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.
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.
7 videos2 readings1 assignment1 peer review1 discussion prompt
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
Duke University has about 13,000 undergraduate and graduate students and a world-class faculty helping to expand the frontiers of knowledge. The university has a strong commitment to applying knowledge in service to society, both near its North Carolina campus and around the world.
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Reviewed on Jan 19, 2025
Good concept on how to handler the AI and there ehtics and use case
Reviewed on Sep 16, 2023
It is an excellent course for anyone in the Data Science field.
Reviewed on Sep 25, 2024
Well structured, very good presenter, training material perfect. Benchmark for a highly effective course!
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Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
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