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Human Factors in AI
  • Level Foundation
  • Duration 17 hours
  • Course by Duke University
  • Offered by

About

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

Modules

Course Overview

    • 3 Videos
    • 1 Readings
    • 1 Discussion
Show info about module content

1 Discussions

  • Introductions (Optional)

3 Videos

  • Specialization Overview
  • Instructor Introduction
  • Course Overiew

1 Readings

  • About the Course

Designing AI Products

    • 3 Videos
    • 3 Readings
    • 1 Discussion
Show info about module content

1 Discussions

  • Task Analysis Example

3 Videos

  • Introduction and Objectives
  • Design Thinking
  • Task Analysis

3 Readings

  • Download Module Slides
  • An Introduction to Design Thinking Process Guide
  • Human-Centered Machine Learning

AI Product User Interface Considerations

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

1 Discussions

  • The Cold Start Problem

5 Videos

  • AI User Experience Design Considerations
  • User Inputs
  • Transparency
  • Communicating Uncertainty
  • Feedback Loops

1 Readings

  • ML has uncertainty. Design for it.

Review

    • 1 Videos
    • 1 Assignment
Show info about module content

1 Assignment

  • Module 1 Quiz

1 Videos

  • Module Wrap-up

Protecting Data Privacy

    • 5 Videos
    • 2 Readings
    • 1 Discussion
Show info about module content

1 Discussions

  • HIPAA

5 Videos

  • Introduction and Objectives
  • Introduction to Data Privacy
  • Fair Information Practices (FIPs)
  • U.S. Privacy Regulation
  • E.U. General Data Protection Regulation (GDPR)

2 Readings

  • Download Module Slides
  • Your apps know where you were last night. And they're not keeping it a secret

Privacy and AI

    • 2 Videos
    • 1 Readings
Show info about module content

2 Videos

  • Privacy Challenges in AI
  • Protecting Privacy in AI

1 Readings

  • Federated Learning: Building better products with on-device data and privacy by default

Review

    • 1 Videos
    • 1 Assignment
Show info about module content

1 Assignment

  • Module 2 Quiz

1 Videos

  • Module Wrap-up

Ethics and Bias

    • 3 Videos
    • 2 Readings
    • 1 Discussion
    • 1 Plugin
Show info about module content

1 Discussions

  • Sources of bias

3 Videos

  • Introduction and Objectives
  • Fair, Accountable & Transparent AI
  • Types & Sources of Bias

2 Readings

  • Download Module Slides
  • Machine Bias

Mitigating Ethical Risks

    • 2 Videos
    • 1 Readings
Show info about module content

2 Videos

  • Mitigating Potential Ethical Risks
  • Detecting & Resolving Fairness Issues

1 Readings

  • Datasheets for Datasets

Review

    • 1 Videos
    • 1 Assignment
Show info about module content

1 Assignment

  • Module 3 Quiz

1 Videos

  • Module Wrap-up

Human - AI Collaboration

    • 3 Videos
    • 2 Readings
    • 1 Discussion
Show info about module content

1 Discussions

  • AI augmentation of human decision-making

3 Videos

  • Introduction and Objectives
  • AI and Human Intelligence
  • Automation vs. Augmentation

2 Readings

  • Download Module Slides
  • Cognitive Collaboration: Why Humans and Computers Think Better Together

AI Product Adoption

    • 2 Videos
Show info about module content

2 Videos

  • Inspiring Model Trust
  • Change Management

Review

    • 1 Videos
    • 1 Assignment
Show info about module content

1 Assignment

  • Module 4 Quiz

1 Videos

  • Module Wrap-up

Course Wrap Up

    • 1 Videos
    • 1 PeerReview
Show info about module content

1 Peer Review

  • Course Project

1 Videos

  • Course Wrap-up

Auto Summary

Discover the essential human elements in AI development with "Human Factors in AI," the final installment of Duke University's Pratt School of Engineering AI Product Management Specialization. This course delves into human-centered design and user experience tailored for AI products, emphasizing ethical considerations and data privacy. You'll explore strategies to identify and mitigate biases, ensuring fairness in AI systems. Additionally, the course highlights the synergy between human and artificial intelligence, focusing on the dual roles of AI in automating and supporting human decision-making. Guided by Coursera, this foundational level course spans 17 hours and offers both Starter and Professional subscription options. It's perfect for those in data science and AI looking to build AI systems that enhance human intelligence and foster user trust.

Jon Reifschneider
Instructor

Jon Reifschneider