Ethics in the Age of AI Specialization

What's the ethical impact of AI making decisions?. Learn how to impose ethical behavior on machine models.

Instructor: Brent Summers

What you'll learn

  •   Define predictive models and analyze how companies use them
  •   Identify how learning algorithms are used in everyday life
  •   Examine the ability of algorithms to influence and decide human behavior in biased ways, and methods to avoid predictive bias
  •   Identify vulnerabilities in public data sets and analyze algorithmic privacy violations

    • Skills you'll gain

  •   Machine Learning
  •   Artificial Intelligence
  •   Game Theory
  •   Predictive Modeling
  •   Data Collection
  •   Large Language Modeling
  •   Machine Learning Algorithms
  •   Business Ethics
  •   Algorithms
  •   Artificial Intelligence and Machine Learning (AI/ML)
  •   Data Ethics
  •   Ethical Standards And Conduct

    • Specialization - 4 course series

    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.

    We live in an age increasingly dominated by algorithms. As machine learning models begin making important decisions based on massive datasets, we need to be aware of their limitations in the real world. Whether it's making loan decisions or re-routing traffic, machine learning models need to accurately reflect our shared values. In this course, we will explore the rise of algorithms, from the most basic to the fully-autonomous, and discuss how to make them more ethically sound.

    In this course, we will explore fundamental issues of fairness and bias in machine learning. As predictive models begin making important decisions, from college admission to loan decisions, it becomes paramount to keep models from making unfair predictions. From human bias to dataset awareness, we will explore many aspects of building more ethical models.

    In this course, we will explore fundamental concepts involved in security and privacy of machine learning projects. Diving into the ethics behind these decisions, we will explore how to protect users from privacy violations while creating useful predictive models. We will also ask big questions about how businesses implement algorithms and how that affects user privacy and transparency now and in the future.

    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 Data Fairness and Bias

    Artificial Intelligence Privacy and Convenience

    Artificial Intelligence Ethics in Action

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