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Ethics in AI and Big Data

Learn how to build and incorporate ethical frameworks in your AI and Big Data technology and business initiatives to add transparency, build trust, and drive adoption.

There is one session available:

6,427 already enrolled! After a course session ends, it will be archived.
Starts Jul 23
Ends Aug 20
Estimated 6 weeks
1–2 hours per week
Self-paced
Progress at your own speed
Free
Optional upgrade available

About this course

Skip About this course

No longer stuck in the fantasy world of science fiction, Artificial Intelligence (AI) today is a reality, and data is its fuel. It is a key component of the Fourth Industrial Revolution in which the physical, digital and biological worlds are being fused together in a way that will have a tremendous impact on our global culture and economy. While the Fourth Industrial Revolution brings along promises and opportunities, it also raises concerns about security, user privacy, data misuse, and more. People distrust artificial intelligence. It is the responsibility of business and data professionals to change that: add transparency, develop standards and share best practices to build trust and drive AI adoption.

Business and data professionals today need AI frameworks and methods to achieve optimal results while also being good technology and business stewards. This course will teach you why AI and Big Data ethics is so critical and how to apply ethical and legal frameworks to initiatives in the data and analytics profession. You'll explore practical approaches to data and analytics problems posed by work in AI, Big Data, and Data Science.

At a glance

  • Language: English
  • Video Transcript: English

What you'll learn

Skip What you'll learn
  • Discuss business drivers for AI, as well as business and societal dynamics at work in an AI world.
  • Discuss the key principles for building responsible AI, and learn what are the initial steps to take when planning your AI framework.
  • Understand what ethics means and how to apply it to AI.
  • Learn where to start, what considerations should inform your ethical framework, and what this framework should include.
  • Review pan-industry initiatives on ethical AI.
  • Discuss the drivers for open source to support AI.
  • Review the technical and non-technical implications of AI.
  • Welcome!
  • Chapter 1. Drivers for Data Science
  • Chapter 2. Overview of AI and Data Science Ethics
  • Chapter 3. Building Your Ethical AI Framework
  • Chapter 4. Open Source and AI
  • Chapter 5. Going Forward with AI
  • Final Exam (Verified track only)

About the instructors

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