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Coursera

Detect and Mitigate Ethical Risks

CertNexus via Coursera

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Overview

Data-driven technologies like AI, when designed with ethics in mind, benefit both the business and society at large. But it’s not enough to say you will “be ethical” and expect it to happen. We need tools and techniques to help us assess gaps in our ethical behaviors and to identify and stop threats to our ethical goals. We also need to know where and how to improve our ethical processes across development lifecycles. What we need is a way to manage ethical risk. This third course in the Certified Ethical Emerging Technologist (CEET) professional certificate is designed for learners seeking to detect and mitigate ethical risks in the design, development, and deployment of data-driven technologies. Students will learn the fundamentals of ethical risk analysis, sources of risk, and how to manage different types of risk. Throughout the course, learners will learn strategies for identifying and mitigating risks. This course is the third of five courses within the Certified Ethical Emerging Technologist (CEET) professional certificate. The preceding courses are titled Promote the Ethical Use of Data-Driven Technologies and Turn Ethical Frameworks into Actionable Steps.

Syllabus

  • Ethical Risk Analysis Fundamentals
    • The first module in the course lays the groundwork for some concepts that are fundamental to data-driven technologies like artificial intelligence (AI). As an ethicist, you may not be putting these concepts into practice yourself, but you still need to understand them. That way, you'll be able to make more informed judgments and communicate with other people about how best to detect and mitigate ethical risks.
  • Manage Privacy Risks
    • This module begins a series of modules in which you'll manage the many different types of ethical risks involved in data-driven technologies. First, you'll learn more about the risks to users' privacy and private data.
  • Manage Accountability Risks
    • This module continues the series of modules in which you'll manage the many different types of ethical risks involved in data-driven technologies. Now, you'll tackle the risks to the organization's accountability.
  • Manage Transparency and Explainability Risks
    • This is the next module in the ongoing series of modules in which you'll manage the many different types of ethical risks involved in data-driven technologies. Next up are the related concepts of transparency and explainability.
  • Manage Fairness and Non-Discrimination Risks
    • This is the penultimate module in the ongoing series of modules in which you'll manage the many different types of ethical risks involved in data-driven technologies. Here, you'll focus on managing risks to fairness and non-discrimination (bias).
  • Manage Safety and Security Risks
    • This is the final module in the series of modules in which you'll manage the many different types of ethical risks involved in data-driven technologies. Lastly, you'll address risks to both safety and security.
  • Apply What You've Learned
    • You'll work on one or more projects in which you'll apply your knowledge of the material in this course to practical scenarios.

Taught by

Renée Cummings, Jennifer Fischer and Eleanor 'Nell' Watson

Reviews

4.5 rating at Coursera based on 86 ratings

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