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LinkedIn Learning

Data Ethics: Making Data-Driven Decisions

via LinkedIn Learning

Overview

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Learn how to design computer algorithms to be more ethical when making complex decisions.

Syllabus

Introduction
  • Ethical decisionmaking
1. Thinking about ethics
  • Being a moral company
  • How to approach ethics
  • Start with ethical objectivism
  • Think about your categorical imperatives
  • What would a virtuous person do?
  • The seven major data ethics challenges
2. Decision Traceability
  • The right to algorithmic traceability
  • Data accessibility and comprehensibility
  • Can anyone access their data?
  • Trace your black box decisions
  • Open the box with Explainable AI (XAI)
  • Self-driving cars' trolley problem
  • Decide how to crash a self-driving car
3. Objectivity
  • What does data objectivity mean?
  • Ways to think about bias
  • How to fix data bias
  • Can data be objective?
  • What is fairness?
Conclusion
  • Next steps

Taught by

Doug Rose

Reviews

4.6 rating at LinkedIn Learning based on 572 ratings

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