Data Ethics: Managing Your Private Customer Data
1h 6mBeginner2019-11-26
Authors

Doug Rose
Teaching Fortune 500s and professionals how to lead change
Course details
Technology provides businesses with real insight into customer’s thoughts, desires, and behaviors. But this unprecedented access can pose real ethical dilemmas. Can you sell customer data to other companies? Can you charge different customers more for the same product? The answers will define your organization. Yet many of these decisions aren’t happening in the boardroom. Instead they’re made in much smaller meetings with people just like you—project managers, business analysts, directors, and software developers. This course gives you the skills you need to make the right decisions. Instructor Doug Rose helps you consider the duties you have to your customer, think about the consequences of your actions, and maintain high employee morale as you wrestle with these key data ethics challenges.
Learning objectives
Define data ethics.
Define and compare relativism and objectivism.
Explore deontological ethics examples.
Explore utilitarian ethics examples.
Define and explore the concept of affinity privacy.
Define and explore data provenance.
Learning objectives
Define data ethics.
Define and compare relativism and objectivism.
Explore deontological ethics examples.
Explore utilitarian ethics examples.
Define and explore the concept of affinity privacy.
Define and explore data provenance.
Skills covered
Data GovernanceData PrivacyLearningData Science
Concepts
0. Introduction
- 01 - Data ethics for business
1. Thinking about Ethics
- 02 - The definition of data ethics
- 03 - Ethical relativism vs. objectivism
- 04 - Deontology
- 05 - Utilitarianism
- 06 - Ethics in ransomware
- 07 - The seven major data ethics challenges
2. Privacy
- 08 - The history of privacy
- 09 - Public vs. private data
- 10 - Individual privacy
- 11 - Group privacy
- 12 - Think about affinity privacy
- 13 - Discuss privacy in meetings
3. Data Ownership
- 14 - Who owns user data
- 15 - Think about data provenance
- 16 - The Internet of Things (IoT)
- 17 - Can you sell customer data
- 18 - Big Data
- 19 - Devices sharing data with one another
Conclusion
- 20 - Next steps
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