Data Ethics: Watching Out for Data Misuse
58mBeginner2021-06-16
Authors

Doug Rose
Teaching Fortune 500s and professionals how to lead change
Course details
Technology has given organizations an opportunity to work with data in interesting new ways, but now governments, citizens, and customers are taking a close look at how companies use or misuse data. If one of your customers posts harmful information, should you take it down? Can you use data to manipulate your customer’s behavior? The answers to these questions have an enormous impact on how your customer views your organization. Yet, these decisions aren’t happening in the boardroom. Instead, they’re made in much smaller meetings by people just like you. Instructor Doug Rose gives you the understanding and skills you need to discuss these issues in a way that's both meaningful and productive. Doug begins with ethical views that you need to consider. He goes over ways data can be misused, by a company and by a customer. Then Doug goes over the responsibility to be accurate and what you can do when inaccurate materials are propagated. He concludes with an overview of data challenges. This course was created for LinkedIn Learning by Doug Rose. We are pleased to offer this training in our library.
Skills covered
Data GovernanceData PrivacyData ScienceOne-Off
Concepts
0. Introduction
- 01 - Data accuracy and misuse
1. Thinking about Ethics
- 02 - What are your ethical duties
- 03 - Do the ends justify the means
- 04 - How to be a virtuous organization
- 05 - Create an ethical contract
2. Data Misuse
- 06 - Data misuse
- 07 - When your customer misuses the data
- 08 - Is it ethical to micro-target
- 09 - Can you exploit human needs
- 10 - How to ethically engage your customer
- 11 - Should you promote democracy
3. Accuracy
- 12 - What does it mean to be accurate
- 13 - Should you present the truth
- 14 - What to do with fake news
- 15 - What to do if your customer spreads propaganda
- 16 - The danger of too much accuracy
4. Data Models
- 17 - What are data models
- 18 - Your customer could game the system
Conclusion
- 19 - Next steps
Related courses
- Data Ethics: Managing Your Private Customer Data
- Data Ethics: Making Data-Driven Decisions
- Data Equity: Ensuring Fair Representation in AI Data Sets
- Data Literacy: Exploring and Describing Data
- Synthetic Data as the Future of AI Privacy, Explainability, and Fairness: An Introduction for Data Scientists and Data Executives
- Analyzing Data with an Equity Lens
- Decision Intelligence: Data Stories
- LinkedIn Learning Highlights: Data Science and Analytics
Related learn paths
- Mastering Data Governance and Ethics
- Introduction to Fundamental Skills for Data Work: Data Management
- Introduction to Fundamental Skills for Data Work: Data Strategy and Planning
- Become a Data Scientist
- Become a Business Intelligence Specialist
- Become a Data Analyst
- Build Essential Data Skills
- Develop Your Data Analysis Skills