Let's start with a quick recap. We've seen how confirmation bias can lead us to cherry-pick data, and how mishandling personal information can break trust and create risk.
Applying ethical frameworks means consciously checking for both bias and privacy issues before, during, and after an analysis.
Engagement Message
What's one way you can build an "ethics check" into your workflow?
Type
Swipe Left or Right
Practice Question
Let's recap bias detection. Swipe left for scenarios showing confirmation bias, and right for those showing objective analysis.
Labels
- Left Label: Confirmation Bias
- Right Label: Objective Analysis
Left Label Items
- Only interviewing users who love the new feature
- Ignoring data that contradicts your initial hypothesis
- Presenting only the charts that support your conclusion
- Focusing on a single metric that makes your project look good
Right Label Items
- Actively seeking data that could disprove your theory
- Analyzing both successful and failed marketing campaigns
- Giving equal weight to all customer feedback segments
- Reporting on both positive and negative results
Type
Sort Into Boxes
Practice Question
Now, let's review privacy principles. Sort these practices into the correct ethical category.
Labels
- First Box Label: Good Practice
- Second Box Label: Bad Practice
First Box Items
- Anonymizing data
- Getting user consent
- Data minimization
- Aggregating results
Second Box Items
