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Putting Ethics Into Action
Lesson One: Ethics
Welcome - Course Introduction (7:21)
Instructor Introductions (3:43)
1. Lesson One Introduction (2:15)
2. Why does Ethics matter? (5:24)
2.1 Ethics as a Risk Mitigator (2:39)
2.2 Ethics as a Competitive Edge (4:53)
3. Understanding Ethical Frameworks (3:15)
3.1 Virtue Ethics (4:22)
3.2 Duty Ethics (3:22)
3.3 Consequential Ethics (4:20)
4. Ethical Framework Thought Experiment (2:49)
4.1 Quiz
5. Technical Thought Experiment (1:41)
5.1 Quiz
6. Closing Remarks (4:19)
7. Assignment
8. Further Reading
Lesson Two: Fairness and Bias
1. Lesson Two Introduction (3:41)
2. What "Eliminating Bias" Really Means (6:29)
3. Why Does Eliminating Negative Bias Matter: Principle of Discriminatory Non-Harm (3:04)
4. Identifying Bias and its Harms (5:22)
4.1 Allocation versus Representation Harm (4:49)
4.2 The Five Types of Harm (11:05)
5. Quiz - Identifying Harm
6. The Importance of Fairness (2:08)
6.1 Measuring Fairness; Technical (7:44)
6.2 Measuring Fairness; Non-technical (3:26)
7. Best Practices for Implementing Fairness (5:54)
8. Quiz - Identifying Best Practices
9. Closing remarks (2:27)
10. Assignment
11. Further Reading
Lesson Three: Privacy in the age of Big Data
1. Lesson Three Introduction (1:43)
2. Data as a Commodity (4:28)
3. Redefining Privacy in the Era of Tech (4:17)
4. GDPR and the Attempt to Regain Privacy (5:06)
5. Data Lifecycle: Pinpointing Privacy Risks (6:33)
6. Quiz
7. The "Sunlight Test" (3:15)
8. Closing remarks (2:12)
9. Assignment
10. Further Reading
Lesson Four: Accountability and Sustainability
1. Lesson Four Introduction (1:22)
2. Moral Responsibility: The Origin of Accountability (4:29)
3. The Accountability Gap (6:59)
4. Mind the Gap: Consequences of a Lack of Accountability (3:16)
5. Closing the Gap (1:22)
5.1 Anticipatory vs Remedial Accountability (3:27)
5.2 Internal vs External Auditing (3:36)
6. Quiz
7. Why Accountability and Sustainability Go Hand in Hand (2:24)
8. Sustainability and AI: Environmental Impact (1:49)
9. Stakeholder Impact Assessment (3:14)
10. Closing Remarks (1:14)
11. Assignment
12. Further Reading
Lesson Five: Trust and Transparency
1. Lesson Five Introduction (1:29)
2. In Tech We Trust (1:52)
2.1 What it Means to Trust (1:46)
2.2 Trusting an AI System (1:54)
3. How Transparency Helps Secure Trust (1:53)
3.1 Outcome Transparency (1:57)
3.2 Process Transparency (2:55)
4. Quiz
5. The Origin of the Black Box (3:55)
6. Explainability and AI Safety (2:59)
7. Looking into the Black Box: Technical (6:09)
8. Looking into the Black Box: Non-technical (3:06)
9. Closing Remarks (2:16)
10. Assignment
11. Further Reading
Lesson Six: AI Ethics Policies
1. Lesson Six Introduction (1:16)
2. International Policies on AI Ethics (2:46)
2.1. European Union: Ethics Guidelines for Trustworthy AI (4:42)
2.2. United Kingdom: The Guide to Using AI in the Public Sector (4:23)
2.3. China: Beijing AI Principles (3:19)
2.4. United States: American AI Initiative (2:34)
3. Comparing the Policies (4:33)
4. Quiz
5. Why the current policies don’t go far enough (2:11)
6. Legal vs Ethical (2:04)
7. Closing Remarks (1:19)
8. Assignment
9. Further Reading
End of Course - Final Remarks (1:07)
2.2. United Kingdom: The Guide to Using AI in the Public Sector
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