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1. Overview of Catastrophic AI Risks
0.1
Preface
1.1
Overview of Catastrophic AI Risks
1.2
Malicious Use
1.3
AI Race
1.4
Organizational Risks
1.5
Rogue AIs
1.6
Discussion of Connections Between Risks
2. AI Fundamentals
2.1
AI Fundamentals
2.2
Artificial Intelligence & Machine Learning
2.3
Deep Learning
2.4
Scaling Laws
2.5
Conclusion
3. Single Agent Safety
3.1
Single Agent Safety
3.2
Monitoring
3.3
Robustness
3.4
Alignment
3.5
Systemic Safety
3.6
Safety and General Capabilities
3.7
Conclusion
4. Safety Engineering
4.1
Safety Engineering
4.2
Risk Decomposition
4.3
Nines of Reliability
4.4
Safe Design Principles
4.5
Component Failure Accident Models and Methods
4.6
Systemic Factors
4.7
Tail Events and Black Swans
4.8
Conclusion
5. Complex Systems
5.1
Complex Systems
5.2
Introduction to Complex Systems
5.3
Complex Systems for AI Safety
5.4
Conclusion
6. Beneficial AI and Machine Ethics
6.1
Beneficial AI and Machine Ethics
6.2
Law
6.3
Fairness
6.4
The Economic Engine
6.5
Wellbeing
6.6
Preferences
6.7
Happiness
6.8
Social Welfare Functions
6.9
Moral Uncertainty
7. Collective Action Problems
7.1
Collective Action Problems
7.2
Game Theory
7.3
Cooperation
7.4
Conflict
7.5
Evolutionary Pressures
7.6
Conclusion
8. Governance
8.1
Governance
8.2
Timelines
8.3
Distribution
8.4
Compute Governance
8.5
Corporate Governance
8.6
National Governance
8.7
International Governance
8.8
Conclusion
9. Appendices
9.1
Acknowledgements
10.1
App. A: Normative Ethics
11.1
App. B: Utility Functions
12.1
App. C: Reinforcement Learning
13.1
App. D: Long-Tailed and Thin-Tailed Distributions
14.1
App. E: Evolutionary Game Theory
15.1
App. F: Other Cooperation Mechanisms
16.1
App. G: Intrasystem Conflict Causes
All
Section
Appendix
6.9

Moral Uncertainty

There are many situations where there may be conflicting moral considerations. AI systems' decisions should be able to take account of moral uncertainty. To ensure that they do this effectively, AI systems could potentially simulate a moral parliament representing important moral views or stakeholders.

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Review Questions

What is moral uncertainty? Why does it matter for moral decision making?

Answer:

Moral uncertainty refers to not knowing which moral beliefs are correct. It matters because different views can conflict; without resolving these conflicts, we cannot know how to act morally.

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Why is it important to address moral uncertainty when developing AI systems?

Answer:

AI systems should represent moral uncertainty to avoid acting on overconfidence, which could lead to outcomes that humans consider morally reprehensible.

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What are some potential advantages of using a moral parliament over hard-coding values into an AI?

Answer:

This could make an AI system more adaptable to changing values over time, encourage compromising options rather than fanatical ones, and provide transparency into AI reasoning.

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0.1
1.1
1.2
1.3
1.4
1.5
1.6
2.1
2.2
2.3
2.4
2.5
3.1
3.2
3.3
3.4
3.5
3.6
3.7
4.1
4.2
4.3
4.4
4.5
4.6
4.7
4.8
5.1
5.2
5.3
5.4
6.1
6.2
6.3
6.4
6.5
6.6
6.7
6.8
6.9
7.1
7.2
7.3
7.4
7.5
7.6
8.1
8.2
8.3
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8.5
8.6
8.7
8.8
9.1
10.1
11.1
12.1
13.1
14.1
15.1
16.1
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