Ai and Human-Decision Making

● Unit 1.
○ The nature of intelligence, in general: biological and artificial
○ The fundamental principles of human intelligence and the inferential cycle of knowledge
■ Human implicit and explicit induction, with an emphasis on causal judgment
■ Human deduction, with an emphasis on the use of causal knowledge
○ Similarities and differences between Human intelligence and the surface behavior of LLM-based AI: knowing them for knowing when to trust them.

● Unit. 2.
○ Single agent human decision making
■ Choice under certainty
■ Judgment under risk and uncertainty
■ Choice under risk and uncertainty
■ Prospect theory, nudging and boosting
■ Perceptual decision making
○ Human multi-agent decision making
■ Strategic interaction
■ Social decision making
○ Human - AI collaborative decision making


● Unit 3.
1. Understanding Rules
- Different Types of Rules
- The Dynamics of Rule Application
- The Essentials of Required Rules
2. The Nature and Function of Rules
- The Role of Constitutive and Regulatory Rules
- The Rationality Behind Norms
- Legal Principles vs. Rules
- Challenges in Rule Terminology
3. Language and Rules
- The Boundaries of Common Language in Rule Contexts
4. Generalization in Rule Application
- General Rules and Their Prescriptive Nature
5. Theoretical Underpinnings of Rules
- The Conceptual Basis for Adhering to Rules
- The Craft of Rule Development and Standardization
6. The Structure of Rule Systems
- The Stratification of Rule Layers
7. Rules as Guides
- How Rules Serve as Justifications
8. The Influence of Rules
- The Origin and Power of Normative Influence
- How Rules Gain Significance and Impact
- The Uneven Distribution of Rule Authority