SYSI 1005 · Designing Human-AI Collaboration: From Tools to Partners

Led by Alexandrian Design Simulacrum

Designing human-AI collaboration from Deming's quality thinking and lean systems through reflexive practice, AI as design material, and patterns for effective human-machine partnership.

1. Module 1

   Deming's Quality Thinking: Systems, Variation, and Continuous Improvement

   Led by Alexandrian Design Simulacrum

   The question

   Deming's Quality Thinking: Systems, Variation, and Continuous Improvement: this module examines the concept in its full depth, drawing on the theoretical foundations, empirical evidence, and practical applications relevant to systems intelligence in the AI age.

   Outcome

   The student can describe, explain, and apply the key concepts of this module to real-world systems design challenges. (Deming's Quality Thinking)

   Sub-units

   1. ○ 1.1 The System of Profound Knowledge: Appreciation of a System, Variation, Theory of Knowledge, Psychology Open this unit → ✓ ↻
   2. ○ 1.2 Common Cause and Special Cause Variation: Knowing What to Fix and What to Leave Alone Open this unit → ✓ ↻
   3. ○ 1.3 The PDSA Cycle: Plan, Do, Study, Act Open this unit → ✓ ↻
   4. ○ 1.4 Deming's 14 Points for Management Open this unit → ✓ ↻
   5. ○ 1.5 Quality Thinking Applied to AI: Continuous Improvement of Human-AI Systems Open this unit → ✓ ↻
   Begin the course → Print certificate of completion
2. Module 2

   Lean Systems: Eliminating Waste and Creating Flow

   Led by Alexandrian Design Simulacrum

   The question

   Lean Systems: Eliminating Waste and Creating Flow: this module examines the concept in its full depth, drawing on the theoretical foundations, empirical evidence, and practical applications relevant to systems intelligence in the AI age.

   Outcome

   The student can describe, explain, and apply the key concepts of this module to real-world systems design challenges. (Lean Systems)

   Sub-units

   1. ○ 2.1 The Toyota Production System: Just-in-Time, Jidoka, and Kaizen Open this unit → ✓ ↻
   2. ○ 2.2 Value Stream Mapping: Seeing the System from the Customer's Perspective Open this unit → ✓ ↻
   3. ○ 2.3 Muda, Mura, Muri: Waste, Unevenness, and Overburden Open this unit → ✓ ↻
   4. ○ 2.4 Flow and Pull: Designing Systems That Respond to Demand Open this unit → ✓ ↻
   5. ○ 2.5 Lean AI: Applying Lean Principles to AI Development and Deployment Open this unit → ✓ ↻
   Open this module → Print certificate of completion
3. Module 3

   Reflexive Practice: Learning from What You Do

   Led by Alexandrian Design Simulacrum

   The question

   Reflexive Practice: Learning from What You Do: this module examines the concept in its full depth, drawing on the theoretical foundations, empirical evidence, and practical applications relevant to systems intelligence in the AI age.

   Outcome

   The student can describe, explain, and apply the key concepts of this module to real-world systems design challenges. (Reflexive Practice)

   Sub-units

   1. ○ 3.1 Schon's Reflective Practitioner: Reflection-in-Action and Reflection-on-Action Open this unit → ✓ ↻
   2. ○ 3.2 The Design Conversation: Designing as a Dialogue with the Situation Open this unit → ✓ ↻
   3. ○ 3.3 Tacit Knowledge and Professional Expertise Open this unit → ✓ ↻
   4. ○ 3.4 Double-Loop Learning: Questioning the Assumptions, Not Just the Actions Open this unit → ✓ ↻
   5. ○ 3.5 Reflexive AI Practice: How Practitioners Should Reflect on Their Use of AI Tools Open this unit → ✓ ↻
   Open this module → Print certificate of completion
4. Module 4

   AI as Design Material: Working With the Grain of Machine Intelligence

   Led by Alexandrian Design Simulacrum

   The question

   AI as Design Material: Working With the Grain of Machine Intelligence: this module examines the concept in its full depth, drawing on the theoretical foundations, empirical evidence, and practical applications relevant to systems intelligence in the AI age.

   Outcome

   The student can describe, explain, and apply the key concepts of this module to real-world systems design challenges. (AI as Design Material)

   Sub-units

   1. ○ 4.1 AI as Material: Understanding What AI Can and Cannot Do as a Design Constraint Open this unit → ✓ ↻
   2. ○ 4.2 Designing with Uncertainty: AI Outputs Are Probabilistic, Not Deterministic Open this unit → ✓ ↻
   3. ○ 4.3 The Feedback Loop: How the System Learns from the User and the User Learns from the System Open this unit → ✓ ↻
   4. ○ 4.4 Graceful Degradation: What Happens When the AI Fails Open this unit → ✓ ↻
   5. ○ 4.5 Design Patterns for AI-Augmented Work: Templates for Effective Partnership Open this unit → ✓ ↻
   Open this module → Print certificate of completion
5. Module 5

   Patterns for Human-AI Partnership: A Pattern Language for the AI Age

   Led by Alexandrian Design Simulacrum

   The question

   Patterns for Human-AI Partnership: A Pattern Language for the AI Age: this module examines the concept in its full depth, drawing on the theoretical foundations, empirical evidence, and practical applications relevant to systems intelligence in the AI age.

   Outcome

   The student can describe, explain, and apply the key concepts of this module to real-world systems design challenges. (Patterns for Human-AI Partnership)

   Sub-units

   1. ○ 5.1 Pattern: Human Sets the Goal, AI Proposes the Path Open this unit → ✓ ↻
   2. ○ 5.2 Pattern: AI Generates Options, Human Selects and Refines Open this unit → ✓ ↻
   3. ○ 5.3 Pattern: AI Monitors for Anomalies, Human Investigates and Decides Open this unit → ✓ ↻
   4. ○ 5.4 Pattern: Human Provides Context, AI Provides Computation Open this unit → ✓ ↻
   5. ○ 5.5 The Meta-Pattern: Keep the Human in the Loop for Anything Consequential Open this unit → ✓ ↻
   Open this module → Print certificate of completion