Teach Compitum (Educator Guide)

Audience

  • Upper-undergraduate/graduate CS, data science, or AI ethics courses; technical managers learning cost-quality tradeoffs.

Learning Objectives

  • Interpret a routing certificate (utility components, constraints, boundary diagnostics, drift).

  • Explain utility U = performance - lambda * cost and willingness-to-pay (WTP).

  • Describe near-frontier behavior and why “close to optimal” can be valuable even without envelope wins.

  • Connect formal constraints to policy/compliance requirements.

Prerequisites

  • Comfortable with basic probability, optimization intuition, and Python. No deep ML required.

Before Class (10-15 min)

In-Class Activity (30-45 min)

  1. Certificate walk-through (10 min)

    • Run: compitum route --prompt "Sketch a proof for AM-GM inequality." --trace

    • Identify fields: utility_components, constraints.feasible, constraints.shadow_prices, boundary_analysis.gap.

  2. Cost-quality tradeoff (10-15 min)

    • Define U = performance - lambda * cost. Discuss how increasing lambda penalizes cost.

    • Show that different WTP slices (0.1 vs. 1.0) can change selections.

  3. Constraints as safety/policy hooks (10 min)

    • Map constraints to compliance (e.g., region limits). Interpret shadow prices: which limits “bind” the choice?

  4. Near-frontier behavior (5-10 min)

    • Discuss frontier gap with 95% CIs. Why being near-frontier can be enough when constraints are respected.

  5. Control of error (5-10 min)

    • Read: Pedagogy and Control of Error (first two sections). Connect “control of error” to the certificate.

    • Prompt: “Which certificate fields make mistakes legible at the moment of choice?”

    • Extension: Propose a small change to constraints or lambda and predict the effect; then test.

Assessment Ideas

  • Short quiz: define utility and WTP; interpret one certificate; explain shadow prices in one sentence.

  • Small assignment: change lambda and describe selection shifts.

Resources

Accessibility

  • Use the text description provided in Media: tess.mp4.

  • CLI outputs are JSON; screen-reader-friendly.

  • Keep slides high-contrast and avoid color-only cues.