Artificial intelligence removes constraints on software creation, triggering economic changes that ripple through labor markets, education, and public policy. This activity evaluates competing hypotheses about AI's economic impact and maps the resulting scarcities to international human rights provisions.
Period 1 — Hypothesis Evaluation
Seven hypotheses attempt to explain AI's economic impact. Your group will evaluate each one against the provided evidence and determine which survive scrutiny.
| Hypothesis | Core Claim | Your Group's Verdict |
|---|---|---|
| H1: Productivity Multiplier | AI doubles developer output | |
| H2: Constraint Removal | Near-zero marginal software labor cost unblocks new activity | |
| H3: Jevons Explosion | Cheaper software triggers demand expansion beyond labor savings | |
| H4: Bottleneck Migration | Removing one constraint reveals the next — value shifts, not disappears | |
| H5: Recursive Acceleration | AI improves itself in a self-reinforcing cycle | |
| H6: Quality Erosion | More AI-generated output correlates with lower average quality | |
| H7: Bifurcated Economy | Uneven adoption creates widening gaps between adopters and non-adopters |
Key evidence to consider:
- METR RCT: experienced developers slowed 19% using AI on real projects
- Faros AI: 75% of organizations report no measurable productivity gains
- Anthropic estimate: 1.8% annualized U.S. labor productivity increase
- Deloitte: only 34% of organizations deeply transform around AI
Period 2 — The Four Scarcities
When AI removes the labor constraint on software creation, bottlenecks migrate toward human capacities. Four scarcities define the post-constraint economy. Map each scarcity to the ICESCR article it connects to.
| Scarcity | Question It Answers | Your ICESCR Article Match |
|---|---|---|
| Judgment | "Does this work?" | |
| Specification | "What should we build?" | |
| Attention | "Which of a million options?" | |
| Energy | Physical substrate for compute |
Key question: Which of these scarcities can education address? Which ones fall outside legal reach?
Period 3 — The Judgment-Diffusion Paradox
Technology diffuses rapidly, but judgment develops slowly — through practice, mentorship, and accumulated context. If AI eliminates entry-level positions where people develop judgment, the economy faces a pipeline break: abundant AI capability with shrinking human capacity to direct it.
Your task: Design a policy proposal that addresses this paradox. Your proposal should:
- Connect to at least one specific ICESCR article
- Address how judgment develops when entry-level work changes
- Consider implementation challenges (the ADA pattern suggests 10-20 years from policy to genuine change)
- Acknowledge what your proposal cannot solve
[Your policy proposal — use additional paper as needed]