AI 2040: Plan A
A longform scenario dubbed “AI 2040: Plan A” imagines rapid progress toward superhuman AI and proposes a US–China-led regime to cap frontier models, tightly regulate compute, and keep research transparent. Commenters are sharply split between those who see coordinated limits as necessary to avoid extinction or authoritarian misuse, and those who argue such controls are unrealistic, risk entrenching a small set of corporations and governments, or underestimate how often grand AI predictions have failed. Along the way they debate historical precedents for self-restraint in dangerous technologies, fears around mass unemployment and centralization of power, and whether present-day concerns over data centers, water use, and regulation are being amplified for geopolitical ends.
Pausing AI and Governance
- Many doubt a deliberate US–China pause at “top human genius” levels is politically or economically realistic; too much money and strategic advantage at stake.
- Some argue any pause would come from populist backlash against tech companies (jobs, inequality, surveillance), not from abstract safety concerns.
- Others warn that relying on misinformation (e.g., exaggerated water use) as a tactical ally is dangerous and morally dubious.
Historical Precedents for Restraint
- Several examples cited: bans on guns in historical Japan, Asilomar self‑moratorium on recombinant DNA, strong norms against human germline editing, biological and thermonuclear weapons limits, and partial success of the Biological Weapons Convention.
- Skeptics note such regimes are leaky (e.g., Soviet bioweapons) and question whether they scale to widely accessible AI.
Open vs Centralized AI Control
- One camp fears that strict regulation would entrench governments and a few firms, increasing authoritarian misuse and regulatory capture.
- Another camp fears that without strong constraints on large data centers and chip flows, covert or monopolistic projects will dominate and disempower the public.
- There is support for openness of ideas and models, but tension over open‑weights vs safety and misuse (e.g., bio, cyber).
Economic, Labor, and Robotics Forecasts
- Some see AI agents already doing “PhD‑level” tasks, predicting rapid substitution of cognitive and eventually physical labor, large robot populations, and high unemployment.
- Others argue physical-world automation is much harder; package‑delivery robots and drones remain limited, and 95% task coverage or 74% unemployment by 2035 are seen as implausible.
- Historical automation is cited as having failed to create mass unemployment so far, with counter‑arguments that speed and scale this time may be different.
Scaling, Trajectories, and Technical Uncertainty
- Debate over whether LLM progress is on an S‑curve plateau vs continuing exponential: some see clear capability jumps (especially in agents), others see marginal gains.
- Some insist transformers fundamentally lack memory, judgment, and legal personhood; others point to active work on long‑term memory and continual learning.
Compute, Datacenters, and Local Impacts
- Forecasts of $100T+ GPU build‑out are widely mocked as economically impossible.
- Datacenters are framed by critics as extractive “post‑industrial mines” (land, water, noise, power; profits exported), with locals seeing few benefits.
- Supporters respond that energy build‑out, better regulation, and increased chip supply could mitigate many concerns.
Geopolitics and China/US Dynamics
- Some view mutual verification on chips and datacenters as feasible (analogy to Cold War arms control); others doubt tracking coverage and Chinese compliance.
- There is pushback on perceived US‑centric framing and “jingoism,” and disagreement over whether China will out‑innovate or follow the US in export controls.
Critiques of Plan A as a Scenario
- Several commenters see Plan A as heavily speculative, overconfident about AGI/ASI inevitability, and narrowly focused on a few outcomes that justify strong regulation.
- Others praise it as the most realistic optimistic takeoff scenario so far, especially for addressing both alignment risk and power concentration, even if timelines and numbers may be off.