---
type: claim
domain: ai-alignment
description: "TSMC manufactures ~92% of advanced logic chips, three companies produce all HBM, NVIDIA controls 60%+ of CoWoS allocation — this concentration makes compute governance tractable (few points to monitor) while creating catastrophic vulnerability (one disruption halts global AI development)"
confidence: likely
source: "Heim et al. 2024 compute governance framework, Chris Miller 'Chip War', CSET Georgetown chokepoint analysis, TSMC market share data, RAND semiconductor supply chain reports"
created: 2026-03-24
depends_on:
  - "compute export controls are the most impactful AI governance mechanism but target geopolitical competition not safety leaving capability development unconstrained"
  - "technology advances exponentially but coordination mechanisms evolve linearly creating a widening gap"
  - "optimization for efficiency without regard for resilience creates systemic fragility because interconnected systems transmit and amplify local failures into cascading breakdowns"
challenged_by:
  - "Geographic diversification (TSMC Arizona, Samsung, Intel Foundry) is actively reducing concentration"
  - "The concentration is an artifact of economics not design — multiple viable fabs could exist if subsidized"
secondary_domains:
  - collective-intelligence
  - critical-systems
---

# Compute supply chain concentration is simultaneously the strongest AI governance lever and the largest systemic fragility because the same chokepoints that enable oversight create single points of failure

The AI compute supply chain is the most concentrated critical infrastructure in history. A single company (TSMC) manufactures approximately 92% of advanced logic chips. Three companies produce all HBM memory. One company (ASML) makes the EUV lithography machines required for leading-edge fabrication. NVIDIA commands over 60% of the advanced packaging capacity that determines how many AI accelerators ship.

This concentration creates a paradox: the same chokepoints that make compute governance tractable (because there are few points to monitor and control) also create catastrophic systemic vulnerability (because disruption at any single point halts global AI development).

## The governance lever

Heim, Sastry, and colleagues at GovAI have established that compute is uniquely governable among AI inputs. Unlike data (diffuse, hard to track) and algorithms (abstract, easily copied), chips are physical, trackable, and produced through a concentrated supply chain. Their compute governance framework proposes three mechanisms: visibility (who has what compute), allocation (who gets access), and enforcement (compliance verification).

The concentration amplifies each mechanism:

- **Visibility:** With one dominant manufacturer (TSMC), tracking advanced chip production is tractable. You don't need to monitor thousands of fabs — you need to monitor a handful of facilities.
- **Allocation:** Export controls work because there are few places to export from. The October 2022 US semiconductor export controls leveraged TSMC, ASML, and applied materials' concentration to constrain China's AI compute access.
- **Enforcement:** Shavit (2023) proposed hardware-based compute monitoring. With concentrated manufacturing, governance mechanisms can be built into the chip at the design or fabrication stage (Fist & Heim, "Secure, Governable Chips").

This is the strongest argument for compute governance: the physical supply chain's concentration is a feature, not a bug, from a governance perspective.

## The systemic fragility

The same concentration that enables governance creates catastrophic risk. Three scenarios illustrate the fragility:

**Taiwan disruption.** TSMC fabricates ~92% of the world's most advanced chips in Taiwan. A military conflict, blockade, earthquake, or prolonged power disruption in Taiwan would immediately sever the global supply of AI accelerators. TSMC is building fabs in Arizona (92% yield achieved, approaching full utilization) but the most advanced processes remain Taiwan-first through at least 2027-2028. Geographic diversification is real but early.

**Packaging bottleneck cascade.** CoWoS packaging at TSMC is already the binding constraint on AI chip supply. If a disruption reduced CoWoS capacity by even 20%, the effect would cascade: fewer AI accelerators → delayed AI deployments → concentrated remaining supply among the biggest buyers → smaller organizations locked out entirely.

**Memory concentration.** All three HBM vendors are sold out through 2026. A production disruption at any one of them would reduce global HBM supply by 20-60% with no short-term alternative.

## The paradox

Governance leverage and systemic fragility are two faces of the same structural fact: concentration. You cannot have the governance benefits (tractable monitoring, effective export controls, hardware-based enforcement) without the fragility costs (single points of failure, catastrophic disruption scenarios). And you cannot reduce fragility through diversification without simultaneously reducing governance leverage.

This is a genuine tension, not a problem to solve. The optimal policy depends on which risk you weight more heavily: the risk of ungoverned AI development (favoring concentration for governance leverage) vs. the risk of supply chain disruption (favoring diversification for resilience).

The alignment field has largely focused on the governance side (how to control AI development) without accounting for the fragility side (what happens when the physical substrate fails). Both risks are real. The supply chain concentration that makes compute governance possible is the same concentration that makes the entire AI enterprise fragile.

## Connection to existing KB

This claim connects the alignment concern (governance) to the critical-systems concern (fragility). The foundational claim that [[optimization for efficiency without regard for resilience creates systemic fragility because interconnected systems transmit and amplify local failures into cascading breakdowns]] applies directly: the semiconductor supply chain has been optimized for efficiency (TSMC's scale advantages, NVIDIA's CoWoS allocation) without regard for resilience (no backup fabs, no alternative packaging at scale).

---

Relevant Notes:
- [[compute export controls are the most impactful AI governance mechanism but target geopolitical competition not safety leaving capability development unconstrained]] — export controls leverage the concentration this claim describes
- [[optimization for efficiency without regard for resilience creates systemic fragility because interconnected systems transmit and amplify local failures into cascading breakdowns]] — the semiconductor supply chain is a textbook case
- [[technology advances exponentially but coordination mechanisms evolve linearly creating a widening gap]] — physical infrastructure constraints partially compensate for this gap
- [[the alignment tax creates a structural race to the bottom because safety training costs capability and rational competitors skip it]] — supply chain concentration means the race is gated by physical infrastructure, not just investment willingness

Topics:
- [[domains/ai-alignment/_map]]
