Pith Number

pith:RGZJ3PUN

pith:2026:RGZJ3PUNJOIMHAGEXHGI7HWPO2

not attested not anchored not stored refs pending

Bounded by Risk, Not Capability: Quantifying AI Occupational Substitution Rates via a Tech-Risk Dual-Factor Model

Minghao Huang (aSSIST University, Seoul, Shuyao Gao, South Korea)

AI occupational substitution is bounded by institutional risk and liability rather than technical capability alone.

arxiv:2604.04464 v2 · 2026-04-06 · cs.CY · econ.GN · q-fin.EC

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\pithnumber{RGZJ3PUNJOIMHAGEXHGI7HWPO2}

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Record completeness

1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

Non-routine cognitive roles highly dependent on symbolic manipulation (e.g., Data Scientists) face unprecedented exposure (OAI ≈ 0.70). Conversely, unstructured physical trades and high-stakes caretaking roles exhibit absolute resilience, quantifying a profound 'Cognitive Risk Asymmetry.'

C2weakest assumption

That a multi-agent LLM ensemble combined with variance-based expert validation can reliably quantify both technical feasibility and the 'institutional premium' of professional liability across 2,087 detailed work activities without systematic bias in the scoring process.

C3one line summary

AI job substitution rates are limited by business risks such as liability and compliance rather than technical capability alone, resulting in high exposure for cognitive roles like data scientists and resilience for physical trades.

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-06-09T01:04:42.576387Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

89b29dbe8d4b90c380c4b9cc8f9ecf76a7e134737bf737ef8fb4d2624a4df098

Aliases

arxiv: 2604.04464 · arxiv_version: 2604.04464v2 · doi: 10.48550/arxiv.2604.04464 · pith_short_12: RGZJ3PUNJOIM · pith_short_16: RGZJ3PUNJOIMHAGE · pith_short_8: RGZJ3PUN

Agent API

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/RGZJ3PUNJOIMHAGEXHGI7HWPO2 \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 89b29dbe8d4b90c380c4b9cc8f9ecf76a7e134737bf737ef8fb4d2624a4df098

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "d63aa2767a3c3a78464ab1d5bf7b9ff03128520498a67382fdb15a3b53fab0ee",
    "cross_cats_sorted": [
      "econ.GN",
      "q-fin.EC"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.CY",
    "submitted_at": "2026-04-06T06:21:08Z",
    "title_canon_sha256": "acab6e94a0628f6a8a8bb8c3b2d2292bc1b054b5858c089bd41d804449679525"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2604.04464",
    "kind": "arxiv",
    "version": 2
  }
}