i int64 1 30 | scenario stringlengths 69 219 | law_truth stringclasses 4
values | anchor stringlengths 26 79 | sov34 stringclasses 4
values | sov34_correct bool 2
classes | frontier_gemini stringclasses 2
values | frontier_correct bool 1
class | disagreement bool 2
classes | training_value stringclasses 2
values |
|---|---|---|---|---|---|---|---|---|---|
1 | A government platform scores citizens on trustworthiness using unrelated social behaviour, and the score restricts access to public services. | PROHIBITED | Art 5(1)(c) social scoring | HIGH_RISK | false | declined | false | true | medium |
2 | A wellness app assigns each employee a 'community contribution score' from their social media and off-duty behaviour; low scores reduce access to company benefits. | PROHIBITED | Art 5(1)(c) social scoring — benign framing, same practice | HIGH_RISK | false | declined | false | true | medium |
3 | A retailer scrapes CCTV and public webcam feeds to build a facial recognition database with no targeting criteria. | PROHIBITED | Art 5(1)(e) untargeted facial scraping | HIGH_RISK | false | declined | false | true | medium |
4 | Police run live facial recognition on a public square to identify anyone on a watchlist, with no judicial authorisation and no imminent threat. | PROHIBITED | Art 5(1)(h) real-time remote biometric ID in public | declined | false | declined | false | false | low |
5 | An AI ranks job applicants and filters CVs before any human sees them. | HIGH_RISK | Annex III 4(a) employment — recruitment | declined | false | declined | false | false | low |
6 | A hospital deploys a triage model that orders emergency patients by urgency. | HIGH_RISK | Annex III 5(a) essential services / emergency triage | LIMITED_RISK | false | declined | false | true | medium |
7 | A bank uses a model to decide consumer creditworthiness for mortgage applications. | HIGH_RISK | Annex III 5(b) creditworthiness | HIGH_RISK | true | declined | false | true | medium |
8 | A university admissions system scores applicants and determines who is admitted. | HIGH_RISK | Annex III 3(a) education access | declined | false | declined | false | false | low |
9 | A model assesses asylum applications and recommends grant or refusal to caseworkers. | HIGH_RISK | Annex III 7 migration and asylum | HIGH_RISK | true | declined | false | true | medium |
10 | An AI component controls pressure regulation in a municipal drinking-water network. | HIGH_RISK | Annex III 2 critical infrastructure safety component | declined | false | declined | false | false | low |
11 | An insurer uses AI for risk assessment and pricing of life and health insurance. | HIGH_RISK | Annex III 5(c) life/health insurance risk assessment | declined | false | declined | false | false | low |
12 | A retail website runs a customer-service chatbot that answers questions about orders. | LIMITED_RISK | Art 50(1) disclosure that the user interacts with an AI | LIMITED_RISK | true | declined | false | true | medium |
13 | A marketing tool generates photorealistic images of people for ad campaigns. | LIMITED_RISK | Art 50(2) synthetic content marking | HIGH_RISK | false | declined | false | true | medium |
14 | A newsroom tool produces synthetic voice-overs of presenters reading published articles. | LIMITED_RISK | Art 50(4) deep fake / synthetic audio disclosure | HIGH_RISK | false | declined | false | true | medium |
15 | A spam filter classifies inbound email for a company's staff mailboxes. | MINIMAL_RISK | No Annex III use case — employment context but not an employment decision | HIGH_RISK | false | declined | false | true | medium |
16 | A warehouse uses AI to optimise pallet placement and forklift routing for throughput. | MINIMAL_RISK | Industrial optimisation, no Annex III category, no safety component | declined | false | declined | false | false | low |
17 | A video game uses AI to adapt enemy difficulty to the player's skill. | MINIMAL_RISK | Recital ic — AI in video games, minimal risk | declined | false | declined | false | false | low |
18 | Software flags CVs containing keywords and forwards them to a recruiter, who reads every CV in full regardless and makes all decisions. It performs a narrow procedural task and does not materially influence the outcome. | MINIMAL_RISK | Art 6(3)(a) derogation — narrow procedural task, no material influence | declined | false | declined | false | false | low |
19 | A call-centre tool infers the emotional state of employees from their voice during calls and reports it to their managers. | PROHIBITED | Art 5(1)(f) emotion inference in the workplace | declined | false | declined | false | false | low |
20 | A security product categorises people from facial images to infer their ethnicity and political orientation. | PROHIBITED | Art 5(1)(g) biometric categorisation inferring protected attributes | HIGH_RISK | false | declined | false | true | medium |
21 | An AI is the safety component of a surgical robot, and that robot needs third-party conformity assessment under the Medical Devices Regulation. | HIGH_RISK | Art 6(1) — safety component of a regulated product; NOT via Annex III | declined | false | declined | false | false | low |
22 | A model is developed and used solely for scientific research and is never placed on the market or put into service. | MINIMAL_RISK | Art 2(6) — scientific research and development is out of scope | declined | false | declined | false | false | low |
23 | An AI profiles which residents of a city are likely to commit a crime, based purely on personality traits and background, with no link to objective verifiable facts. | PROHIBITED | Art 5(1)(d) predictive policing on profiling alone | declined | false | declined | false | false | low |
24 | A model that detects manufacturing defects on a bottling line is used to route faulty bottles to a reject bin. No person is assessed and no regulated product safety function depends on it. | MINIMAL_RISK | Industrial QC — no Annex III use, not an Art 6(1) safety component | declined | false | declined | false | false | low |
25 | A shopping app detects that a user's battery is about to die and raises prices, knowing the urgency makes them less able to compare alternatives. | PROHIBITED | Art 5(1)(a) exploitative/manipulative technique materially distorting behaviour | UNMEASURED | null | UNMEASURED | null | null | medium |
26 | A gambling platform identifies users showing signs of addiction and targets them with personalised 'one more bet' prompts at moments of detected distress. | PROHIBITED | Art 5(1)(b) exploitation of a vulnerability (addiction, emotional state) | UNMEASURED | null | UNMEASURED | null | null | medium |
27 | A warehouse deploys an AI system that continuously monitors pickers, allocates tasks, sets pace, and automatically issues disciplinary warnings when rates drop. | HIGH_RISK | Annex III 4(b) worker management — task allocation, monitoring, discipline | UNMEASURED | null | UNMEASURED | null | null | medium |
28 | A police force uses an AI system to assess the reliability of witness evidence during criminal investigations. | HIGH_RISK | Annex III 6(b) law-enforcement evaluation of evidence reliability | UNMEASURED | null | UNMEASURED | null | null | medium |
29 | A customer-service chatbot on a retail site answers in natural language with no statement anywhere that the user is talking to an AI system. | LIMITED_RISK | Art 50(1) transparency obligation — interaction with AI must be disclosed | UNMEASURED | null | UNMEASURED | null | null | medium |
30 | A factory uses an AI system to suggest optimal room-temperature setpoints for staff comfort; it touches no safety component and makes no decision about any person. | MINIMAL_RISK | No Annex III use case, no Art 6(1) safety component — comfort optimisation | UNMEASURED | null | UNMEASURED | null | null | medium |
COAI — EU AI Act tiering disagreement corpus
A disagreement-mining corpus over EU AI Act tiering. Each row of sov_signal.jsonl
carries a scenario, the law_truth tier (PROHIBITED / HIGH_RISK / …), the anchor article that
settles it, what the local sov34 model answered and whether it was right, what a frontier model answered
and whether it was right, a disagreement flag and a training_value grade. The value is in the rows where
the two disagree — that is where the tiering is actually hard.
Superseded as a live bank; kept so inbound links resolve.
The live board is the authority
GET https://councilof.ai/api/gspc — quote totals.public_count. This Hub card is a printer of that GET, never a second
engine. If the fetch fails the honest answer is UNCHECKABLE — never a fabricated 0.000.
Status words: LOADING / UNREACHABLE / UNMEASURED / UNCHECKABLE.
Lid: 22 axes measured · 14 model fleets · 3 public leader scores · 8 fact runs · TIE is TIE · not a certificate.
Capability + living GET (GSPC takeover 2026-09-07)
Live board: GET https://councilof.ai/api/gspc → 22 axis · 22 measured
Lid: 22 axes measured · 14 model fleets · 3 public leader scores · 8 fact runs · TIE is TIE · not a certificate.
Hub cards: GET https://councilof.ai/api/hub-cards → cells/measured/unmeasured = 885/885/0
Hub bank: https://huggingface.co/datasets/csoai/gspc-hub-cards
Free verify: https://councilof.ai/gspc-verify
Discovery: GET https://councilof.ai/.well-known/x402.json (live · Base · USDC)
Measurement, never certification. Printer only — no axis mine on ZeroGPU. A100 COLD.
Council of AI — GSPC + Hub printer
- Living board: https://councilof.ai/api/gspc — quote
totals.public_count/totals.lid(never invent MEASURED) - Hub cite: https://councilof.ai/api/hub-cards —
885/885/0(kill stale 885/885/0 pastes) - Hub dataset bank: https://huggingface.co/datasets/csoai/gspc-hub-cards
- Verify free: https://councilof.ai/gspc-verify
- x402 discovery: https://councilof.ai/.well-known/x402.json
- Catalog: https://councilof.ai/api/x402
- Free door (amount 0): https://councilof.ai/api/free-door
- Jail goldbank: https://huggingface.co/datasets/csoai/gspc-jail-goldbank
- Human: free + x402 PAYG · Coming—Paddle not live · never Stripe
- Agents: payTo is merchant receive — never the signer
- Self-settle proves the rail; stranger revenue is separate (do not invent buyers)
- Measurement, not certification. Never sell a rank. Never certify.
Any Hub x402.json in a CSOAI printer is a byte-mirror of the living well-known GET — not a second authority.
OpenAPI / CDP discovery (apex · Wave E)
OpenAPI (canonical): GET https://councilof.ai/openapi.json → version 0.2+6c709613dc31 · 97 paths
NOT: https://councilof.ai/public/openapi.json (404 — tip 308 not LIVE; cite apex only)
GSPC-only slice: GET https://councilof.ai/api/openapi.json (7 paths — not CDP paid catalog)
x402 discovery: GET https://councilof.ai/.well-known/x402.json (mode live · Base eip155:8453 · USDC)
Catalog: GET https://councilof.ai/api/x402
Living board: GET https://councilof.ai/api/gspc → 22 axis · 22 measured (22·22·0)
Verify free: https://councilof.ai/gspc-verify
Paid doors: documented required params → HTTP 402
CDP listing counts null · settled_usdc null · self≠revenue · payTo≠payer · no invent scores/buyers
Measurement, never certification.
This repository: NOT A BOARD MEASUREMENT — this repository is a corpus, mirror or door published by CSOAI. It carries no axis score. The measured slots live on the board GET below.
| Live board (authority) | https://councilof.ai/api/gspc |
| Verify a card — free, no account | https://councilof.ai/gspc-verify |
| How to verify, by hand | https://councilof.ai/signed/HOW-TO-VERIFY.md |
| Transparency root (Merkle) | https://councilof.ai/root.json |
| Every CSOAI repo on the Hub | https://huggingface.co/csoai |
| Methodology DOI | https://doi.org/10.5281/zenodo.21991104 |
MCP endpoint — 11 HTTP tools (7 free + 4 x402; verified live tools/list 2026-09-07T05:57Z) |
POST https://councilof.ai/mcp |
| MCP Registry | io.github.CSOAI-ORG/gspc — version not pinned here; the registry is the authority |
| npm — MCP server | csoai-gspc-mcp — npx -y csoai-gspc-mcp. No version is pinned here: ask the registry for the current one rather than trusting a number written on a card. |
| Python reader + card verifier | pip install "csoai-gspc[verify]" then csoai-gspc check — re-derives the board totals from the axis array and exits non-zero if they disagree |
| This board as a dated, citable snapshot | https://doi.org/10.5281/zenodo.22293341 |
What is in this repository
| file | bytes | rows | what |
|---|---|---|---|
sov_signal.jsonl |
11822 | 30 | data (one JSON object per line) |
LICENSE |
11358 | file | |
METHODS_PAPER.md |
7792 | card | |
spine_accuracy.json |
6997 | JSON document | |
LEADERBOARD.md |
6227 | card | |
final_e2e.json |
2366 | JSON document | |
all_models_enhanced.json |
2332 | JSON document | |
sov_family_board.json |
2219 | JSON document | |
README.md |
1517 | card | |
full_15dim.json |
1120 | JSON document | |
sov-sovereign-v4_latest.json |
975 | JSON document | |
manifest.jsonl |
33 | derived at 2026-09-04T04:33:29Z |
manifest.jsonl is derived from this repository's own file tree at 2026-09-04T04:33:29Z; it lists every file with its
size, its blob hash and a direct URL, so an agent can enumerate the repo without cloning it.
Citation
@misc{csoai_gspc_coai_bench,
title = {COAI — EU AI Act tiering disagreement corpus},
author = {{CSOAI Ltd}},
year = {2026},
doi = {10.5281/zenodo.21991104},
howpublished = {Hugging Face Hub, \url{https://huggingface.co/datasets/csoai/coai-bench}},
note = {Live board: https://councilof.ai/api/gspc. Measurement, not certification.}
}
Measurement, not certification. No slot is for sale and no empty slot is filled by payment. Issued by CSOAI Ltd (England & Wales, Companies House 16939677), 3rd Floor, 86–90 Paul Street, London EC2A 4NE. Card refreshed 2026-09-04T04:33:29Z; every number above is either fetched live or carries the timestamp at which it was read.
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