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license: apache-2.0
pretty_name: ConsentBench
language:
- en
tags:
- clinical-ai
- llm-security
- ai-agents
- healthcare
- haarf
- quokkaguard
- synthetic
size_categories:
- 1K<n<10K
task_categories:
- other
---
# ConsentBench
**A FHIR-consent scope gate, AI-disclosure stamper, and signed competency gate for clinical AI agents.**
ConsentBench is the benchmark corpus for *Consent Is a Gateway Responsibility: Enforcing Patient Consent, AI Disclosure, and Participatory Governance for Clinical AI Agents*, the `quconsent` module of the QUOKKAGUARD program. It ships with the [`quconsent`](https://github.com/quome-cloud/quconsent) repository, which contains the `qfire` gateway layer under test, the experiment harness, and the paper.
Four deterministic JSONL corpora under consentbench/: 200 FHIR-Consent-shaped directives, 712 scope/competency scenarios (in-scope, out-of-scope, explicit-deny, withdrawn, expired, draft; missing/uncredentialed/forged operators) with expected gateway behavior, 120 patient-facing prompts tagged with consent status, and 300 scored goals-of-care cases with two synthetic clinician raters; seed 42, no PHI.
**All data are synthetic.** No real patient data or protected health information (PHI) is included; clinical content is generated from templates with fixed seeds.
## Files
| File | Size | Rows |
|---|---|---|
| `consentbench/consent_directives.jsonl` | 42 KB | 200 rows |
| `consentbench/goals_of_care.jsonl` | 50 KB | 300 rows |
| `consentbench/patient_facing.jsonl` | 29 KB | 120 rows |
| `consentbench/scenarios.jsonl` | 121 KB | 712 rows |
### Record schemas
- `consentbench/consent_directives.jsonl`: `base`, `exceptions`, `patient`, `status`
- `consentbench/goals_of_care.jsonl`: `action`, `case_id`, `label`, `patient`, `purpose`, `score`, `values`
- `consentbench/patient_facing.jsonl`: `action`, `case_id`, `consent_status`, `expected`, `patient`, `prompt`, `purpose`
- `consentbench/scenarios.jsonl`: `action`, `case_id`, `expected`, `family`, `operator`, `patient`, `purpose`
## How it was generated
The corpus is produced by the generator in the paper repository and is fully deterministic (fixed seeds), so it can be regenerated byte-for-byte.
```bash
# from the quconsent repository root (deterministic seeds)
python3 scripts/013-consent/gen_consent.py
```
## Intended use
Evaluating the **consent** enforcement layer of a clinical-agent security gateway (HAARF control C4): An agent action can be authorized and clinically correct and still be unlawful: taken outside the patient's recorded consent, or delivered as a patient-facing message that hides its AI authorship.
The experiments that consume it (E-series in the paper) are reproduced from the repository:
```bash
git clone https://github.com/quome-cloud/quconsent
cd quconsent
cargo build --release
```
then follow the *Reproduce the experiments* section of its README.
## Citation
This benchmark was built to evaluate a control of the **Healthcare AI Agents Regulatory Framework (HAARF)**, the source framework for the QUOKKAGUARD program. Please cite both the paper and HAARF:
```bibtex
@unpublished{schwoebel2026quconsent,
author = {{QUOKKAGUARD Working Group}},
title = {Consent Is a Gateway Responsibility: Enforcing Patient Consent, AI Disclosure, and Participatory Governance for Clinical AI Agents},
note = {Preprint. Quome, QUOKKAGUARD program (quconsent module)},
year = {2026},
url = {https://github.com/quome-cloud/quconsent}
}
@unpublished{schwoebel2026haarf,
author = {Schwoebel, Jim and Frasch, Martin and Spalding, Art and Sewell, Ed and Englert, Phil and Halpert, Ben and Overbay, Collin and Semenec, Ingrida and Shor, Joel},
title = {{HAARF}: Healthcare {AI} agents regulatory framework --- a comprehensive security verification standard for autonomous {AI} systems in clinical environments},
note = {medRxiv Preprint},
year = {2026},
month = {April},
doi = {10.64898/2026.04.09.26350519},
url = {https://www.medrxiv.org/content/10.64898/2026.04.09.26350519v1}
}
```
## License
Apache License 2.0. Copyright (c) 2026 Quome, Inc.
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