# Ada Health: CAIHL reassessment

September 8, 2026. Published AI-assisted draft.

Ada’s direct assessments differ from partner-controlled sharing and decisions. Its US policy describes consented health-derived marketing segments. Removing an existing segment requires a separate request, beyond changing the consent setting.

## Scope and agency posture

Direct Ada assessment, partner-embedded Assess, and US advertising-segment consent must be distinguished.

Posture: **Mixed, potentially agency-expanding**.

Axis: 66/100, retained provisionally. No numerical recalibration was performed.

## Sources and documented findings

- The current policy says patients may share a report with clinicians. Partner deployments may require assessment sharing and may make their own automated decisions, with rights directed to the partner. https://ada.com/privacy-policy/

- The US policy describes consented marketing segments derived internally from assessment outcomes and represented by pseudonymized tokens. Revoking the consent setting alone is insufficient to remove an existing segment: an email-address-based request is required. https://ada.com/us/consumer-health-data-privacy-policy/

## Patient authority

Inference from the documented workflow: Direct assessment can support self-directed care seeking. Mandatory sharing in some integrations is an actual deployment condition, while partner routing decisions are not attributable to every consumer assessment.

## Critical capacity

Editorial assessment: Reports support reflection and action. Correcting personal data and contesting an institution's consequential decision are separate routes, and actual report-level revision remains untested.

## Informed control

Editorial assessment: The separate segment-removal action materially affects meaningful withdrawal. Pseudonymization should not be described as the absence of health-derived commercial targeting.

## Assessment and limits

Mixed remains warranted from documented conditions. Update the rationale with the specific withdrawal burden rather than a generic pharma-funding concern.

Confidence: Moderate for policy distinctions.

Remaining uncertainty: In-app consent comprehension, report correction and partner alternatives remain unverified

Published documentation is evidence of stated conditions, not proof of actual implementation. Unknowns did not receive automatic negative points. Funding, sponsorship, and public code do not determine agency by themselves.

## Review provenance

- Reviewer/model: OpenAI Codex / GPT-6.
- Method: Focused public-source reassessment using CAIHL: patient authority, critical capacity, and informed control. Existing evidence plus one focused primary-source pass and at most one targeted follow-up. No live product testing. Numerical scores remain provisional editorial placements, not a new calculation.
- Human review: Hugo Campos authorized publication of these AI-assisted draft reassessments on September 8, 2026. This does not claim comprehensive human verification of every finding.
- Earlier review: 2026-06-30. [Historical assessment](https://github.com/hugooc/HugoScore/blob/7e0ba68fae543832fe5f19009448e473983f48a9/site/reports/ada-health-caihl-report.md). Earlier claims are not automatically reverified by this publication.