← All selected workPERSONAL PROJECT / AI EVALUATION, RISK AND REMEDIATION

ETIA

AI system error evaluation: measurement, qualification and traceability.

Period
2026
Project type
PERSONAL PROJECT / AI EVALUATION, RISK AND REMEDIATION
Role
AI error evaluation design, risk qualification, treatment, remediation, traceability and improvement tracking.

Context and challenge

Structure the observation and qualification of AI system errors to inform evaluation and risk management. This public dossier is limited to that general purpose.

Demonstration

Limited public presentation

This page describes the purpose and general scope of the work. Internal mechanisms, implementation choices and product demonstrations are not published.

Key decisions

  • Distinguish observations, their qualification and the resulting decisions.
  • Document the limits of interpretation of evaluations.
  • Maintain traceability without disclosing internal mechanisms.

Contribution: from assessment to improvement

  1. Scope and baseline

    Define AI uses, affected assets and the errors to qualify.

  2. Analysis and evaluation

    Evaluate impacts and prioritise error, data and operational risks.

  3. Treatment decisions

    Maintain a risk register recording reduction and acceptance decisions and outstanding actions.

  4. Remediation and implementation

    Correct identified weaknesses and link actions to the register and audit findings.

  5. Checks, retests and evidence

    Check corrections, integrity and expected behaviours using identified tests.

  6. Residual risk and improvement

    Track trends, regressions and residual exposure; revisit choices after changes.

Outcomes and deliverables

An AI error evaluation, treatment, remediation and monitoring workflow. Measurement and traceability support documented decisions and improvement.

10
risks in the register
6/10
risks with mitigation reported implemented
26/26
test files reported passing

Historical documentation: 28 June risk register and 2 July 2026 summary. The 6/10 measure reported treatment status; the 26/26 describe the reported test suite. Neither measures an overall risk reduction. Tests were not rerun for this presentation.

Deliverables

  • General evaluation frameworkAvailability to be agreed
  • Test and validation documentationAvailability to be agreed
  • Reporting of observations and their limitationsAvailability to be agreed

Frameworks and tools

  • AI system evaluation
  • Traceability
  • Risk management
  • Security by Design

Public scope

Personal R&D on AI system evaluation. The public scope covers its purpose and general contributions. Internal mechanisms and differentiating elements remain confidential.

Last reviewed: 25 October 2026

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