AI Usage Policy

AI Impact and Risk Assessment (AIRA) Framework

Purpose and Necessity Assessment
Before any AI-driven processing begins, we assess:

Data Necessity – Is personal data required for the intended AI processing, or can anonymized or synthetic data be used?
Purpose Limitation – Is the use of AI aligned with the original purpose for data collection, as outlined in the data processing agreement?
Legitimate Interest & Consent – If processing involves personal data, do we have a lawful basis (e.g., consent, contractual necessity, legitimate interest)?

✔ Decision Point: If personal data is not essential, we remove or anonymize it before AI processing.

Data Protection Impact Assessment (DPIA) Process
A DPIA is conducted where required to assess potential risks and mitigation measures. Key considerations include:

Risk to Data Subjects – Could the AI processing result in discrimination, bias, or harm?
Data Security – Is the data sufficiently protected against leaks, cyber threats, or unintended access?
Transparency & Explainability – Can AI-generated outputs be understood and explained to stakeholders?
Regulatory Compliance – Does the processing comply with UK GDPR and AI governance frameworks?

✔ Decision Point: If risks are identified, we implement additional controls or seek ethical review before proceeding.

AI Bias and Fairness Testing
To ensure AI-generated outputs are fair, unbiased, and accurate, we conduct:

Pre-processing Checks – Examining training data for representativeness and bias.
Model Audits – Testing outputs against benchmarks to detect potential bias in AI decision-making.
Human Oversight – Ensuring human review at critical decision points to validate AI-driven insights.

✔ Decision Point: If bias is detected, we adjust training data, modify AI models, or increase human intervention.

Data Security & Access Control
To protect against data breaches and unauthorized use, we enforce:

Role-Based Access Control (RBAC) – Limiting AI data processing access to authorized personnel only.
Data Encryption – Ensuring data is encrypted at rest and in transit.
Logging & Monitoring – Tracking AI processing activities to detect anomalies.
Secure AI Deployment – Using trusted, secure cloud environments or on-premise solutions with strict compliance controls.

✔ Decision Point: If security vulnerabilities exist, we revise our AI deployment strategy before proceeding.

Ongoing Governance & Compliance
AI use is continuously monitored and reviewed through:

Regulatory Updates – Ensuring compliance with evolving legal frameworks for AI governance.
Audit & Impact Reviews – Reviewing past AI-driven decisions to assess impact and improve future processes.

✔ Decision Point: If compliance gaps are identified, AI processing is halted until issues are resolved.