AI Accountability

Overview

AI Accountability brings forensic discipline to the systems that now make decisions about people. Hiring, screening, evaluation, monitoring. We assess whether those systems are fair, defensible, and accountable, and we design the governance that keeps them that way.

Why this matters

AI is already deciding who gets hired, flagged, and advanced. Most of these systems were never built to explain themselves. When a decision is challenged, in a tribunal, an audit, or the press, the organization owns the outcome, not the vendor. We find where a system fails that test before someone else does.

What we assess

• Selection and evaluation logic. What the system rewards, what it penalizes, and whether that holds up under scrutiny.
• Fairness and adverse impact. Where outcomes diverge across groups, and why.
• Human oversight. Whether a person can see, question, and override a decision.
• Governance and documentation. The record that makes a decision defensible after the fact.

Who this serves

Government, defence, and enterprises deploying AI in decisions about people. Particularly regulated environments where a wrong call carries legal, operational, or reputational cost.

How an engagement works

An engagement begins with a defined system and a clear question. We assess against it, document what we find, and hand back a path to accountability that your own people can maintain. Scope is bounded so the findings are usable.

Outputs

• Accountability assessments
• Governance frameworks
• Oversight and escalation models