by iqentity | Dec 21, 2025 | AI Ethics, AI Governance
Most AI ethics boards are advisory. They review proposals, offer recommendations, and publish reports that the organization is free to ignore. This is governance by suggestion, and it does not work. An effective AI Ethics Review Board needs structural authority,...
by iqentity | Dec 19, 2025 | AI Governance
GDPR was designed for a world of databases, not neural networks. Its principles are sound: data minimization, purpose limitation, the right to erasure, meaningful consent. But applying these principles to machine learning creates friction that most organizations have...
by iqentity | Dec 18, 2025 | AI Governance
The AI industry’s obsession with scale has created a narrative that bigger models are always better. More parameters, more training data, more compute. The arms race produces impressive benchmarks and eye-catching demos. For most enterprise use cases, it also...
by iqentity | Dec 2, 2025 | AI Governance
Every AI deployment creates dependencies. The model architecture, the training pipeline, the inference infrastructure, the prompt engineering, and the integration code all accumulate switching costs that compound over time. Vendor lock-in is typically framed as a...
by iqentity | Dec 1, 2025 | AI Ethics, AI Governance, Compliance
I need to tell you something that will be uncomfortable if you’re the person who drafted your organization’s AI ethics policy. Or the executive who approved it. Or the compliance officer who filed it. Your AI ethics policy is almost certainly theater. I...
by iqentity | Nov 25, 2025 | AI Governance
When an AI system produces a harmful outcome, the first question is always: who is responsible? The answer, in most organizations, is nobody. Or everybody. Which amounts to the same thing. Diffuse accountability is not a people problem. It is a structural one. AI...
