Building a new AI system? Don't wait for regulation to surprise you 🚀
What's the difference and how do you stay relevant?
🗯️ My tip: Start with the OECD, but aim for UFA 🎯 If you align yourself with the OECD principles, you are already on the right track. But to be truly market-ready Globally, it is worth adopting the Unified Framework Approach (UFA): adopting the most stringent standard (usually the European one) as the house standard. This saves expensive "corrections" afterwards.
Quick checklist for alignment (OECD Alignment):
✅ Defining uses and risks: Who are the users? What are the prohibited/sensitive uses? ✅ Data and model: Documenting the sources of information, legal basis (Consent) and separation between training and testing sets. ✅ Pre-launch testing: Accuracy metrics, fairness tests (Bias testing) and robustness. ✅ Transparency and accountability: Clearly wording for the user when he is facing AI, how to challenge a result and who is responsible in the organization. ✅ Continuous monitoring: A channel for reporting failures and setting time points for re-testing (quarterly/semi-annually).
Bottom line: Regulatory compliance is not just a legal "headache" - it is a tool for building trust with your customers. Company A company that documents and manages risks in advance is an easier company to sell and invest in.
