AI Governance 101: What ML Practitioners Actually Need to Know
AI regulation isn't abstract policy anymore. If you're building systems that touch hiring, credit, healthcare, or law enforcement, there are now legal requirements attached to your model's behavior — and the penalties are real. Here's what actually matters for practitioners, without the fluff. The EU AI Act: risk tiers, not blanket rules Adopted in 2024, the EU AI Act is the first comprehensive…
The EU AI Act classifies AI systems into four risk tiers, with high-risk categories requiring extensive documentation, testing, human oversight, and registration. Violations can result in fines of up to 7% of global annual turnover or €35 million. US regulations are more sector-specific and voluntary, but the NIST AI Risk Management Framework (AI RMF) offers a four-function structure for governance, mapping well to the ML lifecycle.
Other countries like China, the UK, and Canada have their own AI regulations. Embedding compliance into the ML lifecycle from the start is recommended, including documentation, monitoring, accountability, incident response, and audit trails.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
