CTO AI Corner: Are open-weight AI models safe to use?

Well… not necessarily.

"Open-weight" simply means we can run these models wherever we have sufficient resources. It gives us control over where our data is processed. But it doesn’t guarantee the model itself is safe or free from malicious elements.

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Issues with open-weight AI models

• Hidden risks in training data – We can’t extract the dataset directly from model weights, and even if we could, detecting built-in biases or intentional vulnerabilities would be incredibly difficult.
• Accidental vs. deliberate issues – If an AI-assisted coding tool repeatedly introduces a security vulnerability, is it because malicious data was inserted into its training set, or was it just an unfortunate coincidence?
• AI-generated propaganda – If a chatbot starts promoting biased views, was it intentional, or did harmful content slip through during training?

Open models don’t automatically mean secure models.

But here's the catch! These risks also apply to commercial AI models. While major providers attempt to filter out harmful content, bad actors are actively trying to poison training datasets with vulnerabilities, propaganda, and other manipulations. The complexity is explained well in this paper from Anthropic.

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How to use AI responsibly

✅ Fact-check AI-generated information – Always apply source criticism.

✅ Review AI-generated code – Pay special attention to security-sensitive areas and maintain strong QA practices.

✅ Implement safeguards – If AI interacts with users, set up guardrails to catch off-topic or harmful responses.

✅ Restrict AI permissions – If AI takes automated actions, limit its access and monitor its behavior.

AI may appear as a friendly, helpful assistant. But it could have a dark side too. Stay vigilant. Stay critical.