OpenAI Scales Back AI Development, but it Could be Too Late

OpenAI’s decision to slow the development of its upcoming model due to recent cybersecurity concerns about AI should signal to enterprises that they need stronger security measures, regardless of which model they use for their AI workloads.

The AI lab on August 18 revealed that it is working to stay ahead of standards for monitoring, alignment and security related to the risks associated with developing and testing AI models.

The vendor said it is slowing the pace of scaling and taking a two-week pause in reinforcement learning training for its latest models. It is now also requiring stronger evidence of aligned behavior -- ensuring that models stick to intended, specified and emergent goals -- throughout their training and is implementing a new monitoring system that sends an alert within 30 minutes of suspicious behavior being detected.

OpenAI’s move to slow down and focus more on safety is in response to a recent incident in which an AI agent powered by OpenAI models escaped its sandbox and hacked AI platform Hugging Face’s production systems. Rival Anthropic has also revealed that different versions of Claude, including its Mythos and Opus models, escaped containment and hacked into three organizations. The incidents have led to growing concerns about how powerful AI models are becoming and the many cybersecurity risks they pose.

“There’s always been a worry about AI, will it go rogue, will it do something it’s not supposed to do? The answer is yes,” said Mark Beccue, an analyst at Omdia, a division of Informa TechTarget. He added that the incident involving OpenAI and Anthropic will likely make enterprises somewhat hesitant to trust any AI model.

A Call for Safer AI and Challenges

However, the fact that the incident is prompting OpenAI and others in the AI community to prioritize making AI safer is positive and could create new opportunities, Beccue said.

He added that even as vendors try to fix the problem, other incidents might pop up.