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.Related:Pony.AI Has Plans For 4,000 Robotaxis Outside China“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 ChallengesHowever, 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.“Maybe they get a little smarter about how to do this, but it also puts opportunity out there. And now you've got cybersecurity experts thinking about how we protect against these kinds of threats?” he continued.However, while vendors such as OpenAI could ramp up their safety efforts and try to slow down reinforcement learning training on upcoming models, the problem of models posing cybersecurity risks cannot be easily fixed, said Chirag Shah, a professor in the Information School at the University of Washington in Seattle.“I don’t think there is a real solution here,” Shah said. “This kind of misbehavior by the models, there are things that you can do to reduce some of those occurrences, but it’s never going to go away.”Related:How Enterprises Can Catch Up With the Rapid Pace of AI AdvancesHe added that even as vendors try to fix the problem, other incidents might pop up.Moreover, though OpenAI discussed trying to fix model alignment to prevent incidents like the Hugging Face one, that will be hard to do for a company that is racing toward AGI (artificial general intelligence), Shah said. Moreover, AGI means OpenAI is intentionally creating systems that it expects to be smarter than humans.“You can’t have both,” Shah said. “You can’t have a system that is generally capable, smarter than us and expect that it will somehow not do these types of things.”He added that OpenAI appears to be doing damage control with its decision to slow development, but it hasn’t revealed technical details on how it plans to fix the models so they stop misbehaving.“Theoretically, this is not something that can be fixed,” Shah said. “You can mitigate it, but unless you quit your agenda of AGI … you're only creating more problems.”What Enterprises Can DoWhile vendors might not be able to eradicate the cybersecurity problems associated with AI models, enterprises should still seek to have the most effective security measures in place, no matter the model they’re using.Related:Speech-to-Text AI Specialist Now Valued at $2B“When hackers get going, it’s not going to matter who made the model,” Beccue said. “It doesn't matter how you're choosing models. Enterprises will have to say, ‘how secure can we be?’”About the AuthorNews Writer, AI BusinessEsther Shittu has covered AI technologies and industry trends since 2021. As co-host of the Targeting AI podcast, she talks with experts, thought leaders and practitioners exploring critical AI developments. Before AI Business, she wrote for SearchEnterpriseAI, the New York Daily News, Bklyner and the Brooklyn Daily Eagle. When she's not diving deep into the world of AI, she spends her time on passion projects and raising her three daughters.