RSA 2024: How to Secure Artificial Intelligence Projects
Most AI Projects Are Not Being Secured
In a new report, “Securing Generative AI,” IBM and Amazon Web Services found that only 24 percent of current generative AI projects are being secured, even though 82 percent of organizations say that “secure and trustworthy AI is essential to the success of the business.”
“While a majority of executives are concerned about unpredictable risks impacting generative AI initiatives, they are not prioritizing security,” the report notes. The survey of more than 2,300 executives identifies a likely reason for the disconnect: Nearly 70 percent of executives say innovation takes precedence over security.
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“It’s very similar to what we saw in the past, with cloud, where the drive for innovation is out in front of where the current security posture is,” Saeedi said. “From a maturity standpoint, there’s a lot of new projects and a lot of people just trying to figure out what’s going on right now.”
Part of the challenge with AI security is that it involves two distinct disciplines: data scientists, who do a lion’s share of the work in building the deep learning models that are foundational to AI, but who don’t know much about security; and cybersecurity experts, who are only now learning about AI, Saeedi said.
That’s where leadership needs to step in and bring the sides together. It’s critical that business leaders understand that for all of their AI projects, security must be built from the ground up; otherwise, they will repeat the mistakes of the past, when they zoomed ahead into the cloud with poor security controls.
“At the highest level, AI that’s not trustworthy is not sustainable,” Saeedi said. “And if you have AI that is not secure, and you have other data that’s being manipulated outside the boundaries of the business’s intent, then it’s not trustworthy.”
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