Cisco is upping the safety game when it comes to AI

The Street

TheStreet’s Conway speaks with Jeetu Patel, EVP and Chief Product Officer at Cisco, about the implementation of safety guardrails when it comes to using AI.

Transcript

00:00So tell me, as AI continues to make progress and becomes more integrated in business,

00:05how can companies make sure the technology they're using is safe?

00:14That's a great question, Conway.

00:16The way that we think about it, there's going to be two classes of companies in the world

00:20as we move forward.

00:21There's going to be ones that are going to be great at the use of AI,

00:24and then ones that are going to struggle for relevance.

00:26And the great ones, what we're finding is they want to move fast,

00:30but they oftentimes get held back because of safety and security.

00:34And so that's an area that actually really needs to get focused on,

00:38because by definition, the models that AI applications are built on

00:43tend to be non-deterministic, and they tend to be rather unpredictable.

00:48And so you need to make sure that you've got the right level of safety and security guardrails

00:52so that they do behave, in fact, the way that we want them to behave.

00:56So what is your number one safety concern when using artificial intelligence in a business setting?

01:04If you think about the big areas that there's concerns that organizations have,

01:08it's around, in safety, you might have things like toxicity or prompt injection attacks

01:15that might happen where the behavior of the model is not quite what you want it to be.

01:20So that's what we need to make sure that we can ensure that there are guardrails for.

01:23So these models, which are inherently unpredictable,

01:26can behave in a way that are far more predictable for the context of the application.

01:31So how do you combat those unpredictable models?

01:36So that's exactly where Cisco comes in.

01:38We just launched a product called AI Defense,

01:41and AI Defense is a product essentially is a common safety and security solution for the market,

01:46because if you think about it, we're going to be living in a multi-model world.

01:50You'll have many, many models that applications are built on,

01:53and what we want to do is make sure that there's a common layer or substrate of security

01:58across all of these different models, across all the clouds and across all applications.

02:02And so what we do is provide the enforcement of guardrails for both the model itself

02:09as well as any external attacks that might happen on the model from threat actors.

02:14We want to make sure that both the safety concerns of the model behaving the way you want it to behave

02:18and the security attacks that might happen on the model to change the behavior of the model,

02:23can be compensated for.

02:24And that's what AI Defense does is allows organizations to innovate fearlessly,

02:29where they don't have to worry about safety and security because we can take care of that.

02:33One of the things that comes to my mind, of course, is like the movies that we've seen in Hollywood

02:39about AI and how AI could take over.

02:43So what are the guardrails that are put in place to avoid a kind of doomsday situation

02:49where companies integrate some kind of AI in order to protect themselves against AI

02:54and then they lose control?

02:58So let me take a step back because what's happening right now is the composition of our workforce

03:03is going to change quite a bit.

03:04So today, 100% of our workforce is humans.

03:08Tomorrow, you're going to have augmenting of that workforce with AI agents,

03:13you might have robots, you might have humanoids.

03:16And we need to make sure that these different AI augmentations can actually work

03:21the way that we want them to work.

03:23So what we would do is, if you think about a model, before a model goes to production

03:28for a specific application, let's say it's a loan processing application,

03:33we want to make sure that that model is behaving exactly the way that you want it to behave.

03:37So we have an algorithmic way of going out and doing a level of validation on the model

03:44to make sure, and typically for an organization, it takes 7 to 10 weeks, Conway,

03:49to go out and validate a model.

03:51For us, with AI defense, you can now do it within 30 seconds.

03:55And so that level of compression of time and not having to worry about the details

04:00makes a huge difference in not just the velocity but also the safety and security

04:04where you can enforce guardrails on this thing that if there's a model that's behaving in a different way,

04:09you can actually provide a compensating control on that

04:12so it doesn't behave the way that it should behave.

04:14For more information, visit conway.com

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