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Speaker 1: Bloomberg Audio Studios, Podcasts, Radio News.

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Speaker 2: You're listening to Bloomberg BusinessWeek with Carol Messer and Tim

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Speaker 2: Stenebek on Bloomberg Radio. So just in the last few days, yes,

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Speaker 2: we've learned that Chinese hackers have targeted the phones of

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Speaker 2: Donald Trump and JD Vance and affiliates of Kamala Harris's campaign.

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Speaker 2: This is all according to NBC News. Then there's this

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Speaker 2: great profile out today by our Bloomberg News colleague, Katrina Manson.

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Speaker 2: It's about how Jen Easterly, who's director of the Cybersecurity

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Speaker 2: and Infrastructure Security Agency, is working to protect election infrastructure

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Speaker 2: from hacks and misinformation. And we'll need to convince the public.

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Speaker 2: Perhaps that's the hardest job of the elections legitimacy after

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Speaker 2: the vote.

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Speaker 1: That's right, needlessen to say, Tim, data security is top

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Speaker 1: of mind ahead of the election, and also always top

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Speaker 1: of mind for business leaders looking to safeguard there and

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Speaker 1: ours data. That's where Lane Best comes in. He's the

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Speaker 1: CEO of the deep learning AI CyberSecure platform deep Instinct.

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Speaker 1: He's also the former CEO of the publicly traded security

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Speaker 1: software company z Scaler, and before that, he was the

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Speaker 1: CEO of Palo Alto Network, So yeah, he knows about

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Speaker 1: this stuff. Tim.

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Speaker 2: It's good to have you with us, Lane, Thanks so

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Speaker 2: much for joining us. Hey, before we get into what

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Speaker 2: exactly Deep Instinct does, because it's it's distinct from some

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Speaker 2: of the other companies that are out there, what is

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Speaker 2: the biggest threat that you think we as a country

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Speaker 2: face when it faces when it comes to cybersecurity, it.

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Speaker 3: Is really the unknown threats. Today, a lot of the

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Speaker 3: money and resources and expenditures are towards known threats, and

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Speaker 3: the unknown threats are becoming much greater. Seventy two percent

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Speaker 3: of the threats that hit companies and governments today are

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Speaker 3: of an unnever seen nature and therefore the systems that

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Speaker 3: had been trained and the machine learning technologies that are

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Speaker 3: typically in place can't stop them. And in the early

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Speaker 3: phases of new technologies and all point specifically to AI,

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Speaker 3: the advantage goes to the attackers because they can use

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Speaker 3: simple tools and sophisticated ones to compromise companies' data and

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Speaker 3: ultimately cause havoc in some cases nation state attacks. It

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Speaker 3: takes a time for the practitioners to catch up because

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Speaker 3: they've already invested millions in the cyber technologies, and they've

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Speaker 3: got to explain why they're going to spend more money

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Speaker 3: to address some of the more challenging, unknown, new, never

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Speaker 3: seen threats. They eventually catch up, but in this early stage,

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Speaker 3: particularly with the AI threats, it can be quite dangerous.

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Speaker 1: So what are the unknown threats? Potentially? Sure?

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Speaker 3: So, known threats are usually in families of threats that

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Speaker 3: have been seen before, and the cloud models which many

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Speaker 3: of the companies in cyber have been able to train,

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Speaker 3: can essentially see them. But typically and using AI tools,

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Speaker 3: they can change code very slightly, and they can inject code,

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Speaker 3: and typically that evades even the best companies defense and

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Speaker 3: depth capabilities, and so simple changes aided in some cases

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Speaker 3: by more sophisticated AI, can take something that was generally

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Speaker 3: in a known category family and creates something entirely unseen before,

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Speaker 3: and therefore it can get through and cause significant data breaches.

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Speaker 2: Are we more concerned about data breaches? Are we more

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Speaker 2: concerned about an entire electrical grid becoming unusable? About traffic

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Speaker 2: signals being disrupted, in tunnels getting shut down, bank accounts

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Speaker 2: being wiped out, or those related?

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Speaker 3: They all are related. And the science, particularly the science

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Speaker 3: that we address at deep instinct addresses both cases. Typically,

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Speaker 3: though what we're seeing right now is the biggest cost

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Speaker 3: to companies is in data breaches. The average data breach

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Speaker 3: is a four point five million, and we've seen some

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Speaker 3: notable ones that have been in the hundreds of millions.

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Speaker 3: But if you talk about infrastructure disruption, these what I

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Speaker 3: consider to be infrastructure and nation state attacks. These can

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Speaker 3: just as easily be launched using the same tools. And

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Speaker 3: if you take a look at the industry, it has

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Speaker 3: been pretty much in a layers of defense, detect, remediate

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Speaker 3: fix afterwards. The posture that governments and also companies has

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Speaker 3: to take now is to get the most sophisticated AI

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Speaker 3: to battle the onslaught of sophisticated AI to prevent these threats,

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Speaker 3: and it does take a specific tibe of technology, one

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Speaker 3: in the form of deep learning that.

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Speaker 1: We have Selene walk us through the difference between AI,

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Speaker 1: machine learning, and deep learning and how cyber criminals are

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Speaker 1: actually using deep learning right now. Yeah.

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Speaker 3: So deep learning is like a brain, a neural network,

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Speaker 3: and without getting too much into the science of how

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Speaker 3: it works, you and I can take massive amounts of

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Speaker 3: data in our brain and we can make determinations and

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Speaker 3: with inferences and in our case, instinctual decisions. Machine learning models,

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Speaker 3: which can be very sophisticated, are based on parameters that

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Speaker 3: have been defined by people and rules that are trained

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Speaker 3: by people, and therefore they don't train upon themselves, only

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Speaker 3: what they've been defined. With deep learning models, Neural network

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Speaker 3: models are self training and take massive amounts of data,

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Speaker 3: in this case anything everything that might be in the

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Speaker 3: cyber space, and essentially extrapolate the potential of something being

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Speaker 3: a threat with ninety nine percent efficacy. So that's probably

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Speaker 3: the biggest differentiation.

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Speaker 2: When it comes to individuals out there, Like I know

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Speaker 2: that a lot of what you focus on is key

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Speaker 2: being companies safe, but at the end of the day,

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Speaker 2: we're only as strong as the weakest link. And I

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Speaker 2: think that's why correct. And I know we do this here,

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Speaker 2: but we do so much training about understanding phishing understanding.

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Speaker 1: I just did another training. I think the deadline was

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Speaker 1: on Tuesday. I was on vacational last week and came

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Speaker 1: back and I had you had to do it. I

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Speaker 1: had to do all the courses or they're going to

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Speaker 1: show off.

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Speaker 2: Correct. But there's a reason why, because with this social engineering,

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Speaker 2: all they need to do to gain access is is

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Speaker 2: get access through one of us.

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Speaker 3: So it's correct.

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Speaker 2: What's the way that we need to recognize threats in

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Speaker 2: a world where I can get a phone call. It

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Speaker 2: looks like it's from Amazon, but it's really somebody who

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Speaker 2: wants to steal money from me. It looks like it's

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Speaker 2: from my brink, but it's really someone who wants to

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Speaker 2: steal money from me.

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Speaker 3: And you hit it on the head most organizations, and

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Speaker 3: it's it's a big business in and of itself. The

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Speaker 3: training and readiness and IT organizations are spending a lot

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Speaker 3: on this, and we ourselves as individuals have to do

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Speaker 3: it because the weakest link is the insider threat, and

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Speaker 3: we've seen many of these stories. Ultimately, though, what happens

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Speaker 3: is those threats get in and in some way they're

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Speaker 3: going to go in and sit within your data sets

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Speaker 3: or within the applications in your environment. So even if

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Speaker 3: they evade through social engineering, having an efficacy level and

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Speaker 3: ability to determine that something that has come in is

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Speaker 3: not quite kosher is going to be a key backup

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Speaker 3: to the training that needs to take place. And most

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Speaker 3: of the detection and remediation is clean up after the

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Speaker 3: accidents already happen, So I would absolutely you're dead on,

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Speaker 3: and I'm happy to hear that Bloomberg is taking the efforts.

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Speaker 3: We do it with our own employees regularly, including myself

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Speaker 3: in terms of the social engineering, and this again is

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Speaker 3: where AI tools and some of the simplest tools with

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Speaker 3: regard to social engineering can help evaide.

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Speaker 1: So I don't know if this happen to you, Tim,

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Speaker 1: but I've been constantly getting messages that are definitely scams,

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Speaker 1: but they're supposed to be from recruiters. But this has

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Speaker 1: been happening to yes or text messages, and this has

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Speaker 1: been happening to some of my colleagues too. But it's

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Speaker 1: it's scary because you're wondering, you know, how you're getting this.

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Speaker 1: Sometimes it happens to me on WhatsApp as well. It

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Speaker 1: used to be more bitcoin messages, but now it's more

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Speaker 1: of these kind of fake recruiting type messages.

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Speaker 3: Right.

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Speaker 1: But I like my current gig, so I'm going to

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Speaker 1: try to keep that. But Lane, what safeguards do you

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Speaker 1: think need to be put in place when this is

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Speaker 1: such a complicated type of issue, and especially with all

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Speaker 1: of the technology involved.

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Speaker 3: Right at the end of the day, common sense is

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Speaker 3: probably the thing that I say to most people, the

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Speaker 3: when you get something from somebody you don't know, and

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Speaker 3: I get it all the time. In fact, while we

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Speaker 3: were talking here, I think I got a spam call

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Speaker 3: coming into my phone. Seriously, it's just every day. And

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Speaker 3: just rule of thumb is if it's not from somebody

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Speaker 3: you know, if it's not from the organization you're in,

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Speaker 3: you just don't click on it. Is enticing, as the

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Speaker 3: headline might be, there's a lot of clickbait we see today,

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Speaker 3: and at the end of the day, this is just

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Speaker 3: going to become an ongoing thing. And again, our goal

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Speaker 3: at Deep Instinct is to make it so that if

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Speaker 3: there is a breach wherever they try to get at

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Speaker 3: critical company data or critical company IP or resources, we

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Speaker 3: will detect it and we will stop it and flack it.

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Speaker 3: So I'd like to think that even if the first

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Speaker 3: line of defense, which is practical behavior by our employees

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Speaker 3: and by individuals, deep instinct deep learning technology, I say

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Speaker 3: it this way, it's the best AI to fight AI.

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Speaker 2: Okay, so let's talk a little bit about that and

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Speaker 2: sort of the technology that's being used here. Because one

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Speaker 2: thing that I always wonder is who has the upper

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Speaker 2: hand right now. Is it the actors who have incredible

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Speaker 2: upside but also a lot of downside or is it

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Speaker 2: the people who are trying to protect us who has

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Speaker 2: more technological advantage right now?

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Speaker 3: Yeah, I hate to say it, particular in the AI space,

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Speaker 3: IT advantage does goes to go to the bad actors.

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Speaker 3: And one of the challenges is and one of the

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Speaker 3: hardest jobs in cyber and n it is the CIO

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Speaker 3: and the chief information security officer. These individuals have gone

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Speaker 3: to the well to put in a tremendous amount of

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Speaker 3: cyber protection and detection technology for number of years, and

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Speaker 3: even still ransomwares and attackers get through. And it's getting

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Speaker 3: even more challenging the pace at which the malicious acts

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Speaker 3: are taking place and the ability for the teams of

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Speaker 3: people within enterprises and governments can address them. The gap

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Speaker 3: is widening, and so again the bad actors have the advantage.

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Speaker 3: And now the challenge that a lot of the IT

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Speaker 3: professionals have is they have to once again go to

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Speaker 3: management say this is a continuing and escalating this is

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Speaker 3: probably one of the most difficult jobs in technology, the

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Speaker 3: cyber protection, and it's only going to get greater and

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Speaker 3: so I encourage organizations to not think about, well, what

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Speaker 3: are we going to replace in our tech stack to

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Speaker 3: justify the cost of prevention. My view is that this

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Speaker 3: is a budget line that unfortunately continues to be need

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Speaker 3: to be evaluated. But more importantly, these practitioners need to

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Speaker 3: go beyond the technologies they've been using and look at

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Speaker 3: the more sophisticated technologies such as the things that we

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Speaker 3: we provide a deep Instinct because the same old tools

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Speaker 3: aren't going to work against the bad actors. Eventually, the

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Speaker 3: chech catches up early on. It's a challenge.

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Speaker 2: Lane, appreciate you joining us. That's Lane Best CEO over

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Speaker 2: at Deep Instinct. He joins us from New York.

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Speaker 1: As you know, Tim, this is a really big issue

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Speaker 1: here when you're thinking about how women are continuing, unfortunately

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Speaker 1: to lose these C suite seats in corporate America. In fact,

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Speaker 1: women's representation in senior level positions at US companies saw

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Speaker 1: signs of fatigue for the first time in two decades,

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Speaker 1: with gender parity and C suite positions potentially not reaching

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Speaker 1: parody until twenty seventy two, according to an S and

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Speaker 1: P report earlier this year.

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Speaker 2: That's literally a lifetime.

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Speaker 1: Yes, that's a lifetime. I will probably be dead that

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Speaker 1: hopefully hopefully not hopefully not that hopefully not though, But anyway,

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Speaker 1: I digress. But while there are lingering issues affecting women's

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Speaker 1: abilities to seek, prepare, and attain business leadership positions, there

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Speaker 1: actually are some signs recently of progress, and the total

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Speaker 1: number of women enrolled in top full time NBA proms

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Speaker 1: this fall by a record setting pace. Here So, joining

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Speaker 1: us now to discuss more is Alyssa sayingster ceo a

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Speaker 1: fort Foundation from San Antonio, Texas and for some insight

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Speaker 1: for our listeners. Forte Foundation is a nonprofit designed to

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Speaker 1: increase opportunities for women in leadership through access to business

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Speaker 1: education and professional development. Thank you so much, Alissa for

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Speaker 1: joining us. And I was looking through this latest report

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Speaker 1: that y'all put together. Here walk us through some of

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Speaker 1: the highlights and what drove women's NBA enrollment this fall.

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Speaker 4: Sure, so, I mean we're seeing some great results. We

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Speaker 4: are seeing women at right now forty two percent enrolled

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Speaker 4: in top business schools and that has been increasing, I

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Speaker 4: believe over the last five years we've seen a four

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Speaker 4: percent increase. We've seen number of schools reach gender parity.

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Speaker 4: Eight of our schools have hit that fifty to fifty

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Speaker 4: or more mark. But we've also seen some great progress

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Speaker 4: at forty five percent and at forty percent.

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Speaker 1: And looking through this too, because there's a lot of

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Speaker 1: interesting points here, and of course Tim and I were

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Speaker 1: just mentioning some of the pitfalls. I mean, what do

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Speaker 1: you think before was really holding back some of that,

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Speaker 1: because I know COVID was a big issue where we

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Speaker 1: saw a lot of women having to pull back from

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Speaker 1: the workforce.

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Speaker 4: Sure, I think you know, there's a lot of choices

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Speaker 4: that people had, men and women when they were going

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Speaker 4: back to school during the COVID times. So it's a

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Speaker 4: big move and it's a big investment, and you have

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Speaker 4: to really think about all the factors. What we saw

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Speaker 4: about twenty years ago is that women were not pursuing

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Speaker 4: business school because they didn't have a lot of role models,

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Speaker 4: They didn't hear from people who influenced them that that

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Speaker 4: was a path they should pursue, and so there were

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Speaker 4: a number of other factors, but those things were holding

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Speaker 4: them back. And that's what we've been working on the

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Speaker 4: last twenty years is how to chip away at some

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Speaker 4: of those misperceptions they had about business school and business careers.

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Speaker 2: You know, I hesitate to tie everything to the election,

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Speaker 2: but it's top of mind for so many people here.

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Speaker 2: Tuesday is election day, and the US could see its

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Speaker 2: first female president in its entire history. It also could not.

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Speaker 2: But I'm wondering if you think a change at the top,

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Speaker 2: and I literally mean at the top, like the most

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Speaker 2: important position in the entire country, if that moves the needle.

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Speaker 4: It I mean, I think it absolutely does, because it

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Speaker 4: is a change in potential policies, it's a change in

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Speaker 4: who you see every day on your television. It's inspirational.

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Speaker 4: I mean, that is the role model for everyone. And

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Speaker 4: so I think you know why it may not inspire

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Speaker 4: more women to go to get their business degree. I

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Speaker 4: think it does inspire them to lead, and I think

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Speaker 4: ultimately that's the position you want to see a woman in.

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Speaker 2: There's also something happening right now that we've been hearing

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Speaker 2: a lot about in the context of the election. Then

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Speaker 2: that's the idea that more women are going to college,

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Speaker 2: more women are graduating from college, and that even though

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Speaker 2: as a whole, women are still at a paid less

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Speaker 2: than men, there's this idea that when it comes to advancement,

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Speaker 2: and this is a lot of been talked about this

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Speaker 2: with regard to the male support for Donald Trump, there's

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Speaker 2: this idea that men have been left back, and I'm

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Speaker 2: sorry that I'm it's hard for me to say that

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Speaker 2: with a straight face, just because you look at all

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Speaker 2: the data and you see that women are still on

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Speaker 2: a salary basis. You know, there's like equal payday as

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Speaker 2: months after the first of the year. So but I'm

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Speaker 2: wondering how you see that playing into this. Melissa Well,

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Speaker 2: I think.

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Speaker 4: It's discouraging when you hear that as a top line message,

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Speaker 4: because I think you're right. Maybe for a blink of

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Speaker 4: the eye, we've seen change happen and women have progressed.

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Speaker 4: But I think if you look back decades and centuries,

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Speaker 4: we're just now getting to the tip of the iceberg.

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Speaker 4: And so so I'm not sure that there's a lot

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Speaker 4: to complain about on either side. I think we just

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Speaker 4: need to kind of let things settle, and we need

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Speaker 4: to make sure that we're focused on, especially in business leadership,

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Speaker 4: building inclusive cultures, building opportunities for all of our people

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Speaker 4: to advance, and to make sure that companies are focused

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Speaker 4: on that, and they're focused on, you know, how to

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Speaker 4: engage all of their employees. In this discussion, I think

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Speaker 4: it's an unnecessary really to say men are not advancing

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Speaker 4: at the same rate as women, especially in business leadership.

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Speaker 4: I mean, there are some other societal things that we

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Speaker 4: want to focus on, and I don't want men to

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Speaker 4: be left behind, But I also don't think that's really

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Speaker 4: reflective of what's going on.

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Speaker 1: Of course, there was a debate, especially over the last decade,

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Speaker 1: as more and more people were getting their MBAs and

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Speaker 1: how much useful that would be as people were getting

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Speaker 1: say CFAs and other things. But when you're looking more recently,

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Speaker 1: especially coming out of COVID, how have especially women been

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Speaker 1: putting their nbas to work in particular industries.

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Speaker 4: Well, I think what you see is a really healthy

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Speaker 4: pipeline of women with their MBA, And what that typically

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Speaker 4: means is you're going to see strong outcomes in the

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Speaker 4: consulting industry and financial services, in consumer package goods companies,

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Speaker 4: and in technology. I mean, those are kind of the

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Speaker 4: four top recruiters that are coming to NBA campuses. It

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Speaker 4: also means that more women are going to be starting

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Speaker 4: their own businesses because they're going to be going through

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Speaker 4: these incubators that are on these business school campuses, and

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Speaker 4: that's really encouraging as well, given the lack of funding

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Speaker 4: in VC. You want to see more companies being started

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Speaker 4: by women and being successfully funded, And.

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Speaker 1: Are you starting to see that in the data as

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Speaker 1: well as far as starting their own companies.

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Speaker 4: I mean, we're definitely seeing women advance. I mean, so

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Speaker 4: we've been doing this work for twenty years and I

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Speaker 4: think you're seeing them just becoming eligible for these very

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Speaker 4: senior C suite positions. So I do think there is

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Speaker 4: a robust pipeline. I think companies do have to continue

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Speaker 4: being intentional about how they advance all of their employees

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Speaker 4: and are they providing career roadmaps and ways for women

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Speaker 4: to advance and making sure again that they're focused on

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Speaker 4: that culture and really engaging all of their potential leaderships

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Speaker 4: in that conversation very transparently about how they see them

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Speaker 4: progressing to the top.

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Speaker 1: And ultimately, I mean, we only have about thirty seconds left,

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Speaker 1: But what do you think really needs to change in

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Speaker 1: order for this to accelerate here and change things?

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Speaker 4: Well, I think in business school, I mean we're getting

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Speaker 4: very close to parody, and so I would say the

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Speaker 4: big thing that needs to change is once those women

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Speaker 4: have graduated, how are we making sure that their advancement

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Speaker 4: is possible. There's a lot more shoots than ladders in

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Speaker 4: a women's career, and we want to make sure that

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Speaker 4: they're given those ladders to continue climbing and excelling.

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Speaker 1: Thanks so much for joining us. Really great insight into

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Speaker 1: all things, and especially such an important topic and great

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Speaker 1: question from Tim about obviously at the top and how

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Speaker 1: that could potentially change things here. But Alyssa Thankster, CEO

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Speaker 1: of Forte Foundation, joining us from San Antonio, Texas. Great

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Speaker 1: getting your insight on all of this.

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Speaker 2: But Tim, I'm sorry the electric just top of I mean,

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Speaker 2: it's a great.

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Speaker 1: Great point though as far as like, does that change

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Speaker 1: the dynamic when we're at the top though

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Speaker 2: It's I mean, I think a lot of people argue

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Speaker 2: it's all about representation, that's right,