Speaker 1: Bloomberg Audio Studios, Podcasts, Radio News.
Speaker 2: You're listening to Bloomberg BusinessWeek with Carol Messer and Tim
Speaker 2: Stenebek on Bloomberg Radio. So just in the last few days, yes,
Speaker 2: we've learned that Chinese hackers have targeted the phones of
Speaker 2: Donald Trump and JD Vance and affiliates of Kamala Harris's campaign.
Speaker 2: This is all according to NBC News. Then there's this
Speaker 2: great profile out today by our Bloomberg News colleague, Katrina Manson.
Speaker 2: It's about how Jen Easterly, who's director of the Cybersecurity
Speaker 2: and Infrastructure Security Agency, is working to protect election infrastructure
Speaker 2: from hacks and misinformation. And we'll need to convince the public.
Speaker 2: Perhaps that's the hardest job of the elections legitimacy after
Speaker 2: the vote.
Speaker 1: That's right, needlessen to say, Tim, data security is top
Speaker 1: of mind ahead of the election, and also always top
Speaker 1: of mind for business leaders looking to safeguard there and
Speaker 1: ours data. That's where Lane Best comes in. He's the
Speaker 1: CEO of the deep learning AI CyberSecure platform deep Instinct.
Speaker 1: He's also the former CEO of the publicly traded security
Speaker 1: software company z Scaler, and before that, he was the
Speaker 1: CEO of Palo Alto Network, So yeah, he knows about
Speaker 1: this stuff. Tim.
Speaker 2: It's good to have you with us, Lane, Thanks so
Speaker 2: much for joining us. Hey, before we get into what
Speaker 2: exactly Deep Instinct does, because it's it's distinct from some
Speaker 2: of the other companies that are out there, what is
Speaker 2: the biggest threat that you think we as a country
Speaker 2: face when it faces when it comes to cybersecurity, it.
Speaker 3: Is really the unknown threats. Today, a lot of the
Speaker 3: money and resources and expenditures are towards known threats, and
Speaker 3: the unknown threats are becoming much greater. Seventy two percent
Speaker 3: of the threats that hit companies and governments today are
Speaker 3: of an unnever seen nature and therefore the systems that
Speaker 3: had been trained and the machine learning technologies that are
Speaker 3: typically in place can't stop them. And in the early
Speaker 3: phases of new technologies and all point specifically to AI,
Speaker 3: the advantage goes to the attackers because they can use
Speaker 3: simple tools and sophisticated ones to compromise companies' data and
Speaker 3: ultimately cause havoc in some cases nation state attacks. It
Speaker 3: takes a time for the practitioners to catch up because
Speaker 3: they've already invested millions in the cyber technologies, and they've
Speaker 3: got to explain why they're going to spend more money
Speaker 3: to address some of the more challenging, unknown, new, never
Speaker 3: seen threats. They eventually catch up, but in this early stage,
Speaker 3: particularly with the AI threats, it can be quite dangerous.
Speaker 1: So what are the unknown threats? Potentially? Sure?
Speaker 3: So, known threats are usually in families of threats that
Speaker 3: have been seen before, and the cloud models which many
Speaker 3: of the companies in cyber have been able to train,
Speaker 3: can essentially see them. But typically and using AI tools,
Speaker 3: they can change code very slightly, and they can inject code,
Speaker 3: and typically that evades even the best companies defense and
Speaker 3: depth capabilities, and so simple changes aided in some cases
Speaker 3: by more sophisticated AI, can take something that was generally
Speaker 3: in a known category family and creates something entirely unseen before,
Speaker 3: and therefore it can get through and cause significant data breaches.
Speaker 2: Are we more concerned about data breaches? Are we more
Speaker 2: concerned about an entire electrical grid becoming unusable? About traffic
Speaker 2: signals being disrupted, in tunnels getting shut down, bank accounts
Speaker 2: being wiped out, or those related?
Speaker 3: They all are related. And the science, particularly the science
Speaker 3: that we address at deep instinct addresses both cases. Typically,
Speaker 3: though what we're seeing right now is the biggest cost
Speaker 3: to companies is in data breaches. The average data breach
Speaker 3: is a four point five million, and we've seen some
Speaker 3: notable ones that have been in the hundreds of millions.
Speaker 3: But if you talk about infrastructure disruption, these what I
Speaker 3: consider to be infrastructure and nation state attacks. These can
Speaker 3: just as easily be launched using the same tools. And
Speaker 3: if you take a look at the industry, it has
Speaker 3: been pretty much in a layers of defense, detect, remediate
Speaker 3: fix afterwards. The posture that governments and also companies has
Speaker 3: to take now is to get the most sophisticated AI
Speaker 3: to battle the onslaught of sophisticated AI to prevent these threats,
Speaker 3: and it does take a specific tibe of technology, one
Speaker 3: in the form of deep learning that.
Speaker 1: We have Selene walk us through the difference between AI,
Speaker 1: machine learning, and deep learning and how cyber criminals are
Speaker 1: actually using deep learning right now. Yeah.
Speaker 3: So deep learning is like a brain, a neural network,
Speaker 3: and without getting too much into the science of how
Speaker 3: it works, you and I can take massive amounts of
Speaker 3: data in our brain and we can make determinations and
Speaker 3: with inferences and in our case, instinctual decisions. Machine learning models,
Speaker 3: which can be very sophisticated, are based on parameters that
Speaker 3: have been defined by people and rules that are trained
Speaker 3: by people, and therefore they don't train upon themselves, only
Speaker 3: what they've been defined. With deep learning models, Neural network
Speaker 3: models are self training and take massive amounts of data,
Speaker 3: in this case anything everything that might be in the
Speaker 3: cyber space, and essentially extrapolate the potential of something being
Speaker 3: a threat with ninety nine percent efficacy. So that's probably
Speaker 3: the biggest differentiation.
Speaker 2: When it comes to individuals out there, Like I know
Speaker 2: that a lot of what you focus on is key
Speaker 2: being companies safe, but at the end of the day,
Speaker 2: we're only as strong as the weakest link. And I
Speaker 2: think that's why correct. And I know we do this here,
Speaker 2: but we do so much training about understanding phishing understanding.
Speaker 1: I just did another training. I think the deadline was
Speaker 1: on Tuesday. I was on vacational last week and came
Speaker 1: back and I had you had to do it. I
Speaker 1: had to do all the courses or they're going to
Speaker 1: show off.
Speaker 2: Correct. But there's a reason why, because with this social engineering,
Speaker 2: all they need to do to gain access is is
Speaker 2: get access through one of us.
Speaker 3: So it's correct.
Speaker 2: What's the way that we need to recognize threats in
Speaker 2: a world where I can get a phone call. It
Speaker 2: looks like it's from Amazon, but it's really somebody who
Speaker 2: wants to steal money from me. It looks like it's
Speaker 2: from my brink, but it's really someone who wants to
Speaker 2: steal money from me.
Speaker 3: And you hit it on the head most organizations, and
Speaker 3: it's it's a big business in and of itself. The
Speaker 3: training and readiness and IT organizations are spending a lot
Speaker 3: on this, and we ourselves as individuals have to do
Speaker 3: it because the weakest link is the insider threat, and
Speaker 3: we've seen many of these stories. Ultimately, though, what happens
Speaker 3: is those threats get in and in some way they're
Speaker 3: going to go in and sit within your data sets
Speaker 3: or within the applications in your environment. So even if
Speaker 3: they evade through social engineering, having an efficacy level and
Speaker 3: ability to determine that something that has come in is
Speaker 3: not quite kosher is going to be a key backup
Speaker 3: to the training that needs to take place. And most
Speaker 3: of the detection and remediation is clean up after the
Speaker 3: accidents already happen, So I would absolutely you're dead on,
Speaker 3: and I'm happy to hear that Bloomberg is taking the efforts.
Speaker 3: We do it with our own employees regularly, including myself
Speaker 3: in terms of the social engineering, and this again is
Speaker 3: where AI tools and some of the simplest tools with
Speaker 3: regard to social engineering can help evaide.
Speaker 1: So I don't know if this happen to you, Tim,
Speaker 1: but I've been constantly getting messages that are definitely scams,
Speaker 1: but they're supposed to be from recruiters. But this has
Speaker 1: been happening to yes or text messages, and this has
Speaker 1: been happening to some of my colleagues too. But it's
Speaker 1: it's scary because you're wondering, you know, how you're getting this.
Speaker 1: Sometimes it happens to me on WhatsApp as well. It
Speaker 1: used to be more bitcoin messages, but now it's more
Speaker 1: of these kind of fake recruiting type messages.
Speaker 3: Right.
Speaker 1: But I like my current gig, so I'm going to
Speaker 1: try to keep that. But Lane, what safeguards do you
Speaker 1: think need to be put in place when this is
Speaker 1: such a complicated type of issue, and especially with all
Speaker 1: of the technology involved.
Speaker 3: Right at the end of the day, common sense is
Speaker 3: probably the thing that I say to most people, the
Speaker 3: when you get something from somebody you don't know, and
Speaker 3: I get it all the time. In fact, while we
Speaker 3: were talking here, I think I got a spam call
Speaker 3: coming into my phone. Seriously, it's just every day. And
Speaker 3: just rule of thumb is if it's not from somebody
Speaker 3: you know, if it's not from the organization you're in,
Speaker 3: you just don't click on it. Is enticing, as the
Speaker 3: headline might be, there's a lot of clickbait we see today,
Speaker 3: and at the end of the day, this is just
Speaker 3: going to become an ongoing thing. And again, our goal
Speaker 3: at Deep Instinct is to make it so that if
Speaker 3: there is a breach wherever they try to get at
Speaker 3: critical company data or critical company IP or resources, we
Speaker 3: will detect it and we will stop it and flack it.
Speaker 3: So I'd like to think that even if the first
Speaker 3: line of defense, which is practical behavior by our employees
Speaker 3: and by individuals, deep instinct deep learning technology, I say
Speaker 3: it this way, it's the best AI to fight AI.
Speaker 2: Okay, so let's talk a little bit about that and
Speaker 2: sort of the technology that's being used here. Because one
Speaker 2: thing that I always wonder is who has the upper
Speaker 2: hand right now. Is it the actors who have incredible
Speaker 2: upside but also a lot of downside or is it
Speaker 2: the people who are trying to protect us who has
Speaker 2: more technological advantage right now?
Speaker 3: Yeah, I hate to say it, particular in the AI space,
Speaker 3: IT advantage does goes to go to the bad actors.
Speaker 3: And one of the challenges is and one of the
Speaker 3: hardest jobs in cyber and n it is the CIO
Speaker 3: and the chief information security officer. These individuals have gone
Speaker 3: to the well to put in a tremendous amount of
Speaker 3: cyber protection and detection technology for number of years, and
Speaker 3: even still ransomwares and attackers get through. And it's getting
Speaker 3: even more challenging the pace at which the malicious acts
Speaker 3: are taking place and the ability for the teams of
Speaker 3: people within enterprises and governments can address them. The gap
Speaker 3: is widening, and so again the bad actors have the advantage.
Speaker 3: And now the challenge that a lot of the IT
Speaker 3: professionals have is they have to once again go to
Speaker 3: management say this is a continuing and escalating this is
Speaker 3: probably one of the most difficult jobs in technology, the
Speaker 3: cyber protection, and it's only going to get greater and
Speaker 3: so I encourage organizations to not think about, well, what
Speaker 3: are we going to replace in our tech stack to
Speaker 3: justify the cost of prevention. My view is that this
Speaker 3: is a budget line that unfortunately continues to be need
Speaker 3: to be evaluated. But more importantly, these practitioners need to
Speaker 3: go beyond the technologies they've been using and look at
Speaker 3: the more sophisticated technologies such as the things that we
Speaker 3: we provide a deep Instinct because the same old tools
Speaker 3: aren't going to work against the bad actors. Eventually, the
Speaker 3: chech catches up early on. It's a challenge.
Speaker 2: Lane, appreciate you joining us. That's Lane Best CEO over
Speaker 2: at Deep Instinct. He joins us from New York.
Speaker 1: As you know, Tim, this is a really big issue
Speaker 1: here when you're thinking about how women are continuing, unfortunately
Speaker 1: to lose these C suite seats in corporate America. In fact,
Speaker 1: women's representation in senior level positions at US companies saw
Speaker 1: signs of fatigue for the first time in two decades,
Speaker 1: with gender parity and C suite positions potentially not reaching
Speaker 1: parody until twenty seventy two, according to an S and
Speaker 1: P report earlier this year.
Speaker 2: That's literally a lifetime.
Speaker 1: Yes, that's a lifetime. I will probably be dead that
Speaker 1: hopefully hopefully not hopefully not that hopefully not though, But anyway,
Speaker 1: I digress. But while there are lingering issues affecting women's
Speaker 1: abilities to seek, prepare, and attain business leadership positions, there
Speaker 1: actually are some signs recently of progress, and the total
Speaker 1: number of women enrolled in top full time NBA proms
Speaker 1: this fall by a record setting pace. Here So, joining
Speaker 1: us now to discuss more is Alyssa sayingster ceo a
Speaker 1: fort Foundation from San Antonio, Texas and for some insight
Speaker 1: for our listeners. Forte Foundation is a nonprofit designed to
Speaker 1: increase opportunities for women in leadership through access to business
Speaker 1: education and professional development. Thank you so much, Alissa for
Speaker 1: joining us. And I was looking through this latest report
Speaker 1: that y'all put together. Here walk us through some of
Speaker 1: the highlights and what drove women's NBA enrollment this fall.
Speaker 4: Sure, so, I mean we're seeing some great results. We
Speaker 4: are seeing women at right now forty two percent enrolled
Speaker 4: in top business schools and that has been increasing, I
Speaker 4: believe over the last five years we've seen a four
Speaker 4: percent increase. We've seen number of schools reach gender parity.
Speaker 4: Eight of our schools have hit that fifty to fifty
Speaker 4: or more mark. But we've also seen some great progress
Speaker 4: at forty five percent and at forty percent.
Speaker 1: And looking through this too, because there's a lot of
Speaker 1: interesting points here, and of course Tim and I were
Speaker 1: just mentioning some of the pitfalls. I mean, what do
Speaker 1: you think before was really holding back some of that,
Speaker 1: because I know COVID was a big issue where we
Speaker 1: saw a lot of women having to pull back from
Speaker 1: the workforce.
Speaker 4: Sure, I think you know, there's a lot of choices
Speaker 4: that people had, men and women when they were going
Speaker 4: back to school during the COVID times. So it's a
Speaker 4: big move and it's a big investment, and you have
Speaker 4: to really think about all the factors. What we saw
Speaker 4: about twenty years ago is that women were not pursuing
Speaker 4: business school because they didn't have a lot of role models,
Speaker 4: They didn't hear from people who influenced them that that
Speaker 4: was a path they should pursue, and so there were
Speaker 4: a number of other factors, but those things were holding
Speaker 4: them back. And that's what we've been working on the
Speaker 4: last twenty years is how to chip away at some
Speaker 4: of those misperceptions they had about business school and business careers.
Speaker 2: You know, I hesitate to tie everything to the election,
Speaker 2: but it's top of mind for so many people here.
Speaker 2: Tuesday is election day, and the US could see its
Speaker 2: first female president in its entire history. It also could not.
Speaker 2: But I'm wondering if you think a change at the top,
Speaker 2: and I literally mean at the top, like the most
Speaker 2: important position in the entire country, if that moves the needle.
Speaker 4: It I mean, I think it absolutely does, because it
Speaker 4: is a change in potential policies, it's a change in
Speaker 4: who you see every day on your television. It's inspirational.
Speaker 4: I mean, that is the role model for everyone. And
Speaker 4: so I think you know why it may not inspire
Speaker 4: more women to go to get their business degree. I
Speaker 4: think it does inspire them to lead, and I think
Speaker 4: ultimately that's the position you want to see a woman in.
Speaker 2: There's also something happening right now that we've been hearing
Speaker 2: a lot about in the context of the election. Then
Speaker 2: that's the idea that more women are going to college,
Speaker 2: more women are graduating from college, and that even though
Speaker 2: as a whole, women are still at a paid less
Speaker 2: than men, there's this idea that when it comes to advancement,
Speaker 2: and this is a lot of been talked about this
Speaker 2: with regard to the male support for Donald Trump, there's
Speaker 2: this idea that men have been left back, and I'm
Speaker 2: sorry that I'm it's hard for me to say that
Speaker 2: with a straight face, just because you look at all
Speaker 2: the data and you see that women are still on
Speaker 2: a salary basis. You know, there's like equal payday as
Speaker 2: months after the first of the year. So but I'm
Speaker 2: wondering how you see that playing into this. Melissa Well,
Speaker 2: I think.
Speaker 4: It's discouraging when you hear that as a top line message,
Speaker 4: because I think you're right. Maybe for a blink of
Speaker 4: the eye, we've seen change happen and women have progressed.
Speaker 4: But I think if you look back decades and centuries,
Speaker 4: we're just now getting to the tip of the iceberg.
Speaker 4: And so so I'm not sure that there's a lot
Speaker 4: to complain about on either side. I think we just
Speaker 4: need to kind of let things settle, and we need
Speaker 4: to make sure that we're focused on, especially in business leadership,
Speaker 4: building inclusive cultures, building opportunities for all of our people
Speaker 4: to advance, and to make sure that companies are focused
Speaker 4: on that, and they're focused on, you know, how to
Speaker 4: engage all of their employees. In this discussion, I think
Speaker 4: it's an unnecessary really to say men are not advancing
Speaker 4: at the same rate as women, especially in business leadership.
Speaker 4: I mean, there are some other societal things that we
Speaker 4: want to focus on, and I don't want men to
Speaker 4: be left behind, But I also don't think that's really
Speaker 4: reflective of what's going on.
Speaker 1: Of course, there was a debate, especially over the last decade,
Speaker 1: as more and more people were getting their MBAs and
Speaker 1: how much useful that would be as people were getting
Speaker 1: say CFAs and other things. But when you're looking more recently,
Speaker 1: especially coming out of COVID, how have especially women been
Speaker 1: putting their nbas to work in particular industries.
Speaker 4: Well, I think what you see is a really healthy
Speaker 4: pipeline of women with their MBA, And what that typically
Speaker 4: means is you're going to see strong outcomes in the
Speaker 4: consulting industry and financial services, in consumer package goods companies,
Speaker 4: and in technology. I mean, those are kind of the
Speaker 4: four top recruiters that are coming to NBA campuses. It
Speaker 4: also means that more women are going to be starting
Speaker 4: their own businesses because they're going to be going through
Speaker 4: these incubators that are on these business school campuses, and
Speaker 4: that's really encouraging as well, given the lack of funding
Speaker 4: in VC. You want to see more companies being started
Speaker 4: by women and being successfully funded, And.
Speaker 1: Are you starting to see that in the data as
Speaker 1: well as far as starting their own companies.
Speaker 4: I mean, we're definitely seeing women advance. I mean, so
Speaker 4: we've been doing this work for twenty years and I
Speaker 4: think you're seeing them just becoming eligible for these very
Speaker 4: senior C suite positions. So I do think there is
Speaker 4: a robust pipeline. I think companies do have to continue
Speaker 4: being intentional about how they advance all of their employees
Speaker 4: and are they providing career roadmaps and ways for women
Speaker 4: to advance and making sure again that they're focused on
Speaker 4: that culture and really engaging all of their potential leaderships
Speaker 4: in that conversation very transparently about how they see them
Speaker 4: progressing to the top.
Speaker 1: And ultimately, I mean, we only have about thirty seconds left,
Speaker 1: But what do you think really needs to change in
Speaker 1: order for this to accelerate here and change things?
Speaker 4: Well, I think in business school, I mean we're getting
Speaker 4: very close to parody, and so I would say the
Speaker 4: big thing that needs to change is once those women
Speaker 4: have graduated, how are we making sure that their advancement
Speaker 4: is possible. There's a lot more shoots than ladders in
Speaker 4: a women's career, and we want to make sure that
Speaker 4: they're given those ladders to continue climbing and excelling.
Speaker 1: Thanks so much for joining us. Really great insight into
Speaker 1: all things, and especially such an important topic and great
Speaker 1: question from Tim about obviously at the top and how
Speaker 1: that could potentially change things here. But Alyssa Thankster, CEO
Speaker 1: of Forte Foundation, joining us from San Antonio, Texas. Great
Speaker 1: getting your insight on all of this.
Speaker 2: But Tim, I'm sorry the electric just top of I mean,
Speaker 2: it's a great.
Speaker 1: Great point though as far as like, does that change
Speaker 1: the dynamic when we're at the top though
Speaker 2: It's I mean, I think a lot of people argue
Speaker 2: it's all about representation, that's right,