Latest / Technology Now / What bots mean for business: Technology Now
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- Aubrey Lovell: Hello and a very warm welcome to Technology Now, a weekly show from Hewlett Packard Enterprise, where we take what's happening in the world around us and explore how it's changing the way organizations are using technology. We're your hosts, Aubrey Lovell. Michael Bird: And Michael Bird. And in this episode, we are exploring the rise of botnets across the internet and what can be done to counter malicious, often AI-driven profiles, spreading misinformation on social media, opening us up to the risk of cybersecurity threats, buying all those Taylor Swift tickets, makes my blood boil. Anyway, we'll also be taking your questions to the expert around AI and computing on the edge, and of course, we'll be looking at the books that are changing the way that you, our beloved audience, see the world. So, if you are the kind of person who needs to know why what's going on in the world matters to your organization, then this podcast is for you. And of course, if you're enjoying it, do you make sure you subscribe on your podcast app of choice so you don't miss out, right Aubrey? Let's get on with the show. Aubrey Lovell: Okay. So bots are big news at the moment. Live Nation CFO and President, Joe Berchtold, recently called for tighter laws on bots, blaming bot nets for scalping tickets to high profile concerts such as Taylor Swift's upcoming tour, which was plagued by a vast network of fake accounts, not only buying up tickets the second they went on sale, but trying to crack into their servers to gain access codes. A lot of Swifties are very angry. Michael Bird: Very angry Swifties. And meanwhile, it seems like only yesterday that tech billionaire Elon Musk, spent 44 billion dollars purchasing Twitter, which was nearly scuppered by the vast network of fake accounts on the platform. Now in Twitter's case, the site argues that of its 285 million active users, 5% of them are bots, spam or fake accounts. However, independent research by SparkToro and Follower Wonk came to the conclusion that the real number was actually closer to 20%. Wow. So that is 56 million active fake accounts on Twitter alone. Aubrey Lovell: And this really does create a large threat for nefarious activities, right? From manipulating follower numbers and buying likes, to spreading misinformation, promoting scams, and even falling into the antics of cyber criminals. And that's a problem that goes well beyond social and retail platforms. So with that said, Michael, who do we have with us as our very first guest to talk about it? Michael Bird: Well, we are delighted to be joined by Matt Armstrong-Barnes, who is a chief technologist at Hewlett-Packard Enterprise. Matt specializes in AI and edge computing with a little sideline in technology in cybercrime. Now, for clarity, that's in technology to tackle it, not for committing it, at least I don't think it is. Anyway, Matt joins us today. Hey, Matt. Aubrey Lovell: Hi, Matt. Matt Armstrong-Barnes: Hello. Thank you for having me. Michael Bird: Matt, why do bots and fake accounts matter to organizations? Matt Armstrong-Barnes: First off, let's look at what a bot is. So a bot is defined as an autonomous program that interacts with systems or users and it's focused on repetitive or predefined tasks. So that matters to organizations because they have lots of repetitive and predefined tasks that need to be done, but also there are nefarious actors, bad people, who also have lots of repetitive and predefined tasks that they need to perform. And as a result, you need to understand, both, how bots can play a proactive and also a negative role in interacting with organizations. So that, from a social media perspective, you could be getting the right information out there, but also understanding how these nefarious actors are using this type of technology for illicit purposes. Aubrey Lovell: So Matt, let's back up a little bit. When we hear this term 'bot' thrown around, what does that mean? Matt Armstrong-Barnes: So social media platforms expose something called an API, an application programming interface, and I'll explain what that means. So let's pick a nice example, like recommending Christmas gifts. So in this instance, we would have an algorithmically driven program that is a bot, that is looking for posts about Christmas gifts. When it sees a particular gift that falls in line with what the algorithm tells the bot to do, the bot will then repost, retweet, like that post. But it also needs some memory. It needs a database to make sure that it is not repeatedly recommending the same thing. And lastly, it needs a way to interact with the social media platform, which it does through this special thing called the API, or application programming interface. Aubrey Lovell: Matt, what are the risks, that you would say, bots pose to organizations around the world? Matt Armstrong-Barnes: Well, they do a few things. Firstly, let's say, so I think at the beginning, you gave some stats. So let's say we have our nefarious actor who has access to half a million bots. What can they do? Well, firstly, they can amplify popularity. So suddenly, somebody can join the social media platform and have a significant follower base because they're all bots. Secondly, they can spread propaganda and misinformation because they can, once again, have quite a large following bases, or the bots themselves can be propagating this. They can also be used as a way of flooding information out to mask genuinely accurate information that social media users would be interested in listening to. And lastly, one of the main areas where bots can be quite dangerous is in something called spearfishing attacks, which is where they are trying to steal something from you, your identity, your credit card number, anything along those lines, remote access onto your machines. So there's quite a lot of ways that bots can be used as well as some of the technology challenges, which is, they can perform denial of service attacks so they can stop sites from running, which means that they can impact the lives of people who are trying to consume those services. Michael Bird: So, I guess, even if organizations, they don't think they're on social media, it's still something they need to be aware of because of the potential spread of misinformation or the spread of other things through other organizations using bots or other nefarious actors using bots? Matt Armstrong-Barnes: Very much so. And I think the other thing you need to be aware of with these bots as people are putting more information out onto social media, bots can be used as way of gathering that information that then allows nefarious actors to target innocent people in a much more active way, and those innocent people can work inside organizations. So what you can do is use these bots as a way of gathering information that you can then use to compromise organizations through compromising an individual's identity inside that organization. Michael Bird: So how can organizations fight these bots? I think you've mentioned before that you need good AI to fight bad AI, so is that basically how they do it? Matt Armstrong-Barnes: EME bots can be very convincing. They can be quite difficult to spot if you're just looking at the language that they're producing. And this is aided by social media platforms restricting the number of characters you can use. The language doesn't necessarily need to make sense. Spotting bots is actually a mundane or frequent task, repetitive task that you need to do, which is one of the things that bots are really good at. Is the person tweeting from the location where they say they are? How quickly are they tweeting? If they're tweeting quicker than a human being can then they can't be a human being. Do they post very, very familiar content with slight changes to the words? Do they have a significant follower base that happened very quickly? Basic things like, do their usernames contain numbers? All of these activities human beings can look at, but it's time consuming and it's repetitive. So what you need is a bot with a friendly algorithm that looks at those characteristics for you, to work out whether or not it's a bot or not. Aubrey Lovell: So Matt, I read a quote recently from you, around... We're talking about the concept of bots and AI and how all this fits together across industries and businesses. AI is a journey, not a destination. So, what advice would you leave with organizations that are considering or wanting to scale their AI for their data and security needs with that considered? Matt Armstrong-Barnes: Definitely. So, artificial intelligence, and bots are no exception, are created using data. And data in any organization, by its very nature, is fluid, it changes, it adapts, it evolves over time. So if you think that you're going to build an artificial intelligence that is one and done, you deploy it and you forget about it, that AI will quickly lose its value to your organization because it does need to be adapted and evolved over time. Secondly, what organizations find is, once they've built AI into their organizations, it's not as difficult as they thought it was going to be. So they then start to look at other use cases where they can execute against this technology and start to bring increased value in. So it is all about taking evolutionary steps on the artificial intelligence journey, bringing it in to start to tackle some key use cases and then continue to execute against more complex ones. But it is all about choosing the right ones up front because if you choose the wrong use case, you never get a second chance to make a first impression. So choose wisely, engage with an AI, bring it into your business processes, and then continue to expand and you'll continue to get the benefits of this type of technology. Aubrey Lovell: Got it. Thanks so much, Matt. This has been a great conversation, really great insights and advice. And for those of you listening, we will drop useful links on the topic in the show notes, and we'll come back to you in a moment, Matt, so don't go anywhere. Michael Bird: Okay. So next, it is down to you, our audience. We are going to open the floor to you to give us your recommendations on books which have changed the way that you look at the world, life and business in the last 12 months. Now, they could be technology based, they could have changed the way that you work, or they could have just made you look at the world in a slightly different way. Aubrey Lovell: And if you want to share your recommendations, there's a link in the podcast description. Just record a voicemail on your phone and send it over. This week, it's Zoe Anderson, a producer from London. Zoe Anderson: So I've been reading Caroline Criado Perez's Invisible Women. It came out in 2019, so still relatively new and very relevant. And I really do think it was groundbreaking in the sense that, it brought to life a topic that people don't really tend to think about, which is the fact that the world is designed with male bodies, male health, et cetera, et cetera, in mind, just because a lot of research and data is censored around men's needs. It really was a sort of seminal text for a lot of people in terms of finding out about this data bias. So for example, some drugs were only tested on men and actually would be very beneficial to women, but we don't know how beneficial because they were just never tested on women. She's really advocating for change in terms of how we collect data and how data bias exists. So yeah, a really brilliant book and would really suggest to anyone, really, who's interested in the topic. Aubrey Lovell: Fantastic. Thanks Zoe. So Matt, while we have you read anything you can recommend to us, recently? Matt Armstrong-Barnes: One of the challenges of the field of artificial intelligence is lots of texts dropped straight into the mathematics and the technical detail. So there is a book that I really enjoyed, it's called Competing in the Age of Artificial Intelligence, and it's by Karim Lakhani and Marco Iansiti, and really, it's business level and it goes into lots of great examples with real world implementations. Michael Bird: Thank you. We'll write that one down and, of course, listeners will include that in the show notes. Right. It is time for questions from the audience and you've been sending in your questions to Matt on the topics of AI and edge computing. Matt, we've got a couple lined up for you now. I'm going to dive into the first one, Abbas from London has asked, "In terms of the way firms operate and normalizing hybrid working culture, what should we watch out from AI in the coming years?" Matt Armstrong-Barnes: Yeah, so we are seeing AI playing a much more significant role in the hybrid space, definitely, and in the places of workplace management, help desks, training needs analysis, because what AI is really great at is repetitive and low value tasks, and the volume of data that is hitting individuals in organizations on a daily basis. It's just a tsunami. And as a result, we need to bring in this concept that Gartner call, which is a sentor, which is artificial intelligence and human beings working together to get the best out of their data and operating environments. And I think the other place where we're seeing is, as people are working much more of a hybrid fashion, security and compliance are becoming increasing challenges as people move out of their traditional work environments. So again, artificial intelligence is playing a significant role because as we spoke about just, AI is both the protagonist and the defender in this role. Aubrey Lovell: So we have one more question for you, Matt. This comes from Jenny from Edinburgh, which asks, "My engineering firm processes a lot of data onsite. How can I use AI to protect my data better and also gain faster decision making? Where do we start on this journey?" Matt Armstrong-Barnes: There's a lot of research and development happening in artificial intelligence playing a role outside of the traditional data center or cloud environment. And when we talk about the edge from a Hewlett-Packard enterprise perspective, we power the International Space Station, we power AI workloads on the International Space Station. So when we have expertise in the edge, you know, you can't get much more edge than the edge of space. One of the things that we are working on is something called Swarm Learning, which is how you get the concept of a flock of birds or a swarm of bees, how you can have lots and lots of intelligences working together where the sum of the part is greater than the whole so that collectively, they are more intelligent than one individual entity. Again, so when it comes to edge based scenarios where you want to deploy artificial intelligence, where you need to have a significantly bigger intelligence scattered across multiple edge locations, then this concept of swarm learning plays a significant role in that. But it is also working in, when you start thinking about data and the role that it plays at the edge, traditional IT security models are starting to be much more challenged. The role of lots and lots of concentric circles around your organizations has a lot of challenges in the modern working environment. So it is about bringing artificial intelligence in as a way of securing that data and playing a role as the defender, because what AI can do through a process called user and entity behavior analytics is understand whether or not somebody's credentials have been compromised, and as a result, they have inadvertently become a nefarious actor within their own organization and in an edge scenario. Aubrey Lovell: Brilliant. Thanks Matt. And again, we'll drop a couple links in the podcast description for more on these topics. Michael Bird: All right then. Now, we are getting towards the end of the show, which means it is time for... Aubrey Lovell: This week in history. Michael Bird: Which is both a look at the monumental events in the world of business and technology, which has changed our lives and also the weekly opportunity for Aubrey and I to just test our vocal chords and... Aubrey Lovell: We have some work to do, Michael, but it's getting there, for sure. So, a very happy birthday to Vanguard Two, the first ever weather satellite, which was launched today in 1959. So happy 64th birthday. One more year, and it's old enough to get a senior citizen's bus pass in the UK. Michael Bird: True story, true story. So, what else? Aubrey Lovell: So the satellite was actually designed to measure cloud cover in a mission lasting 19 days, but a much longer mission saw its position being read from the earth to measure atmospheric drag, a mission which is still ongoing and is due to continue for another 216 years, providing the baseline for our understanding of atmospheric drag. And that's pretty good going for a little ball weighing around 23 pounds, or just under 11 kilograms, for the rest of the world. Michael Bird: Next week, we are going to be heading all the way back to 1455 for an event that changed knowledge and learning forever. Although I didn't really think 1455 was that big in the world of technology. But anyway, if you know what it is, do keep it to yourself. All will be revealed. Aubrey Lovell: That brings us to the end of Technology Now for this week. Next week, we'll be discussing extreme weather events and looking at what organizations can learn from now casting. In the meantime, keep those suggestions for life-changing books coming, using the link and the podcast description. Michael Bird: And until then, thank you so much to our guest, Matt Armstrong-Barnes, and of course, thank you all so much for listening. Technology Now is hosted by Aubrey Lovell and myself, Michael Bird, and is produced by Sam Dta Paulin and Zoe Anderson, with production support from Harry Morton, Alicia Kempson, and Alison Paisley. Technology Now is a lower street production of Hewlett Packard Enterprise. And we'll see you next week. Thank you. Aubrey Lovell: Cheers.