Commercial OSINT challenges with Fivecast

Speaker 1: Welcome to the World of Intelligence, a podcast for you to discover the latest analysis of global military and security trends within the open source defense intelligence community. Now, on to the episode with your host, Harry Kemsley.

Harry Kemsley: Hello, this is Harry Kemsley. I'm the president of Janes Government and National Security Business. Thank you for joining us on this latest podcast. As many of you that have listened to some of these before will know, we've spent quite a long time in recent months talking about the power and utility of open source intelligence, which we've discussed in a number of different ways. We've also talked about some of the challenges that the analysts in government agencies faces tackling with the rigor of open source information, and then trying to create open source insight and intelligence. What we're going to do today is talk a little bit about some of those real- world challenges and how commercial open source providers like Janes and like our guests, Fivecast, have started to solve some of those challenges and how we are supporting government agencies. For that, as I've mentioned, I'm going to ask a couple of colleagues from Fivecast, an organization based in Australia, operating globally. They're a world leading provider of digital intelligence solutions that enable public and private organizations to explore the masses of data, uncovering the actual insights, which are critical to protecting their communities and I'm going to invite Malcolm. Hello.

Malcolm: Hi, Harry. Thank you for having me.

Harry Kemsley: Pleasure, and Abbi?

Abbi: Hi. Thanks for having me as well.

Harry Kemsley: Hey, Abbi, thanks for both joining. Malcolm is the director of the federal accounts at Fivecast. His responsibilities include a range of things from business development and growth strategies for the U.S. and global clients in the defense intelligence and security sector. He also has a broad background in government management consulting and is an Australian military veteran. Abbi, as it will become patently clear I suspect in the conversation that will follow is a senior tradecraft advisor at Fivecast, and has an extensive background as an open source intelligence specialist. Both, thank you very much indeed for joining, and my co- conspirator as always for these sessions, Sean Corbett. Sean, thanks for joining.

Sean Corbett: Hi, Harry. Great to be here as always.

Harry Kemsley: Great. We do like to start this conversation with a quick level set on what we are talking about in the arena of open source information and intelligence. So Sean, you and I have discussed that plenty. I'm not going to come to you for that. Abbi, I'm going to come to you first from Fivecast. When I asked the question, what is open source information intelligence, what's your view of what we mean by that?

Abbi: Yeah, and I think this is absolutely worth spending some time on because it means a little bit of a different thing to each person I talk to, each agency I talk to. So open source intelligence is actually processed publicly available information. Now, I'm just introducing more terms to you. Publicly available information is content that's generally available to the public. Everyone can access that and review it on their own. So I think OSINT, unfortunately, the reason it means different things to different people is it's basically because come digital information, electronic information because that's where the majority of people and persons are accessing their information nowadays, it's on the internet. So it's morphed a little bit as of late, I think

Harry Kemsley: Malcolm, anything you wanted to add to that or do you agree with that overview?

Malcolm: I would just add that, Harry, I guess it's seemed to have grown in importance in the last 10 years or so, particularly because of the growth of technology, really, and the explosion of use of that technology by everyone, not just, governments, but everyone in the global community. I think that's where its value, perhaps, has risen in importance as well here along side some of the other technologies and the ecosystem, I guess, of intelligence technologies that are out there.

Harry Kemsley: Yeah. I totally agree. It's that breadth and depth, actually, that we're going to touch on with the discussion today around the plethora of platforms that are out there to look at in the open source arena. We'll come back to that point in a second, but I certainly agree with your point, Malcolm, in terms of the key that has begun to unlock the potential in open source information, public available information, is the emergence of technologies that actually work that have started to meet the promises they've been making for a very long time. Sean, any final thoughts on that before we move on.

Sean Corbett: Just really to support what Abbi was saying in terms of the reason it's so hard to define is because if you look at with the traditional and links as you call them open source again and Geo International stuff, it's quite specific in terms of the collection capabilities there. But when you talk about OSINT, it's an amalgamate of the all, but just achieved in a different way that is publicly available.

Harry Kemsley: Very good. All right. So let's get to the main course of this conversation, which is going to be around a real world challenge as I alluded to my introduction, which is that as the agencies and the analysts within them are facing the massive challenges of increased societal and political unrest and all the various things that that might mean in terms of issues for public safety and national security, they're also facing the exploding numbers of diverse online platforms and those platforms come and go. Not only do they increase in number, they also are not always as popular at the beginning or at the end. So we are faced with this huge velocity of change, this huge variety of platforms, and the huge amount of information that's within them. So that's the topic I'm going to face off to today, the platforms that are available, and how do we actually find utility in those platforms whilst tracking the issues across potentially multiple platforms? Abbi, I know that's something that you have a great deal of expertise in, so I'm going to come to you first. Can you, first of all, help us understand how that landscape of the platforms that we face in the open source environment has changed, why that has been the case? Then, we'll move from there, perhaps, later to the," So what?" for the analyst. Abbi?

Abbi: Yeah, absolutely. If you don't mind, I actually want to go back to a point that Sean was making about the meshing of ints and sources online. I think that open source intelligence, the meshing of these ints into open source intelligence, because they're now coming available to the general public, albeit a little bit hidden is super important because human intelligence, signals intelligence, imagery intelligence, these are all of data that we see online. We share imagery when we post on Instagram. We are communicating and replicating human networks online because that's the easiest way to communicate nowadays with everything going on with COVID. So these individuals have now had to get smart on open source because that's how it's being conducted nowadays. That's where their information is coming from, and one of the most salient examples I came across for example, human intelligence, you're gathering information from recruited persons or assets. People are talking online nowadays, so think instead of recruiting an asset by meeting them in a bar and chatting them up, you're in an online group that's talking about extremist activities. You have to convince them to relay some information, or instead of surveilling somebody on the streets and trying to see what they're up to, what nefarious activity they're doing, you might just look at where their phone is saying that they are, or where their geolocating themselves when they post on social media. So I think a lot of these things have an entire new nexus online, and I hope that emphasizes the transition you are trying to make, which is not just the data itself is expanding the way we're assessing that data is expanding and the locations we can do that is expanding. for open source intelligence, the platforms can sit in a couple of different places. First of all, they can be on the surface web. They can be in the deep web. I think for a lot of us, when we think of open source platforms, we probably instantly think social media sites, and that's not completely comprehensive, but I think that's a big chunk of what we on because almost everybody has at least one. They created their MySpace back in the day, or they have their Facebook and their Instagram now. So those are, albeit not everything, they are important for us to chat about because those platforms are growing on their own, and they're doing that by either thinking of new ways for people to communicate and connect online. They're servicing new communities and making them more able to chat with one another and connect online, or they're actually enabling and protecting the actual user a little bit better, which we'll get into more. But they're developing all these new capabilities and they're appealing to new types of people and it's led to this explosion. Everybody's releasing a new platform. Everybody's adding a new social media account because they want to connect in a new and unique way. So that, I think, speaks to how all of this data is coming out and why this is so confusing, because I'm pretty sure every other week there's a new platform that's coming out that people want to try.

Harry Kemsley: Yeah, for sure. You alluded to it in your comments there. Sean, I'll come to you in just a second if I may. There are real trends in there in terms of the type of data that's being transferred. So initially, as you see said, a lot of that would've been text based, then it became text with pictures, then it became text with pictures and now with video, and all of that is becoming increasingly complex for the analysts to both delve through and find the utility in it. Sean, I can see you wanted to comment. Over to you.

Sean Corbett: Yeah, I was just reflecting on the environment, the fast- paced environment that Abbi was talking about. Really the," So what?" from that is that if you look at the commercial world, it is probably so much better positioned to respond, react, and adapt to that changing environment with the agility it can, then government organizations, which as we all know, take time to develop that capability. So this really does read into and lean into the open source capabilities and what it can bring to the party.

Harry Kemsley: Just before I come to you, Malcolm, with your point, one of the things I'd like to go to, Abbi, is why do people move around on these platforms? I mentioned earlier in my brief inject there about the text to pictures to video, there's that sense of the newness of conveying what I've been doing this weekend by video rather than by picture. But what are the motivations? Why are people moving around the different platforms? What's pushing them from one platform to the next?

Abbi: Yeah, that's a good question. I like to bucket the ways or the reasons why people move around into two big categories. Someone can add a new platform into their online life because as they are internally motivated to add that, or they could be externally motivated to move to that new location to communicate. Just to describe those a little bit further, internal motivations could be there's that new cool feature that they want to try out. So I know being Facebook user back in the day when I found out," Oh, my gosh. I can just share photos on Instagram, I would rather do that," I moved to that platform. So now you have this new footprint in place. Same goes for Twitter when people are like," Oh, I can just share my forward take on a current event. I definitely want to do that. I don't want to upload all of my thoughts and feelings to my family on Facebook." So I think that new feature of interest can internally motivate somebody to just add a new platform. The second, and this is something we're seeing as huge and in the public space, just how we're reacting to this is privacy. People are suddenly aware of the digital trail that they're leaving in the online space and it makes them increasingly nervous and concerned. So they might move to a new platform because they perceive it, and I'm emphasizing" perceive" here on purpose, they perceive it as more secure to them. So they might see Facebook in the news and Facebook might be using their data in a way that they didn't like, so they jump to a new platform. I used the example Instagram before, Instagram's owned by Facebook. I'm curious about the differences in data processing there. I leave that up to the users to weigh whether or not that's appropriate on their end, but that can motivate people. They might completely leave social media and go to more anonymous, blogging type locations to communicate and connect with people instead, because that really pushed them to. Now, a last internal motivator is there's a new community that they want to connect with. They've discovered a new interest, a new hobby, a new person that they really enjoy the perspectives of. They want to connect with them. So they might move to wherever that person prefers or wherever that community prefers to communicate. So they just want to be a part of the in group, and they'll move there to communicate. Now, all of this leading up to the big external motivator for moving between platforms, if you are banned, if you are unwelcome in a certain space, if you are de- platformed or just, generally, you're being harassed, that can be a huge motivator to get out whether that's because you're like," Oh no, I'm not welcome here. I'll go somewhere else," or you literally can't communicate there anymore. Your account has been suspended and you have to find a new way to meet with your either online network or your offline network. You need to find a seamless way to communicate with them.

Harry Kemsley: Perfect. Malcolm, thanks for your patience.

Malcolm: Yeah, no, I just wanted to comment there, and I think Abbi was making a bunch of great points around the motivators. I just wanted to talk very briefly and just talk about this challenge really demands, I think, as an automated response to some of this, because obviously manually trying to track people as they move and transition across these platforms is a very intimidating hurdle for agencies and people who are trying to protect communities. I think the volume of the data, as we've all said, is already well beyond human scale, so just trying to do that. Even semi- manually, where we see that with some of the people we work with, there's not a lot of value in that, particularly if you get to a point where it can't be actually assessed for risk because it's not the format that allows that. So I just wanted to put that point that I think this is one of the confluences, I think, of the technology is now the ability to actually do that in an automated way.

Harry Kemsley: I completely agree. Actually, as Sean said earlier, the fact that the commercial world is starting to solve those technological problems and, actually, actively going after this problem is because we are commercially motivated to do so. Let's not be afraid to say that, and that motivation generates great outcomes. The same motivation can't be true for the government agency that is working within a fixed budget against us specific set of policies. Abbi, I saw your hand come back up.

Abbi: Yeah. I just wanted to slip in a quote that I heard from one of our partners with Fivecast. We did a video with them at DeliverFund and their statement just captured really perfectly, I think, the need for an automated solution. They said," Technology is part of the reason why this challenge exists nowadays, crosstalk the platforms. Technology has got to be a part of the solution and it's going to be the easy way to counter this problem set." I just thought that was such a succinct way of saying, yep. We got to be part of automating and overcoming those set of challenges that tech presents.

Harry Kemsley: Yeah. Perfect. I'm going to move us on, although, I sense there's probably a lot more we could go into there. Let's start talking about the," So what?" for the analysts. Now, any listener on this podcast who's an analyst probably knows most of what we've been talking about in terms of the challenges that we face, but what are the things that they can do? What are the things that matter to them that they could get out of an understanding of how to use technology, how to use a commercial partner? What are the," So what's?" we can get from this discussion about platform transition, platform spreads, increasing numbers of platforms to face? What can we do with that as an analyst, Abbi?

Abbi: Yeah, I think first of all, having sat in an environment where I'm faced with be ever- expanding number of platforms to pay attention to, I just remember thinking to myself," So not only are you telling me any to pay attention to blogs, to social media, all the news social media, the websites, the surface web, the dark web, but people are going to be rapidly jumping between each of those spaces, and I have to be able to effectively interpret the threat from all of those spaces?" It's overwhelming. So I think you talked about the three Vs in one of our earlier discussions that the volume, the velocity and the variety of data are the challenge. I think for the analysts, the" So what?" is they need to find an effective way to cut through that overwhelming feeling that the data presents. I think for me, when I was sitting in that space, I summed it up into three challenges that I felt like I could overcome, the access to the data. I'm not going to even be able to begin to chip away at the problem if I can't see where people are communicating, so I need to be able to get my hands on what's going on. I have to access that data. The so second thing is, I need a way to store it so that when I begin interpreting what's going on there, I have a place to go back to. So as you all know, the internet is full of highly perishable data, so I might look one day, something's there, I look back the next day it's gone. If I can't store it after I access it creates a whole new set of challenges for me. Then lastly, is once I have that data, once I've stored it, I need to be able to prioritize it. What should I look at first? What should I interpret first, and how can I actually visualize or organize this data in a way so that I'm looking at the biggest threats, the biggest concerns first, and I can actually see from those communications, from those data pieces that I have an effective understanding of where they're communicating and maybe even I can identify where they're moving to next or what threat they're presenting next? So prioritization and organization are the last challenge.

Harry Kemsley: I like that summary of those three challenges, the access without it, nothing starts, the storage for things that are going to vanish, maybe that's the fourth V after velocity, et cetera, as the fourth V, but equally the ability to prioritize. I guess, Sean, if I come to you in just a second with a question about prioritization, because that's been at the center of intelligence tradecraft for as long as people have been worried about intelligence and in the tradecraft associated. So I'll be interested in a second, Sean, in your views about a prioritization in this technology- rich social media platform problem. But in terms of prioritization, Abbi, in your own experience, what are the drivers for that prioritization? How do you know what the priorities should be? Are they because they align most with your tasking or is it something else that's helping you understand? What is the priority that I should be going after?

Abbi: Yeah, I think prioritization can be a couple of different things and I said that at the end there. I think prioritization can be your mission critical items that you are supposed to focus on, your collection requirements as an analyst, you want to prioritize based on those. If you have an area of responsibility, a region that you're focusing on, you don't care about every single bit of online data and social media that's happening in that space; you care about specifically the mission, critical activities and communications to you. So for example, if I'm looking to track new weapons development taking place by Iranian or Iranian offshoot groups, then I don't care about every time somebody talks about anything in that region. I care about when they mention the development of those weapon types. When I mention facilities where those weapon types might be built, I want to focus on those subsets. So priorities, for me, are going to be communications that fall into my collection requirement. The second priority for me is ensuring I'm adequately answering those first two challenges, access and storage crosstalk My second priority is making sure that when I'm looking at this, have they jumped to communicate somewhere else? Is the real conversation happening somewhere else? Is there a gap in my intelligence, which is, again, like you said, a tradecraft question, as old as time. I know what I have, but I can't assume that everything I have is what's going on in this space; whereas, my gap is the conversation happening somewhere else. For OSINT, a lot of the times that means the movement to a new platform like we were discussing earlier, so identifying that movement, identifying maybe indicators of those internal motivators that we were talking about earlier so that I can maybe preempt the move even, and just follow them as they go. So those are my two priorities as I see them.

Harry Kemsley: Very good. Sean, that sounded, to me, like a very similar thought process to the way that intelligence has always been prioritized, mission critical, and then indicates some warnings that help you understand where to go next in your intelligence collection. Does that resonate with you? Is that how you see it, what we heard from Abbi?

Sean Corbett: Yeah, and I would take it up as a higher level. It is really good to hear Abbi is clearly a brilliant analyst, but for me at the more senior level, you've got to set the right demand signal. You've got to really get that into the detail of what it is that you want to know and why you want to know it. So we used to, when I was an analyst, used to say, There's no such thing as stupid answers, just stupid questions," and there was some truth to that because it was like," Well, tell me what you know." Well, in order to what, because there is so much data out there and so much information that unless you really drill down into," This is what we need to know, and this is why we need to know it," that you've got no hope of actually being able to do the triage and then the management, et cetera, that Abbi's been talking about, unless you've got a really good idea. That requires a lot of skills between the analyst and the senior commander, but it requires an intelligent senior commander to really understand how to use the capability better. So for me, it's all about setting that requirement in the right way.

Harry Kemsley: Yeah. So I guess the," So what," from that discussion, guys, is, as the analyst, you've got to be asked a question that helps you do the prioritization so you know where to go, what you've got to access, what you've got to store and then what you've got to go after, and if you are the decision maker, make sure you do provide that guidance for prioritization; otherwise, it's almost an impossible task, the very variety and velocity and volume of all these things and the fact that they vanished all three, as I said earlier, and makes it impossible without those prioritizations. Let's move the conversation now from these initial," So what's?" to some examples of where this capability that we have in the commercial environment with Fivecast can actually drive foresight for the analysts that's sitting behind the firewall that maybe doesn't have access to the kind of capabilities that they would like, but could get through an organization like Janes or Fivecast. Do you have any examples, Abbi, that we can talk about easily on an open line where we are able to give actionable insights from this open source capability that has been built largely through technology, as we said earlier, but can actually drive inside the building behind the firewall that can actually get them to move their exquisite capabilities into the right way?

Abbi: Yeah, and I almost think before we get into the exact examples that understanding the value of open source intelligence and why they should even care about it in the first place is helpful. The volume, variety, velocity, the vanishing, all that stuff is great and we're overwhelmed by it, but if somebody is not even motivated to overcome those because they don't see the value in open source intelligence or publicly available information, they're going to look at those challenges and say," Well, I don't even care," and they'll move on and say," I would rather look at this information that's in process, curated as classified," whatever type of data that they prefer, and I would view the value of open source data, a couple of different ways. I would say one, we alluded to it at the beginning, but people are increasingly moving their lives online. This specifically the digital data subset of open source intelligence, but general data, online publicly available information, it's now so much more accessible online, because everybody can pretty easily get internet access and see that data. So I think the value is that there are actually unique data types online, and you can see representation of persons online that actually don't even exist offline anymore. So if you're not looking at these open source platforms at this publicly available information, you're missing the entire conversation. You're missing all of those indicators and warnings. You're missing all of that important data that you need, so the gap exists because you're ignoring not just a source, but the data itself. The second big value of open source data is it's relatively cheap to get access to that data. You just take someone like me, wind them up and just set them running and they can look at a lot of different information online and they can find things that maybe would've been a lot more expensive to find other ways. We talked about human intelligence earlier, and I alluded to recruiting an asset or surveiling somebody. The cost of a surveillance team is insane. If I can just look at their social media and see where they're tagging themselves and adequately assess the validity of that information, I have now saved a lot of people's time and money in getting that content. So it can serve as an effective, almost a replacement for some things, and then maybe tipping and queuing for when those inaudible are necessary. So, like I say," I found this in open source, you only need this 10% gap filled with your surveillance. Can you do that?" I've now saved them a ton of time. So it's cheap. It's effective to get that information. It's quick to get that information. Then lastly, just open source intelligence, publicly available data, especially online, it is communicated quickly so I can get really rapid updates on the ground from people in a situation so I can have good situational awareness to what's happening. So the speed of the data, and maybe even the background it provides me as an analyst is there and I wouldn't have been able to get that from another space potentially. So I would say those three categories are important just to remind people that open source intelligence, publicly available data, it has its own unique value in and of itself that we should consider and emphasize before we go into, maybe, the examples.

Harry Kemsley: Yeah. Very good. I like that very much. It reminds me of a conversation we had with somebody else recently, Sean. I think it was with Terry Bush when he talked about the context you can get from open source because, and I think it was Michael Horowitz who said in another podcast we did, because agencies aren't very good at retaining the legacy content. They don't store it. They don't retrieve it very well if they have stored it and, therefore, they end up looking at everything from almost first principles every time. Whereas, the open source, particularly the commercial platforms, will be able to provide them with a foundational understanding of almost anything because it's been stored and is retrievable and usable. Malcolm, you've had your hand up for a second. Let me just go to you quickly before I go to the next part, go back to you. Go ahead.

Malcolm: Yeah. No, look and Abbi actually was reading my mind as well in that just how complimentary OSINT can be to other forms of intelligence and, perhaps, previously not seen in the same light and, perhaps, because it's not classified information sometimes seen as, perhaps, not as worthy as some of the other ints. Abbi mentioned humint teams, and just how powerful OSINT can be for those teams as they attempt to verify and validate agents or even just manage the risk associated with some of those operations. It's not the only thing, and it's certainly not the driving force, but it can be a real rich vein to tap, I think in terms of other technologies and other information that is, perhaps, not readily available elsewhere. So yeah, I think a really good discussion.

Harry Kemsley: Yeah. I think there's also a recognition in other parts of government and we are talking here in our mind eye, I'm sure, principally about the intelligence community of the national security ilk. Come with me down the corridor at another part of government, we spoke to one recently, Sean and I, in the diplomatic environment. The diplomats spend their entire lives in the" open source, publicly available domain." Sure, they access to people that not everyone would have access to, but that reality about the power of open source in the diplomatic environment is unquestioned. Come with me back down that corridor to the IC, as you were saying, Abbi, there is, perhaps, an institutional bias away from the open source because it is more difficult to verify, it's more difficult to get; and yet, when you can share it more easily, when you can and get to it more cost effectively and how powerful it can be, it's surprising that we don't do it more often. Sean, did you have anything? Did I see your hand up from you, Sean? No?

Sean Corbett: No. Apologies.

Harry Kemsley: All right. Well, let's move on then, to finish with. Any other examples we can use of where open source has been the driving force? Just to give you some time to think and, Sean, you've heard me talk about this before I know a couple of times, I remember the scene around the horrors of the end of the Boston Marathon, when they had the Boston Marathon bombings. Even back then when mobile phones were relatively new, you could see that the open source environment was being pumped full of information by the telephones that were being held up, either taking images, capturing what's happening on the ground, or indeed, talking to other people about what was going on that I'm safe and so on. At that moment, understanding such as it would've been of what had just happened, was not in the classified domain. It was only in the open source domain. There is a sense of timeliness there in and around a given event that I think is worthy of note in terms of a real world example of the open source environment driving now a lot of public agency activity, of course, after something is horrendous as that. But what other examples can we draw, between the four of us, of where the open source environment and has been preeminent and really driven the classified environment? Abbi, any thoughts?

Abbi: Yeah, absolutely. I like your example around rapidly developing events because getting at the value of open source intelligence, that is one of the unique values of publicly available information and OSINT. For a lot of us in this space, I think the past year or so have given us a couple of examples. I think one of them that we all think of is the events surrounding January 6th in the United States. Not only was open source intelligence key to preempting that this would take place. For example, looking at the conversations, the escalating nature of them, the planning of events, the coordination, the mobilization of actors that took part in these events, all of that was sitting on social media sites and in these online spaces. Preempting could have been a lot more possible with if you have a access storage and the ability to prioritize that data. Afterwards, once things really sparked understanding what happened and how it was actually escalating on the ground, so not just escalating, leading up to the events, but what was taking place, who was at risk, where should we place resources, was guided a lot by the videos, the streaming that was taking place on the ground, people sharing photos of themselves in certain locations, people actually just putting out text data of what they were seeing and viewing on the ground. So that's another example similar to yours of if you were ignoring those data sets, you were missing a big inaudible sure.

Harry Kemsley: Yeah. Yeah. Malcolm, any thoughts?

Malcolm: No. I just agree with the points that Abbi made, that unique value of things that are actually happening. My example that I go to is the NEO out of Afghanistan, which, we all saw play out and, essentially, online; people communicating where they were online, trying to make their way to the airport and, obviously, security agencies and the military on the ground trying to communicate with them as well through any means possible, really, particularly when you have a breakdown of the typical and other established means of communication and interaction, things playing out on Instagram as we all saw, I think.

Harry Kemsley: That's a great example. Actually, since that time, Janes, with a couple of partners has been working very closely with agencies trying to get the remaining people who are still in Afghanistan out of Afghanistan, if not through a center of the airport, some of those smaller airports airfields around the country. In just a moment, by the way, as we start to wrap up, I'm going to come to you with a magic wand. So to give you some idea of what you're going to do with that magic wand, I'm going to give you the opportunity to say," If I could do just one thing, one thing that would change the agency's ability to do the thing they need to do in this open space, it would be X." You get the chance to think about what that is whilst Sean, any other examples, Sean, from yourself in terms of open source preeminence in the power that can bring?

Sean Corbett: None that I should probably mention here, but while I'm on and just to take the V thing a little bit to stage fully, which we haven't talked about, which is probably another full hour's conversation is so we've done six Vs. There's another two, which is probably the same one is validation and verification. That is so important with intelligence that you've got to have more than one source to validate what you've done and to provide that level of confidence. Because when you're scaling social media, there are many different types and so many different people on, then that provides a very strong source of validation. Then the next bit, which is completely not linked, and I can't think of a V, but the scale of it, so sentiment analysis, which you can do in the digital domain very, very well if you've got those numbers, which you can't always do particularly well on by other means is another really important source. You can tell very quickly if something really bad has happened in an area just by what's going on social media, assuming it hasn't been shut down so, and that does lead into the validation bit, because say a bomb's gone off or something you'll know pretty soon whether it has or not by doing that. So I just wanted to add that, but I haven't got any more examples. crosstalk.

Harry Kemsley: The veracity piece, one example that I'll just throw out before I come to you, Abbi, in just a second is the use I've seen of open source for plausible deniability where an agency that knows very well what's happening on the ground has waited, in fact, in some cases, asked a commercial organization to get something out in the public domain because it can then, talk about it without having to reveal source and that plausible liability, by the way, although it doesn't quite fit the examples I was describing, it's certainly a powerful tool that can be used with open source by agencies, and I've certainly seen that. Abbi, you had your hand up.

Abbi: Yeah. I noticed some of the examples that we were giving, I think are largely around these rapidly developing events and staying on top of them. I wanted to maybe bring this back to a reliable source in any circumstance, not just these crises movements. Open source intelligence, publicly available information, in my experience, has been a really reliable source when it comes to understanding the behaviors, the intent, and the capabilities of extremist networks and actors, whether domestic or abroad, I can really readily understand their ideology because they seek to recruit and engage with one another and create their nice little echo chamber online because that's the best, easiest, low barrier way to connect, puts them at less risk. They can stay anonymous if they want. Second, they are pushing out their capabilities and pretty overtly. They encourage people to do exactly what they want them to do online in those spaces once they're able to recruit connect, they are saying," This is what our plans are. This is what our purpose is," from an extremist perspective, and I'm seeing increasingly that a lot of these groups have some footprint and that's the centerpiece of their planning and their mobilization efforts. So if you're not looking at those spaces when you're considering that type of threat, you might miss a lot of the communication, the information, the intelligence that's going on.

Harry Kemsley: Yeah. I like the point you made earlier, which links to that about the fact that you're not in the open source environment, in some cases, you are never going to find something, because it's just not available other than in the online open source environment. Okay. I am going to come to the magic wand point now for Malcolm and Abbi. So the question was as posed before," If you could do just one thing that would improve the lot of the analysts, what would it be?" I'm going to come to you first, Abbi, because your hand is up, but probably from the previous time. What's your magic wand, now that the genie's out the bottle?

Abbi: So I think magic wand, if I only could do one thing, it would probably be more process and education oriented from an open source intelligence perspective. I think I wouldn't even label open source analysts as analysts, I would label them as collectors. They are collecting and exploiting data, and I think if you just relabel and reframe the whole capability of this type of analyst or collector or exploiter, you're going to increase the capabilities of your team as a whole to make intelligence out of that data, because you have people dedicated to interpreting and pulling that information. So I think that's more of a process thing, so I think I would relabel that and reorganize to ensure that they could be exploiters and collectors. I know you only said one, but I'm going to add another. I think the second thing I would give to this space and to agencies to make them more effective is to take the burden off of actual analysts, not collectors, to really collect that data. Collectors can do that. Analysts, themselves, should be faced with spending the majority of their time making important judgment calls and interpretations of data. So if we give the collectors tools to rapidly acquire collect store and prioritize data, they can be rapidly collecting and pushing to analysts so that the majority of their time is just spent on making those judgment calls because that, at the end of the day, is what intelligence is all about is you're taking information and making it actionable and relevant for a unique audience. So emphasizing and using technology and reframing the process so that it allows that, I think, is what I would do.

Harry Kemsley: Okay. Well, Sean, I'm going to come to you in just a second about the idea of in quotes," separating collector from analyst," but that's the point I know you will want to spend a moment on. Malcolm, your magic wand moment?

Malcolm: Yeah. No, look, Abbi had two good points. I would just make the observation as well that at the end of the day, the technology is there to enhance the human, obviously, not the other way around. The tail shouldn't wag the dog, I guess, is one of the other expressions. I think where the technology is really powerful now an, perhaps, where the magic wand has gone is now we're at a point, I think, where it's not just a collection, which is powerful, but the analytic side as well, where you can actually ask specific questions of the data in a way that you couldn't previously. Then that, of course, doing that at scale really is the true value of that augmented intelligence for an analyst. But I'll just leave it there, Harry.

Harry Kemsley: Yeah. Thank you, Malcolm. I totally agree with that. I'm a big believer in the AI being augmented intelligence, not artificial intelligence. It's a much better way of uncoding AI. Sean, any thoughts on collectors, and not analysts.

Sean Corbett: Yeah. I thought Abbi was being controversial there by trying to rename analysts collectors, and she will know only too well that analysts are very, very possessive about their capabilities, but actually, it's not renaming, it is dividing them up. I'm not sure I would agree with that. I think in the traditional days, absolutely, collection managers, I used to be one, actually, specific skill set that requires specific skills to actually achieve I get the answers to questions, which is different from the analysis, the,"So what?" and the," What if?" What I would say today, I think, actually, and I think the next generation is better equipped than certainly I was to do it, is an understanding of the limitations of collection, where it comes from, how it's done, and all the disinformation, misinformation, trust it, all that stuff. I think that's almost, you've got to be both of those things to be a good analyst because at the end of the day, it's confidence statements, et cetera. So I would probably have a good discussion over a beer on that one.

Harry Kemsley: Okay. I would never ask a question without actually having an answer to that question for myself. For me, by the way, it's the same one I've used a couple of times when I've asked the magic wand question, it's data literacy, the greater the audience really understands the power of data, the ability to manipulate data or rangle, which I believe is the modern word, then the greater the chances that they're going to really understand the power of that confluence of classified and unclassified data in the open source domain. That, for me, is the magic one for me, getting people's level of literacy with data to a level where they can really grapple with it. I don't mean everyone becomes a data scientist, by the way, that's not it necessarily. There is a level of competency with data, generally, that I think needs to be enhanced. Now we are a little over time, but that's because the conversation's been fascinating and thorough. Can I, first of all, say a huge thank to you, Malcolm, and particularly to you, Abbi, for the contribution you made, which has both been immense. I think we've covered the topic really well in terms of what are the complexities out there? In this case, we started off talking about the variety, the velocity of change of platforms, the challenges that present in the open source environment, particularly in the social media environment. We looked at the motivations that drive those dynamics, both internal and external, which I think is a great way of looking at it, Abbi. Thanks for sharing that with us. But we also looked at the,"So what?" So what does the analysts do? How does the analyst grapple with those challenges and, indeed, use them to their advantage, which I think we've touched on. Then we finished there, I think, with some great examples of where open source can be preeminent. It can drive the conversation both in terms of time- sensitive, highly- reactive environments, as well as the longer term, giving the legacy, giving the context, giving the foundational intelligence around what's going on, which is so difficult sometimes to find inside the machine. So Malcolm, Abbi, thank you both very much. It's been a delightful conversation. As I've said, I think on every single podcast, Sean, there are probably about four or maybe 500 topics buried in there, which we could at least an hour on each in the future. So if you're both willing and able, I'd really like to invite you both back to tackle some of those. Abbi, thank you very much.

Abbi: Yeah. Thank you both for having us on. I agree with Sean that I want to talk about collectors versus analysts at separate times. So this is really great and awesome that we can maybe speak to a little bit of these challenges and, hopefully, give people an idea of how to overcome them.

Harry Kemsley: Thanks, Abbi. Malcolm, again, thank you.

Malcolm: Yeah. No. Thank you, Harry. Thanks, Sean, and we look forward to speaking again soon.

Speaker 1: Thanks for joining us this week on the World of Intelligence. Make sure to visit our website, janes. com/ podcast, where you can subscribe to the show on Apple Podcasts, Spotify, or Google Podcasts so you'll never miss an episode.