Dr. John Borek
IAFIE Intelligence Education Interview Series - Dr. John Borek
Interviewer: IAFIE Volunteer
Table of Contents:
Question 1). (Author and Professor: Dr. John Borek) Let’s start from the basics. How would you like to present yourself to the International Association for Intelligence Education (IAFIE)?
Question 2). Can you share with our readers what inspired you to pursue the field of intelligence?
Question 3). You have such an exceptional professional and academic background, spanning from Strategic intelligence, Public Policy and Administration, and geography. What role has your educational background played in your professional roles?
Question 4). Dr. Borek, you have experience as a strategic analyst, senior analyst, and analytical branch chief. Can you share with our readers what makes a great analyst?
Question 5). Dr. Borek, you have experience in various analytical roles. How did these positions help you when transitioning to the academic world as a professor?
Question 6). Dr. Borek on your publication - Beyond Information: Analysis, Analysts, and Intelligence. What would you say was the most valuable lesson from conducting your research?
Question 7). How do you see the future of intelligence and analysis, and how should educators orient themselves?
Question 8). What is the work you believe is most representative of your professional life, and what can future analysts, researchers, and intelligence practitioners learn from it?
Question 9). What suggestions or advice would you give to the new analysts and the younger generation?
Question 10). Five keywords that represent you?
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Interview Introduction: Known for his over 30 years of experience in the intelligence community, analytic expertise, and enthusiasm of intelligence studies, in this most compelling interview, Dr. John Borek, a highly esteemed professor of the National Security and Intelligence Analysis Program at the University of New Hampshire, discusses his academic and professional path in the field, providing insight into his career as an analyst and advice to the next generation of IC careerists, and intelligence education educators. Dr. Borek, we thank you once again for participating in the Intelligence Education Interview Series and hope that your research and impact in the field of intelligence studies will inspire our members, as you have inspired me and so many others in your more than three-decade-long journey of analytic excellence.
Question 1). (Author and Professor: Dr. John Borek) Let’s start from the basics. How would you like to present yourself to the International Association for Intelligence Education (IAFIE)?
This might actually be the hardest question to answer since I’m not sure exactly how to characterize myself. As you note in my introduction, I’ve been an intelligence analyst for most of my adult life, both as an active duty Army officer and then as a civilian. But I’ve always loved school, and education more broadly, and I always jumped at the opportunity to take classes, read the professional journals, and attend any training I could. As I settled into my civilian analytic career and had the time to really think about what it was I doing, how the teams I was on were doing intelligence analysis to satisfy our customer requirements, I realized that while there were a lot of opinions about the analytic profession there wasn’t a lot of real research done on it, and what there was just scratched the surface of what we were actually doing. At about the same time, the analytic reforms from the Intelligence Reform and Terrorism Prevention Act were being implemented, for the first time, actual legislation and policy directed how we should do our jobs, and I knew I wanted to dig into that, do my own research, write my own papers and generate some conversation on the profession. So I used my GI bill to pursue my PhD, where I sought to capture what constitutes the analytic process, what it was that analysts actually do, and again, not just individual anecdotes and experiences, but a generalized model. Now, since I always enjoyed the training and teaching aspect of my job as an analyst and senior analyst, bringing on new hires and running the professional development programs, when the time came to leave my analytic career behind, I knew I wanted to move into the field of higher education. Now, I was admittedly a little naïve about how difficult that transition would be; I was in that classic position of a lot of great experience just not in what universities were interested in, and no actual classroom experience. Eventually, I was fortunate enough to pick up an adjunct position teaching graduate courses in government and public policy, and then I was selected for a post-doctoral fellowship at the Army War College, which also gave me the experience I needed to be competitive. So I guess that’s a long way to say I would characterize myself as a very experienced former intelligence analyst and a novice current educator with a real passion for learning new things and the analytic profession.
Question 2). Can you share with our readers what inspired you to pursue the field of intelligence?
Well, I can’t honestly say that I started out looking for a career in intelligence, and not in the analytic side specifically. I was in the Army ROTC program at Penn State because I broadly wanted to give some time back to the country, do something for the country, see the world, and gain some experience in life. I honestly thought I would do my four years and move on. I don’t know if things have changed since my time in ROTC, but as a cadet near graduation, you would submit your wish list of what branches you want to be commissioned in, you know, infantry, armor. Now I don’t come from a military family, so all I knew about the different branches was what I learned in my classes and a little paragraph in the Officer’s Handbook. But I thought that with my Geography degree and my interests, I would be a fit in either Intelligence or Engineering, so those were my number 1 and 2 choices. I was commissioned as an intelligence officer, and after training, my first real assignment was in Korea as the assistant S-2, or intelligence officer, for an infantry battalion north of the Imjin River along the DMZ. That was it, I was hooked, for me there was just something about being an analyst, being that person that put all these different things together, you know, weather, terrain, doctrine, equipment, and come up with the picture that would inform how this unit of 400 men would deploy. I obviously had several different jobs in the Army; they weren’t all analytical, some tactical level collection, other types of staff positions, but I really enjoyed the analytical side, and when the opportunity to apply for what’s now NIU came up, I took it. If I think about why I gravitated towards intelligence analysis, why I pursued that as a career, it’s because I enjoyed the intellectual challenge. I like learning new things and applying them, trying to find out what’s hidden from me; it’s never the same thing day in and day out. As an all-source analyst, you are basically a social science researcher in a hostile, or at least adversarial environment, someone is trying to hide something from you to your detriment, and you do your best to find it. Human behavior is never boring, and that’s what analysts focus on. Now, over 30 years, I’ve had good days and bad days, at times done my job really well and made my share of mistakes, but I’ve never not liked being an analyst.
It’s an interesting question because I think education is much more than just the BS, MS, and PhD degrees. I mentioned my first assignment was in Korea along and then within the DMZ. I didn’t earn any degrees in the 18 months I was there, but I sure got an education. I learned how important a good relationship with your customer is, to understand not just what they’re asking you but why, and what they want to do with that information. To your question, though, the degrees you earn provide the foundation of knowledge you need to be successful and then provide you with the framework for how you see the world. My geography degree has forever imparted to me the importance of space and place to the human condition; I still consider one of my biggest personal wins the time I worked genius loci (spirit of a place) into a finished assessment past the editors. My guess is that people with a business or engineering degree bring that worldview to their analysis. It's not that one is better or worse than another; they’re just different. My time at NIU is probably where I took away that what I was doing was not just a job, but a profession with a history and a future, which obviously influenced how I thought about analysis. So that is the foundation I brought with me to my career, but it’s just the foundation; you have to be open to learn from your experiences every day, to build on them.
Well, I’ve had the good fortune of working with and for many great analysts, and there is no one specific ingredient that made them good at what they did; it was a combination of attributes. So, in no particular order, I think an analyst has to be innately curious, you have to want to know why someone or something is behaving the way it is, you can’t learn that, you either are or you aren’t. Then you have to be forward-looking, not lost in the present or worse, the past. What are the possible ways that tomorrow can turn out, and what would be the unique catalyst that would lead to each happening? Then you have to be confident in your skills and abilities, confident enough to make hard analytic calls despite vague or conflicting evidence. Remember, analysts don’t get easy questions, and too often, analysts will just say enough to say nothing. And I don’t mean false bravado here either, if you don’t know something or there are two or more likely outcomes, be confident enough to say that, and why, what are you missing? I guess that leads to the next attribute, which is tenacity in your research; in the case of an intelligence analyst, that means understanding and using the collection system. If you’re missing something you need to know and you haven’t pestered your collection manager or submitted requests to every collection discipline available for an answer, you aren’t going to succeed as an analyst. Talk to other people working on the same or similar portfolio. Where do they look for answers? You have to be aggressive and innovative in looking for information. Communication skills are important; that’s something you can learn and get better at, and it’s a perishable skill. Getting ideas out of your own head and into a form that is clear and meaningful to someone else is hard. One of the most common discussions I’ve had with new analysts struggling with their first assessments is “what exactly are you trying to say, what do you want me to take away from this.” They get lost in trying to sound smart or with tradecraft verbiage, and the actual message gets lost. Once we work through that, everything else falls into place. You have to take and give criticism well, professionally. Analysis is a team sport, and collaboration makes for better products, whether between agencies or just asking the person in the cube next to you to take a few minutes and read over your draft. There is always someone who knows something you don’t, which will make for a better analytic product. That’s ok, you probably know something they don’t, that’s why collaboration is important. And I guess finally it’s being open to change, to new ideas, whether it’s in the tools you use or the ideas you have about your target. Complacency, or maybe just becoming too familiar with your portfolio and how you think about it, is the beginning of the end for an analyst.
Well, without a doubt, my personal experiences as an analyst have given me the background to speak confidently on the topics I teach, analysis, analytic writing and communication, and an intelligence case study. In addition to that foundational knowledge of the intelligence community, you know how it’s organized, how it works, those universal fundamentals, I think I can bring that taste of what it looks like in the real world. As a senior analyst and branch chief, I evaluated every draft product from my teams, which gave me a lot of experience in focusing on the essentials of good analysis. I didn’t have to be an expert on, say, the use of child soldiers in Rwanda, to know if the product was logically sound, well written, if the citations and sourcing matched the evidence presented, or if confidence levels and source summaries were well reasoned. So now I evaluate and grade student assessments with the same eye, tone, and tenor that I evaluated those draft assessments. When students present their draft topics for their assignments, I offer the same advice that I would give an analyst proposing a topic for an assessment.
And then onboarding new analysts was a part of my job that I really enjoyed. We brought in a lot of bright academic researchers before I left, with no previous experience in the IC at all. Going through the basics, from identifying requirements to querying the databases, evaluating the intelligence information available, that’s all directly relatable to my work now as an instructor. And I think that also helped me personally in working with students who may not have that real-world experience. You know somebody who has worked in an insulated environment, which the IC is, for 30 years, has the real possibility of being a little curmudgeonly to those in the outside world who don’t speak the language, know the acronyms, share the same background. Working with all that new talent in the years before I left really helped me relate to my students and the firehose of information they’re being hit with.
Being asked to contribute to that volume, Topics and Approaches to Studying Intelligence, came at a great time for me. It let me take the work that I had done for my dissertation forward and build in some of the work I had done during my fellowship, and then present that in a way that was useful for students and practitioners, not just for fellow academics or researchers. What writing that chapter cleared up for me was something that was sort of fuzzy in my own head for a long while, and that was the way we think about the intelligence cycle. We knew it was wrong as soon as it was adopted. The Church Committee in 1976 said the realities of what was going on in the IC looked nothing like it. At its core, the intelligence cycle is the consumer asking the question and the analyst answering it, followed by more questions and more answers. That’s it, that’s the intel cycle; everything else, collection, processing, management, is only there to facilitate the question/answer cycle.
And just to follow up on the part about the importance of collaboration, I can’t begin to tell you how helpful the peer review of that chapter was to me, from the basics of organization to some of the deeper conceptual ideas behind it, the comments I received were invaluable.
I think there are some clear and unsurprising trends in the future of intelligence and analysis, and they all come with opportunities and hazards. First of course is AI. AI has been in use for years in the IC in single-source processing and data management. We use AI to review and interpret the terabytes of imagery collected that no human analyst could ever hope to get through, translate text, and all that single-source processing that humans have traditionally done but can be just as easily done by machines. So the question is, how will AI be used by all-source analysts? Some authors think AI will be used as digital assistants or co-pilots for analysts, helping them manage the volume of traffic they have to deal with on a daily basis. The research effort I just worked on with other faculty and students was whether we could train AI to perform certain structured analytic techniques, which can be time-consuming to do correctly. We also discussed whether we could train AI on adversary doctrine and tactics to be the red team, and all of that is possible. This is where I think having a solid understanding of what analysts do, that model of the analytic process, is crucial to thinking about how this tool, or really these tools, can be best integrated into the analyst’s daily work. I’ve seen it too many times over the years where industry develops great solutions to problems that don’t exist, right, solutions in search of a problem. I’d much rather see us be a little more deliberate in integrating these tools to assist analysts. And this is where educators can help. We can’t put our heads in the sand about AI; we need to review our pedagogy and work AI into the course syllabus. Let’s not be afraid to experiment with AI in our courses, let’s learn the pros and cons, what it can and can’t do, and our students will then enter the workforce able to articulate to the designers and program managers what will best work for them.
A subset of AI is Large Language Models. These LLMs at least give the illusion of being able to answer queries, to take natural language questions and provide answers to them. Now we know that we can’t trust the answers that these LLMs give, that they don’t really think and reason, they only provide the mathematically best next word based on the data they’ve been trained on. But the LLM developers are working hard to improve their reliability, and there are experts in the field who think these LLMs will soon be able to reason their way through questions. Just this week, Sam Altman (OpenAI CEO) published his projections for the future of AI, predicting genuine Artificial Super Intelligence, that is, machines with consciousness and understanding, in “a few thousand days.”[1] The real issue I see here is not that LLM will be used by analysts to help write or edit assessments, but directly by consumers. We can tell these policy makers and decisions makers that they shouldn’t use LLM to answer their intelligence needs, but can’t you see where a person that already uses LLM to write performance evals, draft their emails, maybe even pick the teams they’re going to bet on this weekend will go to whatever LLM they have on their desktop first to answer their intelligence questions. I said the real intel cycle is the relationship between the consumer and the analyst. Well, I see how LLM can usurp that relationship. And this is where the analyst is going to have to be aggressive in preserving that relationship, is going to have to continually prove their value to intel consumers, which means that we as educators are going to have to teach analysts to be more than reporters or historians. True all-source intelligence analysis, the breaking down of information into component parts, filling in gaps with assumptions and intuition, evaluating the trustworthiness of a multitude of sources, forecasting possible futures with unique indicators to help narrow down the outcomes, that’s what we need to have in our analytic curriculum. That’s what we as humans can provide that LLM can’t. I tell my students now that if all you are doing is reporting the news, writing book reports, and summarizing what happened, you are already obsolete. Your value to the consumer is as an analyst.
A third future trend is the use of open source and, maybe more generically, big data in analysis. And here it’s not just the volume, which I’m confident that AI will manage for us, but the content. For example, there are some pretty clear rules about using data on US persons in foreign intelligence, for very good reasons. How can we be sure we aren’t violating those rules when we consolidate and homogenize reams of open-source data? Or how can we confidently provide a source summary statement when we really aren’t sure of the sources that AI has parsed and summarized for us? Or even just provide individual source evaluations or source descriptor statements? These are all key elements of current analytic tradecraft and policy implemented in the ICDs. Now, in the long run, I think that Congress and the Executive Branch will have to review existing legislation, policies, and tradecraft standards and see how they need to evolve to meet the inevitable changes. Of course, the realist in me thinks that will only happen after some headline-grabbing intelligence failure or violation of civil rights. In the meantime, though, in the classroom, we can teach the fundamentals behind source evaluation, behind confidence levels, what they mean, and why we do it. When I was an analyst, I saw cases where that had already become a rote element in assessment writing. Phrases on source reliability were regurgitated without any thought to what they meant, source summaries were copied and pasted, and it was tradecraft standard block checking at its worst. If we can impart to future analysts why we evaluate our sources, why we trust some more that others, what that means to the confidence we have in our assessments, how that influences our collection requirements, the why not just the how, they will be better prepared to help shape the evolution of those standards as big data changes what we know.
[1] https://ia.samaltman.com/
Ok, this is a difficult question too. Analytically, I can think of several products I worked on that I think have stood the test of time. Of course, they’re all still classified, and I couldn’t even read them today if I wanted to. And I’m really proud of the courses I’ve developed for UNH and the way they fit into the overall NSIA program. In all honesty, I think this is one of the best programs for analysts there is. I wish I had something like this coming up. But to try to answer your question, the underlying theme of my interests, my research, has been analysts and analysis. You know it’s easy to evaluate and assess physical things, like customer requirements and the output of collection assets and finished products. It’s quantifiable, measurable. But analysis itself has always been a black box; it’s difficult to try and determine what’s happening between the ears of the analyst. For too long, it’s been ignored or only considered anecdotally, you know, “this is how I remember doing it that one time I was right about something.” But if we want to get serious about improving analytic skills, about making the teaching of analysis more relevant, about bringing intelligence studies as a discipline forward, or seriously thinking about how to integrate AI and big data into analysis, then we need to not be afraid to dig into the analytic process. The research I did for my dissertation was a part of that, and importantly, I was able to work through the ODNI to conduct unclassified, pure academic research across the IC in what is a very closed and secretive society. That was several years ago now, and thankfully, it has become more commonplace and accepted, but I guess the takeaway is that there is more to learn about analysis and analysts. We’ve really just started to get serious about it, and yes, it is a soft and squishy topic, but there is a lot of room for academics, students, and researchers to build on what we know about the analytic process.
Don’t be tied down to an analytic specialty or subspecialty early on. You have a lot of time to specialize in something that interests you; take the time early on to gain experience. Are they forming a crisis team to look at the latest issue in the Middle East or Africa, or South America? Volunteer to work on it even if you're currently working in Europe. Your critical thinking skills are like a muscle; they get stronger when you stress and exercise them. If you decide early on that you want to be the expert in counternarcotics or North African insurgencies and only work those issues, you may become a walking encyclopedia of knowledge, but you won’t be an analyst. Refer back to the question on coming trends in analysis. I can get AI to give me a background brief on the Tuaregs, but it can’t tell me why they’re important to me. Build your analytical and critical thinking skills by working on diverse accounts early in your career. Get out of your comfort zone once in a while and stress your brain. When you leave the gym and your muscles burn, you think, Wow, good workout, right. If you don’t occasionally leave work with your head hurting from the new things you’ve learned and your preconceptions about issues challenged, you’re getting lazy. And it also helps to be exposed to other analysts, to see how they approach problems. At the risk of beating a dead horse, as a branch chief, I knew that it would be relatively easy to spin somebody up on a particular person, place, or thing; it was a lot harder to train somebody to think like an analyst.
Question 10). Lastly, can you share with us five keywords that represent you?
Curious, Passionate, Thorough, Calm, Open-minded.