Monday, June 24, 2019

EPIC 2014: The Best/Worst Forecast Ever Made?

The eight minute film, EPIC 2014, made a huge impact on me when it was released in 2004.  If you have seen it before, it's worth watching it again.  If you haven't, let me set it up for you before you click the play button below.   

Put together by Robin Sloan and Matt Thompson way back in 2004, EPIC 2014 talked about the media landscape in 2014 as if it had already happened.  In other words, they invented a "Museum of Media History", and then pretended, in 2004, to look backward from 2014 as a way of exploring how they thought the media landscape would change from 2004 to 2014.  Watch it now; it will all make sense when you do:

In some ways, this is the worst set of predictions ever made.  Almost none of the point predictions are correct.  Google never merged with Amazon, Microsoft did not buy Friendster, The New York Times did not become a print-only publication for the elderly, and Sony's e-paper is not cheaper than real paper (It costs 700 bucks and gets an average of just 3 stars (on Sony's site!)).

Sloan and Thompson did foresee Google's suite of online software services but did not really anticipate competition from the likes of Facebook, Twitter, LinkedIn, YouTube or any of a host of other social media services that have come to dominate the last 15 years.

None of that seemed particularly important to me, however.  It felt like just a clever way to get my attention (and it worked!).  The important part of the piece was summed up near the end instead.  EPIC, Sloan and Thompson's name for the monopolized media landscape they saw by 2014, is: 
" its best and edited for the savviest readers, a summary of the world—deeper, broader and more nuanced than anything ever available before ... but at its worst, and for too many, EPIC is merely a collection of trivia, much of it untrue, all of it narrow, shallow, and sensational.  But EPIC is what we wanted, it is what we chose, and its commercial success preempted any discussions of media and democracy or journalistic ethics."
Switch out the word "EPIC" with the word "internet" and that still seems to me to be one of the best long-range forecasts I've ever seen.   You could throw that paragraph up on almost any slide describing the state of the media landscape today, and most of the audience would likely agree.  The fact that Sloan and Thompson were able to see it coming way back in 2004 deserves mad props.

It also causes me to wonder about the generalizability of the lessons learned from forecasting studies based on resolvable questions.  Resolvable questions (like "Will Google and Amazon merge by December 31, 2014?") are fairly easy to study (easier, anyway).  Questions which don't resolve to binary, yes/no, answers (like "What will the media landscape look like in 2014?") are much harder to study but also seem to be more important.  

We have learned a lot about forecasting and forecasting ability over the last 15 years by studying how people answer resolvable questions.  That's good.  We haven't done that before and we should have.  

Sloan and Thompson seemed to be doing something else, however.  They weren't just adding up the results of a bunch of resolvable questions to see deeper into the future.  There seems to me to be a different process involved.  I'm not sure how to define it.  I am not even sure how to study it.  I do think, that, until we can, we should be hesitant to over-apply the results of any study to real world analysis and analytic processes.

Tuesday, June 18, 2019


Apollo 11 in Real-Time is the very definition of cool.
HUMINT, SIGINT, OSINT--the specialized language of intelligence is all ate up with acronyms for the various collection disciplines.  Intel wags have (for at least the last 40 years I have been doing this stuff) come up with a variety of clever (?) plays on this formulation.  For example:  RUMINT = Intelligence founded on rumors alone.  DUMBINT = Intelligence too stupid to believe.

COOLINT is usually reserved for something that is, well, cool but might not be particularly relevant to the question at hand.  You want to show COOLINT to other people.  You KNOW they will be interested in it.  It's the clickbait of the intel world.

A great example of COOLINT is the Apollo 11 In Real-time website (the mobile version is OK but you will want to look at it on your PC or MAC.  Trust me).  In fact, I used the hashtag "#COOLINT" when I tweeted out this site this morning.  The guys who put this amazing site together have mashed up all of the audio and video, all of the commentary, and all of the pictures into a single website that allows you to follow along with the mission from T - 1 minute to splashdown.  It doesn't really have anything to do with intelligence, but, to a spacegeek like me, you find the Apollo 11 in Real-time website next to the word "cool" in the dictionary.

I intend to argue here, however, that there is a more formal definition of COOLINT, one that is actually useful in analytic reporting.  To do this, I want to first briefly explore the concepts of "relevant" and "interesting"

One of the hallmarks of good intelligence analysis is that it be relevant to the decisionmaker(s) being supported.  ICD 203 makes this mandatory for all US national security intel analysts but, even without the regulation, relevance has long been the standard in intel tradecraft.

"Interesting" is a term which gets significantly less attention in intel circles.  There is no requirement that good intel be interesting.  It is ridiculous to think that good intel should meet the same standards as a good action movie or even a good documentary.  That said, if I have two pieces of information that convey the same basic, relevant facts and one is "interesting" and other is not (for example, 500 words of statistical text vs. one chart), I would be a bit of a fool not to use the interesting one.  Intel analysts don't just have a responsibility to perform the analysis, they also have a responsibility to communicate it to the decisionmaker they are supporting.  "Interesting" is clearly less important than "relevant" but, in order to communicate the analysis effectively, something that has to be considered.

With all this in mind, it is possible to construct a matrix to help an analyst think about the kinds of information they have available and where it all should go in their analytic reports or briefings:
"Interesting" vs. "Relevant" in analytic reporting
Interesting and relevant information should always be considered for use in a report or brief.  Length or time limits might preclude it, but if it meets both criteria, and particularly if it is a linchpin or a driver of the analysis, this kind of info highly likely belongs in the report.

Relevant information which is not particularly interesting might have to go in the report--it may be too relevant not to include.  However, there are many ways to get this kind of info in the report or brief.  Depending on the info's overall importance to the analysis, it might be possible to include it in a footnote, annex, or backup slide instead of cluttering up the main body of the analysis.

Information that is interesting but not relevant is COOLINT.  It is that neat little historical anecdote that has nothing to do with the problem, or that very cool image that doesn't really explain anything at all.  The temptation to get this stuff into the report or brief is great.  I have seen analysts twist themselves into knots to try to get a particular piece of COOLINT into a briefing or report.  Don't do it.  Put it in a footnote or an annex if you have to, and hope the decisionmaker asks you a question where your answer can start with, "As it so happens..."

Info which is not interesting and not relevant needs to be left out of the report.  I hope this goes without saying.

Three caveats to this way of thinking about info.  First, I have presented this as if the decision is binary--info is either relevant OR irrelevant, interesting OR uninteresting.  That isn't really how it works.  It is probably better to think of these terms as if they were on a scale that weighs both criteria.  It is possible, in other words, to be "kind of interesting" or "really relevant."

The other caveat is that both the terms interesting and relevant should be defined in terms of the decisionmaker and the intelligence requirement.  Relevancy, in other words, is relevancy to the question; "interesting", on the other hand, is about communication.  What is interesting to one decisionmaker might not be to another.

Finally, if you use this at all, use it as a rule of thumb, not as a law.  There are always exceptions to these kinds of models.  

Monday, June 10, 2019

How To Teach 2500 Years Of Intelligence History In About An Hour

Original version of the Art of War by Sun-Tzu
As with most survey courses, Introduction to Intelligence Studies has a ton of information that it needs to cover--all of it an inch deep and mile wide.  One of the most difficult parts of the syllabus to teach, however, is intelligence history.

Whether you start with the Bible or, as I do, with Chapter 13 of The Art Of War, you still have 2500 years of history to cover and typically about an hour long class to do it.  Don't get me wrong.  I think the history of intelligence ought to be at least a full course in any intelligence studies curriculum.  The truth is, though, you just don't have time to do it justice in a typical Intel 101 course.

I was confronted with this exact problem last year.  I had not taught first-year students for years, and when the time came in the syllabus to introduce these students to intel history, I was at a bit of a loss.  Some professors gloss over ancient history and start with the National Security Act of 1947.  Some compress it even more and focus entirely on post Cold War intelligence history.  Others take a more expansive view and select interesting stories from different periods of time to illustrate the general role of intelligence across history.  

All of these approaches are legitimate given the topic and the time constraints.  I wanted, however, to try to make the history of intel a bit more manageable for students new to the discipline.  I hit on an approach that makes sense to me and seemed to work well with the students.  I call it the Four Ages Of Intelligence.

The first age I call the Age of Concentration.  In ancient times, power and knowledge was concentrated in the hands of a relatively small number of people.  The king or queen, their generals, and the small number of officers and courtiers who could read or write were typically both the originators and targets of intelligence efforts.  These efforts, in turn, were often guided by the most senior people in a government.  Sun Tzu noted, "Hence it is that which none in the whole army are more intimate relations to be maintained than with spies."  George Washington, as well, was famous not only as a general but also as a spymaster.  

The Age of Concentration lasted, in my mind, from earliest times to about the early 1800's.  The nature of warfare began to change rapidly after the American and French Revolutions. 
Washington and the capture of the Hessians at Trenton.  
Large citizen armies and significant technological advances (railroads, telegraphs, photography, balloons!) made the process of running spy rings and collating and analyzing the information they collected too large for any one person or even a small group of people to manage.  

Enter the Age of Professionalization.  The 1800's saw the rise of the staff system and the modern civil service to help generals and leaders manage all the things these more modern militaries and governments had to do.  Of course, there had always been courtiers and others to do the king's business but now there was a need for a large number of professionals to deal with the ever-growing complexities of society.  The need for more professionals, in turn, demanded standardized processes that could be taught.  

For me, the Age of Professionalization lasted until the end of World War II when the Age of Institutionalization began.  Governments, particularly the US Government, began to see the need for permanent and relatively large intelligence organizations as a fundamental part of government.   
Logos of the CIA And KGB
Staffs and budgets grew.  Many organizations came (more or less) out of the shadows.  CIA, KGB, MI5 (and 6), ISI, and MSS all became well known abbreviations for intelligence agencies.  The need for intelligence-like collection and analysis of information became obvious in other areas.  Law enforcement agencies, businesses, and even international organizations started to develop "intelligence units" within their organizational structures.  

All of this lasted until about 1994 when, with the advent of the World Wide Web, the Age of Democratization began.   Seven years ago (!), I wrote an article called "Top Five Things Only Spies Used To Do But Everyone Does Now."  I talked about a whole bunch of things, like using sophisticated ciphers to encrypt data and examining detailed satellite photos, that used to be the purview of spies and spies alone.  Since then, it has only gotten worse.  Massive internet based deception operations and the rise of deepfake technology is turning us all into spymasters, weighing and sorting information wheat from information chaff.  Not only the threats but also the opportunities have grown exponentially.   For savvy users, there is also more good information, a greater ability to connect and learn, to understand the things that are critical to their success or failure but are outside their control, than ever before--and to do this on a personal rather than institutional level.

There are a couple of additional teaching points worth making here.  First is the role of information technology in all of this.  As the technology for communicating and coordinating activities has improved, the intelligence task has become more and more complicated.  This, in turn, has required the use of more and more people to manage the process, and that has changed how the process is done.  Other disciplines have been forced to evolve in the face of technological change.  It is no surprise, then, that intelligence is also subject to similar evolutionary pressures.

It is also noteworthy, however, that the various ages of intelligence have tended to become shorter with the near-logarithmic growth in technological capabilities.  In fact, when you map the length of the four ages on a logarithmic scale (see below) and draw a trendline, you can see a pretty good fit.  It also appears that the length of the current age, the Age of Democratization, might be a bit past its sell-by date.  This, of course, begs the question:  What age comes next?  I'm voting for the Age of Anarchy...and I am only half kidding.

Is this a perfect way of thinking about the history of intelligence?  No, of course not.  There are many, many exceptions to these broad patterns that I see.  Still, in a survey class, with limited time to cover the topic, I think focusing on these broad patterns that seemed to dominate makes some sense.  

Friday, May 10, 2019

I Am Leaving Mercyhurst And...

Look, Ma!  An (almost) clean desk!
... joining the US Army War College!

It has been an honor and a privilege to work with the faculty here in the Intelligence Studies Department at Mercyhurst over the last 16 years.  Having the opportunity to help build a world class program is an experience I will never forget.

As important as my colleagues, however, are the extraordinary students I have had the pleasure to teach and work with.  Whether we were sweating in the halls of the old Wayne Street building or livin' large in our fancy, new digs in the Center for Academic Engagement, getting to work with really smart, super dedicated students was probably the best thing about the job.  Watching them continue to grow and succeed as alumni is even more rewarding.  I am convinced that, one day, the DNI will almost certainly be a Mercyhurst alum (Several Directors of Strategic Intelligence for some Fortune 500 companies already are).

As much as I am sorry to leave Mercyhurst, I am very excited about my next position as Professor Of Strategic Futures at the War College.  There are few missions as important as developing strategic leaders and ideas for the US Army and I am proud to be part of the effort.

I expect to be out of my office here by the end of the month, so, if you have any last minute business to attend to, please reach out soon.  After the end of the month, the best way to reach me until I get to Carlisle in July is via gmail (kris dot wheaton at gmail dot com).  Once I have new contact info, I will post it.

I fully expect to continue to publish new thoughts, articles, and anything interesting I run across here on Sources and Methods.  In fact, I expect to be able to write more often.  

Stay tuned!  It's about to get (more) interesting...

Tuesday, March 19, 2019

What's The Relationship Of An Organization's Goals And Resources To The Type Of Intelligence It Needs?

"Don't blame me, blame this!"
I was trying to find some space on the whiteboard in my office and it occurred to me that I really needed to do something with some of these thoughts.

One of the most interesting (to me, at least) had to do with the relationship between an organization's goals and its resources coupled with the notion of tactical, operational and strategic intelligence.

There is probably not an entry level course in intelligence anywhere in the world that does not cover the idea of tactical, operational and strategic intelligence.  Diane Chido and I have argued elsewhere that these three categories should be defined by the resources that an organization risks when making a decision associated with the intel.  In other words, decisions that risk few of an organization's resources are tactical while those that risk many of the organizations's resources are strategic.  Thus, within this context, the nature of the intelligence support should reflect the nature of the decision and the defining characteristic of the decision is the amount of the organization's resources potentially at risk.   

That all seemed well and good, but it seemed to me to be missing something.  Finally (Diane and I wrote our article in 2007, so you can draw your own conclusions...), it hit me!  The model needed to also take into consideration the potential impact on the goals and purposes of the organization.

Here's the handy chart that (hopefully) explains what I mean:

What I realized is that the model that Diane and I had proposed had an assumption embedded in it.  In short, we were assuming that the decisionmaker would understand the relationship between their eventual decision, the resources of the organization, and the impact the decision would have on the organization's goals.  

While there are good reasons to make this assumption (decisionmakers are supposed to make these kinds of calculations, not intel), it is clearly not always the case.  Furthermore, adding this extra bit of nuance to the model makes it more complete.

Let's take a look at some examples.  If the impact on resources of deciding to pursue a particular course of action is low but the pay-off is high, that's a no-brainer (Example:  You don't need the DIRNSA to tell you to have a hard-to-crack password).  Of course you are going to try it!  Even if you fail, it will have cost you little.  Likewise, if the impact on resources is high and the impact on goals is low, then doing whatever it is you are about to do is likely stupid (Example:  Pretty much the whole damn Franklin-Nashville Campaign).

While many of these elements may only be obvious after the fact, to the extent that these kinds of things are observable before the decision is made, reflecting on them may well help both intelligence professionals and decisionmakers understand what is needed of them when confronted by a particular problem.