How To Think About The Future (Part 1 -- Questions About Questions)

We don't think about the future; we worry about it.

Whether it's killer robots or social media or zero-day exploits, we love to rub our preferred, future-infused worry stone between our thumb and finger until it is either a thing of shining beauty or the death of us all (and sometimes both).  

This is not a useful approach.

Worry is the antithesis of thinking.  Worry is all about jumping to the first and usually the worst possible conclusion.  It induces stress.  It narrows your focus.  It shuts down the very faculties you need to think through a problem.  Worry starts with answers; thinking begins with questions.

What Are Your Questions?

“A prudent question is one-half of wisdom.” – Francis Bacon
"The art of proposing a question must be held of higher value than solving it.” – Georg Cantor
“If you do not know how to ask the right question, you discover nothing.” – W. Edwards Deming

Given the importance of questions (and of asking the "right" ones), you would think that there would be more literature on the subject.  In fact, the question of questions is, in my experience, one of the great understudied areas.  A few years ago, Brian Manning and I took a stab at it and only managed to uncover how little we really know about how to think about, create, and evaluate questions.

For purposes of thinking about the future, however, I start with two broad categories to consider:  Speculative questions and meaningful questions.  

There is nothing wrong with a speculative question.  Wondering about the nature of things, musing on the interconnectedness of life, and even just staring off into space for a bit are time-honored ways to come up with new ideas and new answers.  We should question our assumptions, utilize methods like the Nominal Group Technique to leverage the wisdom of our collective conscious, and explore all of the other divergent thinking tools in our mental toolkits.  

Speculation does not come without risks, however.  For example, how many terrorist groups would like to strike inside the US?  Let's say 10.  How are they planning to do it?  Bombs, guns, drones, viruses, nukes?  Let's say we can come up with 10 ways they can attack.  Where will they strike?  One of the ten largest cities in the US?  Do the math--you already have 1000 possible combinations of who, what, and where.

How do we start to narrow this down?  Without some additional thinking strategies, we likely give in to cognitive biases like vividness and recency to narrow our focus.    Other aspects of the way our minds work--like working memory limitations--also get in the way.  Pretty soon, our minds, which like to be fast and certain even when they should be neither, have turned our 1 in 1000 possibility into a nice, shiny, new worry stone for us to fret over (and, of course, share on Facebook).

Meaningful questions are questions that are important to you--important to your plans, to your (or your organization's) success or failure.  Note that there are two criteria here.  First, meaningful questions are important.  Second, they are yours.  The answers to meaningful questions almost, by definition, have consequences.  The answers to these questions tend to compel decisions or, at least, further study.

It is entirely possible, however, to spend a lot of time on questions which are both of dubious relevance to you and are not particularly important.  The Brits have a lovely word for this, bikeshedding.  It captures our willingness to argue for hours about what color to paint the bikeshed while ignoring much harder and more consequential questions.  Bikeshedding, in short, allows us to distract ourselves from our speculations and our worries and feel like we are still getting something done.

Next:  What do you control?

Why The Next "Age of Intelligence" Scares The Bejesus Out Of Me

A little over a month ago, I wrote a post titled How To Teach 2500 Years Of Intelligence History In About An Hour.   The goal of that post was to explain how I taught the history of intelligence to new students. Included in that article was the picture below:

I am not going to cover all the details of the "Ages of Intelligence" approach again (you can see those at this link), but the basic idea is that there are four pretty clear ages.  In addition, I made the case that, driven by ever changing technology as well as corresponding societal changes, the length of these ages is getting logarithmicly shorter. 

Almost as an afterthought, I noted that the trend line formed by these ever shortening ages was approaching the X-intercept.  In other words, the time between "ages" was approaching zero.  In fact, I noted (glibly and mostly for effect) that we could well be in a new "Age of Intelligence" right now and not know it.

When I publish a piece like the one mentioned above, I usually feel good about it for about ten minutes.  After that, I start to think about all the stuff I could have said or where to go next with the topic.  In this case, the next step was obvious--a little speculative thinking about what comes, well, now.  What I saw was not pretty (and, to be frank, a little frightening).

Looking out 10 years, I see five hypotheses (The base rate, therefore, for each is 20%).  I will indicate what I think are the arguments for and against each hypothesis, and then, how I would adjust the probability from the base rate.  

The Age of Anarchy  
No one knows what is going on, no one knows what to do about it.  Technology just keeps changing and improving at an ever increasing pace, and no one person or even one organization (no matter how large) can keep up with it.  Strategic intelligence is worthless and even tactical intelligence has only limited utility.

Arguments for:  This is certainly what life feels like right now for many people.  Dylan Moran's rant probably captures this hypothesis far better than I could:




Arguments against:   This is a form of the same argument that has been made against every technological advance since the Ancient Greeks (Socrates, for example, was against writing because it "will introduce forgetfulness into the soul of those who learn it: they will not practice using their memory because they will put their trust in writing..."  Replace "writing with "books" or "computers" or "cell phones" and you have another variation on this Luddite theme).  In short, every age has had to adjust to the risks and rewards new technologies bring.  The next age of intelligence is unlikely to be new in this respect.

Probability:  17%

Age of Irrelevance
Artificial intelligence (AI) takes over the world.  The algorithms get so good at understanding and predicting that we increasingly turn over both our intelligence production and our decisionmaking to the computers.  In this hypothesis, there is still a need to know the enemy there is just no longer a need for us to do all those tedious calculations in our tents.  The collection of intelligence information and the conduct of intelligence analysis becomes an entirely automated process.

Arguments for:  Even a cursory look at the Progress in Artificial Intelligence article in Wikipedia suggests two things.  First, an increasing number of complex activities where humans used to be the best in the world are falling victim to AI's steady march.  Second, humans almost always underestimate just how quickly machines will catch up to them.  Efforts by the growing number of surveillance states will only serve to increase the pace as they move their populations in the direction of the biases inherent in the programming or the data.  

Arguments against:  AI may be the future, but not now and certainly not in the next ten years.  Four polls of researchers done in 2012-13 indicated that that there was only a 50% chance of a technological singularity--where a general AI is as smart as a human--by 2040-2050.  The technology gurus at Gartner also estimated in 2018 that general artificial intelligence is just now beginning to climb the "hype cycle" of emerging technologies and is likely more than 10 years away.  The odds that this hypothesis becomes reality go up after ten years, however.

Probability:  7%

Age of Oligarchy
Zuckerberg, Gates, Nadella, Li, Bezos, Musk, Ma--their names are already household words.  Regular Joe's and Jane's (like you and me) get run over, while these savvy technogeeks rule the world.  If you ain't part of this new Illuminati, you ain't $h!t.  Much like the Age of Concentration, intelligence efforts will increasingly focus on these oligarchs and their businesses while traditional state and power issues take a back seat (See Snow Crash).

Arguments for:  92% of all searches go through Google, 47% of all online sales go through Amazon, 88% of all desktop and laptop computers run Windows.  These and other companies maintain almost monopoly-like positions within their industries.  By definition, the oligarchy already exists.

Arguments against:  Desktops and laptops may run on Windows but the internet and virtually all supercomputers--that is, the future--run on Linux based systems.  Browsers like Brave and extensions like Privacy Badger will also make it more difficult for these companies to profit from their monopoly positions.  In addition, an increasing public awareness of the privacy issues associated with placing so much power in these companies with so little oversight will expand calls for scrutiny and regulation of these businesses and their leaders.

Probability:  27%

Age of Ubiquity
We start to focus on our digital literacy skills.  We figure out how to spot liars and fakes and how to reward honest news and reviews.   We teach this to our children.  We reinforce and support good journalistic ethics and punish those who abandon these standards.  We all get smart.  We all become--have to become--intelligence analysts.

Arguments for:   Millennials and Gen Z are skeptical about the motives of big business and are abandoning traditional social media platforms in record numbers.  They are already digital natives, unafraid of technology and well aware of its risks and rewards.  These generations will either beat the system or disrupt it with new technologies.

Arguments against:   Human nature.  Hundreds of books and articles have been written in the last decade on how powerful the biases and heuristics hardwired into our brains actually are.  We are programmed to seek the easy way out, to value convenience over truth, and to deceive ourselves.  Those who do happen to figure out how to beat the system or disrupt it are likely to hold onto that info for their own economic gain, not disperse it to the masses.

Probability:  12%

Blindside Hypothesis
Something else, radically different than one of approaches above, is going to happen. 

Arguments for:   First, this whole darn article is premised on the idea that the "Ages of Intelligence" approach is legit and not just a clever pedagogical trick.  Furthermore, while there are lots of good, thoughtful sources regarding the future, many of them, as you can see above, contradict.  Beyond that:

• This is a complex problem, and I generated this analysis on my own with little consultation with other experts.  
• Complex problems have "predictive horizons"--places beyond which we cannot see--where we are essentially saying, "There is a 50% chance of x happening, plus or minus 50%."
• I have been thinking about this on and off for a few weeks but have hardly put the massive quantities of time I should to be able to make these kinds of broad assessments with any confidence.  
• The lightweight pro v. con form of my discussion adds only a soupçon of structure to my thinking.    
• Finally, humans have a terrible track record of predicting disruption and I am decidedly human.  

Bottomline:  The odds are good that I am missing something.

Arguments against:  What?  What am I missing?  What reasonable hypothesis about the future, broadly defined, doesn't fall into one of the categories above? (Hint:  Leave your answer in the comments!)

Probability:  37% 

Why This Scares Me
Other than the rather small probability that we all wake up one morning and become the critical information collectors and analysts this most recent age seems to demand of us, there aren't any good outcomes.   I don't really want chaos, computers or a handful of profit-motivated individuals to control my digital and, as a result, non-digital life.  I also fully realize that, in some sense, this is not a new revelation.  Other writers, far more eloquent and informed than I, have been making some variation of this argument for years.  

This time, however, it is more personal.  Intelligence leads operations.  Understanding the world outside your organization's control drives how you use the resources under your control.  My new employer is the US Army and the US Army looks very different in the next ten years depending on which of these hypotheses becomes fact. 

I Made It!

I started my new job as Professor of Strategic Futures at the US Army War College last week.  So far, it has been a fairly predictable, if seemingly unending, series of orientations, mandatory trainings, and security briefings.  I don't mind.  To paraphrase Matthew, "What did I go into the Army to see?  A man running without a PT belt?"

What I have been impressed with is the extraordinary depth of knowledge and genuine collegiality of the faculty.  It is an interesting feeling to be constantly surrounded by world class experts in virtually any domain.

Equally impressive is the emphasis on innovation and experimentation.  I am surrounded by an example of this right now.  I am writing this post on one of a number of open access commercial network machines in the War College library.  In the back of the room, a professor is leading an after action review of an exercise built around Compass Games' South China Sea war game (BTW, if you think it odd that the Army would have students play a scenario which is largely naval in nature, you are missing my point about innovation and experimentation). 

Scattered throughout the rest of the library are recently acquired, odd-shaped pieces of furniture designed to create collaborative spaces, quiet spaces, and resting spaces (among others).  Forms soliciting feedback suggest that the library is working hard to figure out what kind of spaces its patrons want, and what kind of furniture and equipment would best support those needs.  In the very rear of the building, there is a room undergoing a massive reconstruction.  No telling what is about to go in there, but it is clear evidence that the institution is not standing still.  

I will continue to write here on Sources and Methods, of course.  I also hope to get a few things published on the War College's own online journal, The War Room  (Check it out if you haven't.  It's very cool). Other than that, I look forward to pursuing some of my old lines of research and adding a few new ones as well.

For those of you who want to contact me, you can call me in my office at 717-245-4665, email me at kristan dot j dot wheaton dot civ at mail dot mil or, as always, email me at kris dot wheaton at gmail dot com.  You can also message me on LinkedIn.

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: 

"...at 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.

What Is #COOLINT?

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.