Showing posts with label United States Army. Show all posts
Showing posts with label United States Army. Show all posts

Monday, May 10, 2021

The Future Is Like A Butler

Imagine someone gave you a butler. Completely paid for. No termination date on the contract. What would you do?

At first, you’d probably do nothing. You’ve never had a butler. Outside of movies, you’ve probably never seen a butler. You might even feel a little nervous having this person in the room with you, always there, always ready to help. 

Once you got over your nervousness, you might ask the butler to do something simple, like iron your shirts or make you some coffee. “Hey,” you might think after a while, “This is pretty nice! I always have ironed shirts, and my coffee is always the way I like it!” 

Next, you’d ask your butler to do other things, more complicated things. Pretty soon, you might not be able to imagine your life without a butler.

The parable of the butler isn’t mine, of course. It is a rough paraphrasing of a story told by Michael Crichton in his 1983 book, Electronic Life. Crichton, more famous today for blockbusters like Jurassic Park, The Andromeda Strain, and WestWorld, was writing about computers, specifically personal computers, back then. Crichton correctly predicted that personal computers would become ubiquitous, and the main goal of Electronic Life was to help people become more comfortable with them. 

The story of the butler was a launching point for his broader argument that personal computers were only going to get more useful with time, and that now was the time to start adopting the technology. It worked, too. Shortly after I read his book, I bought my first computer, a Commodore 64.

Today’s Army faces much the same problem. The difference, of course, is that the future presents today’s military with a much broader set of options than it did in 1983. Today, it feels like the Army has been given not one but hundreds of butlers. Quantum computing, artificial intelligence, synthetic biology, 3D printing, robotics, nanotech, and many more fields are arguably poised to rapidly and completely change both the nature and character of warfare.


Despite the deluge of options, the question remains the same, “What do I do with this?”

The answer begins with Diffusion of Innovations theory. In his now classic book of the same name, Everett Rogers first defined the theory and the five types of adopters. Innovators, who aggressively seek the “next big thing”, are the first to take up a new product or process. Early adopters are the second group. Not quite as adventurous as the innovators, the early adopters are still primarily interested in acquiring new technology. Early majority and late majority adopters sit on either side of the midpoint of a bell-shaped adoption curve and represent the bulk of all possible adopters. Finally come the laggards, who tend to adopt a new innovation late or not at all.
(Source: BlackRock White Paper)

For example, the uptake of smartphones (among many other innovations) followed this pattern. In 2005, when the smartphone was first introduced, only 2% of the population (the Innovators) owned one. Three years later, market penetration had only reached 11%, but, from 2009-2014, the smartphone experienced double digit growth each year such that, by 2016, some 81% of all mobile phones were smartphones. This S curve of growth is another aspect predicted by Diffusion of Innovations theory.

Not all innovations succeed, however. In fact, all industries are littered with companies that failed to achieve critical mass in terms of adoption. While there are many reasons that a venture might fail, management consultant Geoffrey Moore, in his influential book, Crossing the Chasm, states that the most difficult leap is between the early adopters and the early majority. Early adopters tend to be enthusiastic and eager to try the next big thing. The early majority is more pragmatic and is looking for a solution to a problem. This difference in perspective accounts for much of the chasm.
Source:   Agile Adoption Across the Enterprise – Still in the Chasm


The Army is aggressively addressing the innovation and early adoption problem by developing sophisticated plans and tasking specific units and organizations to implement them. The need to innovate is, for example, at the heart and soul of several recent policy announcements, including the 2019 Army People Strategy and the 2019 Army Modernization Strategy. Beyond planning, the Army is already far along in doing some of the hard work of innovating. Indeed, organizations and projects as small as TRADOC’s Mad Scientists and as large as the Army Futures Command Synthetic Training Environment are examples that show that Army senior leaders understand the need to innovate and are acting now to put early adoption plans into motion.

But what about the rest of the Army? The part of the Army that isn’t directly involved in innovation? The part that is not routinely exposed to the next big thing? That hasn’t, to get back to the original point, ever had a butler?

Again, Diffusion Of Innovations theory provides a useful guide. Rogers talks about the five stages of the adoption process: Awareness, persuasion, decision, implementation, and continuation. For the rest of the Army, awareness, and, to a lesser extent, persuasion, should be the current goal. 

While this may seem simple, in a world of hundreds of butlers, it is deceptively so. With so many technologies poised to influence the Army of the future, it becomes extremely difficult to focus. Likewise, merely knowing the name of a technology or having some vague understanding of what it is and what it does is not going to be enough. No one in the Army would claim that you could learn to fire a rifle effectively merely by watching YouTube videos, and the same holds true for technologies like autonomous drones, 3D printing, and robots.

The only way to engender true understanding of both the strengths and weaknesses of an innovation is to provide a hands-on experience. Cost alone should not be a significant impediment to exposing the bulk of the Army to the technologies of the future. Autonomous drones are now available for under $1000, entry level 3D printers can be had for as little as $200-$700, virtual reality headsets are available for $300-1000 and build your own robot kits are available for a couple of hundred bucks. 

None of these products are as sophisticated as the kinds of products the Army is considering, of course, but putting simpler versions of these technologies in the hands of soldiers today would likely significantly improve the Army’s odds of being able to cross Moore’s chasm between visionary thinking and pragmatic application in the future.

How and where should the Army implement this effort to familiarize the force with the future? Fortunately, the Army has a good place, a good concept, and some prototypes already in place--at the library. The Army library system contains over 170 libraries worldwide. While many people continue to think of libraries as silent spaces full of dusty books, the modern library has been re-imagined as a place not only for knowledge acquisition but also as tech centers for communities.

Nowhere is this more clear than in the “makerspaces” that are increasingly woven into the fabric of modern libraries. Typically offering access to equipment that, while relatively inexpensive, is outside the budget of most households, or to technology that is best first experienced in a hands-on, peer learning environment, makerspaces allow users to try out new technologies and processes at the user’s own pace and according to the user’s own interest. 

3D printers, laser cutters, video and podcasting equipment are often combined in these makerspaces with more sophisticated traditional equipment such as high end, programmable sewing machines. Most times, however, the makerspace has been tailored by the local librarians to meet the needs of the population that the library serves. Indeed, the Army already has at least three examples of makerspaces in its library system, the Barr Memorial Library at Fort Knox, the Mickelsen Community Library at Fort Bliss and The Forge at the US Army War College.

Imagine being able to go to the post library and check out an autonomous drone for the weekend? Or to sit down and 3D print relief maps of the terrain you were going to cover on your next hike? Understanding the basics of these new technologies will not only make the future force more comfortable with them but also allow soldiers to think more robustly about how to employ these technologies to the Army’s advantage.

While the cost of such a venture would be reasonable, acquiring the funding for any effort on the scale of the whole Army cannot be taken for granted. More challenging, perhaps, would be the process of repurposing the space, training staff, and rolling out the initiative. 

But what is the alternative? To the extent that the Army, as the 2019 People Strategy outlines, needs people at all levels “who add value and increase productivity through creative thinking and innovation,” it seems imperative that the Army also have a whole-of-army approach to innovation. To fail to do so risks falling into Moore’s chasm, where the best laid plans of the visionaries and early adopters fall victim to unprepared pragmatists that will always make up the bulk of the Army.

Tuesday, January 4, 2011

RFI: Who Invented The Intelligence Cycle?

If there is one thing that virtually every intelligence professional, every intelligence sub-discipline, every intelligence training course uses, it is some version of the Intelligence Cycle. 

If you don't believe me, do a quick Google image search on the words "intelligence cycle".  While virtually none of the cycles are the same and virtually no intel professional will swear that this is how intel actually gets done, it appears to be one of the few things that everyone -- national security, law enforcement and business -- uses.

A number of years ago, when I began to question the utility of the cycle (more on that later), I also began to do research on where the cycle came from.  Who invented it?  When? And under what circumstances?  Why did the inventor think that a cycle was the best representation of the intel process? 

While you can find the cycle everywhere, I could not find any answers to these basic questions.  While I haven't been particularly aggressive in my research, I have asked numerous old-timers and intel historians and no one has been able to point to anything definitive.

Recently, though, while playing with Google's new Ngram Viewer, I ran across the 1948 book, Intelligence Is For Commanders by LTC Phillip Davidson and LTC Robert Glass.  Both were either instructors or had been instructors at the Command and General Staff College when they wrote the book and it was clearly influenced by the US Army's experience in WWII.

What really intrigued me, though, was their very explicit use of the term, "Intelligence Cycle".  I have scanned in a copy of their cycle and you can see it in the picture at the top of the page.  What is clear from the context of the book is that the intelligence cycle was not a new concept in 1948.  
Just a quick note on Intelligence Is For Commanders:  If you are at all interested in intelligence history and, in particular, military intelligence history, you have to get a copy of this book.  It comes complete with a packet of old school onion skin transparencies that are examples of 1948 analytic methods that later evolved into Intelligence Preparation of the Battlefield  (In fact, one of the authors, Phillip Davidson went on to become the first officer in the Military Intelligence Corps to reach the rank of General).  That is just the tip of the iceberg; for the historically minded, this book is full of interesting tidbits about how intel was done back in the day...
In other research, I have been able to trace some descriptions of the intel process (which sound like the intel cycle but aren't called that) back to the 1920's.  What I am really interested in, though, is who was the first person (or organization) to refer to the intel cycle as the intel cycle and when and why did that happen?

Here's how you can help:

Stories.  When were you first exposed to the intelligence cycle?  Under what circumstances?  I am interested in responses from all three sub-disciplines of intel.  I think it would be fascinating to trace the intel cycle as it migrated through the years from the national security community to the law enforcement and business communities.

Books or manuals.  If you know of any books or manuals that specifically mention the intel cycle, I would be interested and would be particularly interested in any that were written before 1948.  Just give me the names and I will have my team of crack Graduate Assistants track them down.

Any other leads.  This is a bit of a detective story so any ideas that you might have to push the investigation along would be most appreciated.

Finally, I would really like you to leave your story, book or other lead in the comments below so that everyone can follow along.  If you want to contact me directly, though, my email is kwheaton at mercyhurst dot edu.
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Tuesday, June 22, 2010

1975 Experiments Showed Flaws Of A-F, 1-6 Rating System For Evaluating Accuracy, Reliability Of Intel Info(NTIS.gov)

A couple of weeks ago there was a discussion on the always interesting US Army INTELST regarding schemes for grading sources.  I pushed my own thoughts on this out to the list and published a link list on SAM that contained much the same information.

One of the topics that came up as a result of that discussion was "Whatever happened to the old A-F, 1-6 method for evaluating the accuracy and reliability of a source?"  Under this system, the reliability of a source of a piece of info was graded A-E, with "A" being completely reliable and "E" being unreliable.  "F" was reserved for sources where reliability could not be determined. 

Likewise, the info was graded for accuracy on a scale of 1-5 where "1" indicated that the info was confirmed and "5" indicated that it was improbable.  "6" was reserved for info the truth of which could not be judged.

Under this system, every piece of collected info had a unique identifier (B-3, C-2, A-1 -- now you know where that expression came from!) that supposedly captured both the reliability of the source and the accuracy of the info.

Except that it didn't work.

In 1975, Michael G. Samet conducted a series of experiments using the system for the US Army's Research Institute for the Behavioral and Social Sciences titled, Subjective Interpretation of Reliability And Accuracy Scales For Evaluating Military Intelligence.  I ran across it while doing some background research for the link list.  Unfortunately, the good people at NTIS had not had the time to scan this report and upload it yet.  Even more maddening was the fact that the abstract (the only thing available) included details about the study but not the !@#$ results.

So, I had to send away to NTIS for a hard copy.  I have uploaded it to Scribd.com to make this important piece of research more generally available.

The study asked about 60 US army captains familiar with the scoring system to evaluate 100 comparative statements.  The results were pretty damning:
"Findings of the present study indicate that the two-dimensional evaluation should be replaced because:
1.  The accuracy rating dominates the interpretation of a joint accuracy and reliability rating and
2.  There is frequently an undeniable correlation between the two scales."
You can read the full study below or download it from here. 

All of this raises another issue, though.  It seems that every 20 years or so the US national security intel community takes a crack at validating its methods and processes.  Sherman Kent talks about one such effort in the 50's and then, again, in the 70's and early 80s there seems to have been another attempt (the report referenced here is an example).  We seem to be entering into another such era given some of the language coming out of IARPA.

For some reason, however, just when things get good, the effort peters out.  When these efforts peter out in the intel community, however, the results become almost impossible to find.  Not having this research on hand and, frankly, online, means that the government will inevitably pay for the same research twice (the questions don't go away just because we forget what the answers are...) and researchers will be forced to start from scratch even though they don't have to.

I won't repeat my rant from a few days ago, but finding and keeping track of this kind of stuff seems to be a perfect task for academe and the kind of thing the DNI ought to fund (Hint, hint...).

Subjective Interpretation of Reliability and Accuracy Scales For Evaluating Military Intelligence
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