Center Of Mass (Or How To Think Strategically About Generative AI)

It may seem like generative AI is moving too fast right now for cogent strategic thinking.  At the edges of it, that is probably right.  Those "up in the high country," as Lloyd Bridges might put it (see clip below), are dealing with incalculably difficult technical and ethical challenges and opportunities as each new version of Claude, ChatGPT, Gemini, Llama, or other foundational large language model tries to outperform yesterday's release.

 

That said, while all this churn and hype is very real at the margins, I have seen a fairly stable center start to emerge since November, 2022 when ChatGPT first released.  What do I mean, then, by "a fairly stable center?

For the last 20 months, my students, colleagues, and I have been using a wide variety of generative AI models on all sorts of problems.  Much of this effort has been exploratory, designed to test these tools against realistic, if not real, problems.  Some of it has been real, though--double-checked and verified--but real products for real people.  

It has never been standalone however. No one in the center of mass is ready or comfortable completely turning over anything but scut work to the AIs.  In short, anyone who uses a commercially available AI on a regular basis to do regular work rapidly comes to see them as useful assistants, unable to do most work unsupervised, but of enormous benefit otherwise. 

What else have I learned over the last 20 months? 

As I look at much of what I have written recently, it has almost all been about generative AI and how to think about it.  My target audience has always been regular people looking for an edge in doing regular work--the center of mass.  My goal has been to find the universals--the things that I think are common to a "normal" experience with generative AI.  I don't want to trivialize the legitimate concerns about what generative AIs might be able to do in the future, nor to suggest I have some sort of deep technical insights into how it all works or how to make it better.  I do want to understand, at scale, what it might be good for today and how best to think about it strategically.

My sources of information include my own day-to-day experience of the grind with and without generative AI.  I can supplement that with the experiences of dozens of students and my faculty colleagues (as well as with what little research is currently available).  All together, we think we have learned a lot of "big picture" lessons.  Seven to be exact:

1. Generative AI is neither a savior nor Satan.  Most people start out in one of these two camps.  The more you play around with generative AIs, the more you realize that both points of view are wrong and that the truth is more nuanced.
2. Generative AI is so fast it fools you into thinking it is better than it is.  Generative AI is blindingly fast.  A study done last year using writing tasks for midlevel professionals found that participants were 40% faster at completing the task when they used the then current version of ChatGPT.  Once they got past the awe they felt at the speed of the response, most of my students, however, said the quality of the output was little better than average.  The same study mentioned earlier found similar results.  The speed improved 40% but the average quality of the writing only improved 18%.
3. Generative AI is better at form than content.  Content is what you want to say and form is how you want to say it.  Form can be vastly more important than content if the goal is too communicate effectively.  You'd probably explain Keynesian economics to middle-schoolers differently than you would to PHD candidates, for example.  Generative AI generally excels at re-packaging content from one form to another.  
4. Generative AI works best if you already know your stuff.  Generative AI is pretty good and it is getting better fast.  But it does make mistakes.  Sometimes it is just plain wrong and sometimes it makes stuff up.  If you know your discipline already, most of these errors are easy to spot and correct.  If you don't know your discipline already, then you are swimming at your own risk.
5. Good questions are becoming more valuable than good answers.  In terms of absolute costs to an individual user, generative AI is pretty cheap and the cost of a good or good enough answer is plummeting as a result.  This, in turn, implies that the value of good question is going up.  Figuring out how to ask better questions at scale is one largely unexplored way to get a lot more out of a generative AI investment.
6. Yesterday's philosophy is tomorrow's AI safeguard.  AI is good at some ethical issues, lousy at others (and is a terrible forecaster).  A broad understanding of a couple thousand years of philosophical thinking about right and wrong can actually help you navigate these waters.
7. There is a difference between intelligence and wisdom.  There is a growing body of researchers who are looking beyond the current fascination with artificial intelligence and towards what some of them are calling "artificial wisdom."  This difference--between intelligence and wisdom--is a useful distinction that captures much of the strategic unease with current generative AIs in a single word.

These "universals" have all held up pretty well since I first started formulating them a little over a year ago.  While I am certain they will change over time and that I might not be able to attest to any of them this time next year, right now they represent useful starting points for a wide variety of strategic thought exercises about generative AIs.

Cyber Teachers! Here's A Cool Resource You Should Know About...

A couple of my colleagues in the cyber department here at the Center for Strategic Leadership at the US Army War College have put together a very handy resource for anyone working or teaching cyber or cyber-related issues:  The Strategic Cyberspace Operations Guide.

Nothing in the guide should be particularly new to experienced cyber instructors.  It is still extraordinarily useful as it puts everything together in one package.  As the authors said themselves, "It combines U.S. Government Unclassified and Releasable to the Public documents into a single guide."  

The 164 page document contains six chapters:

• Chapter 1 provides an overview of cyberspace operations, operational design methodology, and joint planning, and execution. 
• Chapter 2 includes a review of operational design doctrine and applies these principles to the cyberspace domain. 
• Chapter 3 reviews the joint planning process and identifies cyberspace operations planning concerns. 
• Chapter 4 describes cyberspace operations during the execution of joint operations. 
• Chapter 5 provides an overview of cyberspace operations in the homeland. 
• Chapter 6 includes a case study on the Russian – Georgian conflict in 2008 with a focus on cyberspace operations.

I found the entire document to be very well edited and presented.  It was about as easy a read as this sort of thing can be.  Most importantly, it did the really hard work of getting it all into a single package.  Recommended!

(Reader's Note:  As always, the views expressed in this blog are my own random musings and do not represent any official positions.)

NOW AVAILABLE: The Ancient Viking Game Every Intelligence Professional Should Play

Panel from the comic, Cthulhu Vs The Vikings

 

A couple of weeks ago I posted an article about the ancient Viking game, Hnefatafl, along with some thoughts about why I thought it was a good game for intel professionals to play. 

A lot - and I mean a lot - has happened since then.

The most important thing (at least to me) is that I have developed a new version of the game that is now for sale.  It is called Cthulhu vs. The Vikings and is currently available on Kickstarter.  The backstory to the game, which is told in the form of a comic, mashes-up the Viking sagas with the Cthulhu stories from H.P. Lovecraft (a horror writer from the 1920's).

While the game itself also plays on those themes in terms of the design work (in the board and the pieces), the rules are straight Hnefatafl.  In fact, I got permission from the Fetlar Hnefatafl Panel, which sponsors the Hnefatafl World Championships, to use their rules (Note:  The Hnefatafl World Championships were held AUG 3 in Fetlar Scotland and Amanda Caukwell is the new World Champion!).

Bottomline:  If you are looking for an attractive and affordable copy of the ancient Viking game, Hnefatafl, you can now find one here.

The blog post also got picked up by the radio show, The World, produced jointly by the BBC, Public Radio International and Boston's WGBH.  They interviewed me about the game and about its importance to intelligence professionals.  You can listen to the interview below:

Finally, the game and its relationship to intel also got a little local press and a lot of interest from the readers of this blog (Thanks for the emails and kind words)! 

The Ancient Viking Game Every Intelligence Professional Should Play

On August 3rd, the village of Fetlar, Scotland (go ahead, try to find it - I'll wait), will hold the Hnefatafl World Championships.  With a population of 86, Fetlar might seem an unlikely place to hold the world championships of one of the world's oldest games.  The truth is Hnefatafl, or "King's Table", is nowhere near as popular today as it was in the days of the Vikings.  In fact, for the 250 or so years that make up the Viking Age, Hnefatafl (or games very similar to it) was the chess, the checkers, the go, and the Nintendo for the Norse.   

A modern version of Hnefatafl.  Traditional boards are simpler and pieces were often stones or marbles.  The layout and the rules are, however, the same.

Today, only dedicated tabletop gamers have ever heard of it and many of them have never had a chance to play the game.  That is a shame for it's an extraordinary game with a number of lessons embedded in it for the curious intelligence professional.  For example:

• It is an asymmetric game.  As you can see from the board above, one side starts in the center and the other side surrounds it on all four sides.  One side outnumbers the other by about 2:1.  The sides even have different victory conditions (the player with the pieces in the center need to get the "King", the large playing piece in the middle of the board, to one of the corners.  The other player is trying to capture the King).  It is not too hard to see a game such as this one incorporated into courses, classes or discussions of asymmetric warfare.
• It is a conflict simulation.  Most historians agree that there were relatively few large scale battles involving Vikings. Instead, most of the time, combat resulted from raiding activities.  Hnefatafl seems to reflect the worst case scenario for a Viking raider:  Cut off from your boats and outnumbered 2:1. 
• It provides a deep lesson in strategic thinking.  Lessons in both the strategy of the central position (hundred of years before Napoleon made it famous) and in the relative value of interior vs. exterior lines of communication are embedded in this game. 

What makes this game even more fascinating for me is what it teaches implicitly - that is, what are the lessons it teaches the players without the players knowing that they are learning?  Furthermore, what does this tell us about the Viking culture?  For example:

• It takes two soldiers to kill another soldier.  This is one of the few games where it takes more than one piece to capture another piece.  Basically, one pins and the other piece comes up and deals the killing blow.  
• It is good to be King.  The only piece that really matters is the King.  If the King escapes and loses 90% of his soldiers in the process, it is still a victory.  Likewise, if the King is captured but at a horrific cost to the enemy, it is still a loss.
• It is easier for the player in the center to win.  You heard that right, because of the value of interior lines and because of the difficulty of capturing the King, the player who is surrounded, cut-off and outnumbered 2:1 has the advantage.  In fact, in games with novices a simple, "fight through the ambush" strategy almost always wins.

Now, imagine this game being played night after night in the langhús of some Viking Jarl.  What lessons are being implicitly conveyed to the young Viking warriors?  Work together, protect the King, and don't worry about how bad it looks - we can win!  All in all, not a bad way to teach important lessons in a barely literate society.  More importantly, understanding this game provides yet another insight into Viking culture and strategic thinking. 

The value of this particular game to intelligence professionals and others is one of the reasons I decided to offer a version of it as the second game from my new company, Sources and Methods Games.  It has historical significance as well as providing deep lessons in asymmetric warfare, strategy and cultural intelligence.  It is an excellent addition to the intelligence studies classroom.

Teaching Strategic Intelligence Through Games (Final Version With Abstract)

Abstract:

Strategic intelligence is considered by intelligence professionals to be the highest form of the analytic art.   There is a tremendous demand for this type of intelligence product and a lack of trained professionals capable of producing it.  Developing effective teaching methods for this challenging subject, therefore, is an area of ongoing concern for the business, law enforcement and national security intelligence communities.

Previous research suggests that a game-based approach to teaching can be successful but no report so far has examined game-based learning in intelligence analysis.  I hypothesized that a game-based approach to teaching strategic intelligence analysis would increase learning and improve performance while also increasing student satisfaction with the course.

This paper reports the initial results and lessons learned from teaching three full courses (2 undergraduate and one graduate) in strategic intelligence using games as a teaching tool.  The paper will begin by examining the unique challenges in teaching about strategy, strategic decisionmaking and the types of intelligence that supports those efforts.  This will be followed by a short discussion concerning games based learning generally before examining in detail the specific approaches used in these three courses.   

This paper will also examine both the learning outcomes and student satisfaction with the courses.  Finally, this paper will discuss appropriate course modifications for undergraduate and graduate students when teaching advanced subjects with games based on the evidence from this study.
 

Part 1 -- Introduction

Part 2 -- What Is Strategy And What Are Strategic Decisions?

Part 3 -- What Is Intelligence And What Is The Role Of Intelligence In The Formulation Of Strategy? 

Part 4 -- Why Games? 

Part 5 -- How, Specifically, Were Games Used in Class? 

Part 6 -- So, How Did It All Work Out? 

Part 7 -- What Did The Students Think About It?

Part 8 -- What Else Did You Learn? 

Teaching Strategic Intelligence Through Games

Part 2 -- What Is Strategy And What Are Strategic Decisions? (Teaching Strategic Intel Through Games)

Image via Wikipedia

Part 1 -- Introduction

"As war is a game through its objective nature, so also is it through its subjective. -- Carl von Clausewitz, On War, Chapter 1.

While there are many definitions of "strategy" and "strategic decisions", for the purposes of this paper, a strategy is an idea or set of ideas about how to accomplish a goal and strategic decisions are ones that typically put at risk a substantial portion of an entity's disposable resources.

Defining strategy broadly is important.  Far too often, strategy is only associated with terms such as "long-term" or "large" and strategic thinking is something accomplished only at corporate headquarters or by generals and kings.

Defining strategic decisions in the context of the resources risked by the entity (person or organization) making the decision puts the role of strategy into perspective.  Under this definition, it is possible for the exact same decision to be strategic in one case and tactical (or even trivial) in another context. 

For example, imagine an individual who owns a successful dry cleaning store.  Deciding to open up another branch of the store in a different part of town is clearly a strategic decision for this owner.  This owner will likely spend many of his disposable resources (time, money, personnel) getting the new branch set up and operating efficiently.  Failure with this new branch would likely impact the old branch as well.

The same decision, to open another branch in the same town by the owner of a chain of 10,000 dry cleaning stores does not have the same strategic quality as in the first case.  In fact, such a decision, in such a large, national organization, might not even be made at the owner’s level.  The percentage of disposable resources placed at risk with this decision is likely much less and it is entirely possible that such a decision would be pushed down to regional or even sub-regional levels.

More importantly, defining strategy in terms of the resources at risk broadens the scope of what arguably constitutes strategic intelligence as well.   Under this definition, strategy is not confined to large, powerful organizations.  Small businesses, police units and even students can have strategies and, in turn, require strategic intelligence to support their decision-making processes.

Next:
What is intelligence and what is the role of intelligence in the formulation of strategy?

Teaching Strategic Intelligence Through Games (Original Research)

(Note:  This is another in a series of posts that I refer to as “experimental scholarship” -- or using the medium of the internet and the vehicle of this blog as a way to put my research online for more or less real-time peer review. Earlier examples of this genre include: A Wiki Is Like A Room..., The Revolution Begins On Page 5, What Is Intelligence? and What Do Words Of Estimative Probability Mean?.  

This series of posts is based off a paper I gave at the Game Education Summit last week.)

Strategic intelligence is considered by intelligence professionals to be the highest form of the analytic art.   There is a tremendous need for this type of intelligence product and a lack of trained professionals capable of producing it.  Developing effective teaching methods for this challenging subject, therefore, is an area of ongoing concern for the business, law enforcement and national security intelligence communities.

Previous research (cited in detail in later posts) suggests that a game-based approach to teaching can be successful but no report so far has examined game-based learning in teaching intelligence analysis.  I hypothesized that a game-based approach to teaching strategic intelligence analysis would increase learning and improve performance while also increasing student satisfaction with the course.

This series of posts reports the initial results and lessons learned from teaching three full courses (2 undergraduate and one graduate) in strategic intelligence using games as a teaching tool.  This series of posts will begin by examining the unique challenges in teaching strategy, strategic decisionmaking and the types of intelligence that supports those efforts.  This will be followed by a short discussion concerning games-based learning generally before examining in detail the specific approaches used in these three courses. 

 

This series of posts will also examine both the learning outcomes and student satisfaction with the courses.  Finally, this series of posts will discuss appropriate course modifications for undergraduate and graduate students when teaching advanced subjects with games based on the evidence from this study.

Next:
What is strategy and what are strategic decisions?