You Should Follow Me On Twitter! (I'm Not Kidding -- @kwheaton)

I'm not dead.

I do appreciate the emails (well, email, anyway...) expressing some measure of concern about my health given my infrequent posting schedule over the last several months but I have an excuse. 

I have been busy trying to figure out Twitter.

I know, I know; it seemed useless and futile to me as well.  It felt for so many years like this big swamp of Justin Bieber and Ashton Kutcher at one end and people yakking about what they had for lunch at the other. 

Quite recently, though, it has become something different for me.  It began with a simple decision I made this last summer to migrate my "link list" stuff to Twitter.  Link lists are what bloggers call those long lists of hyperlinks they package in a post for their readers.  They are pretty much a staple of any blog -- when you can't think of anything else to write, you do a link list.

Except that most of the stuff I read -- good stuff -- never made it to a link list at all.  Writing it up takes time and I don't have enough of that.  Twitter seemed like a good way to broadcast the good stuff I had found or, increasingly, have sent to me, without busting the social media, fiddling-with-stuff, time budget.

It worked, too.  More importantly, it led me to explore Twitter more deeply.  Most people familiar with the tool already know it to be an excellent source of real time information and, with a little effort, an outstanding stream of curated news and information.  We have even used it to explore a modern interpretation of the age-old intelligence concept of the "agent network". 

As I move forward, I intend to get back to blogging more.  It is still the best way to express more detailed thoughts about education and intelligence and games and other things that interest me.  Blogs are still, to me, at least, more about the conversation and less about concision.  I have been blogging now for over five years and I just don't see myself giving it up.

Still -- you should follow me on Twitter!

How Many Entry-level Analysts Will The US IC Need In 2013? (Survey)

Good question, right? 

 

If you have direct knowledge of information that might help answer the question in the title or you have indirect knowledge that is relevant to the answer to the question in the title, please take 2 minutes to complete this survey. 

 

What do I mean by direct and indirect knowledge?

Direct knowledge means that you know personally or have good information concerning the hiring plans of your agency or organization (or at least your section or division).  You might work in HR or be a manager with hiring responsibilities. 

Indirect knowledge is information that is relevant to the question that is not due to your direct responsibilities.  You might have spoken with an HR manager or have been involved in meetings where this issue was discussed. 

We are NOT looking for opinion based on purely circumstantial information.  If you are not involved in the hiring process either directly or indirectly, please DO NOT take this survey.

Why are we interested?

Every year, other disciplines announce hiring projections for the year:  "This year's hot jobs are for engineers and chimney sweeps."  That sort of thing.  Entry level intelligence analysts who are searching for a job, on the other hand, receive no such guidance.

We hope to change that.  Working with one of our hot-shot grad students, Greg Marchwinski, we put together this survey to get a better feel for the the job market for entry level analysts for the year ahead.

Once we get enough survey data, Greg will compile it and combine it with the macro-level, mostly qualitative data that we already have and put together a "jobs report" for the year ahead.  I will publish it here once we are done.

We understand that there are some legitimate security concerns here so we have tried to frame the questions such that they are focused on broad developments and general trends.  We are not interested in the kind of deep details that might compromise security.

Finally, we intend to follow this study up with similar surveys of the law enforcement and business job markets for entry-level intelligence analysts as well.

By the way, this is the same question we asked last year and here is the answer we got...

Thanks for your participation!

Want To Do Something Different This Thanksgiving?

Some of the action on DAGGRE.org

Eating, shopping, driving, yelling, more eating...I get it.  What is Thanksgiving without its traditional activities?

But, if you were looking to do something a bit different, you might want to check out the recent updates to the DAGGRE prediction market.

(I know, I know, I am such a shill for DAGGRE...)

Yes, in the interests of full disclosure, I am a member of this IARPA funded research project and yes, I probably love it way too much but the most recent changes to our site's software are, frankly...cool.

Real cool.  Like never before seen cool.

Why?  Because now you can do real-world, real time linchpin and driver analysis in a prediction market.

I am pretty excited about this but it might not be obvious why, so let me break it down.  Prediction markets typically work by asking resolvable questions like "Will Despot X be out of power by 31 DEC 2012?"  Then various people interested in that question will go into the market and make "edits" that assess the probability of the answer to this question being yes or no.  For example, if I thought Despot X would almost certainly be out of power by the end of the year, I would go in and change the probability to, say, 90%.  Someone else might go in after me and think, "What an idiot!" and change it back to 25%.  When 31 DEC rolls around one of us will be closer to right and the other closer to wrong.  The one closest to right scores the most points on the market.

This system works pretty well with straightforward questions that obviously lean strongly in one direction or another (EX:  "Will a shooting war break out between the US and Canada before 31 DEC 2012?"  Uh...no.).  It works significantly less well with more nuanced questions that really deserve to be teased apart.

This is essentially what the CIA's Deputy Director For Intelligence, Douglas MacEachin, was trying to do back in the early 1990's when he insisted on having his analysts identify linchpins and drivers.  To quote an early version of the CIA Tradecraft Manual, drivers are "key variables...that analysts judge most likely to determine the outcome of a complex situation" while linchpins are "the premises that hold the argument together and warrant the validity of the conclusion." 

This kind of analysis is pretty sophisticated stuff and it really is what makes the difference between a bald estimate ("X is 80% likely to happen") and the kind of estimate most decisionmakers expect ("Despite A and due primarily to B and C, X is 80% likely to happen.").

Before, you simply couldn't do this kind of stuff in a prediction market.  Now, with the most recent upgrade to the DAGGRE market, you can.  Let's go back to our Despot X example.  We know that rebel forces are trying to take a key city in this despot's country.  We also strongly believe that if the rebels take the city the despot's days are numbered.  Before, our estimate of the despot's longevity was a mish-mash of many factors, one of which was the possible(?)/probable(?) fall of the key city and our estimate probably was much more wishy-washy than we wanted it to be.

The DAGGRE market now lets you not only make estimates on both how likely the city is to fall and on how likely the despot is to stay in power but also allows you to make the answer to one of these questions, an assumption for the other (EX:  "Assuming key city falls, Despot X is 90% likely to be out of power by 31 DEC 2012.").

In my mind this is a huge step forward in making prediction markets more useful to real-world analysts working on real-world questions.  Definitely worth taking a few minutes to check out over Thanksgiving!

An Interesting Perspective On What It Means To Be A Vet

If you have a few minutes this Veterans' Day, this video is worth your time...

What Can Intelligence Expect From Prediction Markets?

Opening screen of the DAGGRE.org prediction market

Prediction markets have long been touted as tools that have a wide variety of potential uses for intelligence professionals.  Far more accurate in many cases than expert judgement alone, these markets tend to incentivize good thinking and punish poor thinking in ways that, over time, produce quantifiably better results on topics like elections and sales forecasts.  Strong advocates of this method have even suggested that these markets might be able to replace traditional analysts entirely.

Naysayers have (and will likely continue...) to argue that the kinds of questions asked of intelligence professionals do not lend themselves to pat, numerical estimates.  Furthermore, they will say, even in the handful of cases where such answers would be of potential use, combining the estimates of people who know little to nothing about the details of a particular, narrow problem -- the kind that is usually of intelligence interest -- will only serve to create an estimate that is also of little to no use.  Finally, while these estimates are useless in forecasting the future (or so the naysayers will say), they will serve to anchor both intelligence professionals and policymakers alike, reducing their ability to see alternatives to the predicted outcome.

The purpose of this series of posts, then, is to explore both sides of this argument, to look at prediction markets from the point of view of the intelligence profession and in light of ongoing research and to come to some preliminary conclusions about the future of prediction markets as a tool for the working intelligence professional and the decisionmakers they support.

Informing this series will be the results of research done by the DAGGRE prediction market and the scientists involved in that effort.  DAGGRE is run by Dr. Charles Twardy of the C4I Center at George Mason University and is working in cooperation with a number of other universities and organizations (including Mercyhurst University and yours truly) to better understand prediction markets and their potential uses to the intelligence community.  

The DAGGRE project is one of five such projects funded by the Intelligence Advanced Research Projects Activity (IARPA) under their Aggregative Contingent Estimation (ACE) program.  Now in its second year, ACE has already produced a number of interesting results and promises to produce many more.  

In short, whatever your initial reaction is to the idea of prediction markets in intelligence, this series is designed to give the working intelligence professional inside access to some of the most interesting and intriguing results from research currently being done on prediction markets and intelligence questions.  My goal is to turn these results into “plain English” so that you can have an informed opinion about these unique tools.

Next Week:  What Is A Prediction Market?