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I first got introduced to the forecast ra by a long time mine at Dartmouth been Valentino who is
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a political scientist and he alerted me to an opportunity to forecast with the good judgment project and this was right
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around the time when i was leaving baghdad iraq after my second tour there and i was looking for some way of doing
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forecasting because i've been something that I've been interested in for for a
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while and that's why been introduced me to this idea and you know I the timing
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worked out as well I was able to come back to the United States and that was right around the time the the first year
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of the tournament kicked off and I just went from there I think that bottom line intellectual
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curiosity and just a willingness to put in the work and to think hard about specific problems and try to be as
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objective as possible is what allowed me to make more accurate forecasts and others within the pool I wouldn't
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necessarily say that you know what we did or what I did as an individual is the best possible at forecasting because
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they're you know can be so many more improvements I I think in terms of how much you know about a specific subject
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you can always improve your level of knowledge I think you can always improve you know how you're you're specifically
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viewing a situation how that situation could potentially evolve so having a greater understanding of how humans
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interact with each other relate to each other the political contours of specific
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situations and events those are all things that you can gain greater knowledge on and get better at
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forecasting in so yeah yeah being open-minded and being open-minded enough to realize that you need to remain open
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minded I think are some of the keys to being you know for for my own forecasting performance
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so I really had three general rules when I made forecasts especially when I made
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my first forecast on a new question or a situation I'd never seen before so the
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first thing I would say is to be a good forecasters you have to be you have to hold strong opinions weekly and what I
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mean by that is that you do all of your homework up front and you really present
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a good case for why you feel a certain way on a specific question and defending your probability probability estimate at
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that point but when you recognize that somebody else has more information or better information than you having the
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ability to change your mind swiftly to that new forecast I think that was one of the keys to why I was able to you
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know improve my performance over time I think many people really get stuck on their initial forecast and they fall in
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love with it and wind up becoming going into a defensive Crouch when it comes to
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defending their opinion whereas I was on my team sort of notorious for being able
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to switch from one a very hard position all the way to the opposite when I saw new information and come up that led me
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to do that the second thing is to be willing to put in the homework and to put in the effort to understand a
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situation go beyond the Wikipedia page and to go beyond the initial couple of news articles and to really try to
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understand you know what is it what is it about Boko Haram and their composition that you know is allowing
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them to make the kinds of military gains that there that we're seeing and how
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fragile or stable are those military gains compared to other like organizations and to you know not just
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to say Oh Boko Haram looks like every other organization that I've encountered
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to this point but to say to really try to understand what's going on there and
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to contextualize that appropriately and I think the the third thing is to have in your mind the kinds of
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psychological and cognitive biases that you could potentially fall prey to and to be able to overcome those by you know
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listening to your teammates by self-critique and to recognize that you know whatever forecast and argument that
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you're putting forward now you should be able to alter it or change it or improve
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it in light of new information so you know keeping in mind the cognitive biases that really impact and influence
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and reduce our accuracy and to consciously try to D bias them I think you could really do two things
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to become a good forecaster and one eye one is to read and not just read say Phil's book super forecasting or Dan
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economies book Thinking Fast and Slow which I think many of the forecasters who excelled in torment have read and
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done I also think that you know reading say histories like the guns of august or
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books about bureaucracy by james q wilson and others really improves your your knowledge base and gives you a
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better context for looking at situations and being able to figure out whether there are any commonalities or patterns
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there that you can pick up on and that could potentially apply to future situations that look like that so being
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well-read is I think a contributor to forecasting success the second thing is to just to practice don't get hung up on
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wrong forecasts that you make initially you know don't don't get overly you know
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sensitive to those results but to approach forecasting as something that you can improve on and have that growth
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mindset when it comes to making better forecasts and so from there you're able
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to say okay I start at some baseline level I got some feedback tells me I should improve an XY and Z and to really
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make a concerted effort to do that through practice I think being a forecaster and being a
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researcher are similar and different I think that one of the great things about being a forecaster is that we really
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weren't constrained by any of the kind of customs or sociology around for a custom because we were the ones coming
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up with that and so we were able to explore and be very free in how we approach forecasting whereas I think
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research while you have some freedom in the hypotheses that you are tackling a lot of the methodology and the structure
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around writing papers and peer review and submissions is very much rigid and you must follow the the specific process
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so i think that that the highlights a major difference in forecasting versus doing the research in that the research
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seem to be much more process oriented although obviously there there's an outcome component to it whereas when
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when we were doing strictly forecasting really people only care that we were able to come up with the right answers
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rather than you know how exactly we we got there so yeah they're different they're different animals
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you