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