Nate Silver is most famous in the political world for having correctly predicted the results, on a state-by-state level, of the US presidential election in 2008. That’s back when Obama was first elected president. It’s hard to imagine now, but the idea that Obama would win was only given an outside chance by most commentators at the time.
I find it hard to refer to Nate as anything other than Nate since I’ve been listening to the FiveThirtyEight podcast for so long. We don’t know one another, but he’s become a colleague and mentor who lives inside of my head. The reason he is so important to me is because he has become one of my strongest contemporary influences. His success has given me a roadmap for how to lead my life as a mathematical modeller.
I have been developing a series of articles on Mathematics and Biology (article 1, article 2, more to follow). A common theme in these articles is how a mathematically trained individual finds their place in the modern work environment. We want to pursue our art, we also have professional standards and a lot to contribute, but somehow the connection between our skills and the needs of others are missing. By following Nate’s work, I have at least one strong role model who I can attempt to model.
I have spent much of my life looking for role models amongst older generations. My approach to science and academia is very similar to that of gifted individuals 40+ years my senior. A number of them have met me and commented on it with a weird mix of awe and fear – they strongly advise their grad students not to follow this approach!
The world has changed. There are more people nowadays who are good at maths. More importantly, it is no longer clear what it means to be good at maths. Does it mean good at numerical computing? Or at algebraic manipulation? Or differentiation?
Most commonly, being good at maths today means you did well on a set of narrowly focused exams which rewarded rote learning. I am not going to disparage these people. This is what the school system rewards. But rote learning does not set you up so well for deciding between alternative methods. You use the tool you know – and this most commonly translates in practice into – you use the tool you are best able to manipulate.
I was vaguely aware of Nate Silver during and following the 2008 US elections. Back then he just seemed like another talking head. His book, The Signal and The Noise, came out in 2012. I have to admit that I ignored the book at the time. I certainly heard of it, but I dismissed it as a popularisation that I didn’t have time to read.
2012 was another US election year however, and I was glued to FiveThirtyEight for their model and election coverage. I loved the mathematical approach to model building. I loved the openness that the model was not perfect, that it was a work in progress, that it could be improved upon. I am a fan of politics, but I particularly loved the attempt to de-noise the coverage.
2012 was also the year that I moved to the Departments of Statistics and Neurobiology at the University of Chicago. Obama’s house was about 600 metres up the street from my office. And I was in a university that has a certain reputation and specialises in numerical approaches to every field they teach.
Coincidentally, the University of Chicago is also Nate Silver’s undergraduate alma mater. And so, despite the high crime rate, I found a place for myself there. I was finally in a school where you could comfortably hold a single conversation about the impact of language on religion, with meaningful forays into geopolitics and the most appropriate mathematical methods for analysing such questions.
What I have gotten from Nate’s example is a lesson in how a mathematically inclined person can follow their interests without being relegated to the back room. I don’t think that fame is particularly important to either myself or to Nate. I may be wrong, but it seems like any attention seeking is rather calculated on both our parts. Reputation is an enabler, not an ego device.
The problem with being the math guy, is that you are called in to solve difficult tasks and then the rest of the time you are either unemployed or working on uninteresting tasks. I know that data doesn’t solve everything, but it is noteworthy that CEOs in most western economies continue to make their decisions based on intuition (gut) rather than data (2018 KPMG study). As the math guy you are more frequently perceived as a necessary inconvenience rather than a valued member of the team.
Ironically, I have experienced exactly the same problem in my academic career. I would have thought that if any place was free from a bias against mathematicians it would be academia, but my problem was that I wanted to play outside of the traditional mathematicians sandbox. I didn’t just want to make tools for other mathematicians. Nor did I want to write papers that one grad student in 10 years might read. I wanted to apply mathematics to real (academic) problems. However the real problems lay in other academic domains. I was welcome to come and help when they had a serious problem. But they also preferred to trust their guts rather than follow model-driven hypothesis generation. And more importantly, they wanted me to leave the playing field, rather than occupying a valuable tenured position, once the model was done.
Nate has completely overcome this issue in his own career. He has been a serial entrepreneur since 2003 and is rewriting the rule-book on what it means to be a journalist. I imagine the path has been anything but easy. But it also seems eminently worthwhile. Moreover, with every success he opens the doors to future interesting projects, and blazes a trail for the rest of us.
I have learned that I can have a career as a mathematical modeller. And it is not necessary that I do it from a consultancy position. The key seems to be to figure out a product or service in which my mathematical skills are truly a value-add proposition. That’s why I am now able to work in healthcare and Nate works in journalism. We are both following our personal passions, but we chose to situate ourselves at the points of maximal impact of our skills within those fields.
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