In a talk given as part of the 2015 MLC Speaker Series, Dr. Blake Howald discussed the application of his linguistics training to his work in Research and Development. In this clip, he offers advice on maintaining relevance as a subject-matter expert through the ever-changing demands of the market.
Dr. Howald is Manager of Content Strategy and Planning in Thomson Reuters' central technology group where he focuses on efforts to streamline the creation, maintenance and governance of content within an enterprise ("big data") context. Blake received a BA from the University of Pittsburgh, a JD from the University of Detroit Mercy and a MS and PhD from Georgetown University.
What was most important is that you had a very, very strong orientation to things like scientific method. If you were using stats, you really knew about stats. Like, fundamentally knew about stats. When you used the terms like ‘mean,’ and ‘variance,’ and ‘mode,’ you really knew what that meant. You also understood what limitations your analysis would have based on the statistics. That's really, really important, because you would often, given the size of how small it was, you would say, "This week we have this data. So here's, you know, ten gigabytes of data. It's text from whatever, right? We want to know if ‘X’ can happen with it." So you'd have to take the data, pull it apart, run some analyses. You'd have to understand the limitations of what you were trying to show, and that understanding is really essential because the next step was often that you would have to communicate those results out to other people. And when you communicate results out to other people, you're going to be exposed to people who have a very broad range of understanding about lots of different things, not necessarily the thing that you know and you talk about. And you'll encounter this in conference presentations. You might have a room full of linguists, really, really smart people. Maybe, you know, the people that you're citing are actually in that talk. But at that moment, they're running from another talk. And now they're set down in front of you, and you have twenty minutes to tell them about what you're doing. You have to be able to talk in a way that is actually understandable to that individual. So you can't be complex. You can't throw around a lot of heavy terms. You only really get good at doing that through practice, but also really understanding what it is that you're communicating and talking about.
I was talking to Jen about this. We used to rule candidates out coming for jobs who would use statistics all the time but when you actually asked them to explain statistics, they would fail miserably. You know, not that statistics is easy, but we started giving tests, so, “Define this for me. Define that for me.” And some people would really have a hard time. Like we would catch people trying to give the Wikipedia definitions, which we all knew by heart. Because people would come and repeat them right off Wikipedia, like, "Oh! Variance is…blah blah blah." And you're like, "Oh yeah! I'm reading the same thing you are." [laughter] So just in general, whatever it is that you're ultimately interested in doing in linguistics, just do it well. Do it very deeply. Understand it from all different dimensions. That process of really understanding and being a subject matter expert is what's most important. Because when you get into R & D groups, if you ever go down that road, on any given day, it's gonna be a completely new domain. You know nothing about it, but you're gonna have to formally, in some way, investigate it and report out the results. By knowing whatever it is your subject matter is in a very deep and personalized way, will allow you to do that to any domain. So it has to be very genuine.