GUEST COLUMN | By Katie Zhu
I came into Northwestern University as a Journalism major. A year later, I also decided to study Computer Science. On paper, the requirements for my Journalism and Computer Science degrees could not be more different. Reporting and editing on one end of the spectrum; algorithms and data structures on the other. But in the real world?
Having programming skills makes you highly marketable in the journalism industry. Newsroom developers and interactive graphic designers are all the rage. Coding + journalism = mad ups. So naturally, it makes sense for existing j-schools to be integrating the two fields and exploring the emerging discipline of “journalism and technology.” And wouldn’t you know it—that’s exactly the name of one class I took last quarter.
“Innovation in Journalism and Technology” is cross-listed in the journalism and computer science departments (JOUR 390 / EECS 338), so it’s a mix of both journalists and programmers who enroll. The class is taught by professors Jeremy Gilbert and Larry Birnbaum (both affiliated with Northwestern’s Knight News Innovation Lab) and is essentially a practicum: you’re assigned a team and a project at the start of the quarter, working through various deliverables throughout the course that guide you from project conception to execution. At the end of the quarter, we were fortunate enough to present our projects to relevant individuals in news innovation and have our presentations webcast online (using Mediasite by Sonic Foundry). It was great to have the opportunity to present our work to anyone interested in the intersection of journalism and technology—promoting the work and sentiments being done in this field.
I specifically worked on DriveThru, a mobile-optimized website of time-based news. The news app offers users the option between a two-minute news package (The Scoop) and a 10-minute package (The Works). My group and I worked through use cases, user scenarios, wireframes and HTML prototypes before building the dynamic product. Along the way, we did both research into existing news apps targeted to users on-the-go, as well as field testing of reading speeds so we could determine the appropriate word counts of each timed package.
The class did a great job of simulating real-world product development in the context of news applications. Having my feet in both camps—the code and also the words—I appreciate the value of journalism and computer science separately, but really, I think it’s the overlap between the two that’s most exciting. Indulge me for a moment.
Computer science as a discipline is truly beautiful. I can’t even begin to appreciate how fascinating it is: The principles of graph theory used in amazingly efficient algorithms that drive our world today; the artificial intelligence behind Watson; the natural language processing underlying Siri.
Even as a computer science major, I am still only beginning to truly appreciate the beauty, elegance and art of the discipline’s theory. I have nothing but respect for it and admiration for theoretical computer scientists. But it’s abstract. It’s difficult to grasp—let alone understand. What people can point to, what is tangible and has immediate impact, that’s application. That’s computer science applied to journalism. That’s “11FA-JournTech.”
For me, Gilbert and Birnbaum’s class embodies the ever-growing role of technology in connecting users around the world. And it’s natural that journalism plays such a pivotal part in this task, because news fulfills that same function.
Information and technology are converging. Traditionally, news was simply an information product. But it needs to adapt to a technology dimension. Journalists in the current news industry have to expand their scope of what “journalism” means.
At its broadest, it boils down to input and output. And at that level of abstraction, I could just as easily be talking about computer science. Input. Black box. Output. With respect to journalism, the input is sources, quotes, numbers. The black box traditionally encompassed reporters and editors who synthesized information to craft narratives. And the output is the story, be it printed words on a page or on a glossy screen. But while the black box of journalism arguably was more “transparent” in years past (going through a manual process of reporting and research), there are now algorithms to make information processing and data mining much easier. The implementation of a journalistic system is becoming more opaque, more black, more automated, and because of things like Web 2.0, it’s no longer necessary that we implement the black boxes of journalism solely with human effort.
That’s the point driven home by this class.
I could list some of the more concrete skills I learned from DriveThru this quarter. Implementing APIs. More Rails experience. Nokogiri. Heroku. But I wouldn’t say I was taught these things.
Instead, I was taught how to examine journalistic problems through a technical lens. To see opportunities beyond an interactive map or timeline and look instead at a broader scope of news publishing and how to push it forward in non-established ways.
I guess that’s why they call it “innovation.”
Katie Zhu is a student at Northwestern University. Write to: firstname.lastname@example.org
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