Category Archives: innovation

Cultivating the Landscape of Innovation in Computational Journalism

For the last several months I’ve been working on a whitepaper for the CUNY Tow-Knight Center for Entrepreneurial Journalism. It’s about cultivating more technical innovation in journalism and involves systematically mapping out what’s been done (in terms of research) as well as outlining a method for people to generate new ideas in computational journalism. I’m happy to say that the paper was published by the Tow-Knight Center today. You can get Jeff Jarvis’ take on it on the Tow-Knight blog, or for more coverage you can see the Nieman Lab write-up. Or go straight for the paper itself.

Systematic Technical Innovation in Journalism

The idea that innovation can be an organized, systematic search for change is not new — Peter Drucker wrote about it over 25 years ago in his book Innovation and Entrepreneurship — and I’m fairly certain he wasn’t the first. Systematic innovation is about methodically surveying a landscape of potential innovation while also analyzing the potential economic or social value of innovations. For the last several months I’ve been working with the CUNY Graduate School for Journalism on developing a process to systematically explore the potential for technical innovation in journalism. My hope is that this can spur new ideas and growth in Computational Journalism. In the rest of this post I’ll describe how the process is developing and provide some initial feedback we’ve gotten on how it’s working.

One way to look at innovation is in terms of problem solving: (1) what’s the problem or what’s needed, and (2) how do you reify the solution. Sure, technical innovation is not the only kind of innovation, but here my focus of “how to make it happen” will be computing. The problems and needs that I’m focused on are further constrained by the domain, journalism, and include aspects of what news consumers need and want, what news producers (e.g. professional journalists, but also others) need and want, and how value is added to information during the production process.

My basic premise is that if we can identify and enumerate concrete concepts related to needs/wants and technical solutions, then we can systematically combine different concepts to arrive at new ideas for innovation. This is the core idea of combinatorial creativity:  mashing up concepts in novel juxtapositions often sparks new ideas. Drawing on lots of research and, when possible, theory, I developed a concept space which includes 27 computing and technology concepts (e.g. natural user interfaces, computer vision, data mining, etc.), 15 needs and goals that journalists or news consumers typically have with information / media (e.g. storytelling, sensemaking, staying informed, etc.), and 14 information processes that are used to increase the value of information (e.g. filtering, ordering, summarization, etc.). That amounts to 56 concepts across four main categories (computing and technology, news consumer needs, journalism goals, and information processes).

To make the creative combination of ideas more engaging I produced and printed concept cards using Moo, which were color-coded based on their main category. Each card has a concept and brief description; here’s what they look like:

Brainstorming could happen in a lot of different ways, but for a start I decided to have groups of three people with each person randomly picking a card, one card from computing and technology and two cards from the other main categories. Then the goal is to generate as many different ideas as possible for products or services that combine those three concepts in some time-frame (say 5 minutes). A recorder in the group keeps track of the concept cards drawn and all of the ideas generated so that they can be discussed later.

The process seems to be working. Earlier this week in Jeff Jarvis’ entrepreneurial journalism class I spent some time lecturing on the different concepts and then had students break into 5 groups of 3 to play the brainstorming “game”, which looked something like this:

The reaction was largely positive, with at least one student exclaiming that she really like the exercise, and another acknowledging that there were some good ideas coming out of having to think about (and apply) combinations of concepts that they hadn’t necessarily thought of before.

In a series of 3, 5-minute rounds of brainstorming, the five groups generated 54 ideas in total, for an average of 3.6 ideas per group per round. Of course there was some variability between groups and most groups needed a round to warm-up, but there were definitely some 5-star ideas generated. Some of the ideas were for general products or services, but some were also about how technologies could enable new kinds of stories to be told — editorial creativity. For instance, an idea for a general platform was to produce 3D virtual recreations of accident spots to help viewers get a better experience of why that spot could be dangerous. Another idea was to develop an app where citizen journalists could sign up and be automatically alerted when an incident occurs near their location. On the editorial creativity side of things, some ideas included using motion capture technology to recreate crime scenes or analyses, or to illustrate workplace injuries from repetitive stress. Not all of these things would make tons of money or generate millions of clicks, but that’s not the point — for now the point is to get people thinking in new directions.

We’re still thinking about ways to improve the process, like adding pressure, constraints, or context. And generating lots of ideas is good, but step two is to think about winnowing and how to assess feasibility and quality of ideas. Stay tuned as this continues to evolve…