However, as in any craft, when the toolset changes radically, the craftsperson can either take advantage or be replaced to some degree — if not completely.
In the video, the head of ChartBeat, Tony Haile, says he believes that editors of the future will be able to use new analytical tools to monitor readers’ needs and deliver relevant content almost immediately. To do this effectively, they will be one of two things — cyborgs or robots:
. . . the industry is moving away from the “fire and forget” model of posting something and just hoping for the best . . . editors in the future will be either “cyborgs” or “robots” . . . cyborgs being “people who are enhanced by technology” and robots as “people who are replaced by technology.”
ChartBeat works by providing real-time analytics to content producers. Its flashing dashboard tells you which stories are becoming more popular, which ones are fading. There’s a manic quality to it, and the theory is that content producers can respond in real-time to user demand by sourcing similar stories to extend the engagement, surfacing related items from the archive, and so forth.
At first, ChartBeat struck me as the type of thing that content farms or news sites would be most interested in. After all, surfacing content and chasing audience are what they’re all about. For scholarly publishers, there’s less of a frantic pursuit of audience qua audience. Also, how keepsake scholarly information is generated isn’t really comparable to journalism or opinion pieces — if a paper on a new drug or method proves popular, you probably can’t get another published a few hours later.
However, relevance and engagement are still major ambitions for scholarly publishers, and with large archives online, a desire to provide that elusive “one-stop shop,” and users who are moving into less direct engagement because superior curation exists in other venues, approaches like this can feel mighty appealing.
A major challenge for many publishers is to make use of their online analytics. The data exist, but often access to them is delayed by so many days or weeks that by the time you have them in hand, the opportunity to exploit traffic or trends is long gone. This has made analytics an armchair hobby instead of an active endeavor. Real-time stats in the hands of a cyborg editor could change this. Some publishers are responding by creating new roles, such as Retention Writer or Engagement Editor, roles in which people use data to make editorial decisions and choices.
Moving from cyborgs to robots seems a perilous journey until you begin to integrate semantic technologies. Combined with real-time metrics, if you know what people are clicking on at the conceptual level, your robot could be smart enough to surface related content that’s based on more than just ephemeral clickstreams.
Given the abundance of data, perhaps one of the most audacious changes could be moving from not only a “fire and forget” mentality but to a results-oriented mentality. I remember one editor asking me in front of a group of editors exactly how many hits his article had received online since publication. When I answered “zero,” he was crestfallen, but accepted the reality of it. The illusion of print remains that every word on every page is read. Online, there are far fewer illusions, which leads to the idea that perhaps instead of paying for output, you:
. . . evaluate and pay editors not by the quantity of stories they generate but by the traffic and response they produce.
Would an editorial board receive compensation adjustments based on analytics with a brave face? Would a human editor? A cyborg?
Robots may be the only ones who wouldn’t rationalize their value as superseding the data.