Man vs. Machine: Can Software Trump Editors in the Newsfeed Wars?

(Page 2 of 2)

hiring a bunch of people to read the news, sift through the headlines, and rank what they see as the top stories and most important developments.

Breaking News, a unit of NBC, is perhaps the most prominent of the new wave here. Based in Seattle, with offices in New York, London, and Portland, OR, it employs a team of editors who pull together reports from a wide variety of media sources into a “real-time feed that focuses on just what’s new.”

Another prominent real-people newsfeed startup is Circa, based in San Francisco. Circa also employs a team of editors who comb over the news of the day, extracting important facts and bits of information from longer, print- or Web-centric articles and regurgitating those points into a much more smartphone-friendly format.

There are plenty of others—Techmeme in the technology business news arena, which relies partly on editors to help compile a single page of big news, linking to the organizations that originally reported it. And there are some original-wave niche aggregator/bloggers, like Jim Romenesko in the media world—the leading place news people turn to for news about their industry.

This is much more expensive than an algorithm at any sort of large scale. The magic of software, both as a technology and a business, is that a digital machine can be built once and continue performing its task over and over. Even with constant updates in the software-as-a-service era, it’s much cheaper to crawl the entire Web with software than it would be to hire editors to do that task.

And we’ve had some recent examples of why a human decision is still needed. In the days following the Boston Marathon bombings, there were some long periods of information chaos as established news organizations and amateurs alike were spreading information that turned out to be wildly incorrect.

Breaking News general manager Cory Bergman summarized in this blog post how the staff decided to wait in one of these occasions, balancing a number of conflicting reports about whether there had been a suspect arrested early in the investigation. Despite reports from reputable organizations like CNN and The Associated Press, that news turned out to be incorrect—and Breaking News had done well by choosing to not amplify the incorrect reports, even though they were “out there.”

Now, an algorithm could probably be tuned to make some of those same calculations and come up with the same correct call. But the tools on offer today would be much more likely to bring you the latest from the most authoritative sources—even when their reports might look suspect to a practitioner, and eventually turn out wrong.

“Right now, computers can’t empathize,” Circa CEO Matt Galligan recently told AllThingsD. “We need to be able to understand a story, and right now, humans are the only ones that can truly understand a story, or the purpose, or the emotion.”

Of course, as a reporter, I have a very direct interest in the idea that humans are better news editors than algorithms. But I also don’t doubt the ability of software programs to drastically improve on their current abilities.

That’s definitely where Google’s heading. During an appearance at Harvard, in the same week that his company bought Wavii, Google chairman Eric Schmidt said a future of personally tuned newsfeeds was a big reason that the company shut down the Google Reader RSS application.

“The core presumption there is that people will have personalized or personally identified accounts where they’ve chosen to log in—Google Plus does this—and you’ll get your information through those mechanisms, as opposed to RSS feeds,” Schmidt said. “RSS was a tremendous technology from 15 years ago … there are just newer technologies coming along.”

“What I would suggest is that the real thing you want is not a feed, but rather an AI algorithm that knows roughly what you care about and is looking all the time to select the best and most interesting feeds,” he continued. “And we’re on the cusp of being able to do that technologically, based on your preferences and using machine intelligence and data mining. And if Google doesn’t do it, other people will.”

Single PageCurrently on Page: 1 2 previous page