Will algorithms replace human editors on the web? It’s a bogeyman question on one level, but ask any news site about the percentage of traffic they get from search engines — and what the trend looks like — and you’ll realize that algorithms are increasingly deciding what we pay attention to, what is important, what is relevant. It’s part of how journalists and news orgs have abdicated their traditional roles on the web.
And it’s not just Google — news sites are increasingly filled with links generated by algorithms that suggest to readers what else they ought to read. And that’s because most news site still see original content creation as their sole purpose — they don’t see the tremendous need, and the tremendous value in filtering the content that already exists. They don’t see that every link on their site is an important editorial judgment, not an afterthought, not an algorithmic process to set and forget (which often leads to algorithms making bad recommendations, as many news sites who use them will tell you).
Giving over the function of choosing links, of filtering the web, to an algorithm is an implicit devaluation of the quality of human judgment, of what makes an individual editor’s perspective so interesting. That’s why link bloggers like Andrew Sullivan, Glenn Reynolds, Josh Marshall, and Matt Drudge have become such a powerful force on the web. They understood, even where traditional news orgs did not, the value of bringing their unique perspectives to filtering the web, of having a “linking voice.” They understood the editorial power of the link.
Handing over the editorial selection of links to an algorithm is also an implicit concession that human news judgment isn’t up to the task. It’s too overwhelming, too much work, so just let the machines take over.
And there are obviously times when you want a machine to take over — searching the billions of pages on the web for some obscure piece of information, and doing so comprehensively, is where algorithms are a godsend.
But while algorithms may excel at processing vast amounts of data by brute force, they are only as smart as the rules we give them. Algorithms can simulate human intelligence — but algorithms have no judgment — and certainly no news judgment. Algorithms can’t do link journalism.
That’s the brilliance of Google — it’s actually driven by human judgment, by the judgment that someone producing a website makes every time they link to something. Rather than replacing human judgment, Google is actually co-opting it.
Still, the obvious question is how can human editors compete with the brute force of an algorithm, which never tires, never has a busy day, never gets distracted? (Cue Terminator music.)
Well, human editors aren’t going to compete very well with the old go it alone model of journalism.
But they can compete through COLLABORATION.
Digg has proven that collaborative human editorial effort can cover a massive amount of territory on the web.
Imagine if journalists and news orgs brought together their combined editorial intelligence, their combined news judgment.
Suddenly the advantage of an algorithm’s scale in filtering the web doesn’t seem so insurmountable.
It may be overwhelming for one editor to fact check what Google CEO Eric Schmidt called the “cesspool” of false information on the web. But imagine journalists collaborating to verify what they link to.
Even within a newsroom — and even for the many newsrooms grappling with shrinking resources — collaboration could yield a powerful editorial filter.
In fact, the more that resources shrink, the more essential collaboration becomes.
Yeah, I know, collaboration isn’t in the traditional journalism playbook. But insert here the almost cliched reference to swiftly declining business models, now aided by economic decline, and, well… do we really need to be having that conversation anymore?
Just look at where the most innovative, entrepreneurial minds in journalism have focused their efforts — it’s all about collaboration:
Ryan Sholin just launched ReportingOn, a site where journalists share in short Twitter-like messages what they are reporting on — with the aim of actually HELPING each other. With fewer journalists in newsrooms doing original reporting, doesn’t it make perfect sense that more and better reporting could get done collaboratively? Why should a beat be a solo effort?
That’s is also the idea behind Beat Blogging, the brainchild of Jay Rosen, with journalism iconoclast Patrick Thornton now leading the charge. The idea is for journalists to develop social networks to improve their beat reporting — by collaborating with people involved with and interested in the topics they cover, journalists can do better reporting. (Beat Blogging is even collaborating to find great examples of beat blogging.)
Speaking of collaborating with communities, Mark Briggs, of Journalism 2.0 fame, co-founded a company called Serra Media, whose first product Newsgarden is a map-based local news platform that allows news orgs to collaborate with their communities to publish hyperlocal news. And their bet is that journalists and community members all posting hyperlocal news as they come across it can do a better job than algorithm-based local sites in judging what news is important to the community.
And then there’s David Cohn, who will soon be launching Spot.us, where a community can collaborate to actually pay for the journalism that the community needs. A community brings money and interest in issues, journalists bring their reporting skills, and, collaboratively, journalism happens.
See the pattern here? It’s about how a group of people, empowered by technology to collaborate, can accomplish much more than one person can by themselves.
And the idea that news orgs can accomplish more together than they can by themselves isn’t so foreign to journalism — it’s the basis of the newswire. So it’s not that hard to imagine a collaborative newswire based on links, where journalists help each other filter the web.
It’s not that hard to imagine journalists, collaborating with each other and the communities they serve, becoming most powerful editorial intelligence on the web.