Algorithms as a tool to better journalism
April 27, 2012 Anna Wahrman Leave a comment
Wired's recent story about Narrative Science seems to have put some journalists into a bit of a tizz. The article is a must-read for journalists and coders — really interesting tidbits about what's going on in this field now, and what might come to pass in the future.
I'm actually very excited about the possibilities of Narrative Science, an artificial intelligence product that transforms data (currently primarily from the sports and finance world) into stories. This is the exact kind of thing we're after when we encourage J-Schools to put software engineering into journalism curricula so we can teach young journalists valuable new skills so they, in turn, can not end up helpless on the sidelines, as many of us current journos have been during the technology advances of the last decade.
The method does not determine the value
Narrative Science is not a threat, it's a tool, and it fills a need. Instead of some capable writer poring over boring financial statements and trying to add sizzle in reporting on them, a machine reads the data and spits out two grafs. Two serviceable but really snoozy grafs, which probably would have happened if written by a human, too.
Here's what's intriguing, though: Narrative Science is working on ways to be not-snoozy, and in so doing they're calling journalists on our BS, in a way. What I mean is this: Journalists have formulas. We do, and they're taught in schools and learned on the job. "Reverse pyramid." "Nut graf." "Lede." "Attribution." These are plug-and-play tactics most of the time. Sure, these elements vary from story to story, and that is the fun part of what we do. We add details and context. We observe and report. But at core, we tell different stories using some slightly different combinations of these tactics and tools.
Arguably, feature stories have slightly more variety, but I'd also point out that (sadly) many features are also just puzzle pieces, if not downright parodies of themselves. For example, every feature on every female celebrity ever starts this way:
"[Lady celeb] walks into [L.A.'s or New York's] [restaurant or cafe in trendy neighborhood]
looking gorgeous in [brand] jeans and no makeup."
Whether the editors or writers are making the words hacky, hacky they are — and boring, just like the pieces Narrative Science is creating with its algorithmic journalism. Fascinatingly, according to Wired, the company actually has "meta-writers" whose job it is to help the computers add context:
"[Meta-writers are] trained journalists who have built a set of templates. They work with the engineers to coach the computers to identify various 'angles' from the data. Who won the game? Was it a come-from-behind victory or a blowout? Did one player have a fantastic day at the plate? The algorithm considers context and information from other databases as well: Did a losing streak end?"
But to answer the question posed in the headline of the piece, "Can an Algorithm Write a Better News Story Than a Human Reporter?" for now the answer is no. And journalists vs. algorithms is a faulty comparison.
Writers and editors add value using tools
Narrative Science, thanks to algorithms created by human engineers and journalists, is now at the level of being able to programmatically spit out phrases like "whacking home runs." But it can't gauge a crowd's restlessness or excitement. It can't interview a superfan after the game, sense that he's fed up with the team and write a mood piece. It can't connect on a human level to a victim of a crime, or spend days following a subject then put together disparate threads of the subject's life into a coherent portrait.
Which is why it's not a real threat just yet. The way I see it:
Narrative Science : journalists : : spell-check : copy editors
It's a tool that does a programmatic task, but not a contextual one, as well as a human. Does spell-check tell you you have the wrong "hear/here"? No. Does it correct you when you've spelled "embarrassing" incorrectly because it is drawing from an enormous database of correctly spelled words? Sure, easy enough. Can it check a fact's accuracy against a thousand links on the Internet? Probably. But can it call a source and make sure she wasn't misquoted, then correct the quote before publication? Not likely.
Context is everything, and it's ours to use. But we journalists have to use it. Yes, we have formulas. We write ledes, and we edit the story so the most important information is up front. But we have to step up our game. We have to go to the match, or the crime scene, or the meeting, or the fashion show, or the foreign city, or the war, and add context for readers. We shouldn't hack our way through the really interesting stuff — we shouldn't be allowed to. Let's let bottom-scrapers scrape the bottom for us. Let's not waste human effort on shitty content farms that pay $2 (!) an article. Let's leave that for robots and invest elsewhere: in hiring more and better writers and editors to make connections, describe the atmosphere, make sense of things, tease out themes and (cue dramatic music) better humanity. Let's invest in creating data and algorithms that we can program to help us help ourselves.
Readers value editing
Poynter covers Wayne State University prof Fred Vultee's ACES presentation of his recent study on the value editors add. Key takeaway:
"Routine editing makes a statistically significant and moderately strong difference in how audiences perceive the professionalism, writing quality, organization, and value of news articles."
Makes complete sense to me. The problem in my experience is one Vultee saw in his study as well: "We know [editors] add value, but since they don't add content it's been hard to make a specific case of how they add value."
When it's hard to explain how you add value, it's hard to argue against getting laid off. But clearly editors do add value, as the study notes, especially among women readers — it's just that the value is added in ways other than dollars and cents, which is difficult to justify to the types who look only at the bottom line. But the feelings of trust and professionalism are ones that brands should cultivate, not get rid of. Never has the saying "the invisible hand of the editor" been more ironic.
Personalization by way of automation
Interesting peek at what happens when personalization by way of automation and algorithms takes a dark turn.
"Unlike tabloid television, algorithmic personalization does not announce that it's pandering to base interests. When sensationalized reports about violence against children are on TV, I can change the channel — an act that is harder to do on the Internet when seemingly 'neutral' spaces, like Yahoo's homepage, leave no tell-tale trace of manipulation. You can't change the channel when you don't know you're watching the program."
Another argument in favor of the human curator (read: editor) as we stumble through sorting out what can be programmed, what should never be, and where the middle ground is.
Content as a product
Really interesting piece on treating content as a product and what that means for scaled production, if there is such a thing:
"You can't apply industrial-age economics to content production. Content doesn't get cheaper as the volume goes up. Unlike Ford's automobiles, the cost of quality content goes up with the volume because content production involves skilled labour and very few economies of scale. Plenty of organisations try to work around this hard fact using various forms of automation."
The author's point is that it's a gamble to "churn content without a plan":
"While automated tools can be useful, letting general trending topics or ill-chosen metrics replace a strong editorial strategy will drive the relevance of your content down. Licensed or crowd-sourced content will rarely be tailored for your audience's needs, the tone of voice they are most accustomed to, etc. Every mismatch drives relevance down and reduces your chances of the gamble ever paying off."
I'd further argue that, content-wise, in the age of social sharing and a meme a minute, tone and trust are everything.
The limits of automation
More on the art of editing and curation:
"Algorithms cannot solve all problems. It takes a human editor to craft great experiences with the right mix of familiarity and novelty, confirmation and healthy dissent."
Swing back to editorial curation?
Perhaps the editor part is more wishful thinking than reality — there is certainly something to be said for humans make better automations in the future, too — but nonetheless I like the boldness of the prediction:
"But while algorithms once threatened to replace gatekeepers, online media will see a move back to the future: professional, human filters (the artists formerly known as editors) will play an integral role in the next web after all."