More News Is Being Written By Robots
singularityhub.com
singularityhub.com
Some people have said, "Why not just display the raw data?"
Well, to save you the trouble of having to analyze the data.
For instance, suppose I've written a Powerball results script that lists the winning numbers, along with which states had winners.
If I'm just spitting out the raw data, then people might miss the fact that one of the winners was from our state -- whereas if I'm generating a story, I'm going to make that the lede.
Similarly, the magic of a company like Narrative Science and its Quill service is not in taking a ton of data and filling in a bunch of blanks with the values, Mad Libs style. It's in analyzing the data and figuring out what the most important parts are, and constructing a story around those findings.
In other words, it's not hard for a bot to write, "The Tigers played the Wolves yesterday. The Tigers won 1-0. The Tigers' John Johnson scored a home run."
It's more difficult to write, "The Tigers' Tom Thompson pitched the first no-hitter of his career yesterday in a 1-0 game against the Wolves. Remarkably, the Wolves' pitcher, Dobbie Dobson, was moments away from forcing the game into extra innings with his own no-hitter, when, in the ninth inning with two outs and two strikes on the board, the Tigers' John Johnson hit a home run."
(I'm not a baseball writer, so I'm probably bungling it, but you get the point.)
So let's say a major earthquake happens in San Francisco and the Google HQ falls into a bottomless pit. The trading algorithms will know about the earthquake within seconds, and they will also know about likely know about Google's obliteration from speech-to-text of police scanners. The millisecond these reports hit the wire, the HFT algorithms would likely short the hell out of Google's stock immediately while also placing positive bets on Google's competitors as well as construction companies and building suppliers. And this was going on 10 years ago; they're probably light years ahead of this by now.
It's also not very hard to write the second piece given the right machine learning technology. Feed a decade's worth of human-generated articles into an algorithm (which could also be paired with marketing metrics like page views, avg time spent on page, etc.) and the algorithm picks out the types of statistics it should look up from the databases and how those statistics should be incorporated into the story. Heck, if you wanted to get really fancy, you could try to pick the major themes of the game out of a transcript of the play-by-play or specific emotional moments of the game by measuring the level of crowd noise or twitter traffic.
A computer will have better information recall, better research skills and better perspective to write stories that are more appealing to people. Heck, they could even write a story on the fly designed to appeal specifically to the individual's preferences. I understand that there's a place for reporters, but I don't think it's going to be written event-based reporting for much longer.
Also, would writing it be something a beginner/novice like myself could do or does it require pretty advanced skills?
Thanks for any info you can provide.
A Chicago startup called Narrative Science makes scripts that turn raw data feeds such as seismological data or website analytics into accessible natural language reports. Some news outlets are already using them to get out earthquake and Little Leagues baseball reports quickly and cheaply.
The founder, Kristian Hammond, has big ideas. "Pulitzer Prize by 2017." "90% of news written by bots in 2030."
This TL;DR was written by a human. Just saying.
If the data is already machine-readable, in many instances, what I want to see are a few slices through the database and a few visualizations. What I don't want is a big text blob that must first be piped through my brain to re-extract the information.
- The LA Times claims they were first to publish anything on the quake, and outside the USGS, they probably were.
- The LA Times example isn’t special because it’s the first algorithm to write a story on a major news site.
- Indeed, Kristian Hammond, cofounder and CTO of Narrative Science, thinks some 90% of the news could be written by computers by 2030.
- The LA Times earthquake story, written by an algorithm created by one of their staff, included a disclaimer.
This TL;DR was written by a bot.
I mistakenly wrote "Bill Hammond" instead of "Kristian Hammond" in my TL;DR. (Sorry Kristian.)
But this isn't the first bot that the LA Times has operated either. Folks like Ben Welsh (who works at the LA Times, and did this awesome lightning talk: http://www.youtube.com/watch?v=iP-On8PzEy8 ) and Matt Waite (who won a Pulitzer Prize for Politifact & now teaches at University of Nebraska Lincoln) have also been writing bots to help with the reporting process (and yes in some case actually generate copy) for years.
Narrative Science certainly was not the first or only group to do this.
The logical extension of this software is to replace the phrase 'earthquake report'.
"If a writer never had to compose a fifty word Presidential press brief again—few would complain."
"If a writer never had to compose a fifty word news leak again—few would complain."
"If a writer never had to compose a fifty word announcement of a declaration of war again—few would complain."
Let the machine do the writing to expedite publishing, because the accuracy of the source is assumed before the information is even shared publicly, provided the source submits releases in a formulaic manner.
This removes the agency of humans that might ask complicated questions (journalists) – so I don't believe it qualifies as news or journalism, at all. This just helps move the words of the source to the front page of a news agency.
Why dress up the release as unique content at all? Just print the damn press release word for word and cite the source.
That's a nice explanation and particularly common since the 2000s, but the problem with it is that the decline in perception of most mainstream news sources (particularly newspapers) and the resulting decline in the industry was already widely discussed before the internet, as anything other than ARPANET, existed, and certainly before it was a major factor in public perception of the news.
You're asking for a principled, rather than arbitrary, place to insert human writers into the mix? I'd say a human writer might be needed when the story involes human agency; or when there's continuing human interest in the story.
There's no value-add for involving a human in the initial notification of a small earthquake; no human angle, no human perspective. If geologists issue a press release saying this presages Los Angeles falling into the ocean, then you need to involve a human.
Robots can't yet parse human political language (neither can most humans), so there's a possible value-add for interpretation of a presidential press release by an expert human.
Leaks and declarations of war involve human agency, and are assured of continuing human interest. Get a human to interpret them.
For a sense of scale, your comment was 188 words. My comment is 88 words.
My point is that such software is a nod to the primacy of expediency in the field of breaking news. I'm not certain that other kinds of breaking news would be treated differently, particularly those from official sources that utilize standard formats (like corporations and governments).
If I may dig at your comment a little to illustrate my point: Your comment is shorter – more expedient, you seem to think – but you have not actually laid out any of the 'several logical problems' with my 'jump', you've merely made a claim that leaks/war declarations 'tend to require much more information' for complete coverage.
I agree such issues should require that, however, I don't feel they get it. I humbly submit the coverage of the latest US invasion of Iraq, where the evidence overwhelmingly indicated a dearth of WMDs, and yet US government talking points were rarely disputed, and sometimes printed without critique.
So, my hypothesis is that similar issues will definitely not get said coverage if expediency-by-software is valued more highly than analysis.
There's no real solution to our difference of opinion, but you haven't actually refuted my logic, as you claim.
We both agree there are different types of breaking news, and that they need to be treated differently. You trust that they will be, while I do not.
The word count was intended to display just how little information might be conveyed in fifty words. The inclusion of my comment's word count was simply to make the comment self-referential. Both can be safely ignored.
I hope you're right, because contemporary journalism clearly needs to be doing something better with its time.
It's the summarization and finding additional details that is important, just printing the entire interview or entire press release is too much.
Journalism at most newspapers died long before the process of uncritically transcribing information from external sources into publication format started being automated. That's what makes the automation invisible -- and therefore, acceptable -- the transition to robotic regurgitation long preceded the actual use of robots to do it.
We're seeing this in sports (Grantland, Deadspin, 538, Baseball Prospectus), politics (Vox.com/Ezra Klein, 538 again, Politico), and tech (Thompson, Evans, Gruber, The Wirecutter, Anandtech, MG/Dixon/Wilson/Suster/Andreessen/Horowitz/etc/yesIleftamillionpeopleout).
Tech leads the way because those on the cutting edge are often interested in tech, and I believe it's a solid leading indicator of where all journalism is headed—a 'Cambrian explosion' of thoughtful, analytic, but not purely objective writing.
1) Big-picture Op/Ed (of the kind you're talking about)
2) Investigation (of the deep, involved, I-need-to-know-where-to-start, I-need-to-get-people-to-talk variety)
3) Narrative nonfiction (profiles, colorful takes on a subject; see: The New Yorker, Michael Lewis, etc.)
The interesting thing is that each of these domains could be enhanced by the use of better software. And that's the best way to start looking at bot-fueled journalism. I'd love a machine-based fact checker for my pieces. I'd love AI-driven help with compiling and analyzing data. I'd love to outsource the high-frequency grunt work to a machine, just as it's done in many other industries. It would give me more time to think. It would let me focus where my focus matters. Instead of spending 99% of my time chasing raw research, and 1% of my time scrambling to assemble the piece, I could get more data, better, faster, up front, and thus put deeper thought into the analysis.
On that note: the journalists who thrive in the machine age will be the ones who understand what the machine is doing. Data-literacy is already a big, differentiating factor in the market now. Statistical competency will be very important, and the bar for competency will be positioned higher every few years. Beautiful logic will trump beautiful fluff.
This will accelerate the bimodal shake-out of journalism that we're already starting to see. We'll have base, commodified, LCD-pandering content farms on one end, and deep thought on the other. Quantity shops and quality shops, both of them improved by the automation of certain functions. Anyone in the middle ground is in trouble. This will be a good thing for both poles -- provided we can find a way to make the economics of quality work as well as those of quantity.
Also, I lump 1) and 3) together in my mind as not-quite-objective, analytic content, but I admit that was poorly expressed.
Fact checking is a huge problem. I'm not sure if call it a hair-on-fire problem. But it's certainly pissed me off on any number of occasions. Typically, what happens is that I'll write a story mildly critical of BigCo. The PR department at BigCo will catch wind of it, then email me and my editor with as many small "corrections" as they can muster, in an attempt to take down the piece.
When I say corrections, I don't mean broad facts. I mean infinitesimally perceptible technicalities. For instance, I might report someone's title as the "VP of Strategy," because that's what's listed on this company's website and on the person's LinkedIn page. But the company's PR group will come at me, screaming bloody murder, because the guy's title is actually "VP of Strategic Initiatives." They'll do this because they're unhappy with the broader criticism I'm leveling against their business -- so they want to pick away at as many nits as possible. It's a guerilla harassment tactic.
Now, you might well ask: aren't I just being sloppy? How hard can it be to fact check everything? The answer is: it's damned near impossible to catch everything. Some of this information is conflicting across multiple sources. Some of it's out of date or inaccurate. And some of it's not even publicly available, and you wouldn't know you're slightly off until someone corrects you. (Case in point: the "Strategic Initiative" example, a nonsensically titled internal promotion that was never made public.) Add to this the immense pressure of weekly deadlines, and factor in how much time I need to spend ideating, researching, writing, and editing in the first place, and you see how little time I have to get every last thing 100% accurate. I'd love to be 100% accurate 100% of the time, but given my constraints, that's rarely feasible. It's like asking an engineer to write flawless, bug-free code at a hackathon.
I'd love a piece of software I could run my stories through, which would analyze my piece against a public data set (Google, for instance) to check for factual accuracy in all these little places. Or at least a piece of software that would throw up red flags on unverified statements, for which multiple, conflicting data exists on the web. Sort of like the little, red underlines on automatic spell check.
Perhaps that's not a big enough use case or TAM. But broaden it out. I'd love a better way to compile Google research about any given query. This is why I'm rooting for the stuff Wolfram is working on, though I'd love a more modifiable and specialized front end for professional users.
http://en.wikipedia.org/wiki/User:Rambot
http://en.wikipedia.org/wiki/Wikipedia:History_of_Wikipedia_...
More news is really just crudely rehashed or verbatim press releases by particular companies than you might think.
Many times, cool news about a particular company or a new products was written, verbatim, by the company itself.
I had always expected the news to be above it, but "earned media" is totally a thing.
Why aren't news digest sites a thing?
I guess we can look at this from a positive angle - the robots can't do any worse than the human journalists.
Not all news can be made computer readable easily, but there are several classes of news that can be that way, or at least have rich, computer readable meta data (sports results, releases of software, new music albums, movies, upcoming events, announcement of road maintenance, ...).
Update: Is anybody interested in working on such a system with me? If yes, drop me an email (moritz@faui2k3.org)!
For an earthquake, at least for the initial announcement, it's pretty straightforward - where and how big. It's not a great deal different to "a robot" (or more precisely, my phone's weather app) telling me what temperature and likelihood of rain. Trying to do that for, say, the salient points of the banking collapse would be a lot more difficult.
A lot of news sites operate essentially by expanding wire service copy.
Oh but they are. For $$$.
BBC Monitoing offers an excellent World news digest service and used to release part of the output publicly. But governments and companies will pay very handsomely for such services, so now it's only available on subscription
Why don't they just publish raw facts in the computer readable form?
I think there's more to a reporters job than writing, in fact i'd say the writing part is maybe the smallest aspect when it comes to the most interesting stories.
Investigation, interviews, and general "experiencing the world" is required, and computers aren't ready to do that yet. I'd be surprised if they are by 2030 too.
Of course, it could be a sign of how far down the quality of news has fallen. That 90% of it is now formulaic. I guess I had hopes that these new sites that are popping up would becomes a trend in quality. Artisanal news as the hipsters might say.
I'm not sure I hope for the day that computers replace the human analysis, emotion, or opinion in news, but I do believe they could help journalists better spot leads and dig into stories. This would free journalists up to do less leg work and more thinking about the content in front of them.
That said, the process of investigation, etc. does contribute to the experience a journalist brings to the table, so the question then is, does cutting out the legwork undermine a journalists ability to deeply understand and analyze a given story?
(Check out some French, German or Spanish news sources and see how different the world is sometime)
Isn't that a bit too ambitious? I admittedly don't know a lot about the Pulitzer Prize, but I'd assume the main qualities they're looking for in a journalist there are not 'fast', and 'factually correct'. The first one doesn't really relate to the quality of journalism, and the second one's just too basic a requirement.
What I'd assume is worthy of a prize in journalism, is the data collection and investigation process before even starting to write the article. This would include very complex tasks, most covering social interaction, which I just can't see a computer outperforming a human in by 2017.
The future of news is to raw/unredacted/untransformed datas with tracable origin that people can analyse themself and decide to trust / not to trust. Exactly like the Snowden leaks.We dont need "journalist" to source/filter the data.
People then will be able to mashup the data with apps designed for that.