
Robo-reporter writes front-page news - tareqak
https://www.ft.com/content/e2cbe014-8131-11e9-b592-5fe435b57a3b
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neonate
[http://archive.is/h7Daq](http://archive.is/h7Daq)

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wmichelin
The unspoken hero, thank you for your duty

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6gvONxR4sf7o
This is interesting in light of all the worry about generative language models
spreading misinformation (e.g. GPT-2 and company). With mainstream news trying
to automate reporting on real facts, tools to detect auto-generated reporting
won't be sufficient to combat automatic fake news. We'd have to have a way of
telling the good bots from the bad, which is a whole can of worms.

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macawfish
The word that comes to mind is "messy".

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jammygit
I hate Robo stories. They come up on google all the time and they’re just a
waste of time. They seem to generate decent seo I guess

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atakiel
The headline is kind of misleading. It makes it sound like a machine would be
churning out these news, out of thin air, and that's not really the case. The
article itself isn't helping much with all the hype.

The article isn't really about bots writing news. It's also far from OpenAI's
GPT-2. It's about regular reporters writing massively localized stories with
some fine tools. It's pretty cool stuff actually.

What radar is doing is definitely shaping the media landscape, but it is not
news created by bots. It's news generated from templates, which are written by
humans:

> One of six human journalists working at Radar will write a story “template”
> with wording for each of the various possible scenarios — for example, a
> boom, modest rise or sharp fall in violent crime. Then, at the click of a
> mouse, versions of the story are created for each of the UK’s 391 local
> authority areas, pulling in the statistics specific to that region.

They are basically doing what Reuters does, except Radar only provides a
handful of stories a week instead of hundreds of stories. But the trick is
that while stories by Reuters are static, the articles provided by Radar are
localized for each region, based on the data used. (All the localizations are
written into the template, from which the program picks the best fitting
pieces based on the data per region.)

> The UK’s most prolific reporter churns out thousands of stories a month for
> hundreds of publications across the country — a superhuman effort, were it
> not for the fact the journalist is not fully human.

The numbers in the previous quote mean that Radar generates hundreds of
different, localized versions from these dozen or so weekly article templates.

The cool thing here isn't that a model would create these articles, but that
it's possible to create good quality local reporting, from data and a well
written master template, by non-local reporters.

Basically, as news publishers are sunsetting their local papers, Radar has
shown that it is still possible to serve local news to smaller regions.

And all this can be done by more or less regular reporters. There's some
programming involved, but nothing complicated - AFAIK, the programming for the
templates is similar to writing scripts in Excel.

> Gary Rogers, Radar’s editor-in-chief, estimates that half of its stories
> that appear in print are added to by local reporters. However, that drops to
> just 20 per cent for stories republished by online news sites.

Like mentioned in the quote, half of the time, for stories that are going to
be published in physical papers, local journalists add their own reporting to
the stories. Again, these stories don't magically enter the front page. They
are selected to be placed there by the editors, and in many cases, local
journalists add their knowledge to the articles. But still, the language in
them is good enough to be used on prime estate.

In web and mobile, it appears, the rim is lower, and it goes more often faster
to the site, without modifications. But then again, the rules in internet are
different.

Plenty of the problems that people have had with previous template-based robot
journalist writings, has been with repetitive textual structures. With Radar's
model that is not as big a problem, as the master template is only used once
per story. If a reader reads the story from one magazine, it's less likely
that she will also read the same story in another paper. Compare this to sport
robots where you see the same structure repeating in every story.

I've understood that Radar isn't the first in this place, but they have shown
a business model for template based news that manages to avoid the biggest
problems with repetitive structures.

In summary, Radar is doing something cool by automating local news, although
the article isn't the most clearest on what the cool thing is.

There's plenty of ambiguity in stories about Radar, so my guess is this is
partly due to their press release lingo / hype.

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atakiel
There are certain open questions with Radar style localized template based
news.

Mainly it's about automatization, changing the way things are done. New
skillsets are needed, while old ones are out of the door.

There's the existential problem this kind of centralized local news creation
has on smaller desks, mentioned in the article, but then again the trend
appears to be that owners are running the small, unprofitable ones down
anyways, regardless of Radar.

There's also the question whether this style of localization, but not
personalization, of news, is the best way to serve readers. Could these same
local news be served in some other way?

IMO, the way Radar works, mainly happens the way it does, as there exists a
need from small papers, for quality journalism that they don't have their own
resources to conduct. Of course, nothing is stopping Radar of doing something
different in the future.

Then there's also the hypotetical (?) threat on press diversity. Basically a
multitude of superficially distinct voices are repeating the same liturgy.
This zerg of articles on a specific topic, might appear to a news consumer, as
many credible sources supporting a specific view or point.

There's similarity with Reuters et al in this problem, and clearly Reuters
hasn't destroyed news. But with Reuters, the text is most of the time
identical in all the places where it is published. In the case of localized
templates, it might not be clear to the reader that all the different versions
are instances of the same master template, with same bias from a single
writer, if the template is well enough written.

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781
Gives a new sense to "fake news"

Now we need a robo-reader who reverses the article back into the source data.

