Google is funding the creation of software that writes local news stories

You underestimate people's ability to make language errors, including spelling ones. Every time I see somebody I suspect is a native English speaher using "it's" for "its", I grind my teeth. (Another instance is somebody using phrase like "as a programmer, the data bus should be written..." to mean "I, as a programmer, think that..."; this phrasing makes me simply furious.) With those errors they make reading my second language so much harder, and I can't even point their bad spelling or writing style out, because I'm seen as being nitpicking or something.

  * Facts delivered with arbitrary fluff words is pointless even when written by a human - it obfuscates the
    real purpose which is the data
  * Companies pay humans to deliver articles in most cases and the bias of the writer or the institution
    that paid for it shines through. I cannot find a real difference between intentional angling by
    payment or by algorithm
  * When the day arises where computers could generate actually new, intelligent and thoughtful pieces I
    for one will be very interested in reading them. Sadly there would be millions of variations that could
    occur at an astounding pace. We'd then need algorithms to filter the generated content for the things
    that are really noteworthy.
  * News at its core is a sequence of facts which begs the question if we really need the cruft around
    those facts which can often lead to misinterpretation?

Does this version have better fact checking with alternative word processor ?

How detail this version is about moodmapping to connectivity ideology flow ?

Many of your criticisms are totally valid. Lots of the phrasing is awkward - even the lede is really bad ("Tesla, Inc. (TSLA) has been having a set of eventful trading activity"...wat). And it feels really deceptive to put a human byline on an automated article.

We're pretty open about the fact that our solution to this problem is not "magical" at all [1, 2] - it's good, old-fashioned automation. This approach allows our customers to QA their content heavily before pushing it to production, which eliminates many of the problems with awkward/incorrect phrasing that people who rely more heavily on machine learning tend to run into. And the news articles we publish always have a note at the end saying that they were generated by Automated Insights, and don't include a human byline.

There is real value in this type of reporting - a recent study [3] found that the articles we produce for less well-known publicly-traded companies has increased the trading volume for those companies. The idea is that, yes, the content is fairly formulaic, but there's now reporting on companies that had very little coverage before we existed. There are similar arguments for mass personalization work we've done for companies like Activision Yahoo - having prose that describes raw data (even if it is formulaic to an extent) is often better than not having prose.

[1] https://automatedinsights.com/blog/the-state-of-artificial-i...

[2] https://automatedinsights.com/blog/creating-great-automated-...

[3] https://insights.ap.org/industry-trends/study-news-automatio...

Article: "People will be involved in the curation and editing of the stories"