| I work for Automated Insights, a company that makes a SaaS platform very similar to what's in the article. Here's an example "in the wild" of the content we produce - http://www.thenewstribune.com/news/business/article158774809... 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... |
Instead of producing awkward and difficult-to-read English sentences, why not use the same content generator to produce completely accurate and easier to read dynamic data visualizations?