Machine learning looks at the problem the other way around. It would be a deterministic and artless form of review - but could yield somewhat useful first order results.īut our task, given the complexity of language, reporting and, of course, the many different types of journalism, is really suited to machine learning. We could count the number of “experts” quoted and even programmatically look up their expertise and, again, nudge the score slightly. We could also nudge that score based on a count of the adjectives, quotes, characters, companies or countries mentioned. We could program it to search through articles for phrases like, “according to documents,” or, “according to anonymous sources,” and nudge an arbitrary score up or down accordingly. There are essentially two ways to get a computer to score something like a news article. What about the algorithm that chooses the stories users see? How, exactly, would this news-scoring algorithm work? What parameters would go into it? How would you train the algorithm? For that reason, we’re now building an interface through which users can see the results of tens of thousands of articles scored every day in real time, without editorial intervention.īut the frontend is the easy bit. It is cloaked by an editorial process so just looks like any other newsletter that collates online posts. But, ultimately, this fails to highlight our algorithm’s good work. It works remarkably well but, of course, quality is not those companies’ top objective.Ĭurrently, Deepnews’ primary product is a set of semi-automated newsletters on various topics, chosen by the algorithm and then a human editor who is the equivalent of the Guardian editor chopping up GPT-3’s output to publish a somewhat passable opinion piece. Another is predicting what users want it is already being used to customize your Google search results, your YouTube and Netflix video choices and, of course, your Facebook and Twitter feeds. Writing is one facet of machine learning’s ability. #DD 10 ENGINE CASCADEA MANUAL#The piece did require some manual work, according to Guardian editors, and the end product used nice language but, ultimately, made no real sense - precisely the sort of journalism we at Deepnews want to rout out. GPT-3, a machine learning language generator, was recently able to write a Guardian opinion piece. It’s a tough task and our model will never be bullet-proof - how could an algorithm tell if a journalist made up a quote, for example - but what has astonished me in recent months is that it’s working at all.Ĭomputing is undoubtedly capable of amazing feats, even when it comes to the complexity of human language. That means that not only do the metrics of what makes quality journalism need to be agreed upon, they also need to be put into the precise language of code. #DD 10 ENGINE CASCADEA HOW TO#The trouble is how to find it - and encourage people towards it - at scale.Īt Deepnews, we are building an algorithm to differentiate between high- and low-quality journalism based on nothing but the text of an article. Big and small news outlets are producing some excellent work despite the industry’s deep issues. Readers often end up with unsolicited opinion, ”banalysis” rather than analysis and certainly not first drafts of history. Unending discussions on the media industry’s revenue declines often fail to address that much of the industry, only in part due to declining revenue, is outputting garbage: shallow and sloppy articles designed to be nothing more than a vehicle for advertising revenue. My own views on it were shaped by a non-journalistic background in math, physics and programming. As a reporter working all over the world with everyone from Reuters and the New Yorker to the Daily Mail and Vice, I saw vast gaps in how editors and journalists saw quality. But they’d disagree on the importance of good writing, necessary attributions and countless other nuances. Yes, they’d agree on the planks: original and on-the-ground reporting, investigations based on documents rather than anonymous sources and smart analysis based on facts rather than opinion. If you were to put a group of journalists together to discuss what makes for good quality in their field, they’d argue for hours. Deepnews 2.0 will is underway - stay tuned.
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