Editor’s note: On May 30, Joe Procopio, who is vice president of product at Automated Insights and a WRAL TechWire Insider columnist, will be speaking on the future of Digital Journalism at Columbia University at a conference at the Tow Center. In a previous column, he discussed why automated content should be considered a tool and not a threat. Automated Insights focuses on auotmated content.

DURHAM, N.C. - Ever since the L.A. Times “Quakebot” broke the news of a major earthquake back in March — a story it developed, wrote, and published in less than three minutes after the first tremor — the profile of digital journalism and automated content has risen dramatically.

For me and my team at Automated Insights, it feels like vindication, because the industry is starting to scale exactly like we thought it would. I’ve been designing and building automated content for the last four years, and in 2014, Automated Insights will publish over a billion unique articles for dozens of media outlets via the web, email, and social media.

With just 25 humans.

You’ve probably already read automated content without realizing it. This is because the Robot Writer side of digital journalism is already quite polished. It’s a fairly robust technology that we’ve evolved from a process of filling in templates, the method Quakebot employs when it writes an article, to the programmatic determination of topic, tone, style, fact-generation, and lexicon.

In other words, our engine runs dozens of algorithms before the first word is digitally written. It keeps those algorithms going throughout the entire writing process. If you look at what we put into the machine, it looks nothing like prose. It looks more like code. Because it is.

Thus, the process of automated writing is no longer about filling in blanks between words with the proper data. Scalability, variety, point-of-view, sentiment – all the concepts that make a human-written article sound like it was written by a human – can be done by a machine.

The Robot Reporter

So if the last few years of automated journalism were about perfecting the Robot Writer, the next few years will focus on the technology that will make automation even more mainstream: The Robot Reporter.

The Robot Reporter is the unsung hero of automated content. In order for the Robot Writer to create human-sounding stories from data, that data has to first be collected, structured, and made available.

This is not as easy as it sounds, but it’s getting easier. Automated Insights started life as a company with a sports focus, particularly because of the volume and the granularity of the data produced in sports.

At the professional sports level (think MLB, NFL, NBA), data is collected not just at the game and player level, but at the play and performance level. We now know how fast each pitch is thrown and where, how many times and in which direction a quarterback goes long, and even whether or not a game-deciding call was blown, thanks to replay.

In all pro sports and even most college and some recreational, there are now all kinds of sensors and cameras tracking the game, sometimes at the individual level, all of which can support qualitative analysis on quantitative facts. For example, when we tell you a hitter is off his swing, we’re not playing a hunch, we can see it.

It’s like Moneyball to the Nth degree.

Now to The Street

About three years ago, we expanded into other verticals in which that level of data collection was either already there or on the way. Finance and investing were the next logical steps, and they brought about new challenges.

Sports is easy, you win or lose or, usually in the case of soccer, you tie. In the stock market, winning and losing takes on an entirely subjective new meaning, and you have to be very careful with the concepts of good and bad.

Your stock went up today? Great.

Your stock went up less than a percent after a stellar quarterly report on a day when the entire market was up more than two percent? Plus maybe a couple of downgrades? And throw in a flirtation with the 50-day moving average?

Well, it’s not the worst day ever, but I wouldn’t call it a win.

It’s that contextual analysis that makes automated content worth reading. We figured out very early on that you can’t just regurgitate the facts. The story is in how those facts fit into the bigger picture.

Sound familiar, journalists?

Just as the data collection in sports went through a ton of innovation to bring more granular data to the game, the innovators in investing are now structuring all kinds of contextual data for qualifiable analysis. So now we can not only tell you how much a stock moved on a given day, we can pretty much tell you why, and there are big bets being made on being able to speculate which way and how far that same stock will move the next day.

Internet of Things Journalism

The innovators keep innovating, and eventually that kind of contextual data can be wrapped around just about any form of journalism. Enter the Internet of Things and web-enabled devices — once you get past the Big Brother chill — and we’re very quickly heading down a path where the Robot Reporter can provide any kind of news.

You already see this at a personal level. Bands and watches and smartphones can track your fitness. Black boxes and not-so-black boxes in your car can track your travel. Home automation is just now starting to be realized, and it won’t be too long before it’s not just about your thermostat.

If personal is the micro level, then the next logical step is the macro. Quakebot, for all intents and purposes, is powered by a web-enabled device on that macro level. RFID chips, sensors, and cameras, the same kind that are calling balls and strikes with a greater accuracy than human umpires, those are already ubiquitous.

Down the road, drones can put eyes where we couldn’t put feet in the past. City automation can’t be too far behind home automation.

And yes, there are huge, monstrous, scary, and ugly privacy concerns with each advancement of Robot Reporter technology. It’s the real-world version of the purist’s distaste with a machine calling balls and strikes. And it has real-world implications.

But that’s another column. Probably a dozen.

In any event, the sensors, chips, and cameras that power automated journalism shouldn’t be the ones that scare us, because in order for data collection to serve the purpose of automated content, that data collection has to have purpose and be specific. The camera that calls balls and strikes can’t be the same camera that tracks how many hot dogs are sold in the right-field seating area.

The Robot Reporter for Quakebot has one job: When the ground starts moving, gather the data and wake Quakebot up. That’s it. That’s what makes it viable as a Robot Reporter.

As automated journalism permeates more facets of daily life, those sensors, chips, and cameras will be developed to provide the data and the context. And as those sensors, chips, and cameras become more prevalent, the quality of automated journalism will increase, in some cases dramatically.

About the author: Joe Procopio is a serial entrepreneur, writer, and speaker. He is VP of Product at Automated Insights and the founder of startup network and news resource ExitEvent and new venture Teaching Startup. Follow him at @jproco or read him at Joe Procopio.com