How to Create Content in a World With Bots

Robo-content goes mainstream

The most exciting opportunities for using modular, machine-made content are the types of projects that are predictable, repeating, following a template, and in most cases highly reliant on data.

Years ago, when I left traditional employment to become a freelancer, one of my first gigs was transcribing quarterly earnings calls and preparing summaries for the press. Writers like me felt immense pressure to complete tasks quickly because each assignment was priced at a modest, flat rate. If you didn’t move at manic speed, your hourly rate could dip close to minimum wage. (I lasted about two weeks.)

Today, these tasks are completed by machine-learning technologies. The Associated Press, for example, uses robo-writers from Automated Insights for corporate earnings calls. AP freed up 20% of reporters’ time, reduced errors, and improved turnaround times.

Applications support human creativity

These cases show AI replacing humans, yet there are plenty of examples of AI supplementing the work of human writers. To understand the future of robot-assisted content, it’s useful to look at the manufacturing industry, where more companies are using “cobots” – robots designed to interact with and assist humans in a shared space.

Cobots often perform repetitive tasks in partnership with a human (e.g., packaging, pick-and-place tasks, quality checks) and eliminate or minimize the more tedious and dangerous tasks on assembly lines.

AI-powered writer-support tools look a lot like the relationship between humans and cobots. The most common content cobots are Google’s Smart Reply and Smart Compose features in Gmail. As you type, Google predicts the words that likely follow. To date, predictive content cobots like Google’s don’t deliver on the promise. Google’s Smart Compose isn’t particularly time-saving: The keystrokes required to complete the sentence are awkward enough that in most cases it’s simply faster to type the same words.

Give it time. As Google gets access to even more of your data (shudder), its deep-learning AI will more accurately predict larger tracts of what you’d like to say. Ray Kurzweil leads the effort and his team is working on a way to expand on Smart Reply. He explains, “You could have similar technology to help you compose documents or emails by giving you suggestions of how to complete your sentence.”

Aside from these types of predictive, natural-language-processing cobots, there are dozens of creative-support cobots on the market. Among my favorites is Frase, an AI-powered word processor with an integrated research assistant.

As I write a story, Frase searches for third-party media and research, and summarizes relevant sources. The tool even creates footnotes/endnotes based on the information cited. Frase isn’t intended to replace human storytellers but rather make them more efficient and effective.

When the program went live, Philana Patterson, an assistant business editor at the AP in charge of implementing and overseeing the system, explained it this way: “One of the things we really wanted reporters to be able to do was when earnings came out to not have to focus on the initial numbers. That’s the goal, to write smarter pieces and more interesting stories.”

(While there may be some hand-wringing over machines replacing human writers, trust me when I say this type of job is not one that leads to a satisfying writing career.)

AI tools also help companies convert data into stories. Dominion Dealer Solutions enables auto dealers to create customer-ready profiles about the cars on their lots. In the past, a dealer might cut and paste information from disparate sources to create a sell sheet – a process wildly impractical for dealers with thousands of new and used cars in inventory. Using Narrative Science, dealers can access a sell sheet in real time, unlocking plain-English descriptions from a massive trove of vehicle data.

This application isn’t simply about the sales sheet, of course; it’s also about SEO. Using robo-writing helped Dominion Dealer Solutions increase page views by 20% (including a 50% lift in page views across used vehicles), as well as increase inventory revenue.

Content’s still about message, not method

Despite the legislation in California, marketers are in a gray space with the technology evolving more quickly than the regulation of that technology. Just look at the way governments are playing catch-up to the privacy misdeeds of companies like Facebook.

People have known for years that Facebook, Google, and thousands of other smaller players are monetizing people’s personal data. But governments and consumers were slow to realize the implications of this data exchange.

The same is true for bot-powered conversations. Governments are still grappling with how to limit bot armies influencing elections and political activism. They haven’t yet begun to wrestle with the implications of business-sponsored bot conversations. (Let’s be real: It’s not even on their radar.)

Given that regulation won’t likely arrive in time to curb bad behavior with machine-generated conversations, perhaps consumer choices will. A study from the Pew Research Center in October 2018 found that only half of U.S. consumers believe businesses using bots to promote their products is acceptable (not exactly a ringing endorsement). And among those who have a higher level of understanding of what bots are, the acceptance rate is significantly lower.

As marketers race to find new and different ways to reach their audience (hello obnoxious lock-screen advertising, uninvited text messages, and web browser notifications), consumers are finding new ways to limit access. Ultimately, it’s still about the message, not the method. Publish great content, provide useful information, and your audience will open the door to let you in – whether that content is created by machine or human.