In the not-too-distant future, Artificial Intelligence (AI) and Smart Technology will fundamentally change the way organizations process and publish content. Some people in our industry have already welcomed it. Others find it mysterious and slightly dystopian.

Let's establish some common ground around definitions of AI and Smart Technology, and we'll make our way to publishing from there.

Artificial Intelligence

Experts debate the theoretical categories and classification of AI. Some argue there are two categories while others propose as many as six. From a functional, "what does it mean in our everyday lives" perspective, I favor two categories.

The sexiest of the two is Artificial General Intelligence or AGI. This is sometimes called "Strong AI," and thanks to Hollywood, it has often been given a dystopian depiction in movies like The Terminator, The Matrix, and RoboCop.

AGI is focused on machines that mimic human beings by employing reasoning, learning, and situational awareness to solve a problem. We'll leave AGI to Hollywood’s dystopian visions of the future. Most experts agree, we're a long way from having AGI integrated into our daily lives.

The other category of Artificial Intelligence is Narrow AI, and it is everywhere, weaving itself into our daily lives in ways we appreciate but don't often think about. Narrow AI functions in a limited fashion and is an approximate simulation of human intelligence, performing a single task better, faster, and more efficiently than a human being.

Unlike AGI, Narrow AI, with its focus on performing specific tasks, is the best real-world expression of artificial intelligence we have seen so far. Narrow AI continues to evolve as entrepreneurs and innovators find new ways to make it beneficial in our daily lives.

Some Examples of Narrow AI

If you've asked Alexa or Siri for a weather report, to play your favorite music, or what year the Gutenberg printing press was invented, you've experienced Narrow AI.

If you've considered a movie recommendation from Netflix or clicked on a product recommendation while shopping on Amazon, you've experienced Narrow AI.

Search engines, chatbots, facial recognition software, autonomous vehicles, and industrial robots are all examples of Narrow AI.

Smart Technology

Smart Technology is typically identified with the Internet of Things (IoT), and I am going to bend the definition a bit. Generally, it involves an electronic device that uses the Internet to gather and analyze data from a source (some “thing” in your home or business environment). Examples of Smart Technology include shipping container logistics tracking, inventory trackers, wearable health monitors, connected home appliances.

“What the Internet of Things is really about is information technology that can gather its own information. Often what it does with that information is not tell a human being something, it [just] does something.”

Kevin Ashton, technologist, entrepreneur, author of How to Fly a Horse: The Secret History of Creation, Invention, and Discovery, and creator of the term “the Internet of Things.”

There is an overlap between Narrow AI and Smart Technology, making it hard to tell where one begins and the other ends or how they work together. Rather than articulating the difference in a particular use-case scenario, think of them as related things with a common goal: to simplify things.

How Does It Apply to Publishing?

Over the last couple of years, my colleagues and I have asked hundreds of people in the publishing industry to tell us about the most tedious, repetitive tasks in their workflows. Some of the most tedious tasks are some of the most important ones. We’ve also asked these people how they generate and distribute project-specific information, data collected from a source at one point in a workflow that are needed by other role players downstream in that workflow. Some of the stories we’ve gathered paint a gloomy picture of current state practices.

What are some of the most tedious, repetitive tasks in publishing? What are the challenges of generating and distributing project-specific information? Our partial list, assembled from those conversations include:

• Processing proposals and peer reviews
• Trafficking and tracking, illustrations, photographs, media and the associated metadata, including rights and permissions
• Sending publishing agreements and contracts to authors, contributors, and organizations owning the reproduction rights for specific content.
• Author Management, including:
  • Emailing guidelines and instructions
  • Setting schedules and deadlines and following up with people when those deadlines are close, or missed
  • Giving authors and writers access to related content that could be used in their original work
  • Checking author submissions to ensure that all the necessary parts and pieces are there, accounted for, and properly formatted.
  • Responding to author queries.
• Finding the right versions of things that have been submitted, revised, and submitted again, and again.
• Reading and interpreting expert, peer, and market reviews to ensure that the published product will meet standards of quality or achieve some degree of competitive advantage.
• Preparing management reports on the status of things.

The list goes on, but the big picture is clear. Everything on the list is important, and many of them can delay a publication date or compromise the quality of a finished product. Every item on the list is to some degree tedious and repetitive, something most people in our industry have accepted as normal, part of the cost of doing business.

Can Narrow AI and Smart Technology Help?

Absolutely. Most of these tasks are specific and time-sensitive. Many of them involve data collection that requires some action by others in your publishing ecosystem. A combination of Narrow AI and Smart technology that automates a human-driven process can play a big role here.

Let’s look at one example that book publishers face daily: Author Management.

Typically, a publisher emails various documents to an author. These can include project guidelines, contracts, schedules, manuscript submission requirements, peer reviews, etc. The author then acts upon that information. In a perfect world, the author follows instructions, meets the deadlines, and submits high-quality work in a format acceptable to the publisher. In the real-world, however, most authors do not operate this way. To be fair to authors, publishers require them to do a lot of “necessary” things that are outside of their comfort zone. Writing the content may be the easiest part. Handling permissions, creating art logs, tracking versions, following guidelines that can seem confusing to a non-publisher, and submitting it all on time … that’s something else.

Publishers compensate by sending more emails, some providing clarification, some requesting additional information or tasks, and some reminding authors of impending deadlines. At the same time, the publisher is providing critical updates to others in the workflow required to act on information from the author. That is one definition of tedious and repetitive.

If you imagine the roles players (including authors) in a publishing workflow as both a “source of data” and someone that “acts upon data” you’ve taken a step toward recognizing Narrow AI and Smart Technology as a solution. By automating the exchange of data and using a technology that acts upon that data on a role player’s behalf, you’ve put both feet in the water.

The PageMajik Editorial system operates based on workflows and role players. It allows the publisher to set up a workflow, assign and monitor role player tasks, and automatically process information from a data source into something that is essential downstream. For an author this means having a portal where all relevant project information is available to act upon. “Smart” emails remind them of deadlines and are configured to respond to author actions. Content can be submitted, checked for completeness, and automatically meta-tagged. The system handles approximately 70% of the work typically performed by a human.

Our motivation in asking people what tasks they found tedious and repetitive and what information needed to be gathered and acted upon was to see if Narrow AI and Smart Technology (as we have now defined it) could make a difference. With almost 5,000 authors and contributors having used our system to-date, we have evidence of what happens to publication cycles, P&Ls, product quality, and team morale when people can leave the tedious, repetitive stuff to technology. It all improves.

Will there come a day when AGI, the sexier of the two AI categories, can introduce a RoboAuthor or RoboEditor to the workforce. Probably, but most people reading this will have long retired before that kind of AI becomes as commonplace as a weather report from Siri.