The Future is Now: Neuroscience, Chatbots, Voice, and Microcontent
In this article:
- walkthrough of a number of different pieces of content to help build a story that eventually leads to microcontent
- an overview of topic-based authoring and how it makes a difference in some of the limitations that we experienced with topic-based offerings
- a definition of what microcontent is and how it works and how it enables the next generation of delivery channel technology
- an exploration around user intent
A View from Deep Time
Roughly 100,000 years ago, as a species, we started speaking. Emerging oral traditions provided a way for people to share information. The reach, however, was one-to-one, meaning that you speak to one person and they have to repeat it to share it.
60,000 years later, we started committing content to cave walls and onto stone. Technology progressed from stone, to clay tablets, to Papyrus, parchment, and ultimately, to paper in the third century AD. This progression made content more future-proof, durable, transportable, cost-effective, timely, and available. From a one-to-one mode of communication to a one-to-many mode, we can call this Content 1.0.
With the invention of the Gutenberg Press, which was a major development in content technology, content was more available to those who could read. The ability to mass produce content and information for consumption was a significant leap forward.
Looking forward into the computer era and the development of desktop publishing capabilities, allowing more and more people to be able to publish their content, we call this phase Content 2.0–one-from-one to many-to-one, and many more. And finally, we attempted to democratize information by using the world wide web and extending that reach through mobile phones, making it possible for many people to reach many others.
The reach of many-to-many, this is Content 3.0, and the latest era in content technology is voice.
Content 3.0
We are now able to communicate not only with other people, but with machines. And, the machines are communicating back to us, bringing us full circle to where we all began with the dissemination of information through voice.
It is now more and more common for enterprise applications to rely on chatbots and treat chatbots as the paradigm replacing cloud-first or mobile-first platforms. It’s at this point in the evolution of content technology that structured content plays a role. Structured content plays an enormous role in the functioning of chatbots and conversational user interfaces.
Let’s put this into perspective a little bit. When we’re looking at trends, we see that the complexity of content is getting greater and greater as we move from the first written scrolls, to the Codex, all the way to documents, pages, and topics, blocks, and facts.
With increasing content complexity, we see that the size of units gets smaller. With smaller units of information, we’re seeing a tremendous growth in the amount of content that we’re trying to manage. In the 1700s, the average person on the street will be exposed to as much information in their entire lifetime as is in one issue of The New York Times.
IBM tells us that in 2014 we saw the expansion of human knowledge such that it was doubling every 13 months. At that time, their prediction was that by 2020 the vast amount of knowledge that we’ve amassed in digital and print (and other forms) would be doubling every 12 hours.
What’s really disturbing about this trend, is that for the most part within our enterprises this content will be what we call dark data. It is inaccessible, raw, redundant, obsolete or trivial information. Dark data is information that clouds and obscures the good information that we’re trying to work with. We are trying to find strategies to deal with this issue as we manage this tremendous growth in information.
There are some inescapable trends that we see coming in technical communication where content becomes far more precise and technical. Collaboration becomes more important. Content that we create becomes more than merely a document or web page. It becomes part of a total system. The activities around creating content start to become more and more complex and rely heavily on technology to structure it and get it to the right audiences.
At this time in enterprise content, we need to look at the role of micro content. Micro content is useful, at an enterprise level, for technical publications and authoring topic based content.
Using a micro content strategy from a writer’s perspective means that when new content is drafted, it is about one primary idea, fact, or concept. It is easily scannable and labeled for clear identification, and is appropriately written and formatted for use anywhere or anytime. Micro content isn’t micro content just because it’s small! It is micro content because it answers a single question. This is an essential concept to understand when we explore the use of topics to organize content.
Understanding Intent
The ideal, in the world of content development, has always been to deliver the right information to the right people at the right time, in the right context, and on the right device. Although this has been the go-to strategy for content development, it is clear that consumer behaviour is changing. More than simply delivering the right information, we are tasked with delivering answers.
The challenge we are now faced with is: how do we incorporate microcontent into our existing content? The goal is for microcontent to become another channel along with new emerging technologies. With microcontent, we see improved viability, accessibility, and credibility.
For example, when you perform searches online you’ll typically get a page of information and the title of the information may not reflect the goals or the meaning of the content. Even the short description you see associated with the title may not provide everything that you are looking for.
When we deliver content as microcontent, in smaller chunks of information, we see that when we perform a search, we’re much more likely to recognise what it is we’re looking for in search results making that content far more accessible. Microcontent breaks information apart into chunks, making it easier to retrieve, repurpose, and manage. Managing, in this context, means the content has an ideal level of granularity for reuse beyond the capability to answer the topic.
Micro and structured content, make content more accessible to the human brain, making it easier to scan, find and understand. It is also easier to use with technology, to integrate into other systems, making it searchable, and easier for machines to index. It is also important to account for user intent–or what the user is expected to do with the content. Through creating structured content, we need to be able to provide classification that indicates the user intent. User intent will be recognised through how the content is written, labeled, and how that information is presented.
Let’s look at an example. Looking at the instructions for making a cup of tea, organized in a structured way we see the following sequence:
- plug in the kettle
- bring the water to a rolling boil
- pour the boiling water into a cup
- add a tea bag
- allow the tea to steep for five minutes
- serve carefully
These instructions are very basic stripped down facts and what we call reader intent for task-based type of information. It is presented to you in second-person present tense and the function of that information is to instruct you on how to make a cup of tea.
That is the intent. The intended intent for that information is a function of that information.
But if we modified the instructions slightly, and changed the tense to third-person and introduced an actor into the instructions we get something like: the waitstaff turn on the kettle, bring the water to a rolling boil. Then they pour it into a cup and serve it to their customers.
By writing the instructions in third person the function of the information has changed. The instructions no longer tell you how to make a cup of tea. They describe how somebody else makes that cup of tea. The same facts have been leveraged, but an actor has been introduced, and the tense has changed. The intended reader- response is to help you understand how somebody else makes a cup of tea.
Now of course, you could learn how you’re going to make a cup of tea. But that’s not the purpose of the information.
And finally, taking this example and writing it in first-person present tense we get: I woke up this morning, I turned on the kettle and the kettle boiled. I poured the water into a cup with a tea bag and I let it steep before drinking.
The instructions have turned into a story, but there’s no point to the story. The reader intent for each presentation of the instructions changed the reader-response. In first-person, it’s not to instruct you on how to make a cup of tea. It’s not to tell you how tea is made and tell you a story.
The same set of facts structured slightly differently, can produce different results. The trick is determining what we want those results to be and then writing the content that way so that we can achieve those results. We do this through information typing. Information typing is a model for intended reader response.
5 Information Types & The Neuroscience of Memory
We are very deliberate at Precision Content with how we write and present information. We use information types to apply strict guidelines on how we label information. Let’s look at the types we use.
- Reference: Describe things the reader needs to know
- Task: Instructs readers how to do things, how to perform tasks
- Concept: Explains things we want the reader to understand
- Process: Demonstrates to the reader how things work
- Principal: Advises the reader on what they need to do or not do.
All of our structured and technical content falls into one of these five categories. We use this method because it is how our brains work with information. More specifically, how our memory works. Memory, of course, is key to providing context and understanding to what it is that we’re reading. If we have no context with the words on a page or on a screen, then we have trouble making any sense of it. In order to make sense of it, we need to be able to connect with pieces of memory within our brains in order to work with it.
Active & Working Memory
In the frontal cortex we have our active and working memory and this is where we process reference type of information. Information must be easy to understand, but it is also easy to forget. Working information or working memory has memory that we use to perform a task with that information. Then we discard that information or we or we use it to process other types of information and then we discard it.
Procedural Memory
Procedural memory works at a subconscious level. We don’t need to actively try to recall information from procedural memory. It’s just always there. When we think about how we write our software tasks, as in how we work with a piece of software, we don’t need to go through the various steps that your right hand must perform: maneuver your pointing device such that the arrow is over the File menu and right click the left button on the mouse twice. And the File Menu drops down. We don’t need to explain that level of detail. The reason is because this type of action is already embedded or ingrained within our memory, so we don’t need to write it again. This is a function of how task based information works. We’re looking to tap into procedural memory to fill in gaps because if we had to detail every single step, like we do for our machine transmittance, tasks would be unmanageable and unwieldy.
Semantic Memory
Finally, there’s semantic memory. Semantic memory is the most fragile type of memory. It is where we process conceptual types of information. In order to make conceptual information comprehensible we need to tap into something that the reader already knows and to make that association so that we can create new concepts that the reader can store for later use.
It’s very important how we structure conceptual information and that we understand our audience. Reference, task, and concept as concept types work with our memory and our brains to make structured content usable.
The 3 Laws
When we talk about breaking down information using information types, we have three laws that we follow. They are the laws of utility, maintainability, and usability. For utility, we’re really talking about the format of the information. Is your content written in PowerPoint slides? Microsoft Word? WordPerfect? Is it in a Tweet? Is it an email, or is it XML? To understand the utility of that information, what’s required, we need to understand what we need to do with the information. Understanding utility and applying the proper amount of utility to that information is key to success in making content work.
Looking at maintainability we can ask: Is there a content creation process and how do we manage that lifecycle? How do we manage the lifecycle of micro or topic based content? How are we managing the process and the technology that maintains the process? Maintainability requires an understanding of the optimal technology and the best practices needed for maintaining content. Utility and maintainability go together to help determine the technology and processes we employ.
One of the elements that we most often skip over is the usability of the content itself. Accounting for the actual content is important when we look at micro content and delivering content for voice and chatbots. Through our transition from book-based authoring and FrameMaker, to topic based authoring in XML data, for example, many of us simply convert one format to another without taking advantage of what topic-based and semantic, intelligent strategies can bring to that content. Converting content is still work, but it won’t work as intended when we start implementing emerging channels like voice and conversational UIs. It is important now more than ever to consider all three laws when looking at creating a content strategy.
From Topics to Blocks
To better understand what topics and blocks are and their relationship to micro content, we’re going to focus on what comprises the topics: blocks of information. We have a primary block or the short description which describes its purpose. We have blocks within the body of content, which provide context, prerequisite steps, results, and post-requisites.
Now, what’s really interesting is that while this whole piece of information on its own is a task, each of these individual blocks themselves, each one of these pieces of micro content, have their own type of information in order to convey that information. In other words, these other blocks have different rules for writing, for labeling, and for presentation. When we look at context for instance, we see that it (context) is an example of reference types of information. Prerequisites and post-requisites are what we call a principle type of information or information that’s intended to tell the reader what to do or not do and when.
Finally, the reference type includes the steps for a task. By focusing on these blocks of information, we can create standardized, consumable, and definable types of containers for information. This content becomes far easier to repurpose for developing other topics, other types of publications, and other types of delivery channels for that information.
Remember, when we consider user-intent, we’re not looking to deliver topic-based information, we’re looking to deliver answers. Those answers are what we get out of the blocks of information and out of micro content. Using blocks we can then use chatbot type technology or conversational user interface to break that query down, understand its intent and deliver the appropriate resource.
When we take information and make it conversational, we are delivering the right information or the answer in the context of the question, in a consumable way. When we deliver content through voice for example, we don’t have the opportunity to read an entire topic to the person who’s asking the question, we have to answer that with micro content. Our challenge then is to explore how we restructure our content, or leverage the existing structure, to transform it into micro content and reuse and repurpose it across these emerging channels.
Most organizations have not figured out how to make chat bots or conversational UIs work as well as they can. Establishing a micro content methodology and mindset will help push your content and your company forward in this arena. Even if you’re not working with chatbots right now, you likely don’t have the technology you need to start. If you’re asking, is my content ready for this technology? Or, what do we need to make it work better to get started with chat bots? When you start to make your content ready for this technology, you’re going to be improving its machine accessibility. At the same time, your content will be far more accessible to the human brain and to human consumption. No effort is lost in making the transition to micro content.
Is your content ready for what comes next?
There’s no time like the present to get started with preparing your content for the next wave of technologies so that you can move forward with intelligent and scalable solutions — Contact us to start the conversation!
About the Author
Rob Hanna co-founded Precision Content in 2015 to pursue his goals to produce tools, training, and methods that will help organizations make their high-value content instantly available to all that need it including customers, staff, partners, and even other information systems that need to consume that content. Driving this development is the Precision Content® Writing Methods, based on the best-available research over the last 50 years into how the brain works with information. Today Rob leads his highly-skilled team of content strategists, information architects, writers, trainers, and developers to serve the needs for digital transformation for businesses across North America.