If you let one of your houseplants completely dry out and then try to bring it back to life by dumping a large amount of water in the pot, you will end up with water all over the floor. Dry soil cannot absorb moisture quickly so the water you pour in will run through the soil, out the hole in the bottom of the pot, into the saucer the pot is resting on, over the sides, and onto the floor. Damp soil can absorb moisture far more quickly that dry soil. Readers are like that too. Experts can absorb much more information much faster than novices. Thus experts read far more than novices do.
And suddenly every tech comm and content strategy conference seems to be about getting your content ready for chatbots. Makes sense if you are a conference organizer. Chatbots are sexy and sex sells, even if the definition of sexy is a grey box with a speaker sitting on the counter.
But chatbots are not the future of technical communication. Here’s why:
Chatbots are stupid
No, I don’t mean that they are a stupid idea. I mean they are actually stupid. As in they are not very bright. As Will Knight writes in Tougher Turing Test Exposes Chatbots’ Stupidity in the MIT Technology Review, current AI does barely better than chance in deciphering the ambiguity in a sentence like: “The city councilmen refused the demonstrators a permit because they feared violence.” (Who feared the violence?) Human do this so easily we rarely even notice that the ambiguity exists. AI’s can’t.
In the Top Gear Patagonia Special, the presenters come upon an incomplete bridge and have to construct a ramp to get their cars across. This is a great metaphor for technical communication, and, indeed, communication of all kinds: the incomplete bridge.
Technical communication is often described as a bridge between the expert and the user. But that bridge is always incomplete. The user always has to build the final span that connects the bridge to the bit of ground they are standing on.
This is true for several reasons, the most basic of which is that you have to contextualize any information you receive to your own project in order to act on it confidently and successfully. If the document tells you to push the red button, it is still your job to determine if you are looking at the right device and the right red button, and if your purpose will truly be served by pressing the red button at this time. The document can never entirely ensure that you do not press the wrong button on the wrong device or at the wrong time for the wrong purpose. Only the individual reader can determine those things, and thus only the reader can build the final span of the bridge.
A new XML-based content management system that is not based on DITA. Bet you didn’t see that coming. But I think it tells us something interesting about the two sides of structured writing.
Tom Johnson’s recent sponsored post explains the origins of Paligo, a relatively new CCMS out of Sweden. Paligo was developed by a company that had formerly been a DITA consulting shop in an attempt to come up with something that was easier to use (and less expensive) than the DITA solutions they were implementing.
What is interesting to me about Paligo is that they chose DocBook rather than DITA as the underlying XML vocabulary. Why? Quoting Tom:
And it turns out that building on a foundation of Docbook XML is considerably easier than building with DITA. DITA tends to impose more restrictions about what you can and can’t do, Svensson says. Even so, Paligo is only “based on Docbook.” Paligo extends from this foundation, adding what they need and not letting the content model restrict the system, while maintaining full capability to export to the open standard.
This is interesting because DocBook is a large and complex specification. (I want to say larger and more complex than DITA, but I’m not sure if that is true anymore.) Why use it as the basis for what is supposed to be a system that is easier to use than DITA?
The answer seem to be lack of restriction. DocBook may be as large and as complex as DITA, if not more so, but it is much less restrictive. DITA has lots of restrictions on what you can and cannot do in each topic type. DocBook has very few. You can combine DocBook elements in just about any way that might occur to you. And apparently Paligo loosens DocBook even further.
Why is this significant? In a CCMS (Component Content Management System) the whole point of the system is to let you assemble documents out of pieces. The main benefit of this is content reuse. The main problem standing in the way is composability: the ability to put pieces together and have them work.
Composability is an interesting problem. Lego sets and Mechano both have composability within their own systems, but there is little composability between Lego and Mechano. You cannot freely exchange the bits. Composability is similarly a problem between the many different file types used across a typical enterprise. If you want to practice component content management on an enterprise scale, you need a composable format across the enterprise.
There are two ways to get this. One is to allow each group in the enterprise to have their own format, but insist that it must be transparently convertible into a common composable format. The other is to get everyone to use the common composable format directly. The latter sounds easier, so that is what most people choose. (It is not always easier, but people only find that out later.)
To get everyone in the enterprise using a single composable format, you need it to be easy to use, as well as being flexible enough to serve everyone’s needs. What to choose?
DITA has been the default choice for a while now, but the problem is that DITA is not really easy to use. Several companies have tried to make DITA easier to use. (Tom mentions EasyDITA in his article.) But DITA comes with restrictions and restrictions are hard to learn and annoying to comply with unless you really understand the point of them.
Lightweight markup languages such as Markdown and ReStructuredtext have become popular as well, with various CMS and publishing systems being built around them. But while they are simple and easy to use, their simplicity can be limiting. There are things that occur in complex publications that they cannot easily represent.
DocBook offers a far richer set of markup structures that can represent all of these things, but without the restrictiveness of DITA. It makes sense, therefore, for a company like Paligo to choose it for their underlying document structure.
There is a rub here though, and it has to do with the two sides of Structured Writing that I mentioned at the beginning. Those two sides are composability and constraint. I am writing a book about structured writing (currently being serialized on TechWhirl) . That book focuses on the constraint side of structured writing.
The constraint side of structured writing is about expressing and enforcing constraints on content. It is about limiting and shaping what is written to meet a particular need. For example, it may constrain a recipe to follow a particular format and include particular pieces of information.
Here is a constrained version of a recipe:
recipe: Hard Boiled Egg introduction: A hard boiled egg is simple and nutritious. ingredients:: ingredient, quantity eggs, 12 water, 2qt preparation: 1. Place eggs in pan and cover with water. 2. Bring water to a boil. 3. Remove from heat and cover for 12 minutes. 4. Place eggs in cold water to stop cooking. 5. Peel and serve. prep-time: 15 minutes serves: 6 wine-match: champagne and orange juice beverage-match: orange juice nutrition: serving: 1 large (50 g) calories: 78 total-fat: 5 g saturated-fat: 0.7 g polyunsaturated-fat: 0.7 g monounsaturated-fat: 2 g cholesterol: 186.5 mg sodium: 62 mg potassium: 63 mg total-carbohydrate: 0.6 g dietary-fiber: 0 g sugar: 0.6 g protein: 6 g
Sam Jackson makes it look easy, but Siri and her cohorts are still pretty dumb. If experience alone does not illustrate this to your satisfaction, a recent article in the MIT Technology Review, Tougher Turing Test Exposes Chatbots’ Stupidity, shows just how low their success rate is in understanding real language.
The Winograd Schema Challenge asks computers to make sense of sentences that are ambiguous but usually simple for humans to parse. Disambiguating Winograd Schema sentences requires some common-sense understanding. In the sentence “The city councilmen refused the demonstrators a permit because they feared violence,” it is logically unclear who the word “they” refers to, although humans understand because of the broader context.
Affordances, those features of a product that help you figure out how to use it, are relative.
Most of the busses in the Kitchener-Waterloo region have rear doors that open when you wave your hand in front of them. The one I took downtown this morning must have been an older model because it just had two vertical push bars on the doors.
When we arrived at the terminal, the young woman at the front of the queue to get off started to wave her hands in front of the door, which did not respond. Puzzled and alarmed, she began to shout at the driver to open the doors, until someone behind her said, “push the handle”.
tl;dr: We can apply engineering methods to content development, but we do not have the body of proven algorithms or known-good data to justify formal certification of communication professionals they way we have for doctors and engineers.
We talk about content engineering. I call myself a content engineer sometimes. But can content really be engineered? Is content engineering engineering in the same way that engineering a bridge is engineering, or only engineering by analogy?
This post is prompted by a fascinating conversation with Rob Hanna and others at the monthly STC Toronto Networking Lunch. The conversation morphed into something I think I can fairly characterize as: is there a uniform methodology to technical communication, one that can form the basis of a curriculum, a certification, or a toolset, or is there a legitimate diversity of approaches, roles, methods, and tools.
It is often appealing to think of technical communication as a process of answering user’s questions. The difficulty with this view is that one answer can have many questions. If you answer each of those questions, you would be providing substantially the same answer over and over again.
This is very easy to see on StackOverflow, a question and answer site for programmers. Privileged user of StackOverflow can mark a question as a duplicate of another question. Here’s an example:
The question here is “How to check if a variable is a dictionary in python”. This is a question that programmers are going to ask themselves many times. It is a specific instance of a more general question, which is, “how do you check if a variable is of a specific type in Python?”
In our data-driven age, we tend to give short shrift to story. Story tends to get herded off into the ghetto of drama. Story is for amusement; at work we stick to data.
When I wrote my last post, suggesting a switch of terminology from “content” to “story”, many people naturally interpreted story as meaning drama. As Larry Kunz put it, “In technical writing, the story’s hero is your reader, who’s trying to accomplish something or learn something.”
That may be a useful way to think about your tech writing, but it is a definition of story derived from the world of drama. When I talk about story in the world of tech comm (or marketing communication, for the most part) I am not talking about drama, I am talking about general human communication about everything. Because story is not a special preserve of entertainment. It is how we communicate about everything.
In a recent LinkedIn discussion on “Most important competencies for technical writers“, I commented that the most important skill for technical writers was explanation, and that the ability to write and the ability to explain are not the same thing, and that the ability to explain is significantly less common that the ability to write well enough.
This scarcity of natural ability to explain well, I argued, is why we need to pay attention to tools and structure, because we need to find ways to help people who do not have a natural gift for explanation to explain things at least reasonably well. Tacitly, this argument suggests that there is a reproducible method for explaining things.