Industry 4.0 is a defined model for automating factories and data exchange that first emerged in Germany. The goal is the creation of factories that self-govern with hardware components (e.g., robots, assembly lines) that can essentially “self-heal” through context sensing.
Information 4.0 is the informational component for Industry 4.0. Though not yet precisely defined, Information 4.0 acts like an information exchange ecosystem that encompasses all aspects of Industry 4.0.
- Excerpt of The Future of Content Starts with Collaboration
Welcome to Towards a Smarter World. This is your host Cruce Saunders and I'm here in Shanghai China with Ray Gallon, the president of “The Transformation society". Ray has been working in the field of technical communications, content, digital transformation, organizational learning and many other avocations throughout his career. He is a contributor to numerous research journals and books, and a keynote speaker throughout the world. Ray, thanks for joining me today.
It's a pleasure. I'm really happy to be just sitting here in this hotel room and having a conversation with you.
Pleasure's all mine and I really appreciate the chance to talk broadly about many of the changes happening in our world. Ray, could you give us a little background on yourself, your personal history, and how you evolved from radio through the world of techcomms and into the many diverse areas of inquiry you pursue today?
Well, I suppose you'd have to say that the thing that's always interested me and the thing that is like a through line in everything that I've done is a fascination with the meeting place between communication, culture, and technology. Those are three things that have always fascinated me and I suppose, even central to that is the notion of communication. So I started out as a radio producer and journalist, eventually becoming a radio manager. Then I moved on into electronic networking, very early on in the 80’s when electronic networks were basically private, and moving into technical communication as an outgrowth of the work in electronic networking especially because it was really hard to make a living doing electronic networking in the 80s. Nobody knew what it was.
So I started working as a “technical communicator” and originally I did that basically to support my art habit, because I liked doing certain things in the art and culture world, and I'd spent a long time in that domain. But eventually, I discovered that the technical communication work was every bit as creative as doing art. It wasn't art, but it was creative. And it was fascinating and it became actually a passion - a more than full-time passion.
As the field has evolved, opened up and expanded, that has given me so much opportunity to get my fingers in so many different pies and to play around in so many different playgrounds and sandboxes, that I just never get bored. I don't know if that's too compressed.
That’s perfect. Well, information 4.0 is an area you've spent some time thinking about and fact founding the Information 4.0 Consortium. Can you talk a little bit about what information 4.0 refers to? What does it mean, and what was the founding impetus behind the consortium?
Well, together with my colleague Andy McDonald, we were looking at the world of an industry 4.0. “Industry 4.0” is a term that was actually invented by the German government to talk about their initiative in creating smart factories that basically were powered by the combination of the Internet of things and artificial intelligence. So connected objects, and some sort of smart technology behind them.
This term in industry 4.0, sometimes you'll hear people talk about the fourth industrial revolution which I think it really is, and other people, especially in North America, refer to it as the industrial internet, or the industrial Internet of everything. But why is it so important? It's the fourth industrial revolution, which means that for the first time in the 21st century,
That is a huge change in the way that we're relating to industry and to all the technologies that are surrounding industries, so by extension smart cars, smart houses, smart schoolrooms, and smart everything. And that's a huge change.
Andy and I were looking at the government initiatives and industry platforms and so on about industry 4.0 and we kept saying, “Well, where's the information? Where is it?” Nobody is talking about it. I think there's one sentence on the German government site that says eerily, “Data will be converted into information,” and that's it.They don't say by whom, how, under what circumstances or why it's interesting to do that. It’s just this one sentence there.
And so we thought, wait a minute, if we don't get information designed into this stuff from the get-go, from the first days it's going to be a disaster because as our slogan goes,
Information is what drives all this. If you look at the technologies, the algorithms that are being used for machine learning, deep learning, natural language processing and various other aspects of artificial intelligence. They're all based on statistical analysis. So it's a statistical analysis of data but if you just do pure statistical analysis you also run a very great danger of things like cognitive biases.
Just to give a really simple example, if you had a human resources application that was designed to choose good coders based on history. You know who has made a good coder in the past? No woman would ever be hired as a coder. Because if you look statistically in the existing base of coders there are far more men than women. So that would be a cognitive bias that we come into it just by pure statistical analysis, and that's the thing we want to avoid.
So in the Information 4.0 Consortium, which we founded to provide an informational response to these technologies, we talk about how information needs to be molded, cut- paste, massaged, distributed and so on. But we also talk about providing a humanist response to these technologies, so that the technologies serve humans and not the other way round.
I'd love to return to humanism. The characteristics of this new era of information that's defined by the Information 4.0 Consortium include: information that is molecular dynamic, spontaneous, profiled, and ubiquitous, everywhere, and offered to the user as opposed to being dormant waiting for a user to interact with it.
So those definitions are really becoming more real every day. “It is not ubiquitous across devices and platforms and ecosystems of interaction. But in fact, it is isolated and in single repositories or single web sites, single web pages or Pdfs.
So there's a lot of current state around information that doesn't live up to these aspirations. I wonder if you could reflect on what we, as people invested in the future of content experiences, can do to help bridge to this new world of spontaneous, molecular, dynamic, offered, profiled and ubiquitous information?
Wow! You've just explained very clearly what William Gibson said some years ago when he said, “The future is here already. It's just not evenly distributed.” A lot of what you say is absolutely true. It's also true that not everybody needs this right now. But some people need it really badly. So I would say the place to start with all of this is the place where the need is greatest because that's where we're going to demonstrate the value of what we're talking about. Now there's this list that you just read off from the definition of information 4.0, a lot of it is not new.
We've been talking about structured information for quite a few years and we have DITA, we have S1000D, we have other standards, and other ways of structuring information even without standards. If you use any one of the traditional help authoring tools something like RoboHelp or MadCap or whatever. You're doing structured information, because of the nature of the tool demands structure. You can do structured information if you want and if you have a lot of self-discipline, even in Microsoft Word.
The thing about tools is that they impose discipline or they facilitate the discipline so that you can do structure better, and with more reliability. But structure itself is a human concept and requires some intelligence to do well. That's number one.
Number two: we're talking about chunking information but we're talking about chunking it maybe a lot smaller than say, a DITA topic. Why do we need to do this? Because in a world in which information is delivered in a very, very highly personalized way, in which information delivery to a given person may need to take into account not just where they are, or where they are in a process, but where they are physically, whether they're in motion or still, whether they're inside or outside. Because now we're delivering information everywhere, any time, always on. Even the emotional state of the user so that we might deliver the same information in a different tone. If the user is frustrated, or if the user is happy.
We also might deliver the same information with different levels of granularity depending on what the software that's doing the information delivery knows about that person's level of expertise. And so there's a lot of technology there that we haven't got yet. But we know that we need.
We also know that the same technology is going to be operating some of these devices that we're talking about. So we can lean on that technology and use that same technology in order to provide this personalization and the notion of offer. I'm going to dwell on that for a minute. The idea of offering information, because I think that's a key difference to what we do today. You mentioned information which is dormant and waiting for somebody to come to it and we have that, we have lots of that. But we also have a situation in which information is pushed out at people, and is shoved out there. There's a problem with that because the way that we get information today - in the old days we would read a school book, or a textbook, and we'd get a lot of linear information. So we'd start to begin at the beginning, go through a whole progression and end up at the advanced level. That's not how we do it today.
Today we want information right now. I want to know what button do I push to make this work and do what I want to do right now. And so where do I go. I go ask my good friend Google or Bing or whatever search engine you like. For most of us most of the time it's Google. Let's be honest. We get back a piece of information that might be highly advanced without having any of that fundamental background information that leads up to it.
We've all got, because of this is the way we get the information, we all have these gaps. These black holes of information that are missing in between whatever fundamental information we have, advanced information, and intermediate information. So the problem is that if I'm an information provider and you're a user I don't know what your gaps are. I don't know what the next person's gaps are.
So how do I provide that person with useful information that will help him or her do the thing they want to do without teaching them to suck eggs. Without telling them what they already know and boring them to tears. Which is what happens when you go through say, a printed manual or something like that and to find the bit you want.
Well, the way to do it and in my view, this will touch on a subject that I know is dear to your heart Cruce, which is ontologies. If we have a well-constructed ontology. Well-constructed ontology covers a number of issues that we could have with this automation and this personalized delivery. One is, it should give us enough of an offer that we can select what we need and we'll find it without it being so large as to be overwhelming, which is often what a Google research result is.
There are thousands or even millions of pages that are referenced and none of us ever looks beyond page one or two. Because it's just too overwhelming and we don't know where else to find something interesting. So there is that, but then there's another problem that comes up when we're using automation and that is what's often known as the search bubble or just plain digital bubble, which is that -
There will be a tendency to narrow down and to give us a narrower and narrower set of results in an attempt to please us and to give us what we're looking for. But sometimes we need a surprise. Sometimes we need to see something that we weren't looking for. Because that's also important, and that's another way in which we learn, and all of this is about learning. And an ontology can give us that if it's well constructed. An ontology can show you something that's your center of interest and then show you a bunch of things around it, some of which you would expect to see and some of which you wouldn't.
So that element of surprise that takes us out of the digital bubble is also extremely important if we are going to continue to grow and to become expert users of products or experts about a given subject, etc.
This is really interesting. We spend a lot of time working towards contextual presentation of content experiences that are more personalized in order to reduce the cognitive load on our users. Because
But to your point, there's also a need to be able to discover ancillary information. If I'm going for a book in the library, I might want to pull out that one chapter out of that one book on that one shelf in order to get just the information I need. But if I were to actually browse through that whole area of the library I might be able to understand related things that I was not planning to connect in my original search for that answer.
So there's this interesting dichotomy between the reductive minimalism necessary to give a user the precise answer to a query or an intent, and then there's this contextual cloud of the edges of concepts that are connected to the node we're looking for.
Yeah, Mark Baker talks about “information grazers” and it's that. You’re sort of out there chomping on the grass and “here's a nice interesting patch just next door. I think I'll chomp on that. Oh, that tastes good. You know I'll try that out.” And everybody who's ever spent time in the pages of a real paper dictionary knows how easily you can get lost in them because it's fascinating. You find the word you've looked up, but then you see something else and you go after that, and you go after that, and you just keep going.
This is part of human nature, and it's part of why this profession is so much fun actually, at least from my point of view, we're all the time discovering new things. So I want to do exactly what you were just saying Cruce which is - yeah we want to reduce cognitive load. We have to, because there's way too much stuff out there. But at the same time in doing so, I want to make sure that somewhere in there, there's the little grain of sand in the oyster that creates the pearl. The little disturbance, the little something or other that will set you off in some new direction or in some interesting new exploration because without that we might as well just be imitating the machines, and the
Interesting. Facilitating faceted discovery in order to both provide the one node that is being sought, or that is most useful to the user's context, but then also exposure to the edges around that node that are potentially useful to other aspects of discovery. Because
Therefore we have to create a holistic learning experience. That's a good bridge to this next conversation which is about the future of knowledge and learning. You just returned from Korea where you gave a talk about Pedagogy. Can you talk a little bit more about what you were discussing with the Korean audience and also your thoughts about the future of learning on the planet Earth?
Well, in Korea was a conference for people who use media as a tool for teaching English, and what we were talking about- the main theme of this conference was trans-media, which is where you have a complete story or a complete picture only if you go out to several different media or platforms.
Just to give an example, let's say, if in order to understand something you needed to check some things out on LinkedIn, and then some other things on Facebook, and then get involved in a conversation on Twitter, which are all aspects of the same information-set but presented in different ways. And then you might also want to look at, say a video on YouTube or a TED-Talk or something like that. So we have multiple platforms, multiple media and that's what trans-media is all about.
In marketing, we call that Omnichannel.
Right. Well but omnichannel usually means, you get the whole message going to one or more channels. In this case, the whole message requires multiple channels. And that's a subtle difference. You won't get the entire message unless you go to multiple channels.
So we're assembling bits of the puzzle from each of the different media with which the whole experience is constructed.
Right. I think to answer the question that you posed, if you look at the world of information and the world of, let's say, technical communication because that's a domain that I come out of. It's also not very different from when I was a journalist, which is to say, what are you doing? You’re explaining stuff to people. you're telling people what is an inner-working, how it works, what the motivation is. And so all of this is a kind of learning. And what I've seen as I get more and more involved in the education field is that education, whether it be formal, non-formal or informal, it’s learning.
What do you do when you provide, let's say, user information for a technological product? That's also learning. John Carroll who is the father of Minimalist user information design is a specialist in learning theory. That's what he does, and that's what all of us do in fact, whether we think of ourselves that way or not.
There's been a lot of conversation and sometimes, unfortunately, siloed walls between the world of technical documentation and the world of training, though that's a silo that absolutely shouldn't be there. If there are any two departments that need to be talking to each other, collaborating, and interworking it's those two, because it's about the same thing. And you don't always use the same language. You don't always use the same order of information and so on. But it's all the same stuff. It's all the same material. People should be collaborating on that, and that brings up something else too.
You used the term “Knowledge Creation” when we were talking just a moment ago, and there's a young professor whose name is, “Nikita Basov” who teaches in Saint Petersburg in Russia and also in Bielefeld in Germany, who has developed some ideas about knowledge creation in which he says very clearly that for knowledge creation to take place, this is a social activity.
We already do this to some extent when we ask Siri or we talk to Alexa, but now it's mostly question and answer. Eventually, it's going to become more like dialogue, where we will receive input from artificial intelligence, and we will also be giving artificial intelligence input which will then change its output.
We're going to have to learn how to do that. Hopefully, without anthropomorphizing the algorithms because that's always dangerous. But still accepting them in some way as collaborators in this knowledge building, knowledge creation process, and that's uncharted territory. I think it's very exciting. I also think it's very dangerous. Most things that are exciting are also dangerous. That just means that we have to be on our toes and do a good job of it, and not cock it up.
Indeed. Allow a lot to unpack there. The next generation of customer experiences will be born out of increasingly interconnected knowledge sets within an enterprise. You brought up learning in tech docs as really obvious ones where we're both dealing with the same entities from either side of the fence. It could be a product, it could be a process but it isn't. It is a common topic, and within structured authoring, we know that topics can be extended in their number of elements and what those elements address within a structural content model.
So there's no reason that a content model shouldn't include topic-based content that is both learning content, that's driven for techdocs and support, and another one that's driven around a linear educational process for product onboarding.
So both of those may be authored in a common way, against a common model- might be by different contributors- but sharing a structural model in order to help to deliver some common experiences, and then the machines can start to pick parts of the model that are most useful to that user based on their context.
Yeah, I totally agree with that. We tend to learn best by doing. Learning by doing is very, very effective. Some people have interpreted the minimalist focus on learning by doing as suggesting that conceptual information has no place. That's erroneous. That's never been said by anybody that I know that's actually been a developer of the minimalist idea. It's simply that the place to learn conceptual information is in the act.
For example, let's just take something really simple like a series of steps in a procedure. So you do something you get a result. And the user assistance explains the result. That's conceptual information. That explanation might only be one or two sentences. You don't need a great long tomb to do it. Mostly, every once in a while you do. But mostly you don't. And so you just explain that there.
People are more likely to retain that than say reading a long conceptual document apart from the actual procedure and process, and if you think about it, and this is something that really turned my mind around when it was explained to me.
In the traditional process, whether it’s say, a printed manual, which we read before we then go and use a product. It's not the manual that gives meaning to the product. It's the product that provides the meaning of the manual. It's a lot like a movie script. Reading a movie script is not seeing a movie. You read a movie script, it's an abstraction. It is given meaning when you start shooting the movie, editing the movie, and eventually watching the movie.
In the same way, a printed manual has no sense unless the product is there. So if the product gives meaning to the manual- now that's not, I think, what we want. I think what we want to do is to put the meaning in the product or the process, and that's done through this active learning, learning by doing, in which we embed concepts.
This is so huge. The customer experiences are very much like a participatory experience, just like a movie is a participatory experience. We bring our own histories and presence to every interaction we're experiencing from the screen, and the actors, and the cinematographers, and the animators and all of the creatives, are all bringing their shared experience into that one setting. And then we're creating learning together from all aspects, and so our product interactions and our customer experiences similarly bringing the user the customer into an interaction with the shared experiences of all of the contributors creating that contextual interaction with the product. it's sort of like a co-created improvisational and multisensory experience of collective learning that is happening.
So you're bringing kind of that perspective into this understanding of the role of the technical communicator. That it's scripting a much bigger experience that lives with the product. It's not necessarily possible to divorce it from the product, and our next generation experiences are going to provide a lot of that contextual understanding directly in the product interfaces, rather than in a separate manual that ships with the product or that you have to read later. There's more sort of in-context and co-created interactions with that same information. Am I characterizing all of that correctly?
Yes, absolutely. Furthermore, I'm going to take it a little bit farther, because when we talk about a product, sometimes that can sound very banal. But I think that given the time that we are living in, the phenomena that are going on around us, things like global warming and threat to biodiversity and so on. That we really have to think about the products that we put out into the universe as having - if we're going to make them they should be doing some good in the world.
So what we're talking about is very social. Simply in the sense of interaction, but also in the sense of the overall well-being, and given that we now have a whole panoply of goals set out by the United Nations, which are the sustainable development goals for 2030, which are being taught as curricula in schools to young people, and which should be part of the objectives of enterprises, and there are a lot of them that apply very specifically to the economy and to production.
These are not these goals that are sort of “pie in the sky.” These are things that are very down to earth, that we need to do in order to make the world a better place by 2030. 2030 is not very far away at this point and we're just talking about 11 years. 11 years is nothing in the scale of time.
Whether it's on a simple level of product-use where we bring people from beginner to expert level. That's raising consciousness. Or whether it's on a more global conceptual level or a more abstract level. That's part of what we do. And that's also one of the reasons why I think this is so exciting.
I love it. I feel like we could talk for hours but that is such a beautiful note to end our conversation on, and I believe that we should at some point find additional venues for this kind of conversation as we branch into humanism in an A.I. driven world, and this smarter and better world that comes out of information experiences and the interaction between machine intelligence and human intelligence. The evolution of both of those things is happening all around us. But not evenly distributed.
I am very pleased to get to explore that, and I know our audience will be as well. Thank you, Ray, very much for your time. If folks would like to look into your work where can they seek?
Well, there are a number of places. There are pages on ResearchGate and academia.edu where you can find research documents, and there is, of course, the web site of the Information 4.0 Consortium, www.information4zero.org. And of course, my company's site, the transformation society (www.transformationsociety.net).
You're on Twitter as well at?
@RayGallon and the company at @TransformSoc.
Great. Ray, thanks again so much.