All manner of utopian science fiction works in popular culture have attempted to paint a picture of the society of the future. From 1984 to Blade Runner to Minority Report, many have tried, most have failed, and some have come surprisingly close. But now we’re on the verge of what you’d be forgiven for thinking sounds like yet another sci-fi story, but is very much set to become reality.
The Fourth Industrial Revolution is a topic that’s come up in conversation with several of my content marketing clients recently, but ultimately got placed on the back burner because they’re not totally sure what it is or how it relates to them. The truth is that neither was I, until I attended a Content Wrangler webinar that discussed how it relates to information professionals.
The webinar was really eye-opening and piqued my interest in the potential ramifications not just for our working lives, but for humanity generally. Deep right? Anyway, I thought I’d share some of the key learnings that had got me thinking about this topic in as simple a manner as possible.
What is the Fourth Industrial Revolution?
You’ve probably at least heard of it, and you’ve probably also heard of Industry 4.0. That’s because they’re the same thing. The German Government first coined the phrase — Industrie 4.0, to be precise — to summarise a high-tech project it was working on to promote the computerisation of manufacturing.
The core principle of Industry 4.0 is the automation of technology processes, hence the logical concept of the next industrial revolution — whereby we’ve advanced from steam engines, to industrialisation, to electronic automation and now into smart automation.
This next step in the evolution of industrial revolutions is where the sci-fi geek within us gets to run wild. Because this means we’ll see machines begin making decisions in our place, with ‘actually smart’ machines making cognitive decisions based on AI engines. This smart automation concept encompasses cyber-physical systems, the Internet of Things, cloud computing and cognitive computing, and is essentially a smart network across which machines can communicate with each other and with humans in real-time.
There are all manner of challenges ahead of us before we reach this point, from security concerns, legal issues, a lack of regulation and reliability of machines, through to the threat this poses to businesses’ traditional IT departments, their general reluctance to embrace change and the lack of commitment from senior management. But businesses need to act sharp and embrace the change or they risk being left behind by savvier, more innovative competitors.
The Industry 4.0 Big Picture
This shift isn’t all about technology. Sure, we’re going to see machines start talking to each other and actually begin making their own independent decisions without us ratifying them — which, when you think about it for too long, is slightly terrifying. But the bigger picture is how this is going to impact our society and affect everything we know, everything we do and how we act as humans.
The rise of Artificial Intelligence and the ever-expanding Internet of Things network of devices are making us more comfortable with this concept of talking to machines on a daily basis. We’re now more than au fait with telling Alexa to do our most basic tasks and relying on Siri to open applications that we’re far too lazy to tap ourselves.
And, if that’s you, then the good news is we’re going to be doing more of that. Much more, and not just in the comfort of our own home. Furthermore, we’re going to start seeing machines communicating with each other, which raises a whole bunch of questions that we don’t yet have answers to, for example:
· What information are they going to be sharing?
· What code will they be using? And will we be able to read it? (More than likely not)
· How do we track the decision-making process?
The latter question is a hugely intriguing one. At the moment, any decision we make is likely to be documented somewhere and stored for future reference. But in a world where machines make decisions based on information shared in a code we can’t read, how can we possibly decide accountability?
This is just one of the many intriguing ambiguities and anomalies that the rapid acceleration towards Industry 4.0 throws up. And, in an increasingly complex world of mind-boggling amounts of data being shared across billions of devices, that’s why we need machines to help us. But, someone has to help us understand it before it’s able to become a success.
With Industry 4.0 comes Information 4.0
The rise of the machines — to loosely quote Terminator in a slightly less apocalyptic manner — is fully reliant on data. You may have noticed that data is already massive. Like, ridiculously impossible to comprehend levels of massive. To put this in context, 90% of the data currently in circulation was generated in the last two years alone, if not even less, and the data wheel is only spinning faster.
People are searching Google around 70,000 times per second. Every minute amasses 16 million sent text messages, 176,220 Skype calls, 2.1 million Snaps, 4.3 million YouTube video views, 473,400 tweets, 750,000 Spotify song streams and 1,111 Amazon packages being shipped. As this data creation spirals out of control we need to be able to harness it and reap the value of it. We can’t do everything ourselves, so we need machines to do the dirty work for us.
This is why Industry 4.0 is being met by the technical communication community’s response: Information 4.0.
This essentially offers a death knoll to traditional documents. So it’s bye-bye paged structures, content pages, glossaries and all that dull stuff, and hello minimalist, standalone, highly contextual, granular content. This new look content will be highly relevant to the user’s needs, discusses one specific topic and, crucially, is small enough for machines to manage its storage and delivery.
The resulting unimaginably massive mass of microcontent will be too much for humans to create or manage, so we’ll need machines to take the lead. So expect to see the content creators’ role replaced by an AI rule writer and curator. Gulp.
To make this a little easier to understand, the Information 4.0 Consortium has created the below document, and assigned the following characteristics to Information 4.0:
· Molecular: The last decade has seen a large portion of technical communicators authoring content using the DITA structure, which supports modular content creation, single sourcing, and reuse. With Information 4.0, content is going to become even more granular.
· Dynamic: Content is automatically updated based on analysis of content metrics and customer interactions.
· Offered: Content is created and stored as molecular chunks of information, which are then assembled depending on context and delivered when the user requests it.
· Ubiquitous: Content is online, searchable, and findable. It is also single-sourced with multiple delivery channels.
· Spontaneous: Information is assembled and displayed in real time based on the context of information requests.
· Profiled Automatically: Content is no longer generic. The information delivered is aligned with the user profile and their needs.
If you’ve read this and thought “this won’t happen for ages, there’s no need for me to worry about it yet,” actually you couldn’t be more wrong. The machines are coming but, rather than taking our jobs, they’re going to help us do more productive jobs, do different jobs and completely shake up our lives as we know them.
One thing is for sure, change is coming fast, and it’s a really exciting time. To understand more about Industry 4.0 and help shape the content of the future, I recommend you join the Information 4.0 Consortium here.
In the meantime, I plan to read up more on both and try and wrap my head around what’s coming our way in the future of content.