Completing the 4th Industrial Revolution
Are we living through a fourth industrial revolution driven by digital data?
Almost certainly we are. Data is acting as a telescope and microscope opening up new insights and discoveries. It enables automation of processes, reducing the work input needed to get things done. Using data we are more able to organise and align activities (a capability that is the unsung hero of productivity improvements and broader wealth creation). It’s speeding up, reducing the cost of, and enriching the ways people and organisations communicate and interact, all at the same time.
And, crucially, like all ‘general purpose technologies’ from iron-making to fossil fuels, it applies to every industry, every society, every walk of life. No matter what ideology, religion or political regime, you won’t find a major city in this world not using electricity. And you won’t find one that’s not increasingly reliant on data.
A distorted lens
However, most current debate about this ‘fourth industrial revolution’ is distorted. You’ll find torrents of commentary, analysis and prediction about things like Big Data, Artificial Intelligence, Algorithms, Internet of Things and so on. But this tidal wave of interest (and concern) suffers from two flaws.
First, it fails to distinguish hype from reality. ‘Artificial Intelligence’ is a complete misnomer (and an excellent marketing vehicle) that misconstrues what’s going on. It is a far, far cry from human beings’ ‘general purpose’ intelligence that can see things in context, switch attention and logical analysis from one thing to another, make value judgements, imagine alternative scenarios, be creative, be empathic, and so on.
Like fossil fuels before it, it extends certain human capabilities. Fossil fuels freed us from the constraints of human and animal muscle power (and the limitations of wind and water mills), thereby extending what we can do with energy. So-called artificial intelligence frees us from the human brain’s limited abilities to see patterns and make statistical calculations, thereby extending what we can do with data.
That’s great. But it’s not going to water the Sahara or achieve many of the other miracles (and dystopias) that publicists claims (and duped policy makers desperately hope for).
Likewise with algorithms. Yes, their potential is amazing. They are the automated machines of the information age. And they have the same core feature of the machines of the industrial age: if they were designed well and operated well they can work wonders. But if they are designed badly or operated badly they can be worse than useless. We are beginning to discover that now with all the stories of bias and error now appearing.
So yes, we are in the midst of a 4th Industrial Revolution but we are also in the midst of an explosion of hype about this revolution that, if not tempered, will end in huge amounts of wasted effort, dashed hopes and yes, real damage.
Which leads us to the second flaw.
The ‘special case’ of personal data
The 4th industrial revolution is driven by data. But there are different types of data. There is data about things, like the weather. And there is data about persons. There is statistical data that doesn’t identify or relate to any particular individual. And there is personal data which does relate to a particular identifiable individual.
In most of the hype about the 4th Industrial Revolution you’ll find scant recognition of the differences between these two types of data. For every ton of breathless excitement about the potential of ‘analytics’ you might find a few ounces of dismissive caveats about personal data along the lines of: “Of course, in unleashing all these marvellous opportunities we must pay attention to privacy concerns”.
It’s quite clear from the way many AI enthusiasts talk, if they had their way even if there are laws like GDPR pertaining to these ‘privacy concerns’, they they’re just an awkward interference, a nuisance, to be ignored or otherwise got round — a lesser concern to be sacrificed on the altar of the bigger potential of ‘Big Data’.
A flawed model
How wrong these people are! If we follow this ‘pay lip service to it but ignore it’ approach to personal data, the 4th Industrial Revolution will be stopped in its tracks and its full potential never realised.
Why? Because many, if not all, of the benefits of this revolution only crystallise when they apply to individuals (via, for example, new data-driven efficiencies or new information services) and at this crucial transition point we are no longer dealing with Big Data, Artificial Intelligence, Internet of Things data. We are dealing with personal data, which has to follow a different set of rules shaped by a different set of considerations.
Let’s put it another way. At this crucial point we are no longer dealing just with ‘data’. We are dealing with people. And if you forget or ignore that you cannot fail to go wrong.
There is a simple but important reason why we have reached this impasse: most of today’s proponents of Big Data/Artificial Intelligence have a flawed mental model about how data works. Their big fat false assumption is that data is something only Big Organisations ‘do’.
The way Big Data and AI works, they assume, is that Big Organisations collect lots of data about people, to generate insights about them, in order to do stuff to them and throw stuff at them. People as individuals don’t figure as part of this model. They are only important in their role as data feeds to statistical engines and as objects and targets of Big Organisations’ activities. They only figure as inputs and outputs, not as active agents, stakeholders or participants.
Viewed from this perspective, ‘privacy concerns’ are just an obstacle, implicitly belittled as if the multiple issues raised by the privacy debate boil down to close-to-irrelevant coy personal sentiments of no economic or societal importance.
Completing the 4th Industrial Revolution
But there is a different way of looking at this issue. Increasingly, personal data is the means by which services are created and delivered and the means by which people manage their lives.
Personal data isn’t just about ‘privacy’ (which is extremely socially and economically important in its own right). Increasingly it’s how the economy works. And it’s about people — individuals, households, families — being able to collect and use data for their own purposes, to get stuff done in their own lives.
In fact, come to think of it, just like the industrial revolution, the real full potential of the 4th Industrial Revolution will only be realised when all the marvels and benefits of Big Data, AI, Internet of Things and so on are applied to individuals in their daily lives. Which necessarily and universally involves the sharing and using of personal data.
At this crucial transition point, the 4th Industrial Revolution isn’t about ‘Big Data’ any more. It’s about personal data. It isn’t about statistical analytics any more. It’s about flesh and blood people. Without the means to manage this transition from Big Data to personal data the 4th Industrial Revolution will end up either horribly distorted or still born.
As a parallel, think of it in terms of energy generation and distribution. Power stations produce electricity at 25,000 volts, enough to fry human beings in an instant. Domestic power supplies operate at voltages of 110 or 230, with multiple safety rules and requirements to go with them. Only by managing the transition from Big Electricity to ‘small’, ‘personal’ electricity have we reaped the full benefits of electrification — and to do this we needed to create a special layer of infrastructure focused on this specific task and managing this transition safely and efficiently.
The same needs to happen with personal data. But how?
The answer, of course, is already to hand: a new layer of personal data infrastructure that provides individuals with the means to translate personal data into big data and vice versa (via their personal data stores) in a way that insulates and protects them from Big Data’s multiple dangers as they do so.
‘Big Data’ and AI are only one part of the 4th Industrial Revolution. The second part — the other side of the coin — is personal data, including a translation layer to the collection, storage and use of personal data. This extra layer of infrastructure is necessary for many others reasons. But it also has this crucial role: by making a safe connection between individual, identifiable people and bigger broader sets of data, it includes citizens (human beings) as an essential, active participant in a data driven economy. And in doing so, it ensures the benefits spread and reach as far as they can and should.
If we throw ‘privacy/personal data issues out of the 4th Industrial Revolution we throw people out of it too — turning it toxic in the process. Thankfully, that’s not necessary.
There is a way to complete the 4th Industrial Revolution. It’s via a new safe connection between its big statistical aspects and its small personal aspects, achieved via a personal data store-based personal data infrastructure. It’s time policy makers recognised this fact.
