The Digital Customer exposes the need for value in all interactions

We already have digital versions of ourselves populating our increasingly digital world: Your Linkedin, Facebook and Twitter profiles, your Amazon and Google footprints are all examples.
For the most part they are not yet autonomous. But it cannot be long before the 'MeBot' - an autonomous and intelligent you - becomes a ubiquitous part of our daily interaction with people, things and data.
All of which strongly suggests that brands and organisations must start developing strategies that place the digital customer at their heart.
Let me be clear, that digital version of you will always be informed by and learning from the real you. But increasingly it will be the digital rather than analogue version of you who will be making the transactions (tilting, as these thing are, to online more heavily by the day).
And if Digital You has got the spends - Digital You is going to be the target.
So what does advertising/targeting/relationship-building/comms/PR/you-name-it look like when it is aimed at our MeBot?
Well - I suspect MeBot's will rapidly learn which lies to ignore, which content sources to trust, which deals are for-real. They may even be less swayed by the Herd mentality humans find it so hard to resist (think of the impact on the Stock Markets...).
This is likely to starkly expose some of the realities and truths of relationships of trust - such as...

1. Customers are not inhabitants of your omnichannels waiting to be managed from one to the next. They live in a 4D world with limitless touchpoints. The analogue digital combination will evidence that by the truck-load. Map that!
2. Customers are not waiting to be engaged, made your friend, or have anything else 'done' to them. They need a reason to interact with you... which leads us to point 3.
3. Customers are not loyal. Forget loyalty - focus on proof of value. Unless you are offering a good enough value proposition your wheels will just keep on spinning.

Predicting how long your job will last

If you want to predict the future, look at what has stood the test of time.

When we talk about the future of work - naturally there are going to be new roles. There may be less or different tasks, the latter more likely.

But what you can bank on is that the roles that were here 100 years ago are far more likely to be here in another 100 years than those roles that have been with us for just a few short years.

That's not to say none of the new ones will stand the test of time, but a far higher percentage of the old ones will.

The longer anything lasts - the longer it is likely to continue to last. This is one of the lessons we can draw from Antifragility and other work by Nassim Nicholas Taleb. He would say it is a lesson we can learn from the wisdom of our grandparents.

Will a teacher's job exist in 100 years time? 90% yes. Will a social media strategists? 90% no.

We are often dazzled by the new and make projections into the future on very shallow data. This fails. As AI is proving all over again.

To create value with AI the proposition needs to be reframed in terms of prediction. But unless the correct weighting of what has come before is built into the programming, researchers find they hit the problem they call 'catastrophic forgetting'. The solution is to build in virtual memories (eg Deep Mind's Differential Neural Computer).

For AI to succeed it has to factor for what you and I instinctively know - the longer something has lasted, the longer it will succeed.

Imagination beyond experience - the leap to Super-Human

Image from the movie Superman

Humanising AI is a worthy and common dream. And it is where and how we should focus to create value in the near term. But a greater challenge looms.

While we always seem to want to make AI 'think like a human', we know that when it doesn't, it can outperform us (in narrow fields, where ambiguity is constrained, at least) for example in the games of Chess and Go!

While we always seem to want to make bots look like humans, we know that there are many more efficient designs to meet specific needs. The human body is a bit of a jack of all trades, master of none (compare us with the highest performers in any particular parameter from the animal kingdom.)

And while we always seem to want to make AI behave like humans, we know humans behave irrationally and often against our best interests.

Imagining super-human (ie outside of human) thinking, design and behaviours will be our next great challenge. And for that we are going to have to truly partner the machines because this will take us beyond our own experience.

Why robots are essential to kick-start our next age of innovation

Yamaha's Robot rider could one day end the  chore
of riding fast motorbikes... er, ok it's not all good.

There is an argument - and a well made one at that - that our era is not an age of great technological change - but actually one that is quite stagnant.

Robert J Gordon made the case in his book 'The Rise and Fall of American Growth'. He points out that the Great Inventions that caused real change arrived between 1870 and 1970.

The internal combustion engine changed the way we travel (removing the growing threat of horse manure - which experts predicted would reach 9 feet deep on London's roads by 1950 if allowed to go unchecked). It changed the way we travel much more than any subsequent improvement in performance or styling.

Urban sanitation similarly had a greater impact on our health than medical inventions of more recent years. The invention of the telegraph versus the written message carried by ship, horse and hand which preceded it is a far bigger shift than fax to email or phone to mobile.

The impact was that we got to live (US childhood mortality tumbled from 1/3 in 1860 to 1/200 today), we got to live longer, and we got more time to do with as we pleased (being liberated from household tasks such as washing clothes and preparing meals which had taken 58 hours in 1900 - and 18 in 1970).

Jesse Frederick argues in his assessment of Gordon's ideas that our blindness to the comparative stagnation of the modern era can at least be partially attributed to the fact that the technology of the past mainly created time, whereas today’s technology fills it.

Gordon, published in 2016 - sees this stagnation as permanent. Mostly because the big wins for technology have already been won. But part of the problem is for all our technology we feel as though we have less time. And time is essential for the ideas that make real change.

Enter Robots. the AI revolution and the robotics it is driving are about to answer Jesse's criticism of today's inventions. They are certainly not a technology that fills time, they will create at least 18 hours for us (finishing up the last bits of housework our inventors have failed to resolve so far - ironing, dusting, food prep and cooking, physically moving the devices about etc). The internet of things completes the picture in shopping.

Ok, an 18 hour saving isn't as great as the 40 hour leap that got us here - but this one will come in 5-10 years. The last took 70.

And we haven't even considered the saving in time AI will bring to our working (and commuting) lives. Finally, the time technology promised to free for us will actually arrive.

And yet, even for the slam-dunk win our robot friends will provide, there's an even bigger opportunity for genuine life change: How we organise is changing.

How we organise is society and society is how we live.

As I have long argued; the web enables adhoc self-forming groups to get things done. That's a fundamentally different form of organisation than preferred by 1870-1970. That era was also an era of centralisation and mass production. The next 10 years is about decentralisation and personalisation; whether it be through micro factories in every home (3D printing), the move away from public transport (driverless cars, drones) medical technologies that self diagnose and repair (nanobots) or how we learn, get justice, make contracts and exchange value (blockchain).

We will have the opportunity to live entirely unique, separated lives. But all the evidence of the world since the web is that we will use it to become closer and better connected - without the need for central organisation.

A future without centralised or top-down direction is being enabled through the technologies of this decade and the next. 

Very soon we will have the collective time to carefully consider what our future should look like and imagining how we can reach it - kick-starting the next age of innovation.

And that, when we pause to reflect on the shift from 2010 to 2030, will, I believe, provide us with a case to say we really do live in a time of not just fast, but radical change.

Could your next vote be your last?

My recent focus on trying to understand the constituent parts of experience (particularly in relationship to the experience of customers) when combined with the impact of the capabilities of both Cognitive Computing and Artificial Intelligence raise challenging questions about the primacy of the self and therefore of liberal democracy.
This starts from the premise that we don't know ourselves particularly well - and therefore we may not be best placed to know what is in our best interests.
And that's built out of the Open Business principle of Trust. Trust is built from the belief that the entity you are dealing with has your best interest at heart (this is what partnership requires, too).
So first - why don't we know ourselves particularly well - and why does that matter. Anyone who has read my articles, the third and fourth dimensions of customer experience will have had a reminder of the work of Daniel Kahneman onwards showing how we make short cuts all the time when making decisions. We recall experience using the Peak-End Rule. We average our low score and our score at the end. We don't aggregate the sum of our experiences.
We have evolved to experience this way to enable us to survive in fast moving environments. It was the most effective way of dealing with the data.
Wouldn't it be better if we could take account of all our experiences when making a decision. Like whether to turn left or right at the next junction.
Google Maps already does a better job of this. It (potentially) takes the sum of all the experiences of all the drivers on the road and plots your routes in the best interests of all. It does this very even-handedly. There's no way to upgrade so that everyone else gets sent out of your way, for example.
It makes better decisions for us than we do. In Google we trust.
Ok, so why not let Google select our partners? By storing and being able to access and analyse all of our experiences (at least those shared with Google - which are plentiful enough) Google could claim to know us better than our Narrative Self (the one that makes decisions based on recalling experience in its short-cutting Peak-End Rule way. It also has everyone else's experiences and outcomes to draw upon for its calculation.
Should you marry prospective partner A or B?
Those using dating sites are already handing over much of this cognitive spade work to algorithms. In Google we trust?
And if you want to hand the decision making to the algorithm for the selection of your life partner, why not to cast your vote?
If the algorithm knows your best interests better than you know yourself, why not let it make the right choice for you - uninfluenced by your short-cutting Narrative Self?
En Masse, why bother with voting at all. Are we ready for Government by Algorithm?
Humans have been, for a long time, the best things we had available to gather and intepret data.
Control (via Trust) has tended to concentrate with those who both have access to and interpret data for practical benefit. Priests could interpret the word of God to give you temporal guidance. Astrologers could read the starts to tell you when best to plant your crop. As economies grew more complex being able to read helped you make better decisions, bureaucracies grew, measuring, recording, predicting data about fields and roads and cities and people and incomes and food production and disease and health and threats and technologies and the instruments of Government grew around these data warehouses.
Now, to predict the complexities of the weather, the markets, the needs of the people, we turn to algorithms. They have become faster and better at interpreting more and more data than the best human agencies.
So why not be Governed by Google? By knowing us better than we know ourselves it can provide for us better than we can choose for ourselves. If only Google cars were on the roads, we would need a fraction of the cars currently produced (most are parked at any one time) and we would all get to where we wanted to go faster, with less pollution.
Give it control of our health and we would all live longer happier lives and our medical care could be delivered at a fraction of the current costs. Take a look at what Google Deepmind is currently engaged with the NHS to deliver for one small segment of improvement the algorithm could deliver.
Give it control of the economy and imagine the potential for supply to meet demand and the wastage that would cut.
This feels really uncomfortably like centralised, command and control economics to those in the liberal tradition.
And it's hard to deny that's very much what it is. But the difference is there is no politburo, no five year plan - no numbers set by politicians. This would be an economy run in the best interests of those engaged in it by a benign dictatorship of an algorithm which genuinely has your best interests at heart. The command and control is the needs and desires of the people.
When the time comes that the algorithm really could do a better job of governing us than our politicians, would you be prepared to make your next vote your last vote?