My vision of the future - Tracey Follows

Future Visions is the series that explores the surreal world of tomorrow through the finest minds of today. Chapter five sees us step into the future as imagined by Tracey Follows, one that will see the emergence of a dominant ‘hi-technology lo-geography’ system.

Meet our expert, Tracey Follows. Tracey is an award-winning futurist and works with clients such as Google and Diageo. She speaks and writes regularly on the future of artificial intelligence (AI), gender, work and culture.

Key insights from Tracey’s vision of the future

  • The internet has overcome geography to the extent that anyone and anything can in theory be 'global'.
  • Businesses won’t focus on the scalability of production, or the scalability of distribution, instead scalability of information will win out.
  • We may see the emergence of crime prediction, with behaviour tracking, pattern recognition and anomaly spotting all resulting in being able to recognise the intent to commit a crime before it has occurred.

This is my vision of the workplace in 20 years’ time...

For as long as any of us can remember we’ve been living in a system of industrialisation. It has involved the specialisation of tasks, the institutionalisation of rules and regulations and the organisation of resources on a mass scale.

Two big forces are changing all that though: technology and geography.

As Tim Marshall explains in his book Prisoners of Geography: "The land on which we live has always shaped us... and the choices of those who lead the seven billion inhabitants of this planet will to some degree always be shaped by the rivers, mountains, deserts, lakes and seas that constrain us."

However, information technologies that enable borderless products and services and require none or very little, physicality, can be exploited in a way that ignores the geography of the land as business evolves to become an intangibly conducted set of services that can take place virtually. The internet has overcome geography to the extent that anyone and anything can in theory be 'global'.

Products become services

As such the internet has enabled the transformation of many tangible products into intangible, but no less valuable, services. Transcending the mountains, the lakes, the deserts and the seas, much of our day to day business is now done in the Cloud.

This transcendence of place has business all of a quiver. Huge opportunities to cut costs, to disintermediate suppliers in long supply chains and to offer more value to customers directly lie ahead in the 'hi-technology lo-geography' world that is emerging. But equally there are questions as to the value of local, the identification of what is national, the empowerment of the regional and overall the rooting of business in known factors that can be understood and trusted in the real world.

My vision of the future - Cindy Gallop

How and where we shop, what we do and how much we get paid, how we communicate, what we owe others and why we even work at all are all questions that society, not just businesses, are grappling with because a hi-technology lo-geography world is a long way from a system of industrialisation. In 2017 we are still manufacturing cars for actual people to drive, those people are still commuting to a physical location for work and the working week is basically Monday to Friday still. We are normally paid a monthly salary, attend meetings with other people and plan our business activity and budgeting for resources on an annual planning cycle.

However, at the same time, more and more people are freelancing or working to a temporary contract or project basis, they are working for or with more than one employer, they are doing their own start-ups on the side, they hardly ever have to meet in a physical location because they communicate in groups online, and they aren’t aspiring to own a home in a suburb of a city but to live between two or more global locations at the same time or over time. This is not industrialisation but entrepreneurialism. 

These two systems are co-existing. But it’s as if we are at the end of one system yet still waiting for the next one to fully get up to speed and become the norm. We are playing both games at once and each has a different set of rules. But one of these will win out as the dominant way of doing business over the next 20 years or so.

The era of information

We can expect that scalability is still the ambition of businesses. If you can scale, you can grow. But what we will be scaling will be different from the past. In the past system of industrialisation, the engine of growth was the scalability of production. People in factories were incentivised to produce as much as possible, and the more you could produce the more you could sell, and the cheaper it was to make: economies of scale in products: in an era of production.

But as information technologies grew, and society became less hierarchical and more networked, the game of scale was played out in distribution.

Listen to episode three of the Future Visions podcast - next week's episode will feature the visions of Tracey. Subscribe on iTunes.

If you could start a business and distribute your service to as many people as possible (even if you were initially distributing it for free) there would come a time when there were so many users that you could extinguish your competition and monetise your offer: economies of scale in services: in an era of distribution.

In 2037 what is it that we will need to scale? It won’t be about the scalability of production, or the scalability of distribution. It will be about the scalability of information - or coordination at scale.

Welcome to the Strange Hotel

Bots became the new apps last year when Facebook and others took the concept to the masses by opening up their platforms to third party bots. "By 2020 the average person will have more conversations with bots than with their spouse," predicted Gartner, trying to show the scale of the impact, whilst at the same time normalising it.

Other service sectors are going further than online bots, moving into real world robotics. The 'Hen na Hotel' (or, 'Strange Hotel') in Japan is a hotel almost exclusively staffed by robots, there are only seven humans employed there. The hotel group plan 100 more hotels just like it. In time, our connected living spaces will be more and more immersed in this kind of technology, creating a rich world of conversations, which will include, as Microsoft’s Satya Nadella said, "people to people, people to personal assistants, people to bots, even personal digital assistants calling bots on your behalf". To the extent that brands are working out how to create messages that are appealing to bots, bots will become the new consumer, with plenty of autonomous purchasing power.

We seem to have no problem forming intimate and emotional relationships with AI. Nesta claimed that over one quarter of 18 to 34 year olds in the UK said they would happily date a humanoid robot and Jeff Bezos has already said that Alexa has received more than 250,000 marriage proposals. Professor Yuval Harari recently wrote that: "In a Dataist society I will ask Google to choose. "Listen, Google," I will say, "both John and Paul are courting me. I like both of them, but in a different way, and it’s so hard to make up my mind. Given everything you know, what do you advise me to do?"

Automation and employment prospects

AI is being used to create editorial, to recruit new employees, to write songs, to sit on boards and even to diagnose terminal illness. People are worried that AI will steal jobs and the forecasts are indeed gloomy - a loss of anywhere between 35 and 80 per cent of jobs to automation. One group who should be more worried is women. The World Economic Forum predicts that a robot will take one job for every five given to men but that a robot will take one job for every three given to women. That means that women’s jobs are more in jeopardy than those of men and so businesses today should not just be focussing on closing the present-day gender pay gap between men and women (given extra impetus by the change in UK law requiring businesses to disclose this) but they should be trying to avert the forthcoming pay gap between women and machines altogether so that it does not take hold in the first place.

In my view, the whole discussion is being held on the wrong premise. The question should not be what jobs will be replaced but what decisions will be replaced. Thinking of AI as a companion rather than a substitute is a much more helpful vision of the future. By 2037, we will have outsourced so much of our decision making to AI that we will be freeing ourselves up to carry out other tasks, using newly developed skills. We need to think now about what those might be.

Cybercrime to pre-crime

When work becomes truly 'lo-geography hi-technology' and massive co-ordination of data is possible, we will see the era of information give rise to the prospect of prediction.

Take the area of policing and crime. The resources in this force, like any public service are stretched too thin across a growing and needy population. Would it be best to wait until criminals are caught in a criminal act that costs the taxpayer, insurers and others a small fortune? Or would it be better to forecast the likelihood of a crime and try to prevent it from happening - and therefore prevent it costing anything at all? In a world in which everything can be tracked, monitored, analysed and scrutinised it may be incumbent on public services - and private enterprises - to invest in the crime prediction game. It may be that the only way to fight crime, so much of which will be automated by then – will be to forecast it, and an industry will spring up that is about tracking behaviours, pattern recognition and anomaly spotting that suggests crime before it has occurred - cybercrime 'pre-crime'. And if a company has not invested in all of these elements and is hit or hacked to the detriment of its business or the needs of its customers, the business will be liable for penalties. People will say, 'well it could easily have been forseen'.

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Assistance to advice

Working out human intent will become instinctual for AI and the business of search in particular will become the business of prediction. Using voice data, contextual data and other personal data provided in the past as well as the present, personal assistants will be doing more than just assisting, they will be predicting. In this sense, search will shift from answering to inspiring, and users will receive suggestions for things that they hadn’t even realised they had wanted. It is safe to say that there will be a burgeoning industry called 'advice'. From social networks, to hospitality to insurance, any business that can employ machine learning and can co-ordinate data at scale will become 'advisory'.

Retailers too will become more sophisticated at predicting consumer spending patterns and gauge stock levels accordingly. In fact, it is more likely that they will not have any stock, and will call on their suppliers to create or deliver it in a 'just-in-time' manner. Once a retailer’s physical stores are better connected to their digital store, there is no reason for stores to stock anything, and we’ll see the rise of stockless stores that create a service-led experience but don’t require you to walk away with a bagful of heavy items. The physical store may well become a place one enters carrying one’s digital footprint, and a place we go to for nothing but advice.

Marketing to educating

If business can predict what skills are required and also that they will be scarce, it is the responsibility of businesses to create the educational environment in which they can be nurtured. We can already see glimpses of this now. The Dyson Institute of Technology plans to double its engineering workforce to 6,000 by 2020 and Sir James Dyson plans to invest £15m in the institute over the next five years. Students will not pay fees, and receive a salary of up to £16,000 per year. "The UK’s skills shortage is holding Dyson back as we look to increase the amount of technology we develop and export. We are taking matters into our own hands," states Sir James Dyson. In some ways it echoes the past of Cadbury’s Bourneville or Unilever’s Port Sunlight, who also needed skilled workers to ensure they weren’t left behind. And now a return to investing in and educating the skills and talents of the future will take on renewed importance. Decision-making and negotiation become less important human skills, given that these can be outsourced to AI. And feminine traits such as emotional intelligence, empathy, vulnerability and intuition will become the future human drivers of businesses that are delivering intuitive advice, preparedness and prediction.

How to prepare yourself for change...

  1. If businesses are to operate in the era of prediction, then they themselves will need to re-think the basic tools of business. For years we have been sold on the idea of a five-year plan but actually that is becoming less and less useful: the mid term is over. Businesses are now focusing on two time horizons to achieve growth: the long term vision and the short term activation.
  2. One thing businesses in 2037 will be doing a lot more of than they do today is preparing. More and more business schools are teaching strategic foresight and futures studies, and more and more companies are hiring futures consultants - either in house or for learning and development at an organisational level. In addition, entrepreneurs are taking on board foresight models to work out their own personal futures.
  3. Investing in R&D should include end users, turning your Lab into more of a Clinic. Not just collaborating with other partners, but involving the users of the future in the development of new to market products and services are all signifiers of 21st Century innovation. If you are developing ‘advisory’ services that require AI, machine learning, speech recognition, and emotional data the success of your service is dependent upon outstanding user experience not just traditional product, price or promotion. Reconsider the need for a Chief Innovation Officer as this emergent approach falls under the remit of the Chief Prediction Officer.


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