By Mark Skilton

We take for granted many of the technological advances of recent years. We listen to music streaming on our wireless devices with barely a second thought.

We Skype or FaceTime family, friends and colleagues thousands of miles away with devices that fit comfortably into our pockets. We barely raise an eyebrow when our favourite stores target us with offers that seem telepathic in their accuracy.

Yet all of these activities are marvels of connectivity and automation requiring multiple networks and technologies. The streaming music, for example, relies on Wi-Fi to the local home network that passes through an internet gateway through the Internet Service Provider (ISP) and to the music streaming service hosted on the subscribed service cloud datacentre. The return connection passes from the mobile phone to the Bluetooth device in milliseconds.

In the background, the smartphone is also managing its battery energy through algorithms that make localised decisions to optimise battery life and update GPS location tracking. And on and on it goes.

If we choose to move to another room or building, the connection automatically switches to an available mobile cellular connection service provider and the music continues uninterrupted. All the while the mobile application is making recommendations alongside each music track, suggesting alternative artists to suit the listener’s musical tastes, using matching techniques that rely on so-called machine learning. 

This is just a tiny example of what machines are now capable of. Machine learning is the term on everyone’s lips at the moment (along with its close relative Artificial Intelligence). So what is machine learning and why is everyone getting so animated about it?

Machine learning is a field of computer science that uses statistical techniques to provide feedback loops that give computer systems the ability to progressively improve their performance of a given task – in other words to effectively “learn” over time. This has huge implications for other technologies too.

Inventions previously only imagined in science fiction, such as virtual and augmented reality, 3D printing, robotics, blockchain, quantum computing, nanotechnology and bioengineering are now a reality - changing how materials, money, products and services are made, exchanged and consumed.

The World Economic Forum (WEF) has named these technologies collectively as the fourth industrial revolution because they represent a new paradigm, changing productivity through automation.

WEF founder Klaus Schwab described it as a culmination of emerging technologies, arguing that this revolution is different in scale, scope and complexity from any that have come before.

It is characterised by a range of new technologies that are integrating the physical, digital and biological worlds, affecting all disciplines, economies, industries and governments, and even challenging ideas about what it means to be human.

Already, they are changing how we live, work and consume through new industry processes, smart cities, connected homes, driverless cars, wearable devices, and new approaches to healthcare. In the future, they will disrupt and reinvent business, jobs and every other aspect of our lives.

So how can you position your business to survive and thrive in this brave new world?

There are four key lessons:

 

1 Long time coming

The first thing to say is that the concept of the thinking machine is not new – its origins can be traced all the way back to the Second World War and the likes of Alan Turing, deciphering the Enigma code at Bletchley Park. (Most of the new technologies of the fourth industrial revolution are hidden in plain view if you know where to look.)

The term machine learning was coined by Arthur Samuel as long ago as 1959, and evolved from pattern recognition combined with AI.

Machine learning uses algorithms that can learn from and make predictions based on data and is now used in a growing number of applications – everything from predicting what you might want to buy from Amazon to using facial identification to screen for terrorists at airports or hooligans at football matches. It is the ability to improve performance rapidly – and process data much faster than the human brain – that excites the techies.

But the world didn’t change over night: many of the breakthrough technologies that underpin the fourth industrial revolution have origins that can be traced back through several evolutionary steps before moving into the mainstream. The big difference now is that these technologies have reached critical mass. They are acting in unison.  

 

2 Commercial fusion

It is important to take a holistic view. Machine learning should not be seen in isolation. It is not the only show in town. A cluster of new (and not so new) technologies is entering the mainstream at the same time. These include: cloud computing multisided platforms, the Internet of Things (IoT), virtual and augmented reality, blockchain, and nanotechnology, to name but a few. What we are witnessing is the coming together of these technologies.

The technological and commercial planets are now aligned. It is the ‘fusion’ of the physical, digital, and biological – through the integration of existing technologies that is powering the new revolution. The companies that win will be the ones that integrate them most imaginatively and effectively.

For example, 3D printing, also called additive manufacturing, represents a new digital to physical fusion of technology, printing and materials design and fabrication.

It originated from stereolithography dating back to 1986. The speed and choice of materials are increasing rapidly to a stage where 3D printing machinery is now embedded into mainstream flexible and reconfigurable manufacturing processes, including General Electric printing jet engine parts and medical breakthroughs for human tissues.

Biological fusion is also coming of age. Miniaturised IoT sensors can be attached to the human body, ingested or integrated with organs, enabling biological monitoring and augmentation.

These devices now play a vital role in mHealth and eHealth solutions, including mobile monitoring and measurement of medical and wellbeing status. Biological fusion also includes plant, animal and biosphere monitoring used in automated agriculture and hydroponics.

 

3 Think big, but also think small

The revolution is at the macro and micro levels. There’s been a lot of talk about big data and the ability of machines to crunch huge amounts of data. When coupled with supercomputers, this treasure trove of data will provide unprecedented ‘big picture’ insights.

But the fourth paradigm is just as much about ‘small data’ – personalised information about an individual, and the ability to conduct commerce on a one-to-one basis.

Today, for example, the combination of cloud computing and digital platforming strategies, such as the multi-sided platforms (MSPs) that can service multiple markets and customer sizes, as well as facility sharing and co-selling of the platform, is changing the face of business. 

Commerce is being democratised through a multitude of platforms, from eBay and Alibaba, to Uber, PayPal and Stripe, and social media platforms like Facebook and Twitter. Even small community platforms are getting in on the act, enabling the residents of a small town or village to buy and sell goods and services virtually.

This is the shift to the so-called ‘gig-economy’, which relies on massive networked marketplace infrastructure for exchange, collaboration and trading.

It is now possible to conduct business one-to-one with individuals on the other side of the world without the requirement of an international company or bank. Fuelling this market are ubiquitous technologies such as smartphones and apps that allow a readily available platform for on-demand with pay-as-you-go services.

 

4 New questions  

The final point to realise is that the fourth industrial revolution doesn’t only pose technological conundrums; it asks new questions about how we manage our organisations and communities – and society as a whole.

The new kinds of automation made possible by advances in AI and the other technologies require a re-evaluation of leadership and new ways of thinking.

The opportunities made possible by the fourth industrial revolution are as infinite as the human imagination. We are fortunate to live in such exciting times, but the opportunities also carry threats – even for the winners.

Concerns about cybersecurity have become a major crosscutting feature of fourth industrial era technology and will continue to be. And we are only just beginning to consider the ethical dilemmas new technologies pose for issues such as privacy, public safety, genetic engineering, jobs, incomes and inequality.

The leaders of Facebook, Uber, Google and Tesla have all found themselves in the dock of public opinion lately, answering questions about everything from the use of personal data, to fatalities caused by driverless cars. They will not be the last business leaders to feel the heat from the fourth industrial revolution.

Mark Skilton, Professor of Practice of Information Systems & Management, teaches Business Consulting on the Undergraduate programme and is Industry Director of the AI Innovation Network.

Follow Mark Skilton on Twitter @mskilton.

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