• If we are to rely on machine intelligence, we need to understand the two types of knowledge.
  • Understanding knowledge means we can distinguish where we want machines to do the mundane work and where we want humans to perform intuitive tasks.
  • Such an approach will be as beneficial for business as for education.

As virtual and physical worlds become increasingly interdependent, knowledge – and how we manage it – will become the secret ingredient to manage the situation. And thrive.

Virtual technologies are swiftly becoming intertwined with our physical world, and companies need to adapt. But that doesn’t simply mean replacing humans with robots or relying on artificial intelligence (AI) to make all of our decisions.

This is because technology, though powerful, is just part of the equation. In fact, human intelligence will be one of the most valuable assets in today's Fourth Industrial Revolution (FIR), and companies may flounder if they fail to strike the right balance of automated technology and human insights.

This comes down to knowledge management. When leading teams of both humans and machines, executives need to understand the two major types of knowledge – implicit and tacit – and how to utilise each type best.

How have we got here?

"The Fourth Industrial Revolution creates a world in which virtual and physical systems of manufacturing cooperate with each other in a flexible way at the global level,” wrote Founder and Executive Chairman of the World Economic Forum Klaus Schwab in his 2016 book The Fourth Industrial Revolution.

In the same book, he coined the very term, writing: "We are at the beginning of a revolution that is fundamentally changing the way we live, work and relate to one another.”

Like the previous three industrial revolutions, the FIR will fundamentally change the way we live and how businesses operate. Preceding revolutions have brought us everything from steam engines and mechanisation, to electricity and mass production. Most recently, the third added digitalisation and computers into the mix.

The FIR it is already inspiring seismic shifts across many industries. Critically, it will see the convergence of our physical experiences with rapidly advancing technologies, such as AI, machine learning, virtual and augmented reality, robotics, bio-engineering and cloud computing.

It will blur the boundaries between the online and offline, the technological and the biological – think real-time automated speech recognition, disaster rescue drones, genome editing, and AI-powered customer service chatbots.

While many describe the FIR as a virtual revolution, that’s only half the story. At its heart, the FIR is also a knowledge revolution – going forward, we will rely on a combination of human and machine intelligence to create truly transformative businesses, services and products.

Do you really know what knowledge is?

To succeed during the FIR, business leaders first need to understand how knowledge works. In a nutshell, there are two types: explicit and tacit.

Explicit knowledge can be easily articulated, quantified, codified, shared and programmed. For example: company manuals, research reports, white papers, how-to videos and data sets. They are programmed into routine tasks and procedures, and then assigned to machines.

The two types of knowledge and the areas they house
Image: Rocket Source

By contrast, tacit knowledge is much harder to pin down. It’s intangible, ranging from insights gained through personal experiences to accumulated expertise and even basic instincts.

For instance, a veteran sales representative may naturally sense that they can close a deal, while a doctor may have a gut instinct to order a diagnostic test for a disease that doesn’t match a patient’s symptoms.

Humans can easily pass explicit knowledge to machines, but it is significantly more challenging, if not impossible, for a machine to internalise and replicate tacit knowledge.

That said, tacit knowledge does not have to exist in a silo.

We can capture some tacit knowledge through interviews, training, mentorship, workshops, and forums. A company can then transcribe, analyse and organise the insights using AI speech recognition software to create a valuable bank of institutional knowledge and train new employees.

Managing knowledge will dictate business success

How we manage knowledge will impact every aspect of business operations, from route procedures to training, high-level decision-making and customer service. Naturally, many people have resisted the FIR, fearing that robots or automation will render humans redundant. But in reality, only the nature of our roles will change.

Over the last 15 years, technology eliminated 800,000 jobs in the UK, yet created 3.5 million new positions. Notably, these new jobs paid £10,000 more per year on average than those that were lost, adding some £140 billion to the UK economy, according to a study by Deloitte UK.

AI and machines took over routine, repetitive tasks informed by tacit knowledge, elevating humans to positions that required intelligence, creativity, experience, instinct and talent – implicit knowledge.

Of course, knowledge management takes different forms depending on the industry. For example, in banking, companies have already automated routine processes like deposits, transfers, and even common customer service inquiries.

Meanwhile, humans handle high-level transactions and complicated customer service issues.

Trading has followed a similar trajectory. While machines can handle basic trades, analysts with extensive tacit knowledge manage complex trading strategies and input the actual data points – what, when and how much to buy and sell – to programme trading algorithms in the first place.

Managing knowledge in education

In the education field, there’s also massive potential for better knowledge management.

Schools could potentially automate learning objectives that revolve around explicit knowledge – be that multiplication tables or chemistry principles – as well as administrative tasks, paperwork, lesson planning, inventory management and prep work.

This would then free up overworked teachers so they could focus on more intuitive tasks, such as fostering critical thinking, creativity, personal feedback, practical training, coaching, mentorship and real-world career training.

Conversely, the healthcare industry depends on tacit knowledge – it is incredibly complicated to codify years of medical training as many symptoms, diagnoses, treatments do not follow expected patterns. And the cost of bad data is human lives

However, AI could be applied to diagnostics. For example, humans can train machines to read test results and X-rays and then offer a preliminary diagnosis before a human doctor makes a treatment recommendation.

No matter the industry, if business leaders truly understand and manage tacit and explicit knowledge, they will be able to optimise their operations, create better products and services, and ultimately thrive during the Fourth Industrial Revolution.

James Lin holds a Ph.D. degree from the Massachusetts Institute of Technology with a concentration in integrated energy, economic, and environmental modelling.