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Fears about the impact of technology on jobs are not new. Over the past few years, the debate has been reignited by evidence of computers substituting for a number of jobs, most notably bookkeepers, cashiers and telephone operators. The reasons why the new technology revolution will provoke more upheaval than the previous industrial revolutions are those already mentioned in the introduction: speed everything is happening at a much faster pace than ever before , breadth and depth so many radical changes are occurring simultaneously , and the complete transformation of entire systems.

In light of these driving factors, there is one certainty: New technologies will dramatically change the nature of work across all industries and occupations. The fundamental uncertainty has to do with the extent to which automation will substitute for labour. How long will this take and how far will it go? To get a grasp on this, we have to understand the two competing effects that technology exercises on employment.

First, there is a destruction effect as technology-fuelled disruption and automation substitute capital for labour, forcing workers to become unemployed or to reallocate their skills elsewhere. As human beings, we have an amazing ability for adaptation and ingenuity. But the key here is the timing and extent to which the capitalization effect supersedes the destruction effect, and how quickly the substitution will take. There are roughly two opposing camps when it comes to the impact of emerging technologies on the labour market: those who believe in a happy ending — in which workers displaced by technology will find new jobs, and where technology will unleash a new era of prosperity; and those who believe it will lead to a progressive social and political Armageddon by creating technological unemployment on a massive scale.

History shows that the outcome is likely to be somewhere in the middle. The question is: What should we do to foster more positive outcomes and help those caught in the transition? It has always been the case that technological innovation destroys some jobs, which it replaces in turn with new ones in a different activity and possibly in another place. Take agriculture as an example.

This dramatic downsizing took place relatively smoothly, with minimal social disruption or endemic unemployment. The app economy provides an example of a new job ecosystem.

It only began in when Steve Jobs, the founder of Apple, let outside developers create applications for the iPhone. The techno-optimists ask: If we extrapolate from the past, why should it be different this time? They acknowledge that technology can be disruptive but claim that it always ends up improving productivity and increasing wealth, leading in turn to greater demand for goods and services and new types of jobs to satisfy it.

The substance of the argument goes as follows: Human needs and desires are infinite so the process of supplying them should also be infinite. Barring the normal recessions and occasional depressions, there will always be work for everybody.

The early signs point to a wave of labour-substitutive innovation across multiple industries and job categories which will likely happen in the coming decades. Labour substitution Many different categories of work, particularly those that involve mechanically repetitive and precise manual labour, have already been automated.

Many others will follow, as computing power continues to grow exponentially. Sooner than most anticipate, the work of professions as different as lawyers, financial analysts, doctors, journalists, accountants, insurance underwriters or librarians may be partly or completely automated.

So far, the evidence is this: The fourth industrial revolution seems to be creating fewer jobs in new industries than previous revolutions. This is corroborated by a recent US Economic Census, which sheds some interesting light on the relationship between technology and unemployment.

It shows that innovations in information and other disruptive technologies tend to raise productivity by replacing existing workers, rather than creating new products needing more labour to produce them. In addition, the trend is towards greater polarization in the labour market. Employment will grow in high-income cognitive and creative jobs and low-income manual occupations, but it will greatly diminish for middle-income routine and repetitive jobs.

This job simplification means that algorithms are better able to replace humans. Discrete, well-defined tasks lead to better monitoring and more high-quality data around the task, thereby creating a better base from which algorithms can be designed to do the work.

In thinking about the automation and the phenomenon of substitution, we should resist the temptation to engage in polarized thinking about the impact of technology on employment and the future of work. But this does not mean that we face a man-versus-machine dilemma. In fact, in the vast majority of cases, the fusion of digital, physical and biological technologies driving the current changes will serve to enhance human labour and cognition, meaning that leaders need to prepare workforces and develop education models to work with, and alongside, increasingly capable, connected and intelligent machines.

Impact on skills In the foreseeable future, low-risk jobs in terms of automation will be those that require social and creative skills; in particular, decision-making under uncertainty and the development of novel ideas.

This, however, may not last. Consider one of the most creative professions — writing — and the advent of automated narrative generation.

Sophisticated algorithms can create narratives in any style appropriate to a particular audience. The content is so human-sounding that a recent quiz by The New York Times showed that when reading two similar pieces, it is impossible to tell which one has been written by a human writer and which one is the product of a robot.

These trends vary by industry and geography, and so it is important to understand the industry and country-specific outcomes of the fourth industrial revolution.

As Figure 1 shows, survey respondents believe that complex problem solving, social and systems skills will be far more in demand in when compared to physical abilities or content skills.

The report finds that the next five years are a critical period of transition: the overall employment outlook is flat but there is significant job churn within industries and skill churn within most occupations. While wages and work-life balance are expected to improve slightly for most occupations, job security is expected to worsen in half of the industries surveyed. It is also clear that women and men will be affected differently, potentially exacerbating gender inequality see Box A: Gender Gaps and the Fourth Industrial Revolution.

First, at the current pace of progress, it will take another years before economic gender parity is achieved around the world. Second, progress towards parity is remarkably slow, and possibly stalling.

In light of this, it is critical to consider the impact of the fourth industrial revolution on the gender gap. How will the accelerating pace of change in technologies that span the physical, digital and biological worlds affect the role that women are able to play in the economy, politics and society? An important question to consider is whether female-dominated or male- dominated professions are more susceptible to automation. Losing a job has negative effects in many circumstances, but the cumulative effect of significant losses across whole job categories that have traditionally given women access to the labour market is a critical concern.

Specifically, it will put at risk single-income households headed by low- skilled women, depress total earnings in two-income families, and widen the already-troubling gender gap around the world. But what about new roles and job categories? What new opportunities could exist for women in a labour market transformed by the fourth industrial revolution? While it is difficult to map the competencies and skills expected in industries not yet created, we can reasonably assume that demand will increase for skills that enable workers to design, build and work alongside technological systems, or in areas that fill the gaps left by these technological innovations.

Because men still tend to dominate computer science, mathematical and engineering professions, increased demand for specialized technical skills may exacerbate gender inequalities. Yet demand may grow for roles that machines cannot fulfil and which rely on intrinsically human traits and capabilities such as empathy and compassion. Women are prevalent in many such occupations including psychologists, therapists, coaches, event planners, nurses and other providers of healthcare.

A key issue here is the relative return on time and effort for roles requiring different technical capabilities, as there is a risk that personal services and other currently female-dominated job categories will remain undervalued. This would be a negative outcome of the fourth industrial revolution, as it would increase both inequality overall and the gender gap, making it more difficult for women to leverage their talents in the workforce of the future.

Many of the traits and capabilities traditionally associated with women and female professions will be much more needed in the era of the fourth industrial revolution. While we cannot predict the different impact on men and women that the fourth industrial revolution will have, we should take the opportunity of a transforming economy to redesign labour policies and business practices to ensure that both men and women are empowered to their full extent.

Today, we cannot foresee exactly what these will be but I am convinced that talent, more than capital, will represent the critical production factor. For this reason, scarcity of a skilled workforce rather the availability of capital is more likely to be the crippling limit to innovation, competiveness and growth. Traditional definitions of skilled labour rely on the presence of advanced or specialised education and a set of defined capabilities within a profession or domain of expertise. Given the increasing rate of change of technologies, the fourth industrial revolution will demand and place more emphasis on the ability of workers to adapt continuously and learn new skills and approaches within a variety of contexts.

As a consequence, there is a mismatch between the magnitude of the upcoming changes and the relatively marginal actions being taken by companies to address these challenges. Organizations require a new mindset to meet their own talent needs and to mitigate undesirable societal outcomes. Impact on developing economies It is important to reflect upon what this might mean for developing countries. As yet, the precise impact of the fourth industrial revolution remains to be seen.

In recent decades, although there has been a rise in inequality within countries, the disparity across countries has decreased significantly.

Does the fourth industrial revolution risk reversing the narrowing of the gaps between economies that we have seen to date in terms of income, skills, infrastructure, finance and other areas? Or will technologies and rapid changes be harnessed for development and hasten leapfrogging?

These difficult questions must be given the attention they require, even at a time when the most advanced economies are preoccupied with their own challenges. Ensuring that swathes of the globe are not left behind is not a moral imperative; it is a critical goal that would mitigate the risk of global instability due to geopolitical and security challenges such as migration flows. If this pathway closes, many countries will have to rethink their models and strategies of industrialization.

Whether and how developing economies can leverage the opportunities of the fourth industrial revolution is a matter of profound importance to the world; it is essential that further research and thinking be undertaken to understand, develop and adapt the strategies required. The danger is that the fourth industrial revolution would mean that a winner- takes-all dynamic plays out between countries as well as within them.

This would further increase social tensions and conflicts, and create a less cohesive, more volatile world, particularly given that people are today much more aware of and sensitive to social injustices and the discrepancies in living conditions between different countries.

It is crucial that people are secure in the belief that they can engage in meaningful work to support themselves and their families, but what happens if there is insufficient demand for labour, or if the skills available no longer match the demand?

Today, the on-demand economy is fundamentally altering our relationship with work and the social fabric in which it is embedded. Professional activities are dissected into precise assignments and discrete projects and then thrown into a virtual cloud of aspiring workers located anywhere in the world.

This is the new on-demand economy, where providers of labour are no longer employees in the traditional sense but rather independent workers who perform specific tasks. As human cloud platforms classify workers as self-employed, they are — for the moment — free of the requirement to pay minimum wages, employer taxes and social benefits.

Some independent workers see this as offering the ideal combination of a lot of freedom, less stress and greater job satisfaction. Although the human cloud is in its infancy, there is already substantial anecdotal evidence that it entails silent offshoring silent because human cloud platforms are not listed and do not have to disclose their data. Is this the beginning of a new and flexible work revolution that will empower any individual who has an internet connection and that will eliminate the shortage of skills?

Or will it trigger the onset of an inexorable race to the bottom in a world of unregulated virtual sweatshops? If the result is the latter — a world of the precariat, a social class of workers who move from task to task to make ends meet while suffering a loss of labour rights, bargaining rights and job security — would this create a potent source of social unrest and political instability?

Finally, could the development of the human cloud merely accelerate the automation of human jobs? The challenge we face is to come up with new forms of social and employment contracts that suit the changing workforce and the evolving nature of work. We must limit the downside of the human cloud in terms of possible exploitation, while neither curtailing the growth of the labour market nor preventing people from working in the manner they choose.

It entirely depends on the policy and institutional decisions we make. One has to be aware, however, that a regulatory backlash could happen, thereby reasserting the power of policymakers in the process and straining the adaptive forces of a complex system.

The importance of purpose We must also keep in mind that it is not only about talent and skills. Technology enables greater efficiency, which most people want. Yet they also wish to feel that they are not merely part of a process but of something bigger than themselves. This is particularly the case for the younger generation who often feel that corporate jobs constrain their ability to find meaning and purpose in life.

In a world where boundaries are disappearing and aspirations are changing, people want not only work-life balance but also harmonious work-life integration. I am concerned that the future of work will only allow a minority of individuals to achieve such fulfilment. There is no doubt that emerging technologies, almost always powered and enabled by digital capabilities, are increasing the speed and scale of change for businesses. This also reinforces an underlying theme in my conversations with global CEOs and senior business executives; namely, that the deluge of information available today, the velocity of disruption and the acceleration of innovation are hard to comprehend or anticipate.

They constitute a source of constant surprise. Is there evidence of the organization and leadership capacity to learn and change?

Is there a track record of prototyping and investment decision-making at a fast pace? Does the culture accept innovation and failure? Everything I see indicates that the ride will only get faster, the changes will be fundamental, and the journey will therefore require a hard and honest look at the ability of organizations to operate with speed and agility. Sources of disruption Multiple sources of disruption trigger different forms of business impact. Examples abound.

New storage and grid technologies in energy will accelerate the shift towards more decentralized sources. The widespread adoption of 3D printing will make distributed manufacturing and spare-part maintenance easier and cheaper. Real-time information and intelligence will provide unique insights on customers and asset performance that will amplify other technological trends.

Disruption also flows from agile, innovative competitors who, by accessing global digital platforms for research, development, marketing, sales and distribution, can overtake well established incumbents faster than ever by improving the quality, speed or price at which they deliver value.

This is the reason why many business leaders consider their biggest threat to be competitors that are not yet regarded as such. It would be a mistake, however, to think that competitive disruption will come only through start- ups. Digitization also enables large incumbents to cross industry boundaries by leveraging their customer base, infrastructure or technology.

The move of telecommunications companies into healthcare and automotive segments are examples. Size can still be a competitive advantage if smartly leveraged. Major shifts on the demand side are also disrupting business: Increasing transparency, consumer engagement and new patterns of consumer behaviour increasingly built upon access to mobile networks and data force companies to adapt the way they design, market and deliver existing and new products and services.

Overall, I see the impact of the fourth industrial revolution on business as an inexorable shift from the simple digitization that characterized the third industrial revolution to a much more complex form of innovation based on the combination of multiple technologies in novel ways. This is forcing all companies to re-examine the way they do business and takes different forms.

For some companies, capturing new frontiers of value may consist of developing new businesses in adjacent segments, while for others, it is about identifying shifting pockets of value in existing sectors. The bottom line, however, remains the same. Business leaders and senior executives need to understand that disruption affects both the demand and supply sides of their business. In short, they have to innovate continuously.

Four major impacts The fourth industrial revolution has four main effects on business across industries: — customer expectations are shifting — products are being enhanced by data, which improves asset productivity — new partnerships are being formed as companies learn the importance of new forms of collaboration, and — operating models are being transformed into new digital models. Customer expectations are being redefined into experiences. The Apple experience, for example, is not just about how we use the product but also about the packaging, the brand, the shopping and the customer service.

Apple is thus redefining expectations to include product experience. Traditional approaches to demographic segmentation are shifting to targeting through digital criteria, where potential customers can be identified based on their willingness to share data and interact. As the shift from ownership to shared access accelerates particularly in cities , data sharing will be a necessary part of the value proposition. For example, car- sharing schemes will require the integration of personal and financial information across multiple companies in the automotive, utility, communications and banking sectors.

Most companies profess to be customer-centric, but their claims will be tested as real-time data and analytics are applied to the way they target and serve their customers. Today, data and metrics deliver in quasi-real time critical insights into customer needs and behaviours that drive marketing and sales decisions.

This trend of digitization is currently towards more transparency, meaning more data in the supply chain, more data at the fingertips of consumers and hence more peer-to-peer comparisons on the performance of products that shift power to consumers.

As an example, price-comparison websites make it easy to compare prices, the quality of service, and the performance of the product.

In a mouse click or finger swipe, consumers instantaneously move away from one brand, service or digital retailer to the next. Companies are no longer able to shirk accountability for poor performance.

Brand equity is a prize hard won and easily lost. This will only be amplified in a more transparent world. To a large extent, the millennial generation is setting consumer trends. It is a world of the now: a real-time world where traffic directions are instantly provided and groceries are delivered directly to your door. It would be a mistake to assume that this is confined to high-income economies.

Take online shopping in China. Tesla, for example, shows how over-the-air software updates and connectivity can be used to enhance a product a car after purchase, rather than let it depreciate over time. Not only are new materials making assets more durable and resilient but data and analytics are also transforming the role of maintenance. Analysis provided by sensors placed on assets enables their constant monitoring and proactive maintenance and, in doing so, maximizes their utilization.

It is no longer about finding specific faults but rather about using performance benchmarks based on data supplied by sensors and monitored through algorithms that can highlight when a piece of equipment is moving outside its normal operating window.

On aircrafts, for example, the airline control centres know before the pilots do if an engine is developing a fault on a particular plane. They can therefore instruct the pilot on what to do and mobilize the maintenance crew in advance at the flight destination.

In addition to maintenance, the ability to predict the performance of an asset enables new business models to be established. Asset performance can be measured and monitored over time — analytics provide insights on operational tolerances and provide the basis for outsourcing products that are not core or strategic to the needs of the business.

SAP is an example of a company that is leveraging data from physical products embedded in agriculture to increase uptime and utilization.

The ability to predict the performance of an asset also offers new opportunities to price services. Take the example of truck fleets. Long-distance haulers are interested in propositions where they pay tire manufacturers by the 1, kilometres of road use rather than periodically buying new tires.

This is because the combination of sensors and analytics enables tire companies to monitor driver performance, fuel consumption and tire wear to offer a complete end-to-end service. This is true for incumbents and established businesses but also for young, dynamic firms.

The former often lack specific skills and have lower sensitivity to evolving customer needs, while the latter are capital poor and lack the rich data generated by mature operations. This partnership gives Siemens access to a partner that can help solve complex challenges of extracting insights from vast data, while Ayasdi can validate its topological data analysis approach with real-world data, while expanding market presence.

Such collaborations, however, are often far from straightforward. They require significant investment from both parties to develop firm strategy, search for appropriate partners, establish communication channels, align processes, and flexibly respond to changing conditions, both inside and outside the partnership. The first edition of the novel was published in April 12th , and was written by Lin-Manuel Miranda.

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