
Our workplaces are becoming more attuned to human wellbeing, and more nimble to its requirements – in large part due two things: One, the growing body of evidence-based research being conducted to support design-led wellbeing initiatives; and two – the wide-reaching impact of technology.
In its most recent quarterly report, the McKinsey Global Institute, business and economics research arm of the global management consulting firm McKinsey & Company, tackled the topic, “Tech for Good: Smoothing disruption, improving wellbeing.”
The 80-page report offers its readers a wealth of data-driven insights into the limitless ways technology touches our lives today.
It examines six wellbeing themes that are most frequently discussed in the context of technology adoption: job security, material living standards, health, education, environmental sustainability, and equal opportunities – “areas in which technology could potentially be disruptive and create problems but can also be used to mitigate those same risks and add significantly to welfare. They are also areas where existing use cases illustrate the potential of technology to ‘do good.’”
The first theme, “Job Security” deals directly with the future of work, and we have excerpted it below. The remaining five themes are equally compelling – offering a broad-scale view of topics those in workplace design encounter daily. We encourage our readers to explore the full report. However, if you’re pressed for time, we have also excerpted the report’s summary. Happy November, and enjoy!
Excerpt: “Tech for Good: Smoothing disruption, improving wellbeing – Summary”
“The development and adoption of advanced technologies including smart automation and artificial intelligence has the potential not only to raise productivity and GDP growth but also to improve well-being more broadly, including through healthier life and longevity and more leisure. To achieve these benefits – and reduce disruption and potentially destabilizing effects on society – will require an emphasis on innovation-led growth and careful management of the workforce and other transitions related to technology adoption and diffusion.”
“Technology has no overall purpose on its own; its effects are driven by human choices and actions. History is filled with examples of its potential both to do good and to cause harm: electricity brought substantial productivity gains, but also long transitions from agriculture to industry that were accompanied at times by stagnating real wages. Once-thriving manufacturing and mining towns have been depleted by the shift to a services-based economy.
How different will automation and AI be as they build on now-ubiquitous digital technologies? These technologies could displace some jobs but also improve work when technology is used to complement human capabilities. They could cause stress by increasing the intensity of work but also improve health and longevity if their uses include breakthroughs in personalized medicine and better disease prevention. Their deployment will require new skills but could also help make education more accessible. They consume large quantities of energy even as they help make homes, offices, and vehicles more fuel-efficient. Automation may bring heightened risks of unemployment and social change – and has already contributed to the wage polarization between high-skill and low-skill workers. Robotics deployed since the 1980s have raised productivity and changed the workplace, while at the same time creating new jobs elsewhere.
In short, technology will not improve lives on its own: it will need a development agenda for policy makers and business leaders that mitigates some of the downside effects of technology adoption, both in the short and longer term.
This discussion paper, the latest in our ongoing research on the impact of technology on business and society, is an attempt to understand both the positive and negative effects in more detail and to examine and evaluate ways in which new and mostly digital and smart technologies could potentially enhance welfare and soften disruptive transitions in advanced economies.
For the research, we compiled a library of about 600 use cases of technology applications that contribute to well-being, especially in relation to key societal challenges such as job security, health, and equal opportunities. More than 60 percent of these cases use some AI capabilities. We then developed a comprehensive welfare model of technology adoption that quantifies technology impacts beyond pure GDP. It incorporates critical dimensions of inequality, risk aversion to unemployment, leisure, and health and longevity, building on recent economic literature on welfare and well-being. Using this model, we conducted a simulation of welfare outcomes that enables us to compare the contribution of the new generation of technologies to previous generations and to identify key priorities for moving toward what we call a “Tech for better lives” outcome. Our preliminary insights from this exercise include the following:
- >Technology is not intrinsically good or bad, but it can produce positive or negative outcomes – and often both – depending on how it is used. It affects different parts of the population unequally. In general, actions by business leaders and policy makers need to accompany technological innovations to ensure that the overall effects, and how they are distributed, create a positive balance.
- >While technology adoption may be disruptive in the short term, especially to jobs and incomes, our library of applications (use cases) highlights a variety of ways in which technology itself can help smooth those disruptions and preempt risks. For example, online training programs and job-matching digital platforms can help workers improve skills and find employment, while mobile payments for financial access and online marketplaces that reduce prices of goods and services can positively affect material living standards. Other socially beneficial use cases include adaptive-learning applications to better prepare young people for the labor market, AI-powered drug discovery and personalized medicine for longer and healthier lives, and clean technologies for environmental sustainability.
- >While technology has been a significant contributor to welfare growth in Europe and the United States in the past 40 years, our modeling suggests that, for the next decade, welfare growth may continue on the same trajectory only to the extent that new frontier technology adoption is focused on innovation-led growth rather than purely on labor reduction and cost savings through automation, and that technology diffusion is actively accompanied by transition management that increases workers’ mobility and equips them with new skills. Other measures may also be needed to ensure a successful transition, potentially including support for wages. For all its potential, technology that enhances wellbeing is a tool kit that cannot address all the issues on its own.
- >A first attempt to estimate the approximate monetary value of a scenario in which proactive management smooths transitions related to technology adoption and innovation-driven growth suggests that the potential boost to welfare – the sum of GDP and additional well-being components – can be between 0.5 and 1 percent per year in Europe and United States by 2030. This is as much as double the incremental growth from technology that we have modeled under an average scenario. Other scenarios that pay less heed to managing transitions or boosting innovation could slow income growth, increase unemployment risk, and lead to fewer improvements in leisure, health, and longevity.
- >Government and business have important roles to play in ensuring good outcomes. The public sector can help drive innovation and improve welfare by supporting research and development including in health, spurring technology adoption through procurement practices and progressive regulation, and ensuring retraining and transition support for workers coping with workplace disruption. Business can focus technology deployment on new products, services, and markets, augment the skills of the workforce including with technological solutions, and increase worker mobility by creating new career paths, among other steps. They can also prioritize technology solutions that simultaneously improve their bottom line and the outcomes for society.
This paper is aimed at stimulating discussion about the opportunities and challenges surrounding technology adoption and how technology itself could help mitigate negative outcomes. This is a debated area of economics and policy. We hope our efforts and preliminary findings will stimulate other research in this field that will spur improvements in methodology and refine our insights. We intend to return to the issues raised in more detail in due course.”
Excerpt: “Tech for Good: Smoothing disruption, improving wellbeing – Theme 1: Job Security”
“Research shows that job security – which includes being unemployed or being worried about the risk of unemployment – has an asymmetric effect on well-being: whereas being employed is not associated with a strong effect on life satisfaction, losing a job or not being employed has a highly negative and lasting impact on life satisfaction, especially where it is linked to loss of income.”
“As noted earlier, technological innovation in the past both created jobs, through innovation, higher wages, and higher demand, and destroyed them, through substitution by machines. While the long-term effects are positive, the short-term disruption from the transition can be wrenching.
From our use-case library, we see that sharing platforms and AI-driven decision-making can increase the speed and effectiveness of innovation within companies. The rapid creation of new and better products and services will not only benefit consumers, but also create more demand and offset some of the reduction in labor demand due to automation. These are critically important elements of job security, which is at the heart of well-being for many people. At the same time, we acknowledge that the effect of these and other technologies may take time to become tangible, whereas the impact of job losses could be felt more quickly.
Our work on AI and automation anticipates that some jobs will be displaced, others created including through a surge in innovation unleashed by the technologies, and almost all will change. We have identified three key transitions relating to job security and the adoption of automation and AI that will need to be navigated. First, millions of workers will likely need to change occupations: we estimate that about 75 million people worldwide will need to switch occupations by 2030 in the event that automation takes hold at a pace in the middle of our range of adoption scenarios. If the speed of adoption is faster, at the top end of our range, it could affect up to 375 million people, or about 14 percent of the global workforce.
Second, workers will need different skills to thrive in the workplace of the future. Demand for social and emotional skills such as communication and empathy will grow almost as fast as demand for many advanced technological skills. Automation will also spur growth in the need for higher-level cognitive skills, particularly critical thinking, creativity, and complex information processing. Many companies already see skill gaps as a top priority, and almost two-thirds of firms we surveyed believe that at least 25 percent of their workforce will need to be retrained or replaced in the next five years. Globally, some large companies including Walmart, SAP, AT&T, and emerging-market companies including Tata, Infosys, and Tech Mahindra are adopting broad “reskilling” initiatives, but they remain exceptions.
Third, workplaces and workflows will change as more people work alongside machines. This will be challenging both to individual workers, who will need to be retrained, and to companies, which must become more adaptable. Such changes may not be easy to implement and may create significant friction in the economy. This mismatch risk is real, as automation will affect many sectors and geographies at the same time. Typically, a large fringe of the population is not mobile in the short term, especially those who own their homes or have family commitments.
Even if unemployment does not materialize at a large scale, many workers’ jobs will change. We have estimated that for about 60 percent of workers, around 30 percent of work activities have the potential to be automated, based on technologies that have already been demonstrated. The prospect of even partial automation of their work can increase the fear of unemployment for many, including middle-class workers who have traditionally been more insulated from unemployment.
How can technology reduce the risk to job security? Critically, it will bring innovation that is valued by the economy and will thus boost demand for labor. As we will see in our modeling of potential welfare outcomes later in this paper, innovation is an essential element for achieving positive outcomes. To that end, collaboration platforms such as Slack and Asana, and communication solutions such as WebEx and Circuit, play an enabling role: they can be used to crowdsource ideas, help share knowledge across multiple locations, and create effective spaces for collaboration. Innovation can also be boosted by governments’ adoption of platforms—following the lead of countries such as Estonia—making it easier to create and register a company. The World Bank estimates that the time it takes to start a business somewhere in the world has already fallen from about 50 days in 2005 to about 20 today on average.
Alongside innovation, technology can make a significant contribution to workforce fluidity, helping people retrain and businesses redeploy human resources, while minimizing the time and cost of displacement. Digital platforms and AI can be used to improve the chances that job seekers find opportunities to match their skills and preferences. This can reduce the length of time people spend between jobs and improve their earnings prospects. For employers, talent-matching technologies can improve worker productivity and provide savings in recruiting, interviewing time, training, onboarding, and attrition costs. Recent research further amplifies the significance of better talent matching for firm productivity and individuals’ wage levels. Learning platforms, remote learning technologies, and new forms of digital-based businesses can all start to bridge some of the remaining gaps. Such technology tools can enhance labor-market efficiency and on-the-job training, which international evidence suggests contribute to low unemployment (Exhibit 11).
Governments in some countries are launching initiatives to promote new skills. For example, Skills Norway, the country’s agency for lifelong learning, offers individually adapted training online in literacy, numeracy, ICT, and oral communication for adults. Numerous online tutorials, and certain MOOC platforms such as FutureLearn, offer free or freemium classes on how to better prepare for interviews and how to apply for a job.
The development of platforms and other remote working tools, such as online help desks, videoconferences, and simultaneous shared access to documents, can have an impact on well-being by allowing many more people not only to find work but also to work flexibly, as best suits their needs.”
Excerpts included in this article were originally published by McKinsey & Company, www.mckinsey.com. Copyright (c) 2019 All rights reserved. Reprinted by permission.