MGI Research

‘Tech for Good’: Using technology to smooth disruption and improve well-being

| Discussion Paper
Focusing on innovation, skills, and labor fluidity will be keys to good social outcomes of technology adoption.

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. Alongside such benefits, these technologies also have the potential to reduce disruption and the potentially destabilizing effects on society arising from their adoption.

Tech for Good: Smoothing disruption, improving well-being (PDF–1MB) examines the factors that can help society achieve such benefits and makes a first attempt to calculate the impact of technology adoption on welfare growth beyond GDP. Our modeling suggests that good outcomes for the economy overall and for individual well-being come about when technology adoption is focused on innovation-led growth rather than purely on labor reduction and cost savings through automation. This needs to be accompanied by proactive transition management that increases labor market fluidity and equips workers with new skills.

In this article, we explore the key findings of our research in the following sections:

Part 1

Technology, for better and for worse

Technology for centuries has both excited the human imagination and prompted fears about its effects. Today’s technology cycle is no different, provoking a broad spectrum of hopes and fears.

Opinion surveys suggest people tend to have a nuanced view of technology but nonetheless worry about the risks: while generally positive about longer-term benefits, especially for health, many are also concerned about the negative impact on their lives, in particular in the areas of job security, material living standards, safety, and trust.

Intrinsically, technology is neither good nor bad—it is the use to which it is put that makes the difference. Technological innovations over the ages have brought major welfare gains in the form of better and longer life as well as higher incomes and extended leisure. In our age, frontier technologies such as the Internet of Things, smart robotics, automation, and artificial intelligence will boost productivity growth, raising prosperity and replacing mundane or dangerous tasks. They have the potential to do good across a wide range of domains, from healthcare to education.

As in previous periods of technological innovation, these technologies may also have perverse effects that will require preventive or counteraction, such as AI being used unethically. More everyday negative impacts may also prevail. For example, technology can boost labor productivity but also make work environments more intense and, in some cases, lead to high levels of stress. Moreover, like historical technology transitions, the current wave may bring with it significant workforce dislocations, rising income inequality, and pressure on middle-class jobs.

Part 2

Six areas where technology can smooth disruption and improve well-being

While technology adoption may be disruptive to people’s well-being in the short term, especially in relation to jobs and incomes, technology itself could be put to use to help smooth those disruptions. We focus on six well-being themes that are most frequently discussed as particularly relevant in the context of technology adoption: job security, material living standards, health, education, environmental sustainability, and equal opportunities. Our examination is based on a library of about 600 use cases that we assembled using a wide range of industry sources, insights from our previous work, experts, and academic literature.

The use cases are not exhaustive and can highlight both sides of the story. For example, while technology can increase the cost of healthcare through expensive new treatments such as cell therapy, it could also improve efficiency in the health system by identifying and eliminating areas of waste. In the workplace, while automation could displace many jobs, digital platforms can equip workers with new skills and match employers and job seekers more effectively than traditional labor-market mechanisms, potentially reducing the time spent between jobs and improving productivity.

We are not seeking to sugar-coat the potentially disruptive effects of automation and other technologies on job security, material living standards and inequality. The loss of income accompanying job displacement would have a negative effect on well-being that job platforms or other technologies could not rapidly offset. Nonetheless, technology provides a tool kit of solutions to significant problems in our societies. We call this tool kit “Tech for Good.” By deploying it, business and government can help ease the workforce transitions that acceleration of technology innovation itself creates.

We selected technologies that have been or are in the process of scaling up adoption. They are: data and AI, which include both advanced analytics and artificial intelligence; connectivity and platforms, under which we group the mobile internet, digital platforms, and the cloud; robotics including autonomous vehicles; the Internet of Things; virtual and augmented reality; digital fabrication including 3-D printing; new materials and biotech; and clean tech, which mainly consists of renewable energy sources such as solar energy. Mapping technologies to our six themes highlights some clear patterns (Exhibit 1).

Exhibit 1
Three technology categories have significant potential to improve key areas of well-being.

Proven uses of technology to improve outcomes can be found across all of the themes. Several of the technologies have broad and general applicability across multiple themes:

  • Advanced analytics and AI feature in more than 60 percent of our use cases. Among other characteristics, they can ensure that help is targeted at the right people most effectively. AI capabilities including natural language processing can be used to tailor classes to individual students, for example, adjusting for their level of understanding and measuring their progress. AI can also significantly reduce administrative burdens on teachers, freeing up time for interaction with students.
  • Connectivity and platforms, including the mobile internet, are core applications in 35 percent of the use cases we compiled. Platforms are already widely used to improve the matching of employers and workers, create new forms of independent work, and raise skill levels—thereby addressing critical issues of job security and material living standards. Mobile connectivity and platforms can also be used in digital finance and telemedicine, for example, giving millions of people the opportunity to access services from which they have been excluded. In India, for example, we estimate that telemedicine could replace as many as half of in-person outpatient consultations by 2025, saving $4 billion to $5 billion annually.
  • Robotics, which has applications in 16 percent of our use cases, emerges as an especially significant enabler of equal opportunities and environmental sustainability. Advanced robotics, such as exoskeletons and wheelchairs with tablet and voice control, can help people with specific disabilities to communicate with others and increase mobility, for example.

The broad range of “tech for good” applications play out across our six themes as follows:

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, especially where it is linked to loss of income.

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.

How can technology reduce the risk to job security? Critically, it will bring innovation that is valued by the economy and will thus increase overall demand for labor. Collaboration platforms such as Slack and Asana, and communication solutions such as WebEx and Circuit can be used to crowdsource ideas, help share knowledge across multiple locations, and create effective spaces for collaboration, thus boosting 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. Smart talent platforms 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 of up to 7 percent in recruiting, training, onboarding, and attrition costs.

The development of platforms and other remote working tools, such as online help desks, videoconferences, and simultaneous shared access to documents, can allow many more people to work independently. We have estimated that, by 2025, online talent platforms could enable as many as 60 million people find work that more closely suits their skills or preferences.

Material living standards

As with job security, automation and AI could have a negative effect on material living standards if adoption leads to job losses with resulting loss of income. Technology adoption could also put downward pressure on wages and increase inequality. At the same time, technology can improve material living standards, by providing access to cheaper and better products and through generating new sources of income.

Technology can support innovation by developing platforms of local ecosystems of smaller firms. Connectivity platforms such as eBay and Etsy allow individuals and small businesses to generate additional source of income with lower intermediation costs than traditional retail channels.

Mobile payment technology has given millions of previously “unbanked” people access to financial services, especially in emerging economies, and much more can still be done. The M-Pesa mobile-money system in Kenya is often cited as an example—the share of adults in Kenya using it grew from zero to 40 percent within its first three years of launching in 2007.

Automation can lower costs as productivity rises, allowing firms to pass on savings to consumers; clothing prices, for example, have dropped by about 10 percent in real terms since 1998. Platforms can also help reduce the bill for essential goods, including education, housing, and electricity, by allowing consumers to find affordable goods and services. The French site CrossShopper and others offer deals to customers by matching prices of all local retail competitors and major online competitors, and they allow easy switching between providers (including utilities).

Finally, technology can optimize social transfer models. Mobile internet and connectivity platforms allow greater reach of public services. Digital IDs allow people everywhere who lack a legally recognized form of identification to gain access to banking, government benefits, education, and other critical services.

AI already shows results in applications ranging from diagnosis of pneumonia, malaria, or Alzheimer’s to prediction of strokes and heart attacks, or of autism in infants.

Health and longevity

Technology has significant potential to improve health. The possibilities range from AI-powered drug research, which is pushing the frontiers of drug discovery, to personal lifestyle wearables that can help individuals monitor their health and track improvements. Technology can also ease access to health, including through telemedicine, and create new efficiencies and reduce waste in healthcare systems, whose rising costs are increasingly affecting living standards and putting pressure on public finances in some countries.

AI already shows results in applications ranging from diagnosis of pneumonia, malaria, or Alzheimer’s to prediction of strokes and heart attacks, or of autism in infants. Robotics, meanwhile, has potential in surgery.

One UK-based startup that has partnered with several large drug makers, Exscientia, applies AI capabilities to test new drug molecules based on massive data sets. This allows drug makers to experiment with products based on similar molecules, speeding up drug development while reducing cost.

In the case of epidemics, advanced analytics and predictive models can help identify transmission routes and prevent transmission in the most efficient way possible.

At a personal level, lifestyle wearables and fitness trackers could contribute to improving health for many individuals and help healthcare professionals monitor patients on a continuous basis—for example by providing blood glucose readings—remotely. One example is Boston-based Partners Healthcare, which used at-home monitoring devices to track weight, blood pressure, and other metrics for 3,000 congestive heart failure patients. The program reduced hospital readmissions among the participating patient population by 44 percent while generating cost savings of more than $10 million over a six-year period.

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Finally, technology can be an important tool for improving public health by bringing greater efficiency to complex health systems. For example, staff members at Hospital Estadual Getúlio Vargas, a public hospital that serves citizens in Rio de Janeiro, are using advanced analytics to help improve patient care and treatment. The team has shortened the length of stay for ICU patients by three days.


Education is a critical enabler of positive welfare outcomes, as it increases the prospects for a better job and higher income. School systems and curricula will need to change, including with a reinforced emphasis on science, technology, engineering, and mathematics (STEM). Other skills, which are not currently part of the curriculum, will also be in demand. For example, the need for social and emotional skills, including empathy, adaptability, the ability to negotiate, entrepreneurship, and initiative taking, will experience a steep increase in demand, based on our research. Basic literacy and numeracy will no longer be enough for the jobs of tomorrow.

AI could become a valuable tool for teachers, with functions including grading exams and coursework. One company, GradeScope, uses computer vision and machine learning to grade students’ work quicker than a teacher, starting by deciphering handwriting. For now, it can work on topics including computer science and economics, which require less human interpretation to identify “correct” answers.

Technological applications can also improve the efficiency of learning tools. Examples of this range from using chatbots in the classroom to ask for student feedback to more sophisticated programs of adaptive learning that adjust teaching to the abilities and preferences of individual students.

Technology in the classroom has a mixed track record, however. Studies have shown that investing heavily in school computers and classroom technology does not always improve pupils’ performance. Nevertheless, technology application in schools could solve one pain point identified by teachers: administrative tasks, which take up between 6 and 15 percent of their time across countries.

Environmental sustainability

The increasing depletion of natural resources, rising incidence of extreme weather conditions, and growing pollution in oceans make for daily headlines and calls for action. Technology contributes to energy use; the world’s ICT ecosystem uses about 1,700 terawatt-hours of electricity annually, or about 8 percent of the global total.

AI-based traffic management in cities, including optimizing traffic light networks to improve the flow of cars and trucks, can reduce the impact of air pollution on health by between 3 and 15 percent. Cities are also using technologies to optimize waste pickup. In Seoul, for example, municipal authorities equipped garbage bins with RFID sensors that weigh trash and generate a bill for each household, a scheme known as “pay as you throw.”

Technology can help improve energy efficiency—including its own. The world’s ICT ecosystem currently uses about 1,700 terawatt-hours of electricity annually, or about 8 percent of the global total.

Technology can also reduce greenhouse gas emissions through energy efficiency, renewable energy sources, and battery and control technologies for balancing supply and demand. Electric utilities could use smart grid technology to improve system efficiency by 12 to 21 percent, or $310 billion to $540 billion, between 2015 and 2035. AI and IoT help reduce energy consumption through automated management of operations; for example, DeepMind helped reduce the cooling bill at Google’s data centers by up to 40 percent. Smart building technologies can also optimize energy consumption and monitor indoor air quality for improved physical well-being.

The circular economy’s new services and business models, which are largely facilitated by digital platforms, could unleash as much as 1.8 trillion euros of annual benefit, or a 7 percent additional GDP increase relative to the current development scenario in Europe alone by 2030. A number of large consumer goods companies including Coca-Cola, Danone, PepsiCo, Unilever, P&G, and L’Oréal have committed to reducing plastic packaging or making it recyclable.

Finally, technology has a role to play in conserving biodiversity. AI-powered drones can help monitor wildlife parks and identify the location of poachers, and similarly monitor for illegal fishing, for example.

Equal opportunities

We looked at technology’s impact on five groups: women; minorities; people with physical or mental disabilities; the lesbian, gay, bisexual, transsexual, and intersexual (LGBTI) communities; and the elderly.

Technologies can improve equality at work, including by revealing pay gaps and biases. Women constitute 50 percent of the working-age population but hold only about one-third of managerial positions. One startup, Textio, is using machine learning to debias job advertisements that could appeal more to men than women. One of its clients, Vodafone, saw a 7 percent increase in female recruits since it started scanning ads and rephrasing them to attract female talent.

Some specific products improve access for particular groups. For example, Hoobox Robotics has developed a wheelchair that can be controlled by facial expressions, facilitating mobility using AI technology. Affectiva, which was spun out of the MIT Media Lab, and Autism Glass, a Stanford research project, uses AI to automate the recognition of emotions and provide social cues to help individuals along the autism spectrum interact in social environments.

Part 3

Modeling scenarios of the welfare effects of technology adoption

Recent research has focused on measures of well-being and living standards that go beyond GDP. The Stiglitz Commission report was one of the first to propose alternative indicators of economic performance and social progress. The United Nations Human Development Index, the Social Progress Index put forward by Harvard economist Michael Porter and his colleagues, and the OECD’s Better Life Index are examples of such indicators, which seek to capture dimensions that have value to individuals and society. A growing evidence base shows that individuals’ subjective well-being is influenced by a large number of factors, only some of which are directly linked to GDP and incomes (Exhibit 2).

Exhibit 2
Many factors besides income contribute to individuals' well-being.

For our modeling, we use the concept of economic welfare as a way to put the well-being factors on a par with GDP and to simulate the impact of technology paths on them quantitatively. Welfare is a specific branch of economics that quantifies utility across the population and allows us to present well-being outcomes in monetary—or “consumption equivalent”—terms. For our research, we draw on a methodology applied by Charles I. Jones and Peter E. Klenow of Stanford University, and subsequently developed by others, including the International Monetary Fund.

We take GDP as the starting point for quantifying economic welfare and then adjust it for key components that affect individuals’ utility. The non-GDP components of welfare we incorporate into our calculation are:

  • Consumption: Only the proportion of income that is actually consumed—not saved—contributes to utility in each year. In line with welfare literature, we adjust utility for changes in the ratio of consumption and GDP. In our simulation, this is primarily driven by changes to unemployment.
  • Consumption inequality: This component captures the aversion of society to inequality. We quantify it by estimating the variance of the distribution curve for consumption. The variance is primarily influenced by unemployment, wage inequality, and changes to the capital vs. labor share of income.
  • Risk of unemployment: Even if a person is employed, the risk that they might lose their job and the anticipated consequences in terms of earning loss are a factor in their well-being.
  • Leisure: We model the likely increases in both the quality and quantity of leisure time due to productivity improvements, home automation, and other technology.
  • Health and longevity: We model the likely improvements in life expectancy due to technology and incorporate this into the welfare calculation. As a healthy life year is significantly more valuable to individuals than simply an extra year of life, we add a separate health component to the utility function.

There are two key dimensions that could make a crucial difference to the impact of technology transitions on welfare. The first is the focus of technology deployment—whether it is used primarily for innovation and growth or for labor reduction and cost cutting. The second is the degree to which the transition effects of technology adoption are actively managed, through retraining, labor mobility, and talent matching, among other measures.

Our scenarios are market-based and do not cover major policy levers, such as support to wages; instead, they represent prioritization decisions by businesses and governments within a set of choices that are consistent with economic incentives. The geographic scope includes the 28 European Union countries and the United States, and the time period modeled is 2017 to 2030. The scenario with the best outcome, which we call “Tech for better lives,” combines technology adoption focused on innovation and a range of measures that add up to a proactive management of the transition (Exhibit 3).

Exhibit 3
Adopting technology with a focus on innovation and proactive transition management could lift both GDP and welfare growth.

Our simulation of welfare growth under different technology adoption scenarios produces five initial insights:

First, the potential incremental boost from the “Tech for better lives” scenario to total welfare growth is material, in the order of 0.5 to 1.0 percent per year. That is as much as double the incremental growth from technology under an average scenario. The upside in the “Tech for better lives” is due to both higher productivity growth and lower unemployment, following from a more innovation-focused investment in and adoption of technology, and the public-private collaboration that leads to rapid retraining and redeployment of workers.

Second, the additional welfare effects, over and above GDP, are important. In the “Tech for better lives” scenario, they could add between 0.3 to 0.5 percent of welfare growth per year, the same order of magnitude as the additional GDP growth in this scenario.

Third, improvements in health and longevity are likely to be the largest contributors to increased welfare beyond GDP. In the “Tech for better lives” scenario, the modeling suggests that the gains in longevity and health can outweigh the negative effects of inequality at the aggregate level.

Fourth, the negative influences of technology transitions on welfare growth—such as income inequality and risk of unemployment—are present and of a similar size in all scenarios. Resisting technology diffusion therefore doesn’t reduce the welfare downside, while it does reduce the upside.

Finally, other, bolder moves that go beyond our scenarios may be required. Even in the most desirable scenario, while the net effect is positive, inequalities and negative effects persist. Therefore, market-based technology diffusion on its own, even with supportive government action, is unlikely to solve all the problems that arise.

Part 4

Implications for government, society, and business

Significant obstacles stand in the way of the best outcomes from technology adoption. Three are the most prominent: the lack of sufficient infrastructure and access to the digital economy for all; the high level of required investment and high complexity of implementation; and finally, technology itself comes with new risks, such as data violation and cyberfraud, that require mitigation in the form of new approaches, regulation, and cultural norms. To overcome these obstacles will require concerted action by stakeholders.

Government action is a key for managing technology transitions and encouraging innovation

Governments can be instrumental in ensuring that technology transitions are well managed and in encouraging innovative development and use of technologies. Governments can use public spending to reduce innovation costs for business and set the direction of technology development through procurement and open markets for public services. Adopting technologies in the public sector itself will improve the quality and efficiency of services and hasten broader diffusion in society.

For access to infrastructure, governments can make a significant difference through policies and investment aimed at improving infrastructure coverage and quality, for example with broadband rollout and public Wi-Fi. Digital ID programs can be a powerful tool for connecting citizens with public services and nudging digital adoption.

Finally, governments have an essential role to play in proactive management of data usage. Open data initiatives can create a broad-based culture of data sharing. At the same time, the state is a critical regulator of data rights and usage, including privacy protection.

Civil society can help build a Tech for Good ecosystem

Individuals and civil society can contribute to the overall focus on proactive management of technology by helping build a Tech for Good ecosystem. They can contribute to data collection initiatives, including through open-data platforms, and joining crowdsourcing initiatives.

Public pressure can ensure that new technologies are deployed for improved well-being and highlight where outcomes are negative. Already, some precedents for this exist, such as the Algorithmic Justice League created by an MIT student, Joy Buolamwini, which is committed to raising awareness about issues of bias and fairness in AI capabilities.

A new imperative for business leaders

Companies can harness the benefits of the current technology wave by adopting an approach of enlightened self-interest. At the company level, a workforce that is better trained, less stressed, healthier, and happier will also be more productive, more adaptable, and better able to drive the technology adoption and innovation surge that will boost revenue and earnings. We see three paths forward.

First, business leaders will need to be convinced of the argument that proactive management of technology transitions is not only in the interest of society at large, but also good for business. This paper is an opening salvo; more work will be needed to show how individual sectors and companies can benefit.

Second, the focus on innovation and proactive management will need to be embedded in company plans for technology adoption. They are essential ingredients for successful digital reinvention. Our library of use cases points to a wide range of applications that are good for well-being, improve innovation, or mitigate some transition effects—and sometimes all three. Their relevance varies by sector, but positive use cases include of AI-powered optimization of employee recruitment, evaluation, and training; robots that replace humans in mundane or dangerous tasks; AI-based R&D for new materials; and advanced analytics for logistics, which can cut costs while reducing companies’ environmental footprint.

Third, successful adoption of AI and other advanced technologies will require cooperation by multiple stakeholders. Education and skills is one example: business leaders can help inform education providers with a clearer sense of the skills that will be needed in the workplace of the future, even as they look to raise the specific skills of their own workforce. Other critical public-sector actions include supporting R&D and innovation; creating markets for public goods, such as health, so there is a business incentive to serve these markets; and collaborating with businesses on worker retraining.

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