How does the digital transformation affect people’s life and well-being? With the Going Digital Project, the OECD has undertaken a large number of studies in order to better understand the impacts of the digital transformation on the economy and society and to derive policy recommendations. This chapter summarises the main digital issues at stake and lists the available indicators that reflect both positive and negative impacts of the digital transformation. It uses the OECD well-being framework as a tool to analyse the various impacts of the digital transformation on people’s lives.
How's Life in the Digital Age?
Opportunities and Risks of the Digital Transformation for People's Well-being
Chapter 1. Understanding how the digital transformation affects people’s well-being
Abstract
“Technology is neither good nor bad; nor is it neutral.”
Melvin Kranzberg’s first law of technology (Kranzberg, 1986)
Introduction
More and more people are making use of personal digital devices such as the computer and the mobile phone to access the Internet. From 2010 to 2016, the number of fixed broadband subscriptions increased by 26% in OECD countries, while mobile Internet subscriptions increased from 824.5 million to 3 864 million worldwide (OECD, 2017a). In addition to greater penetration of Internet access, new applications of digital technologies, such as the Internet of Things (IoT), big data analytics and Artificial Intelligence (AI) are becoming increasingly widespread and are exerting an influence on many aspects of people’s lives. These developments have the potential to dramatically change the way people interact, live, work, or spend their leisure time today and in the future.
The impacts of the digital transformation can be felt in virtually every area of people’s lives. For example, the digitalisation of job tasks requires students and workers to acquire the skills needed for a computerised work content and workplace environment. At the same time, the Internet allows for improved job matching, with people increasingly searching for jobs online. Similarly, the Internet and digital platforms are transforming our social and civic lives: they allow people to interact with each other and build communities, to obtain services from government and commercial providers more efficiently. On the other hand, digitalisation exposes people to new risks. Children may suffer from cyberbullying on social media platforms and citizens who do not possess digital skills may be disadvantaged when trying to access government services. These are just some of the opportunities and risks from the digital transformation for people’s well-being.
This report is a first attempt at mapping how the digital transformation affects well-being. While previous OECD reports (OECD, 2017a; OECD 2017b) have documented the effects of digital technologies on the economy and on society (see Box 1.1), this report uses the OECD well-being framework (OECD, 2013a, 2015a) to systematically assess how the digital transformation affects people’s lives. The OECD well-being framework encompasses those dimensions of people’s well-being that are deemed important for living a good life, and therefore provides a valuable lens to analyse the opportunities and risks for well-being brought about by digitalisation.
Following Kranzberg’s first law of technology, this report makes an explicit distinction between the opportunities and risks that the digital transformation presents for people’s well-being. This distinction allows highlighting the heterogeneous nature of this transformation, based on the recognition that innovations are not intrinsically positive or negative. Rather, it acknowledges that policy-makers need to assess and monitor the various impacts of the digital transformation in order to ensure that the digital transformation ultimately comes with an improvement of people’s well-being.
The analysis is supported by an extensive review of a large but scattered literature, and by a set of indicators that are currently available. Because the analysis of the digital transformation as a key phenomenon affecting people’s well-being is relatively new, however, many of the relevant statistics and indicators are not currently available. The evidence presented here is therefore necessarily incomplete and preliminary; a secondary goal of this report is therefore to assess the data gaps in measuring the well-being impacts of the digital transformation.
Box 1.1. The OECD Going Digital Project
The digital transformation’s cross-cutting effects on the economy, society and individuals create new opportunities and challenges for governments and policy-makers. To support OECD Members and Partners in becoming more pro-active to unleash these opportunities and address these challenges, and to ensure the coherence of policies in the digital era, the OECD has launched the project Going Digital: Making the Transformation Work for Growth and Well-being (the Going Digital project). This project aims to help policy-makers better understand the policy implications of the digital transformation and to provide them with the tools needed to develop a whole-of-government approach to policy making in a world that is increasingly digital and data-driven. How’s Life in the Digital Age? is one of almost 100 outputs produced by the OECD under the Going Digital project. Many of these outputs provide new insights about the implications of the digital transformation in areas ranging from productivity to tax, skills, governance and digital security.
One central tool developed by the OECD over the course of the Going Digital project is an Integrated Policy Framework. This framework distinguishes seven policy building blocks: 1) access, 2) use, 3) innovation, 4) jobs, 5) trust, 6) society, and 7) market openness. Each of the building blocks identifies several key policy areas among which co-ordination is increasingly crucial to ensure policy coherence. For example, to enhance access to digital technologies and data, policies to be co-ordinated include those affecting communications infrastructures and services, competition, investment, and regional development. Each of the framework’s building block is accompanied by a set of indicators to measure countries’ progress towards key objectives in the policy areas covered by the framework. Where individuals are concerned, these indicators overlap with indicators used in this report. Together, they ensure that governments and stakeholders have the evidence to shape a digital future that makes the most of the opportunities that digital transformation holds to improve people's lives, while ensuring that nobody is left behind.
Mapping the well-being impacts of the digital transformation using the OECD well-being framework
The digital transformation covers a wide range of technological, economic and societal innovations that result from digitalisation and digitisation (see Box 1.2). The origins of the digital transformation go back to the first half of the twentieth century, when the first mainframe computing machines were developed. These machines boosted the computing capacity that supported scientific advances in a wide range of fields, allowing for breakthroughs in areas such as medicine that had large impact on people’s lives. Similarly, starting in the 1980s, in the early phases of personal computers, most functionalities greatly improved working environments (e.g. through text processors, information storage, calculations); and individual entertainment possibilities (e.g. games or cultural consumption on discs).
Box 1.2. OECD definition of the digital transformation
Digital transformation refers to the economic and societal effects of digitisation and digitalisation. Digitisation is the conversion of analogue data and processes into a machine-readable format. Digitalisation is the use of digital technologies and data as well as their interconnection that result in new activities or in changes to existing ones (OECD, 2018). Together, digitisation and digitalisation make up the digital transformation.
The arrival of the Internet in the early 1990s was another game-changer that led to some of the most transformative consequences of digitalisation for societal and individual well-being. Since then, a number of new technologies have arisen that shape the digital transformation in the present moment. The most important emerging technologies that contribute to current changes are:
The Internet itself is considered to be the “decisive technology of the Information Age” (Castells, 2014). It is the free and open interconnection between computing devices facilitated by the Internet that bestows upon digital technologies their potential for societal transformation. These interconnections are instant, rather than time-consuming; they are global, rather than local or national; and they are often free, rather than costly. Due to its reliance on networks, the value of the Internet increases with the proliferation of its use (Zhang et al., 2015). In 2017, 3.5 billion people worldwide used the Internet, including 70% of the world’s young population (ITU, 2017). The Internet is social in nature and allows for the creation of networks. Facebook, one of the most popular social media platforms, accounts for 54% of users’ online time globally.
Mobile devices allow individuals ubiquitous access to the Internet, revolutionizing the way people communicate, socialise, and entertain themselves through the use of a new range of applications (Lee and Lee, 2014). Smartphones, which are mobile devices that are able to perform many of the functions of a computer, are rapidly growing in the share of web page views as a proportion of the total. In 2013, 75% of Facebook users logged in to the site using a mobile device (OECD, 2016a). Smartphones have simplified the way people maintain personal relationships by allowing constant and instant access and are increasingly essential in participating in society (Lee, 2013). The degree to which smartphones are becoming a necessary element of modern life is highlighted by a recent PEW Research Center study, which found that 46% of smartphone owners say they could not live without their phone (Smith et al., 2015).
The Internet of Things (IoT) is the ecosystem of digital devices and objects that optimises the use of such devices by allowing for their interconnection. It includes objects and sensors that gather data and exchange this with other devices and with humans. As a result, devices linked to the Internet of Things allow for the input of information necessary for intelligent systems to model and solve complex problems, in fields from health and medicine to traffic and logistical systems to the natural environment. According to estimations, the number of connected devices in and around people’s homes in OECD countries will expand from one billion in 2016 to 14 billion by 2022 (OECD, 2015a).
Big data analytics refers to the use of sophisticated techniques to analyse and understand natural or societal trends using the availability of large amounts of new data that emerges from the digitisation of content and the monitoring of human activities (OECD, 2017a). Big data analytics exerts an impact on people’s lives by improving processes and allowing for new advancements in science and medicine, government and public administration, education and business (OECD, 2015a).
Artificial Intelligence (AI) or intelligent systems represent a new step in the evolution of computers that allow machines to perform human-like cognitive functions (OECD, 2017a). These systems use big data and machine learning to be able to operate independently and intelligently without human intervention. While AI is already being used today, for example in applications that learn from consumers’ preferences to make suggestions, most of the promises of AI are still forthcoming. In time, AI is slated to help solve complex questions and allow for productivity and efficiency gains (OECD, 2017a). It is also the form of digital innovations that raises the most ethical concerns (see Box 1.3).
Blockchain is a digital ledger that allows for secure, decentralised and disintermediated transactions of information. It relies on automated encrypting algorithms that prevent the altering of information using peer-to-peer networks that contain a copy of all historic transactions. Blockchain can therefore be applied as a secure and decentralised store of value, the documentation of legal contracts or even democratic processes such as voting.
At a societal level, the Internet and the innovations that came with it (e.g. open interconnections between digital devices, social media platforms) have fundamentally changed, and will continue to change the way humans interact with each other as well as the social fabric. In what is referred to as the “Network Society”, networks have become the basic unit of society, and social organisations revolve around electronically processed information networks (Castells, 1996). In addition, according to some theorists, this shift is in parallel with an increased degree of networked individualism as a form of social organisation, which contrasts with traditional social structures that revolve around location-bound social groups such as the family or the community (Rainie and Wellman, 2012). Instead, society has become organised around networks that are based on shared interests, values or activities that are not constrained by geographical proximity.
These societal changes are met with equally large transformations in the structure of the economy. First, in the digital economy, the creation of value occurs no longer primarily in the production of goods or services, but instead is more and more concerned with the production of information and knowledge-based assets (Brynjolfsson and Kahin, 2000). Moreover, economic transactions have seen immense efficiency gains thanks to the ability to conduct trade between businesses and between businesses and consumers through electronic commerce on the Internet (OECD, 2012). And finally, new and upcoming innovations in the field of Artificial Intelligence and big data analysis have the promise to change the nature of work and potentially replace human labour.
Box 1.3. Digital transformation, well-being and ethics
The OECD well-being framework is not explicitly underpinned by normative or ethical considerations. However, in the context of the digital transformation, some have argued that a system of normative principles is necessary in order to protect individuals from potential intended or unintended negative effects. For example, in Automating Inequality (2018), Virginia Eubanks argues that while Big Data and machine learning may foster a more efficient functioning of criminal justice systems, they may also lead to increasing exclusion and marginalisation of the poor. Likewise, Cathy O’Neil argues in Weapons of Math Destruction (2016) that Big Data and machine learning have a risk of increasing social exclusion and inequalities. In 2013, a group of ex-tech workers founded the Center for Humane Technology to raise awareness about technology companies’ attempt to increase people’s digital addictions. In 2017, the United Nations Special Rapporteur on extreme poverty and human rights warned that digital innovations around Big Data and Artificial Intelligence would become increasingly a human rights issue, especially for minorities. The Toronto Declaration on non-discrimination in machine learning, supported by Human Rights Watch, Amnesty International, The Wikimedia Foundation and Access Now, among others, calls on stakeholders of the digital transformation to establish a set of principles that secure human rights in machine learning algorithms. Similarly, the Institute of Electrical and Electronics Engineers (IEEE) is working to develop a framework for Ethically Aligned Design (EAD) that includes human rights, well-being metrics and ethical principles as core principles.
In September of 2018, the OECD has created an expert group (AIGO) to provide guidance in scoping principles for artificial intelligence in society. The formation of the group is the latest step in the organisation’s work on artificial intelligence to help governments, business, labour and the public maximise the benefits of AI and minimise its risks. The group is made up of experts from OECD member countries and think tanks, business, civil society and labour associations and other international organisations. In addition, the OECD has collaborated with the IEEE on its Global Initiative for Ethical Considerations in Autonomous and Intelligent Systems. In terms of well-being, the goal of the IEEE project on Ethically Aligned Designed (EAD) is to not only encourage their members to consider well-being outcomes in their product design, but also develop well-being metrics that allow measuring the impacts of their products on a variety of dimensions of well-being, in order to increase the knowledge base on the impacts of such innovations.
The focus of this report, however, is on individual, rather than economic and societal impacts of the digital transformation. Most of the opportunities or risks identified in this report are presented in terms of the direct consequences on people’s lives. This means that certain important impacts of the digital transformation, such as “winner-take-all” dynamics in the economy, are generally not reflected in the indicators presented here. Because this report focuses largely on individual impacts, the Internet and personal digital devices feature prominently in the set of indicators. At times, the Internet or computers are used as a proxy for the digital transformation as a whole. For example, when estimating the impacts of the digital transformation on the quality of the working environment, the analysis relies on people who use computers or other digital devices at work. The measurement therefore does not capture how the digitalisation of entire industries, work processes and tasks impacts people’s working environment, including for those that do not even use digital devices themselves.
To assess how the digital transformation affects well-being at the individual level, this reports uses the well-being framework that the OECD has developed as part of its Better Life Initiative. This Initiative was launched in 2011 to promote a people-centred approach to policy making. As part of this initiative, the OECD developed a conceptual framework, which builds on a large body of theoretical and empirical studies in this field (Stiglitz, Sen and Fitoussi, 2009; OECD, 2011 and Boarini et al., 2012, for a review) and reflects consultation with experts from academia and governments in OECD countries. The OECD well-being framework follows a number of principles. First, it is concerned with the well-being of people rather than just economic conditions. Second, it focuses on outcomes rather than inputs or outputs, recognising that different combinations of inputs and outputs may be equally effective in delivering the same outcome. Third, it considers both objective and subjective aspects of people’s life, as people’s evaluations and feelings matter as much as the objective conditions in which they live. Fourth, it emphasises the need to measure the distribution of outcomes, and to identify inequalities across population groups. Finally, it also considers the long-term sustainability of well-being.
The OECD framework distinguishes between 11 dimensions of well-being today (income and wealth, jobs and earnings, housing, health status, education and skills, work-life balance, civic engagement and governance, social connections, environmental quality, personal security and subjective well-being) and four sets of resources that generate well-being in each of the dimensions mentioned above: economic capital, environmental capital, human capital and social capital. The 11 components of current well-being are outcomes that are intrinsically important to people, grouped under the two main headings of “material conditions” (i.e. economic well-being) and “quality of life” (Figure 1.1).
Figure 1.1. The OECD well-being framework
Source: OECD (2017c), How’s Life? 2017: Measuring Well-being, OECD Publishing, Paris, https://doi.org/10.1787/how_life-2017-en.
The conceptual framework presented above has been operationalised through a dashboard of country-level indicators, published regularly in the report How’s Life? Measuring Well-Being, that provides evidence on people’s well-being for OECD countries and partner economies, and underpins the Better Life Index, an interactive web tool designed to engage with the public on the issue of well-being.1
The aspects of the digital transformation in this report sometimes go beyond the outcome indicators under each dimension of the OECD well-being framework. For this reason, this report presents a range of indicators aiming to capture the most visible impacts of digitalisation on the most salient aspects of people’s life. Due to measurement limitations, “housing” is not covered by the indicators presented in this report, although some of the effects of digitalisation on housing are discussed in Chapter 2. Finally, only opportunities and risks of the digital transformation on current well-being are considered, although the digital transformation also affects resources for future well-being, and hence the sustainability of well-being outcomes over time.2
While the OECD well-being framework is not the only possible starting point for an assessment of the impacts of the digital transformation (Box 1.4), it has the advantage of comprehensively covering the most salient aspects shaping people’s life, all of which are being affected, in direct or indirect ways, by the ongoing digital transformation.
Box 1.4. Alternative approaches to measuring the well-being impacts of the digital transformation
Other approaches to assessing the well-being impacts of the digital transformation may uncover different impacts or place emphasis in other areas. For example, Gluckman and Allen (2018) proposed an analytical tool to assess impacts on: institutions of the self (e.g. self-worth, self-expression, privacy), institutions of social life (e.g. social connections, education, friendships, romantic life, values and cultural expression) and institutions of civic life (e.g. politics, media consumption, governance and rule of law). Using this analytical tool, they defined five priority areas in the context of the digital transformation:
1. Human development and early childhood learning
2. Mental health across the lifespan
3. Social inclusion (e.g. group formation and dynamics, social capital and trust)
4. Personal and public security
5. Governance
Gluckman and Allen (2018) also identify the large policy research gaps that exist in many of these areas. Better monitoring and evaluation of these various impacts are needed in order to better understand the digital transformation and to inform public policy, which often has not sufficiently addressed these challenges.
Assessing the well-being impacts of the digital transformation
The assessment of the impacts of the digital transformation on well-being faces both practical and conceptual limitations. First, the digital transformation spans thousands of individual technological innovations and covers almost every area of people’s lives. Its reach is enormous and impacts are at times very direct, at times indirect and interconnected. This makes causal analyses difficult, in particular because: 1) there is no clear counter-factual, as technologies are adopted gradually over time, and their impact cannot be tied to a particular moment or technological uptake; 2) even though the uptake of digital technologies is faster than ever before, their adoption differ across groups of people, implying heterogeneous effects across society; 3) the emergence of the digital transformation coincides with other major economic and societal changes, which makes it difficult to single out the specific role played by digitalisation. For example, while Twenge et al. (2018) has drawn attention to the fact that the introduction of the smartphone has gone hand in hand with higher teen depression and suicide rates, there is no strong evidence of a causal relationship as other factors may be at work.
In addition, there are a number of practical obstacles that impede the measurement of the digital transformation. These practical obstacles concern the ability to find relevant indicators based on timely data harmonised across OECD countries. For these reasons, the focus of this report is not on “causal” impacts but rather on identifying potential opportunities and risks associated with the digital transformation for each of the dimensions of the OECD well-being framework. Moreover, the list of opportunities and risks strives to cover the most important impacts for people’s well-being, without pretending to provide a comprehensive picture of the full range of impacts of the digital transformation. Rather, the opportunities and risks presented here should be seen as a starting point to compare how people in different countries are affected by digitalisation.
Table 1.1. Key opportunities and risks of the digital transformation for people’s well-being
The opportunities and risks identified in this report are listed in Table 1.1. This list presents 39 key impacts that are based on the evidence presented in Chapter 2. Each item in this list corresponds to a section in Chapter 2 that describes the impact and presents available indicators.
It is difficult to identify and synthesize the common patterns of the digital transformation across all dimensions of people’s life. However, it is useful to simplify the complexity of the phenomenon by contrasting the efficiency gains arising from digital technologies with three different types of digital risks:
Digital technologies are a source of efficiency gains...
On the one hand, digital technologies provide a lot of information and services to people at a reduced cost: for instance, they can simplify access to education, to health information, to consumption goods via online shopping, they cut transportation time via teleworking, they improve the efficiency of energy management at home and at the city level, in sum, they make human activities more efficient.
…for those endowed with strong digital skills…
However, not everyone has the capacity to use digital technologies for real-life activities in an optimal way, which implies a new form of inequality, namely a digital divide that may reinforce existing forms of socio-economic inequality (Box 1.5). The digital divide materialises for instance in the differential usage of internet across age and socio-economic groups, and in the wage gap between high and low-digital skill workers.
…and digital literacy…
People spend more time in the digital space, which offers new ways of working, communicating and socialising that are valuable as such. On the other hand, digital life may crowd out the time spent in real-life interactions, or may create digital addiction and have other adverse effects on mental health. Making the best use of digital technologies without hampering the fundaments of human well-being requires a diverse set of cognitive and emotional skills, which can be referred to as “digital literacy”. For instance, critical assessment is needed to sort out high and low-quality information, while self-control over digital involvement can prevent digital addiction.
…and who evolve in safe digital environments
As in real life, digital life raises issues such as cyber-bullying and cyber-security breaches.
Box 1.5. Inequalities and the digital divide
While the Internet has the potential to act as an equalising force, the Internet and digital technologies also carry the risk of serving as catalysts for greater inequalities of well-being. New technologies have the potential to amplify existing inequalities as they change the returns on existing forms of capital (Weber, 1978; Witte and Mannon, 2010). Economic capital (e.g. computer equipment) is needed to gain Internet access, social capital is needed to understand how to use it and engage with its content (van Deursen and van Dijk., 2014). In turn, people who have access to the Internet can generate additional economic and social capital from its use, leading to the perpetuation of inequalities. This mechanism allows for the emergence of a digital divide, which has been a concern for policy-makers since the early stages of the digital transformation (OECD, 2001).
The digital divide pertains to the “gap between individuals, households, businesses and geographic areas at different socio-economic levels with regard both to their opportunities to access information and communication technologies and to their use of the Internet for a wide variety of activities” (OECD, 2001). The digital divide can refer to both horizontal (i.e. across groups) and vertical inequalities and be related to both access to digital technologies and to the ability to use them (the so-called second digital divide). This report includes indicators that relate to both Internet use and digital skills.
The framework for well-being in the digital age used in this report takes stock of a number of fundamental inequalities that the digital transformation presents through the inclusion of indicators for specific “risks”, such as inequalities of Internet use, the divide in digital skills, as well as the wage gap and job polarisation induced by differentiated impacts on labour markets. In addition, for impacts that increase horizontal inequalities, particularly by age, gender and education level, differences in exposure to opportunities and risks among these groups are highlighted.
Measuring the well-being impacts of the digital transformation
An important limitation in providing evidence on the opportunities and risks created by the digital transformation for each dimensions of well-being is the availability of relevant, internationally comparable and quality indicators. Many countries do not include technology-related variables in their standard survey vehicles. Even when relevant indicators exist at national level, the lack of internationally-agreed definitions or harmonised data collection makes cross-country comparisons difficult. In addition, many indicators are not available for all OECD countries, limiting cross-country comparability. A number of indicators presented in this report are based on large European-wide surveys, which provide a lot of information on various life dimensions, but have no or limited comparability with survey vehicles in other, non-European, countries.
There is also an issue of timeliness, which is particularly important in the case of the digital transformation, because new technologies spread at a high pace. Data on Internet access or use or on technology-related activities from even a few years ago may not be representative of the situation today. This can pose problems when comparing performance across countries For example, the latest available year for data on the number of people who look for health information online is 2014 for Australia, while it is 2016 for most other countries. Such small differences in timeliness can have large consequences for comparability given the speed at which digital innovations take place.
As a result, ensuring good country coverage has been a major challenge for the comparisons made in this report. Data used come from a number of sources, and efforts have been made to select the highest-quality data with the broadest international comparability. Data come primarily from large survey vehicles. The OECD ICT Access and Use database contains (broadly) harmonised data on a range of individual-level indicators of Internet access and use. This database is based on the OECD model survey on ICT access and usage by households and individuals, 2nd revision (OECD, 2015b), which provides a framework for the collection of cross-country data on individual and household use of digital technologies. Despite improved efforts, however, there are still differences in survey questions across countries. A number of indicators also come from the OECD Survey of Adults Skills (part of the Programme for the International Assessment of Adult Competencies, PIAAC) and the Programme for International Student Assessment (PISA). These two sources contain information about adults’ and students’ use of computers and digital technologies at work and at school. In addition, a number of European-wide surveys provide data for all European countries. These include Eurostat’s European Statistics on Income and Living Conditions (EU-SILC) vehicle, Eurostat’s model surveys on ICT usage, as well as the European Working Conditions Survey (EWCS) and the European Quality of Life Survey (EQLS), both implemented by Eurofound.
Some of the data used in this report also come from non-official sources. These sources include: the WHO’s Health Behaviour in School-aged Children (HBSC) survey, implemented by an international alliance of researchers; data on self-reported exposure to disinformation collected by the Reuters Institute for the Study of Journalism in collaboration with YouGov; the Global E-Waste Monitor implemented by a consortium of organisations including the United Nations University and the International Telecommunications Union; and the Gallup World Poll.
The set of 33 selected indicators used to assess the key opportunities and risks of the digital transformation for the 11 dimensions of people’s well-being is shown in Table 1.2. The selected indicators are available for most OECD countries, with a minimum coverage of 20 countries. This means that even in the case of sources with good international coverage, data are generally not available for all OECD countries. For each selected indicator, the last column of Table 1.2 indicates whether it measures a risk or an opportunity. In total, Table 1.2 includes 20 indicators of digital opportunities and 13 indicators of digital risks.
As an additional caveat, the indicators included in this set represent the measurable opportunities and risks of the digital transformation on well-being included in Table 1.1. They have been selected to represent wider processes for which more comprehensive data is unavailable, and as such should be considered more as “proxies” than as measuring the full set of impacts. For example, for the health dimension, the indicator “medical appointments online” is chosen to represent a range of innovations at the intersection of digitalisation and health care processes for which no other data is currently available. For a number of opportunities and risks of the digital transformation identified in the literature, it has not been possible to identify any relevant indicators. For this reason, the indicators shown in Table 1.2 should not be considered as a comprehensive measurement framework of all opportunities and risks of the digital transformation but rather, as providing information on those well-being areas for which data is available. More details on the main data gaps and the statistical agenda ahead are provided in Chapter 3.
The available indicators of opportunities and risks of the digital transformation allow for a detailed analysis of OECD countries’ relative strengths and weaknesses as well as an assessment of the way that the digital transformation impacts well-being in individual OECD countries. These two issues are examined in Chapter 3 and Chapter 4, respectively.
Table 1.2. Selected indicators of opportunities and risks of the digital transformation for various dimensions of people’s well-being
Note: 1ICT access and use is not a dimension of the OECD well-being framework per se. However, having access to digital technologies pre-conditions their possible impacts on well-being dimensions. ICT access and use has thus been added to the framework used in this monograph as a horizontal dimension.
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Database references
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OECD ICT Access and Usage by Households and Individuals database, http://oe.cd/hhind.
OECD Programme for International Student Assessment (PISA) database, www.oecd.org/pisa/data/.
OECD Survey of Adult Skills (PIAAC) database, www.oecd.org/skills/piaac/publicdataandanalysis/.
Notes
← 2. Some of the impacts identified using the 11 dimensions of current well-being also directly or indirectly affect resources for future well-being. For example, the indicator of e-waste might also be considered to have an effect on natural capital. Similarly, the relationship between self-reported disinformation and trust in government suggests that there may be indirect effects on social capital. Human capital is also affected by a range of impacts of the digital transformation, such as through changing skills needs, potential consequences of automation on long-term unemployment and potential improvements in health outcomes.