The OECD Digital Economy Outlook 2024, Volume 1: Embracing the Technology Frontier provides new insights on key technologies that underpin the digital technology ecosystem and their impacts. Using big data and machine-learning techniques, Volume 1 provides new estimates of the growth rate of the ecosystem’s core – the information and communications technology (ICT) sector. It then looks toward the technology frontier with perspectives on the future of artificial intelligence (AI) and how it can be shaped into a positive force. Volume 1 also analyses how people, firms and governments are adopting digital technologies, offering insights into the scale and scope of digital divides and how to boost equal opportunity and inclusion. To that end, it looks at the critical need for next generation wireless networks to provide unlimited connectivity everywhere. Moving beyond the hype of immersive technologies, Volume 1 examines the proven ability of virtual reality (VR) to scale, while identifying its opportunities and risks. Finally, it shines a spotlight on mental health in digital environments, including those most at risk.
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Table of Contents
- Foreword 5
- Table of Contents 7
- Reader’s guide 9
- Acronyms 9
- Country groupings 11
- Abbreviations 12
- Executive Summary 13
- Key findings 13
- The ICT sector continues to outperform the total economy 13
- AI actors must collaborate to unleash innovation responsibly and ensure its benefits are widely shared 13
- Next generation wireless networks are key to unlimited connectivity everywhere 13
- Digital technology diffusion and the skills to use them effectively are uneven, limiting equal opportunity and inclusion 14
- Immersive technologies like VR enable extraordinary experiences, but safety on and off line is key 14
- Negative behaviours in digital environments are rising and disproportionally affect girls 14
- Chapter 1. The growth outlook of the ICT sector 17
- Key findings 19
- An overview of the efforts to measure the digital transformation 20
- DSUTs will improve measurement in the medium term 20
- Box 1.1. The SNA and the digital economy 20
- Data on the uptake of digital technologies provides complementary information 20
- Other approaches to measuring digitalisation of the economy 21
- Despite these efforts, there is a lack of timely monetary measures of the digitalisation of the economy comparable across countries 21
- Methodology for measuring the growth of the ICT sector in real time 22
- A nowcasting approach that is parsimonious with data 22
- Table 1.1. An indicative matching of Google Trends categories related to the ICT sector 22
- Extracting useful information from Google Trends data 23
- Figure 1.1. Sampling noise distribution before and after correction 23
- Figure 1.2. Raw and cleaned SVI time series for ten Google Trends categories in the Netherlands, 2004-23 24
- A neural network to measure ICT sector growth in real time 25
- An agnostic modelling approach 25
- Evaluating nowcasting performance 25
- Figure 1.3. The nowcasting model performs strongly 26
- The growth outlook for the ICT sector across countries 26
- Timely estimates of ICT sector growth 26
- Figure 1.4. The ICT sector is resilient in the face of economic headwinds 27
- Figure 1.5. The ICT sector shows remarkable dynamism 32
- In the past decade, the ICT sector grew in most OECD countries, but not equally 32
- Figure 1.6. ICT growth rates vary markedly across countries 32
- ICT sector growth rates in OECD countries are nevertheless converging 33
- Figure 1.7. Six percentage points separate the top and bottom ICT sector performers 33
- Figure 1.8. ICT sector growth rates are converging across countries 33
- The ICT sector performed strongly in all OECD countries in 2023 34
- Figure 1.9. ICT sector growth is strong across countries 34
- Measuring the ICT sector is key to evaluating its performance and designing sound policies 34
- References 35
- Notes 36
- Chapter 2. The future of artificial intelligence 39
- Key findings 41
- Figure 2.1. Examples of interrelated factors that will likely shape AI governance in future decades 42
- The AI technological landscape today and tomorrow 42
- Advances in neural networks and deep learning are resulting in larger, more advanced and more compute-intensive AI models and systems 42
- Box 2.1. “A” is for artificial intelligence 43
- Box 2.2. Increasingly general AI systems 44
- Foundation models are enabling increasing AI generality across application domains, industries and tasks 44
- AI development and use is expected to continue to depend on access to computing infrastructure 45
- The availability of vast amounts of data for training AI has greatly enhanced systems’ capabilities, including their ability to generate realistic content 46
- Figure 2.2. More than half of open-source AI training datasets are in English 46
- Privacy-enhancing technologies are emerging, including confidential computing methods and federated learning 46
- Generative AI could lead to more representative datasets but also raises concerns about manipulation 47
- Open-source resources can make progress more broadly accessible but introduce other challenges 47
- Computer vision capabilities continue to develop, but applications like facial recognition raise concerns 48
- Robots are getting better and smarter thanks to AI 48
- Will scaling-up current AI models continue to drive advancements in AI capabilities? 49
- Experts offer varying predictions for the future trajectories and implications of AI 49
- AI is expected to yield significant future benefits 49
- Potential benefits of AI come with risks and uncertain future trajectories 50
- Figure 2.3. Generative AI-related incidents and hazards reported by reputable news outlets have increased steeply since 2022 50
- Many solutions are being proposed to help yield AI’s benefits and mitigate its challenges 52
- Demystifying debates on maintaining human control of AI systems and on the alignment of AI systems and human values 52
- Policy considerations for a trustworthy AI future 53
- Where are countries in the race to implement trustworthy AI? 53
- AI research and development priorities feature prominently on national policy agendas, with investments poised to continue in the years ahead 53
- Figure 2.4. China, the European Union and the United States lead in the number of AI research publications, with India recently making strides 53
- Figure 2.5. China’s share of “high-impact” AI publications has steadily risen since 2000, notably overtaking the United States and European Union in 2019 54
- While global venture capital investments in AI and overall have declined since 2021, investments in generative AI start-ups have boomed 55
- Figure 2.6. VC investments in generative AI start-ups have boomed since 2022, while VC investments overall and in AI start-ups reached a peak in 2021 56
- Governments are building human capacity for AI as demand for AI skills grows 56
- With industry outpacing academia in developing advanced AI, countries increasingly see AI compute capacity as a crucial resource to be managed 56
- Figure 2.7. Advanced economies are competing for AI talent 57
- Countries are embedding values-based principles into AI legislation, regulation and standards, moving towards future-fit policies for trustworthy AI 58
- Technical standards will play a key role in the implementation of trustworthy AI 59
- Initiatives supporting international co-operation for trustworthy AI continue to grow 59
- Challenges lie ahead in crafting future-fit AI policies that also spur innovation 60
- The future of AI is uncertain and complex, posing great opportunities but also risks for society and economies 61
- References 62
- Notes 68
- Spotlight. Next generation wireless networks and the connectivity ecosystem 71
- Terrestrial connectivity: Beyond 5G technologies 73
- Figure 1.S.1. The road to 6G: Potential timeline 74
- Figure 1.S.2. Interrelated factors that will likely shape 6G during the next decade 75
- Non-terrestrial connectivity: Developments in satellites and other non-terrestrial wireless technologies 77
- High-throughput geostationary satellites and non-geostationary orbit satellite constellations 77
- High-altitude platform stations 79
- Hybrid topologies for connectivity: Towards the integration of terrestrial and non-terrestrial network technologies 79
- Figure 1.S.3. Towards vertical coverage: Convergence of terrestrial and non-terrestrial networks 80
- Box 1.S.1. Flying taxis with electric vertical take-off and landing aircrafts for future transportation 80
- References 82
- Notes 85
- Chapter 3. Digital technology diffusion and data 89
- Key findings 91
- The ability to use the Internet effectively is key for equal opportunity and inclusion 91
- The incidence and frequency of Internet use have increased, but gaps remain 92
- Figure 3.1. Internet adoption has increased 92
- Figure 3.2. Divides in Internet use are pronounced by age, education and income 93
- Figure 3.3. Gaps in Internet use are narrowing but remain pronounced among the elderly 94
- Online activities differ in the extent to which they require education and ICT skills 94
- Figure 3.4. Uptake of Internet banking and online government services varies across countries 95
- Figure 3.5. Online activities such as Internet banking and online purchases are correlated with formal education and ICT skills 95
- Younger and more educated Internet users engage in a larger variety of online activities 96
- Figure 3.6. Younger and more educated Internet users engage in a larger variety of online activities 96
- COVID-19 led people to rely more on online services... at least temporarily 97
- Figure 3.7. Uptake of online services increased during the pandemic 98
- While more telework seems to be here to stay... 98
- ...the large uptick in e-commerce seems to be fading 99
- Figure 3.8. Much of the initial increase in e-commerce during COVID-19 has dissipated 99
- During the pandemic, those with the requisite skills were in a better position to use online services to their advantage 100
- Figure 3.9. COVID-19 was often associated with slowing convergence in uptake of online services 100
- Data-dependent technologies are diffusing at a slow pace 101
- Uneven diffusion of data-dependent digital technologies may undermine productivity growth 101
- Uptake of data-dependent technologies such as big data analytics and AI remains low 101
- Figure 3.10. Adoption of data-driven technologies remains low 102
- Cloud computing has been diffusing three times more rapidly than big data analytics 103
- Figure 3.11. Cloud computing has been diffusing three times more rapidly than big data analytics 103
- AI adoption is concentrated in the ICT sector 104
- Figure 3.12. Adoption of cloud computing and IoT technologies is distributed evenly across sectors 104
- Firm size is more important for adoption of data-dependent technologies and software than for IoT or cloud computing 104
- Slower diffusion of data-dependent technologies might be linked to scale economies, financial frictions or lack of access to data 105
- Figure 3.13. Firm size is a more important predictor of adoption for data-dependent technologies and software than for IoT technologies or cloud computing 105
- Far-ranging adoption of AI might require yet more experimentation and co-invention 106
- Boosting equitable uptake and diffusion of digital technologies are vital to bridging digital divides and fostering productivity growth 107
- Annex 3.A. Regression tables 108
- Annex Table 3.A.1. Effect of education, ICT skills and income on uptake of online services 108
- Annex Table 3.A.2. Effect of COVID-19 on uptake of online services 108
- Annex Table 3.A.3. Effect of COVID-19 on uptake of online services by level of education attainment 109
- Annex Table 3.A.4. Effect of the semiconductor shortage on M2M SIM cards 109
- Annex Table 3.A.5. Diffusion of big data analytics and cloud computing 109
- References 110
- Notes 114
- Chapter 4. Virtual reality and its opportunities and risks 119
- Key findings 121
- Understanding VR 122
- A continuous cycle of tracking, rendering and display enable VR 122
- The technological features of VR 123
- Touch and smell are complex to render in VR 124
- The benefits and opportunities of VR 125
- Teaching empathy 125
- Medical rehabilitation 126
- Mental health 126
- Training 127
- VR digital twins 128
- The downsides and risks of VR 128
- Privacy risks 128
- Box 4.1. Tracking data: Actions speak louder than words 129
- Simulator sickness 130
- Cognitive development and behaviour of children 130
- Distracted driving 131
- Overuse and addiction 131
- Governing VR 132
- Policy action on VR and immersive technologies is focused on promoting the domestic VR industry 132
- Towards the development of “rights” or “principles” for VR and immersive technologies 133
- Data from VR applications bring new challenges to existing privacy frameworks 133
- VR mental and physical safety must be carefully considered 134
- VR businesses have been self-regulating 135
- References 136
- Notes 141
- Spotlight. Mental health and digital environments 143
- Anonymity, disembodiment and disinhibition help explain why people communicate and interact differently on line 145
- Cyberbullying, PIU and PSMU are associated with mental health problems 146
- Immersive technologies bring new opportunities for mental health but can also exacerbate the risks 147
- Evidence suggests that negative behaviours in digital environments are on the rise and they disproportionally affect girls 147
- Cyberbullying is becoming more prevalent across countries, with girls experiencing higher rates than boys 148
- Figure 2.S.1. Cyberbullying rates have increased in nearly all countries 148
- Girls are more likely than boys to be problematic users of social media and the gap is widening 149
- Figure 2.S.2. Girls are problematic social media users more often than boys 149
- Moderate use of digital technologies tends to be beneficial, but “overuse” may be detrimental 149
- Box 2.S.1. Is time spent on line associated with problematic behaviour? 150
- Figure 2.S.3. Evidence suggests that intensive use of online communication is associated with PSMU 150
- Towards a policy agenda for fostering mental health in the digital age 151
- Raise awareness about negative behaviours in digital environments and promote media literacy 151
- Promote safety by design 151
- Identify specificities of immersive environments that present risks for mental health 151
- Improve the evidence base on mental health and digital environments 151
- Engage in partnerships with a range of stakeholders to prevent and address negative behaviours in digital environments 152
- References 153
- Notes 157
- List of Figures 159
- List of Tables 160
- List of Boxes 160