The internet and a number of emerging technologies of the Fourth Industrial Revolution present a particular challenge for international governance and cooperation. Unlike other policy domains, there is no institutional focal point for technology governance in the international system, just as there tends not to be an integrated focal point for such policy in national governments. In addition, because the technologies are developing rapidly and being applied in constantly evolving and intersecting ways, traditional, formal rule-setting processes often may not be the most appropriate or effective approach to strengthening cooperation and governance in the public interest.

Yet the economic, social and security stakes are enormous. This is perhaps nowhere better illustrated than in Japan’s “Society 5.0”^[1] integrated technology vision in which people, things, and systems are connected in cyberspace with the resulting data analysed by AI and fed back into physical space in ways that bring extraordinary new value to industry and society.

One study estimates that artificial intelligence (AI) could generate an additional $15.7 trillion^[2] (US) in economic value by 2030, slightly more than the current annual economic output of China and India combined, with 40% of this value likely to accrue to China and the US alone. The EU estimates^[3] its digital market “could contribute €415 billion [$472 billion] per year” to the economy, while projections for ASEAN^[4] digital integration are around $1 trillion (US) in gains by 2025. Meanwhile, genome-editing technology CRISPR may develop a market of over $10 billion by 2027^[5], and cryptocurrency markets already register gains and losses^[6] in the billions, sometimes within a single day.

But while AI is likely to generate new wealth, some analysis^[7] suggests it could make inequality worse^[8] and even increase the risk of nuclear war^[9]. There are also potential environmental and social costs of the technology revolution. Bitcoin, for example, requires a network with energy consumption^[10] roughly equal to Singapore,66 producing 262 kg of CO2 for each of its more than 250,000 transactions per day, and the recent concern over “fake news” has been connected to the proliferation of “bots”^[11], automated accounts driven by algorithms. As emphasized by the Stewardship Board of the World Economic Forum’s Digital Economy and Society System Initiative in its recent report, Our Shared Digital Future^[12], greater cooperation among all stakeholders is necessary to bolster trust in technology.

The report of the UN Secretary General’s High-Level Panel on Digital Cooperation^[13] has rightly suggested that digital cooperative governance should take the form of a “distributed co-governance” approach, encompassing various purpose-built configurations that involve governments, the private sector, civil society, international organizations, academia, the technical community and other relevant stakeholders. A new and quite variable geometry of international digital cooperation remains at an early stage but is developing (some might say proliferating) very rapidly. Following are a number of illustrative examples, both multidisciplinary and issue-specific:

On the multidisciplinary plurilateral front, the Digital 9^[14] group of leading digital nations have been gathering in different configurations since its launch in the UK in 2014. Canada convened the group, which shares world-class digital practices, collaborates to solve common problems, and identifies how digital government can provide the most benefit to citizens, in December 2018 as part of the follow up activities related to its G7 presidency.

On the multidisciplinary multi-stakeholder front, the World Economic Forum launched the Centre for the Fourth Industrial Revolution Network^[15] (C4IR) in 2017 to serve as a public-private platform for the collaborative development and refinement of governance frameworks and protocols that more fully anticipate the risks and accelerate the benefits for societies of advanced technologies. It brings together governments, business organizations, dynamic start-ups, civil society, academia and international organizations to co-design human-centred governance protocols and policy frameworks, and pilot them with government and industry partners. The Centre Network is headquartered in San Francisco and is establishing operations in Japan, India, China and several other countries in cooperation with their governments at the highest level along with leading business, civil society and academic figures. Its programme of multi-stakeholder policy development and piloting is active in nine technology domains. With nearly 30 government partners now engaged, the C4IR established leader-level global councils in six domains in 2019, composed of ministers and heads of regulatory agencies, chief executive officers and leading technical and civil society experts to cross-pollinate international policy experience sharing and public-private cooperation. The aim is to help shape the global technology policy and corporate governance agenda by providing a unique place in the international system where policy dialogue, practical learning and international agenda setting can take place across stakeholders and regions on an ongoing basis.

Artificial intelligence and machine learning

As part of the 2018 G7 process, Canada and France announced the creation of a multistakeholder International Panel on Artificial Intelligence (IPAI)^[16] that could become a global point of reference for understanding and sharing research results on AI issues and methodologies as well as convening international AI initiatives. The stated mission of the panel is to support and guide the responsible adoption of AI that is human-centric and grounded in human rights, inclusion, diversity, innovation and economic growth. It aims to facilitate international collaboration among the scientific community, industry, civil society, related international organizations and governments. By relying on the expertise of important stakeholders and providing a mechanism for sharing multidisciplinary analysis, foresight and coordination capabilities, the panel plans to conduct analysis intended to guide policy development and the responsible adoption of AI.

The Institute of Electrical and Electronic Engineers’ (IEEE) Global Initiative on Ethics of Autonomous and Intelligent Systems (A/IS)^[17] was launched in April 2016 to incorporate ethical aspects of human well-being that may not automatically be considered in the current design and manufacture of A/IS technologies, and to reframe the notion of success so that human progress can include the intentional prioritization of individual, community and societal ethical values. The initiative seeks to ensure that every stakeholder involved in the design and development of autonomous and intelligent systems is educated, trained and allowed to prioritize ethical considerations so that these technologies are advanced for the benefit of humanity. It has two primary outputs: the creation and iteration of a body of work known as Ethically Aligned Design: A Vision for Prioritizing Human Well-Being with Autonomous and Intelligent Systems; and the identification and recommendation of ideas for standards projects focused on prioritizing ethical considerations in A/IS. The Global Initiative has recently increased from 100 AI/ethics experts to more than 250 individuals, including new members from China, Japan, South Korea, India and Brazil.

The OECD Principles on Artificial Intelligence promote artificial intelligence (AI) that is innovative and trustworthy and that respects human rights and democratic values. They were adopted in May 2019 by OECD member countries when they approved the OECD Council Recommendation on Artificial Intelligence^[18]. The OECD AI Principles are the first such principles signed up to by governments. Beyond OECD members, other countries including Argentina, Brazil, Colombia, Costa Rica, Peru and Romania have already adhered to the AI Principles, with further adherents welcomed. The OECD AI Principles complement existing OECD standards in areas such as privacy, digital security risk management and responsible business conduct. In June 2019, the G20 adopted human-centred AI Principles^[19] that draw from the OECD AI Principles.

The Forum’s Centre for the Fourth Industrial Revolution AI and Machine Learning Platform^[20] has begun work on several artificial intelligence governance projects. The first is developing a governance framework or toolkit for boards of directors to aid them in asking the right questions, understanding the key trade-offs and meeting the needs of diverse stakeholders, including how to consider approaches such as appointing a chief value officer, chief AI officer or AI ethics advisory board. It is being designed around four pillars: technical, brand, governance and organizational impacts of AI, each providing an ethical lens for creating, marketing and sustaining AI in the long term. The second is drafting a framework to guide government procurement of AI products and services. Government procurement rules and purchasing practices often have a strong influence on markets, particularly in their early stages of development. The third project is designing best practice guidelines and policy measures for the protection of children in cooperation with UNICEF. In the absence of clear guidelines, parents and caregivers are left to make decisions about toys and other AI-enabled products with incomplete information about the implications for their children’s well-being and privacy. As these devices come onto the market, mechanisms will be needed to protect children while enabling the benefits of “precision education”.

The Partnership on AI (PAI)^[21] is a multistakeholder organization that brings together academics, researchers, civil society organizations, companies building and using AI technology, and other groups working to better understand AI’s impacts. The partnership was established to study and formulate methodologies on AI technologies, to advance the public’s understanding of AI, and to serve as an open platform for discussion and engagement about AI and its influences on people and society.

Data

The data intensity of the Fourth Industrial Revolution is posing multiple policy challenges relating to privacy, security, bias, accountability, abuse of personal data, antitrust, international trade, access to public services, etc. Most governments are still in the early stages of developing policy frameworks, and international coordination is similarly nascent but greatly needed.

There are over 120 different data protection and privacy laws in effect around the world, raising concerns about the compliance and transaction costs for firms navigating this patchwork quilt of regulation. A particular concern is the burden compliance may place on small and medium-sized enterprises (SMEs), which do not have the large legal departments and budgets of multinational firms.

China, the US and Europe have fundamentally different regulatory approaches to data protection and enforcement. The US and China tend to take a light regulatory approach unless or until a specific harm is identified. In addition, the US regulates data by sector and type. There is no uniform omnibus privacy law in the US, although the recent passage of the California Consumer Privacy Law has sparked renewed interest in the passage of such a law to pre-empt 50 different state laws and potentially countless local laws. While the US appears to have a less protective privacy model than Europe, comparisons of enforcement practices seem to indicate that privacy outcomes are not dramatically different.

Europe’s General Data Protection Regulation (GDPR) went into effect in late May 2018. In creating a strict regulatory framework for data, Europe has set a high bar. It hopes to encourage countries to coalesce around its model, thereby setting a de facto global standard. Many countries are indeed working to achieve GDPR “adequacy”, and several new laws have been adopted in countries such as China and Brazil that look very similar to GDPR. But the distinguishing feature of GDPR is the potential cost of non-compliance, which can run up to 4% of global revenue. Prior regulations included fines that had little to no deterrent effect on companies with market values in the tens and hundreds of billions of dollars.

China has adopted a security law that requires all foreign companies to localize data about Chinese consumers within China’s borders. Other rules accompanying the new security law include requirements that look very similar to GDPR, but it remains to be seen how enforcement will be carried out, including whether foreign companies will be treated differently from domestic entities.

Between the differing data localization requirements, data protection rules and approaches to data ownership and online content and expression around the world, there is a growing risk that the internet will fragment into separate, parallel systems. There is also rising concern that the centrality of data to value creation in the Fourth Industrial Revolution will serve to widen the already large digital divide in the world, particularly between the US and China (which host all 20 of the world’s largest technology companies by market valuation) and other countries.

Indeed, growing appreciation of the value of open data has led municipalities and nations to begin mandating open data laws. For example, France’s Digital Republic Act^[22] requires government agencies to move to an open data orientation and to set quality standards for such data. Barcelona’s Open Data BCN^[23] is just one example of a municipality administrative initiative that prioritizes the availability of public-sector data for free use by interested parties and includes statistical and public-service data. At the international level, a multistakeholder set of good governance principles, A Contract for the Web^[24], is gathering support from companies, governments and civil society groups. These principles establish a set of commitments on the part of governments, companies and citizens that aim to increase the agency of citizens over their data and protect the open web as a public good and basic right for everyone.

Blockchain and distributed ledgers

Blockchain, an early-stage technology that enables the decentralized and secure storage and transfer of information, has the potential to be a powerful tool for tracking and transactions that can minimize friction, reduce corruption, increase trust and support users. Cryptocurrencies built on distributed ledger technologies (DLT) have emerged as potential gateways to new wealth creation and disruptors across financial markets. Other revolutionary use-cases are being explored in almost every sector, ranging from energy and shipping to media. Blockchain has the potential to upend current models of data ownership, giving users greater control over their data, granting access at a more granular level and enabling micropayments for data usage. In addition, the digital representation of real-world assets on a blockchain, as well as the emergence of new categories of crypto assets, offer new financial opportunities for stakeholders. New economic models could enhance privacy, security, inclusion and individual rights, potentially shifting control of user data from shareholders to consumers while providing access to new funding flows. In sum, DLT has the potential to upend entire systems, but it also faces important policy and cooperation challenges, including lack of interoperability, security threats and potential environmental and financial system impacts. Innovative policy mechanisms are needed to unlock this potential and manage the unforeseen consequences of these new paradigms.

The C4IR Global Network is co-designing and piloting governance protocols to ensure the interoperability and inclusivity of the myriad blockchain experiments attempting to track and manage supply chains. And it is developing approaches to balancing transparency and anonymity on blockchains as well as supporting the creation of a collaborative framework within which Central Banks can responsibly explore and experiment with blockchain given its important potential financial services applications, including digital currencies.

Internet of Things and Connected Devices

There are more connected devices in the world today than humans. These devices, commonly known as the internet of things (IoT), come in infinite forms, from smart building technologies that monitor and manage energy usage to connected vehicles that help anticipate and avoid potential collisions. By 2020, the number of IoT devices is projected to exceed 20 billion, and as they spread to all aspects of day-to-day life, and even become embedded in the human body, questions about data ownership, accuracy and privacy protection take on greater importance. Similarly, in an interconnected world where electric grids, public infrastructure, vehicles, homes and workplaces are capable of being accessed and controlled remotely, the vulnerability to cyber-attacks and the potential for these security breaches to cause serious harm are unprecedented. The C4IR Global Network has co-design an Industrial IOT Security protocol with diverse stakeholders that is now being piloting in various industries. And as new voice-enabled speakers, smart home systems and wearables enter the consumer market, the C4IR Global Network is exploring the possibility of standardized labels or disclosures about public safety risks. Efforts are needed to align the private sector, government and civil society on common approaches to inform, educate and build trust among consumers on topics such as privacy and security. Finally, a very small amount of data (less than 1% according to some studies) is actually used to drive decisions and add value. To unlock data silos and unleash the full potential of the IoT, the C4IR Global Network is developing new models of data sharing within and across the public and private sectors that will be critical to enable cities and rural communities to maximize the cross-cutting value of IoT data and enable more sustainable business models.

Conclusion

This recent profusion of cooperative innovation on digital cooperation shows great promise and is in line with the UN High-Level Panel’s vision of distributed co-governance. However, it does pose a number of specific cross-cutting issues. For example, agility and flexibility in technology governance is one thing, but how and where will broader efforts to strengthen inclusion be advanced and coordinated? This includes not only the digital infrastructure, human and institutional capacity and human rights imperatives emphasized by the UN High-Level Panel Report but also the fundamental question of how economic policy more generally must structurally adapt^[25] to the labor and community dislocation and opportunity- and income-dispersing effects of digital disruption.

It also raises an overall question about systemic coherence: how and where will the dots be connected among initiatives and norms being created in this bottom-up fashion within each technology governance domain, not to mention among them? The IGF is an obvious candidate, as an inclusive multistakeholder forum for dialogue anchored in the United Nations. However, to perform this function well going forward, its official scope will need to expand beyond “internet governance” to digital cooperation and governance more broadly, reflecting the major additional aspects of digital or Fourth Industrial Revolution governance this chapter has surveyed and beyond.

^[1] See https://www8.cao.go.jp/cstp/english/society5_0/index.html

^[2] See https://www.pwc.com/gx/en/issues/analytics/assets/pwc-ai-analysis-sizing-the-prize-report.pdf

^[3] See https://ec.europa.eu/commission/priorities/digital-single-market_en

^[4] See https://www.bain.com/contentassets/37a730c1f0494b7b8dac3002fde0a900/report_advancing_towards_asean_digital_integration.pdf

^[5] See https://www.prnewswire.com/news-releases/global-crispr-technology-market-2018-2027-market-is-expected-to-reach-10-55-billion-300636272.html

^[6] See https://www.blockchain.com/en/charts

^[7] See https://www.nber.org/papers/w24174

^[8] See https://www.nber.org/papers/w24174

^[9] See https://www.rand.org/blog/articles/2018/04/how-artificial-intelligence-could-increase-the-risk.html

^[10] See https://digiconomist.net/bitcoin-energy-consumption

^[11] See https://www.sciencenews.org/article/twitter-bots-fake-news-2016-election

^[12] See http://www3.weforum.org/docs/WEF_Our_Shared_Digital_Future_Report_2018.pdf

^[13] See https://digitalcooperation.org/

^[14] See https://www.canada.ca/en/treasury-board-secretariat/news/2018/11/canada-welcomes-leading-digital-nations-into-the-digital-9.html

^[15] See https://www.weforum.org/centre-for-the-fourth-industrial-revolution

^[16] See https://pm.gc.ca/eng/news/2018/12/06/mandate-international-panel-artificial-intelligence

^[17] See https://standards.ieee.org/industry-connections/ec/autonomous-systems.html

^[18] See https://legalinstruments.oecd.org/en/instruments/OECD-LEGAL-0449

^[19] See https://www.mofa.go.jp/files/000486596.pdf

^[20] See https://www.weforum.org/communities/artificial-intelligence-and-machine-learning

^[21] See https://www.partnershiponai.org/

^[22] See https://www.republique-numerique.fr/pages/in-english

^[23] See http://opendata-ajuntament.barcelona.cat/en/

^[24] See https://contractfortheweb.org/

^[25] See http://www3.weforum.org/docs/WEF_Advancing_Human_Centred_Economic_Progress_WP_2017.pdf