The UK is under no illusions as to the cyber threat posed by China. The UK government and critical industry sectors, such as defence, telecommunications and IT, have all been subject to Chinese cyber intrusions designed to steal data on an industrial scale. This was last called out publicly in 2018 by then-foreign secretary, Jeremy Hunt, who described Chinese attacks against UK managed service providers as ‘one of the most significant and widespread cyber intrusions against the UK … uncovered to date’.

Drawing on its own experiences in the cyber domain, the UK will also fully understand that espionage capabilities can quickly become sabotage capabilities – the hack of a network to steal data can quickly become the hack that brings the network down. And the UK knows that China’s intelligence law requires Chinese companies to provide it assistance if asked to do so. The UK’s assessment of the cyber threat posed by China does not differ from that of the US.

2. The UK may have managed the use of Huawei kit in its 3/4G networks, but its use in 5G networks significantly increases the risk of Chinese espionage and sabotage.

Just as 3/4G networks are entangled together today, 5G will be entangled with 3/4G networks. Given that Huawei is already providing kit in the UK’s 3/4G networks, the theoretical ability of the Chinese to access and sabotage the UK mobile network would be little changed even if Huawei kit were not used in the 5G elements of the networks.

3. Even if the risk doesn’t increase from 3/4G to 5G, the UK shouldn’t be using Huawei in any ‘G’ network because the threat of serious cyber espionage cannot be mitigated.

The basic cyber security measures that have been used for 3/4G also apply to 5G, with the proper use of encryption to ensure the confidentiality and integrity of data being a crucial one. Ironically, it remains the case that those with the best chance of reading traffic on anyone’s mobile networks are the companies providing ‘over-the-top’ encrypted applications, as well as whichever government hosts those companies under the terms of their domestic lawful intercept (so in the UK that is overwhelmingly the Silicon Valley companies and the US government).

Increasingly, the UK finds itself unable to read the encrypted traffic between suspected terrorists in London and Manchester without Silicon Valley’s help. The presence of Huawei makes no difference – even if the Chinese government were able to use the Huawei kit to listen in, it would face the same problem as the UK government. Let’s be clear – Google can get to the content of gmail passing over a bit of Huawei kit, but China cannot.

4. Ok, the real risk isn’t about spying, it is about China’s ability to use Huawei kit to sabotage the network.

The provision of kit into UK mobile networks and the interfaces between those networks and the rest of the UK’s telecommunications infrastructure are complex processes. Any kit that Huawei provides into UK networks will be integrated with kit and over networks run by other providers – such as BT, Vodaphone, Virgin Media, EE and others. Those providers have a degree of visibility and control over the various interfaces, with ‘redundancy’ built in – another basic UK requirement being to build redundancy into traffic routing to ensure the network as a whole can survive the loss of a single element (network resilience).

Additionally, many of the components inside Huawei kit are manufactured by other nations, particularly the US – software from Microsoft, microchips from Intel and Qualcom. Removing kit within a complex twenty-first century telecommunications network based simply on the nationality of the kit’s ‘supply chain’ is almost impossible. National ownership of a piece of kit is not the only deciding factor when it comes to ‘ease of interference’. As an illustration, if the US were behind the Stuxnet attack, as alleged, it interfered with the kit of a German company, Siemens.

In short, bringing down a complex modern telecommunications network is not easy, whichever bit of kit within the network you ‘own’. But even if you could, when would you do it? It is effectively a ‘one shot’ capability – if used by China, it would undermine the position of all Chinese companies in the world tech market, effectively handing the market to exclusively non-Chinese companies. China would therefore presumably save the ‘one shot’ for war or near-war, in which case it would need to be sure it would work. As I have outlined above, that is not easy.

The sabotage risk is, in reality, probably far subtler. It is more likely that China might try to insert damaging code via mobile networks remotely and deniably, with the Huawei kit used to facilitate an insertion or exfiltration of code/data into other networks – it is part of a pathway or a small but essential cog in a bigger wheel. Note again, however, that other countries could get into Huawei (or Nokia or Ericsson for that matter) kit remotely to do the same thing.

5. Given that there is a potential sabotage risk, can the UK really isolate the core of its network from Huawei?

5G is a cool technology, providing greater bandwidth, faster speeds, better quality and instant connections. It is this faster, smarter layer that will enable the truly innovative applications that we call the ‘Internet of Things’, for example, self-driving vehicles.

Sitting behind this are various technologies. The use of higher frequencies (ultimately including ‘millimetre waves’) means that the system can carry more information and support more devices (‘smart things’) at the same time (4G uses data at rates of 200–300 megabits per second, while service providers are ultimately looking to get 5G to above 40 and even up to 100 gigabits per second). There are many more and smaller transmitting and receiving antennae, using less power and covering smaller geographic areas – allowing the transmission and receipt of signals simultaneously through multiple antennae.

5G uses a Cloud Radio Access Network, meaning cheaper infrastructure and less maintenance. Unlike current generations, 5G base stations use ‘beamforming’ to detect and locate the user, and only transmit in that direction. 5G uses ‘Full Duplex Mode’ enabled by high-speed switching that can handle simultaneous transmission and receipt. Using all of the above, a 5G network can be ‘sliced’ and dedicated to a specific task (e.g. one part for phones and one part for driverless cars).

So 5G looks complicated and distributed. But it can still be divided into core and non-core. The latter refers to the myriad of small antennae, small cells and base stations distributed on masts, street corners and rooftops creating ‘smart’ environments. But there still has to be a controlling brain – the handful of main data centres at the heart of the network, with there being only two or three more centres needed in a 5G network than in a 3/4G network. That is the core, which can be owned and protected by UK service providers, such as Vodaphone and the like, including if held in the ‘cloud’. That is why the UK thinks it might be able to manage the overall risk by restricting Huawei kit to the ‘non-core’ network.

6. But isn’t Huawei kit rubbish anyway?

Perhaps the single-most important reason why Huawei 5G kit seems to outperform its rivals is the amount it has invested in R&D, and its deployment support is very good. The UK’s National Cyber Security Centre has, however, been very critical of Huawei’s coding. Nonetheless, kit can still perform well even when the underlying coding is a mess, meaning that it is not configured in a uniform way and is therefore very ‘buggy’, like Huawei’s. The presence of bugs in software is ‘normal business’ – they are not back doors in themselves, but they can be used to create back doors.

An international standard that set how coding is done would have reduced the number and type of bugs, and, therefore, made the kit inherently more secure. This is a crucial point: the international community should have baked security standards into the design of 5G networks from the outset, rather than now trying to retrofit security measures by means of, for example, the core/non-core debate.

This is the key lesson from the current Huawei saga for future generations of critical technology, including Artificial Intelligence. If we did not do enough to establish the right standards for 5G, we should now start developing the best standards for the 6G that we will be installing in a decade.

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This briefing analyzes these surveys in order to make the case for policymakers in key countries and international organizations to expand their use of surveys to better identity, measure, and analyze cross-border data flows and digital trade—and barriers to them. This is particularly important, as what gets measured and surveyed is more likely to get managed and addressed. Countries that value an open, competitive global digital economy need to do more both at home and with like-minded regional and global partners, such as at IDB and OECD, to fill this information gap to better inform domestic policy debates and trade negotiations at the World Trade Organization (WTO) and elsewhere.

Data will naturally flow across borders unless governments enact barriers. Flows of data are important, as they stimulate growth and productivity. They are also critical to trade in all sectors—not just tech—as the Swedish Board of Trade makes clear in its report No Transfer, No Production: a Report on Cross-border Data Transfers, Global Value Chains, and the Production of Goods.Despite the large and growing role of data flows, a growing number of countries are making it harder and costlier—or even illegal—to transfer data.

However, there remains a large gap in the understanding of the extent and impact of these restrictions. Econometric modeling is the most common tool, providing macro-level estimates of the economic impact of restrictions.Firm-level interviews and surveys are a micro-level tool policymakers and other stakeholders should use more extensively to complement formal modeling and fill the knowledge gap regarding the specific impacts.

Surveys are useful, because they allow firms to quantify the levels and values of data flows without disclosing commercially sensitive information. Survey responses provide details about how different firms use and move data to create value, and they provide subjective assessments that help policymakers understand the harms that transfer restrictions create. They also help calibrate the underlying estimates econometric modeling is based on, such as firm data intensity and ad valorem equivalents (i.e. the tariff or tax rate equivalent) of data-flow restrictions.

These surveys come at an important time for the global digital economy. Over 70 countries are negotiating potential new rules on e-commerce and digital trade at the WTO (as well as in other bilateral and regional trade negotiations). The initial insights from these surveys show why there needs to be rules to protect the flow of data, given its critical role in digital trade. If countries are truly committed to updating the global trading system, and making it relevant for modern business, it needs to include strong rules around data flows. In addition, given the growing digitalization of the global economy, policymakers and other stakeholders should build on these surveys to better capture, measure, and analyze the growing role and value of cross-border data flows, digital trade, and e-commerce, and the impact of barriers to them. 

Read the full report here

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“The numerous blockchain networks and DLT platforms will help realize the potential of digital transformation to drive greater economic inclusion. The International Chamber of Commerce (ICC) together with its partners, as neutral conveners of all trade stakeholders across the world, aims at connecting and coordinating these disparate groups in order to accelerate efforts to digitalize trade” said David Bischof, Deputy Director, Finance for Development, International Chamber of Commerce.

“Having a constant need to know all developments and involved parties, this report is an indispensable tool for the entire ecosystem to keep track and align actions.” Bischof added.

Reality Check

We’re living through exciting times. While international trade in goods has seen little innovation since the invention of the container in the 50s, the tedious, labour- and paper-intensive processes required to ship around the world could well become a story of the past thanks to the advent of new technologies, particularly distributed ledger technology (DLT) – colloquially termed “blockchain”. 

Rarely has a technology spurred so much hype and hope amongst the trade and trade finance community. Not without reason: The possibilities that blockchain unlocks to track transactions and exchange assets in real-time, in a trusted and highly secure environment using peer-to-peer validation and networks makes it an appealing tool to remove many of the inefficiencies that hinder one of the oldest forms of traditional finance today.

Over the past few years a myriad of projects have been launched to enhance processes related to trade finance, to digitalize trade documentation, and to reduce inefficiencies in transportation and logistics. Some take the form of multi-player consortia and networks, others are building a fabric layer to interconnect these different projects, and others are built to digitize particular aspects of the trade and supply chain.

These international trade actors are changing fast, but how many of these initiatives have moved beyond a proof-of-concept? What are the challenges that these new actors now face as we go past the trough of disillusionment and exploratory phase of DLT in trade?

Building on the WTO publication “Can Blockchain Revolutionize International Trade?” authored by Emmanuelle Ganne and TFG’s white paper “Blockchain and Trade Finance”, this study provides an overview of the main projects underway in trade, with a focus on trade finance, shipping, and the digitalization of trade documents, and assesses their stages of maturity. Based on a survey of more than 200 actors in the field, it analyses the key challenges that companies involved in blockchain projects are facing and discusses actions that may need to be taken to allow the technology to truly transform international trade. After years of hype around blockchain, the time has come for a reality check.

To access the original source: Click here

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This is to our great loss. A number of countries are currently negotiating international agreements that will constrain the ability of sovereign governments to regulate AI, such as the North American Trade Agreement (NAFTA) and the Trans- Pacific Partnership (TPP)- 11. Likewise, governments around the world are freely spending public funds on new AI clusters designed to shift international comparative advantage toward their favored regions, including the Vector Institute in Toronto and the Tsinghua- Baidu deep- learning lab around Beijing. The international dimensions of AI innovations and policies have not always been well thought out.

This work begins the conversation. China has become the focal point for much of the international discussion. The US narrative has it that Chinese protection has reduced the ability of dynamic US firms such as Google and Amazon to penetrate Chinese markets. This protection has allowed China to develop signifi cant commercial AI capabilities, as evidenced by companies such as Baidu (a search engine like Google), Alibaba (an e-commerce web portal like Amazon), and Ten-cent (the developer of WeChat, which can be seen as combining the functions of Skype, Facebook, and Apple Pay).

While no Chinese AI- intensive company has household recognition outside of China, everyone agrees that this will not last. Further, a host of behind- the- border regulatory asymmetries will help Chinese firms to penetrate Canadian and US markets.Even the Pentagon is worried. Chinese guided- missile systems are sufficiently sophisticated that they may disrupt how we think of modern warfare; large and expensive military assets such as aircraft carriers are becoming overly vulnerable to smart weapons.

This may do more than transform the massive defense industry; these AI developments may radically shift the global balance of power.As international economists, we are used to hype and are typically dis-missive of it. Despite AI’s short life —AI’s rapid insinuation into our daily economic and social activities forces us to evaluate the international implications of AI and propose best- policy responses. Current policy responses often rest on a US narrative of a zero- sum game in which either the United States or China will win.

Is this the right premise for examining AI impacts and for developing AI policies? Further, calls for immediate action by prominent experts such as Bill Gates, Stephen Hawking, and Elon Musk will likely encourage governments to loosen their pocketbooks, but will government subsidies be effective in promoting broad- based prosperity or will subsidies become yet another form of ineffective corporate welfare? What specific policies are likely to tip the balance away from ineffective corporate handouts?Using comparative advantage theory, trade economists have thought long and hard about the right mix of policies for successfully promoting industry.

Many of our theories imply a laissez-faire free- trade approach. However, since the early 1980s our theories have shown that certain types of government interventions may be successful,. These theories emphasize the role of scale and the role of knowledge creation and diffusion. Unfortunately, the precise policy prescriptions produced by these theories are very sensitive to the form of scale and the form of knowledge creation/ diffusion. And competition can play an important role too.

We therefore start in section 19.2 by identifying the key features of AI technology in regard to scale and knowledge.

To date there are no models that feature the particular scale and knowledge characteristics that are empirically relevant for AI. In section 19.3 we use these features (a) to off er some suggestions for what an appropriate model might look like, and (b) to draw implications for policy.

This leads to high- level thinking about policy. For example, it provides a foundation for assessing recent proposals put forward by AI researcher Geoff Hinton and others on the potential benefit of public investments in AI.

However, these models are not sufficiently fine-grained to directly capture existing regulatory issues that “go behind the border” such as privacy policy, data localization, technology standards, and industrial regulation. In section 19.4 we therefore review the many behind- the- border policies that already impact AI and discuss their implications for comparative advantage and the design of trade agreements. We begin with a factual overview of the international dimensions of AI.

Read the full report here

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Do industries shed or create jobs when they adopt new labour-saving technologies? This column shows that manufacturing employment grew along with productivity for a century or more, and only later decreased. It argues that the changing nature of demand was behind this pattern, which led to market saturation. This implies that the main impact of automation in the near future may be a major reallocation of jobs, not necessarily massive job losses.

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Many nations are racing to achieve a global innovation advantage in artificial intelligence (AI) because they understand that AI is a foundational technology that can boost competitiveness, increase productivity, protect national security, and help solve societal challenges. This report compares China, the European Union, and the United States in terms of their relative standing in the AI economy by examining six categories of metrics—talent, research, development, adoption, data, and hardware.

It finds that despite China’s bold AI initiative, the United States still leads in absolute terms. China comes in second, and the European Union lags further behind. This order could change in coming years as China appears to be making more rapid progress than either the United States or the European Union. Nonetheless, when controlling for the size of the labor force in the three regions, the current U.S. lead becomes even larger, while China drops to third place, behind the European Union. This report also offers a range of policy recommendations to help each nation or region improve its AI capabilities.

Download the report.

Introduction

The United States reaped tremendous economic benefits from the last wave of digital innovation, becoming home to some of the world’s most successful tech companies, such as Amazon, Apple, Facebook, Google, Intel, and Microsoft. Meanwhile, many parts of the world, including the European Union, paid an economic price staying on the sidelines. Recognizing that missing the next wave of innovation—in this case, AI—would be similarly problematic, many nations are taking action to ensure they play a large role in the next digital transformation of the global economy.

China, the European Union, and the United States are now emerging as the main competitors for global leadership in AI. Indeed, China, which achieved success in the Internet economy in part by shutting out U.S. firms, has clearly stated its ambition of achieving dominance in AI—both to increase its competitiveness in industries that have traditionally been vital to the U.S. and EU economies, and to expand its military power.^[1] Moreover, the EU’s coordinated plan on AI states that its “ambition is for Europe to become the world-leading region for developing and deploying cutting-edge, ethical and secure AI.”^[2] The outcome of this race to become the global leader in AI will affect the trio’s future economic output and competitiveness, as well as military superiority.

Findings

Overall, the United States currently leads in AI, with China rapidly catching up, and the European Union behind both. The United States leads in four of the six categories of metrics this report examines (talent, research, development, and hardware), China leads in two (adoption and data), and the European Union leads in none—although it is closely behind the United States in talent. Out of 100 total available points in this report’s scoring methodology, the United States leads with 44.2 points, followed by China with 32.3 and the European Union with 23.5.

The United States leads for several reasons. First, it has the most AI start-ups, with its AI start-up ecosystem having received the most private equity and venture capital funding.^[3] Second, it leads in the development of both traditional semiconductors and the computer chips that power AI systems.^[4] Third, while it produces fewer AI scholarly papers than the EU or China, it produces the highest-quality papers on average.^[5] Finally, while the United States has less overall AI talent than the European Union, its talent is more elite.^[6]

China is ahead of the European Union in AI and appears to be quickly reducing the gap between itself and the United States. It has more access to data than the European Union and the United States, which is important because many of today’s AI systems use large datasets to train their models accurately. In venture capital and private equity funding, Chinese AI start-ups received more funding than U.S. start-ups in 2017, but not in 2016 or 2018.^[7] China, however, is clearly behind both the United States and the European Union in high-quality AI talent. Several European Union member states, including Italy, had more AI researchers ranked in the top 10 percent internationally than China as of 2017.^[8] Nonetheless, China has made clear progress relative to the United States in most metrics, and significantly outpaces the European Union in funding and AI adoption.

The European Union has the talent to compete with the United States and China. Indeed, it has more AI researchers than its peers, and typically produces the most research as well.^[9] However, there is a disconnect between the amount of AI talent in the EU and its commercial AI adoption and funding. For example, AI start-ups in the United States and China both received more venture capital and private equity funding in 2017 alone than EU AI start-ups received in the three years covering 2016 through 2018.^[10] The European Union’s laggard position reduces its ability to not only enjoy the economic and social benefits of AI, but also influence global AI governance, which is a goal of the European Commission.^[11]

To read the full report, please click here. 

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It can be argued that geopolitical practice is increasingly changing from direct and indirect territorial competition over strategic resources into competition over direct or indirect control of the key functions of global connections, such as the maritime, air, space, and digital domains. The focus here is on the newer type of functional competition over the digital domain and its social media platforms.

For resourceful state-level players, these new vulnerabilities offer lucrative, exploitable opportunities by: (1) Destabilizing: innovating new means of sowing and catalyzing societal divisions before, during and after democratic processes such as elections and referendums. (2) Scaling up: massively scaling up older practices such as espionage, as well as building multipurpose informer, influence, and corruptive networks.

In the first sense, social media can be utilized as a part of destabilizing campaigns, as the recent redacted version of the 2019 Mueller Report – presenting the findings of the official investigation into Russian meddling in the 2016 US elections – revealed. One aspect of the meddling operation was the use of the Russian quasi-governmental Internet Research Agency (IRA) across different social media platforms. According to the report, ‘by the end of the 2016 U.S. election, the IRA had the ability to reach millions of U.S. persons through their social media accounts. Multiple IRA-controlled Facebook groups and Instagram accounts had hundreds of thousands of U.S. participants. IRA-controlled Twitter accounts separately had tens of thousands of followers, including multiple U.S. political figures, who retweeted IRA-created content’. The digitalized geopolitical abuses of the platforms were also in evidence in European politics. Most of the discussions in this respect have focused on the 2017 French and German elections, and on the 2016 UK referendum on EU membership.

[To read the original column, click here.]

Copyright© 2019 Finnish Institute of International Affairs. All rights reserved. 

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• Explosive growth of digital products and services shows that the benefits of data flows far outweigh the costs. Real anxieties about privacy and security, however, could undermine confidence in the digital marketplace if we do not update our laws, norms, institutions, and technologies.
• Slow productivity growth in many industries stems from a lack of information intensity—too little data. Policy should encourage the use of more data, while putting consumers in control of sensitive information.
• We need a new national law to consolidate existing industry-specific laws, prevent a patchwork of conflicting state laws, and clarify the Federal Trade Commission’s enforcement strategy for the digital age.

Introduction 

In a world of exploding information, privacy and security are central but vexing policy questions. How we govern the collection and use of data will affect public trust of commercial and public institutions and also help determine the rate of innovation across the economy.

Intense engagement with digital products and services, resulting in an exaflood of data usage, demonstrates that firms and consumers enthusiastically embrace the digital world. In 2018, US internet traffic reached nearly 50 exabytes per month, and in 2019, global data center traffic is expected to reach 14 zettabytes.¹ Voting with their feet, consumer actions show that the benefits of these data flows far outweigh the costs.

At the same time, high-profile data breaches, surprisingly intrusive web tracking, and the confusing nature of social interactions in a hyper-transparent world have caused anxiety—for consumers seeking reassurance, for businesses seeking guidance, and for policymakers seeking the right legal balance.

As information continues to diffuse across the economy and culture, digital privacy and security questions are likely to grow in dimension and intensity. Successful economies and cultures are built on trust. If consumers lose trust in the firms offering them products and services, or in the government’s basic protections, the health of the digital economy and our civic culture could deteriorate.

Current laws, written for siloed industries in a pre-digital era, are likely not up to the task. In a world of extreme data abundance and dynamic cross-industry and cross-border data flows, we may need a new privacy law to protect consumers and encourage open-ended innovation. Privacy is a slippery concept, and it is therefore important to set expectations by defining an analytical framework. Bolstering the approach of the Federal Trade Commission (FTC), which focuses on consumer welfare and rigorous analysis of costs and benefits, is a good place to start.

Laws and regulations, however, cannot solve every problem. Evolving social norms, more robust institutions, and new privacy-promoting technologies will play central roles.

[To read the original column, click here.]

Copyright © 2019 American Enterprise Institute. All rights reserved.

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[To read the original article, click here]

Copyright © 2019 Center for Strategic and International Studies. All rights reserved.

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