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The Obama Administration’s bold agenda to establish these rules across Europe and the Asia-Pacific did not yield lasting success, with the failure of the Transatlantic Trade and Investment Partnership (TTIP) negotiations and the Trump Administration’s withdrawal from the Trans-Pacific Partnership (TPP). Nonetheless, the key elements of US digital trade policy enjoy bipartisan policy support, providing a promising basis for the next Democratic administration to re-engage with Europe, our biggest digital trading partner.

Part 1 of this issue brief explains why international rules are needed to protect and facilitate digital trade. Part 2 describes the turbulent past decade in transatlantic trade relations and the growing importance of US digital trade with Europe. Part 3 explains why the US government and the European Union (EU), during TTIP negotiations, were unable to agree on a digital trade chapter, including a key provision guaranteeing the free flow of data. Finally, Part 4 suggests how two parallel sets of trade negotiations beginning early this year — between the EU and the United Kingdom (UK) and between the United States and the UK — may help a future US Administration end the transatlantic stand-off over digital trade.

To view the full report at Progressive Policy Institute, please click here

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Economies with already strong underlying information technology are proving to be more resilient than those without this infrastructure already in place.  At a recent event, I listened to officials from Cambodia and Kenya explain how their strong digital track records are paying off during the current crisis.

In Cambodia, which had previously established an enabling regulatory environment around digital financial services, citizens were already accustomed to sending and receiving payments digitally, making it possible for the government to add tax functionality on to the pre-existing digital payment platforms. Similarly, in Kenya, citizens’ relative comfort with digital payments led to a recent uptick in the use of its e-tax system. The Kenya Revenue Authority has also been able to rely on its digital systems to obtain real-time data on emergency-related shifts in consumer spending, which helps the agency to predict the impact on revenues.

But the type of digital transformation necessary to get to this level is comparable to moving a boulder to the top of a mountain. It’s a long, arduous process, and it’s possible to lose footing along the way. Many economies, especially developing countries, rely on deeply entrenched systems and fight an uphill battle when it comes to public trust. In fact, many of the world’s lowest-income economies struggle to collect enough taxes to cover basic state functions. Add a global crisis into the mix and these tenuous relationships between taxman and citizen are likely to fall apart.

The current crisis provides an opportune moment to rework revenue strategies to be more digitally driven.  Tax administrations must shift the focus from simply processing taxpayers’ data to proactively improving compliance, policies, and efficiency. Modern revenue strategies will, to a large extent, have to run on digital platforms because they are necessary to effectively pursuing critical policy objectives such as:

• Broadening the tax base. Data-centric approaches can be used to close gaps and take advantage of missed opportunities without necessarily increasing the level of taxation. Such measures include: requiring e-commerce platforms to report sales in order to facilitate the collection of VAT and customs duties; analyzing past tax filings of citizens seeking relief under current stimulus programs to verify compliance; and supporting the collection of property taxes by matching the land registry with the taxpayer file.
• Enhancing transparency and trust. Establishing electronic platforms for tax registration, filing, payment, and dispute resolution make processes clear for citizens, provide assurances that tax payments end up in an actual government account, and reduce the risk of officials abusing their discretion. Implementation of technologies such as the MIT-incubated OPAL (Open Algorithm) provides researches, think tanks, or any citizen the ability to independently analyze tax data without having access to personally identifiable information. This will provide unprecedented transparency.
• Reducing the compliance burden. We know from a survey of 190 economies that it is getting easier for people and businesses to pay taxes. There are now 106 economies using electronic filing systems, double the number in 2004. Digital technology is reducing the time spent on paying taxes as well as the total number of individual payments taxpayers must make each year.
• Improving administrative efficiency. As governments mature in their use of information technology, they will be able to achieve substantial efficiency gains. For countries beginning their digital transformation, AI-enabled data capture of paper-based records can speed up the digitalization and reliability of the data. Others find significant value through the simplification of procedures and matching of filing information with third-party data sets. For more advanced tax administrations, the use of advanced analytics to identify underreporting will be a key value driver. In the current crisis, some administrations are also rethinking their balance between offsite and onsite audits.
• Advancing growth and other policy objectives. As the central depository of citizen data, tax administrations play an increasing role in advancing non-tax related objectives. For example, by using taxpayer data to: verify beneficiaries under cash transfer programs, monitor the consumption of goods with detrimental health impacts (e.g., alcohol and cigarettes), model tax policy responses to curb carbon emissions, identify growth drivers in the economy, detect labor market violations, and ascertain the well-being of vulnerable groups in society.

Progress toward these objectives has been uneven and the World Bank cannot get this “modernization boulder” to the top of the mountain alone. To help countries accelerate digital transformation, we need partners with multidisciplinary expertise who can help pull while we push. To that end, we co-founded the Prosperity Collaborative. This new multi-stakeholder initiative is dedicated to helping countries create better tax systems through innovative technology. Together with EY, New America, MIT and the Boston Global Forum, we are just getting started on a journey to bring tangible benefits to developing countries.  Our current priorities are –

• Developing global solutions to build capacity among developing countries and emerging market to undertake a successful digital transformation of their tax administrations;
• Promoting thought leadership on tax and technology;
• Exploring the creation of a mechanism to identify, prioritize, fund, and implement digital public goods for use by tax administrations;

By bringing these leading organizations together under the banner of the Prosperity Collaborative, we aim to create solutions that are well-targeted and easily replicable across different country contexts. Ultimately, we aim to create digital public goods that can be built once and deployed anywhere.

To view the original World Bank Blog post, please click here

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While powerful megatrends like global trade tensions, climate change, new technology innovations, and the current COVID-19 crisis impact all parts of the globe, the reality of those impacts – and therefore the necessary responses to them – are inherently driven by unique regional characteristics and the regional enabling environments. The Global Network of Advanced Manufacturing Hubs (AMHUBs) connects regional manufacturing ecosystems to help rapidly transform manufacturing to keep pace with the global megatrends that might otherwise create disruptions for manufacturers around the globe.

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These models affect millions of people through critical decisions related to credit approval, insurance claims, health interventions, pre-trial release, hiring, firing, and much more. While facial recognition, autonomous weapons, and artificial general intelligence tend to dominate the conversation, the debate on regulating more commonplace applications is equally important.

The new white paper echoes the principles of the earlier AI Ethics Guidelines: non-discrimination, transparency, accountability, privacy, robustness, environmental well-being, and human oversight. This new paper goes beyond many prior AI ethics frameworks to offer specific AI regulatory options. Some of these options would be alterations to existing EU law, such as ensuring product liability law can be applied to AI software and AI-driven services.

More noteworthy, however, is the proposal to consider entirely new requirements on high-risk AI applications. The high-risk categorization is limited to specific use-cases within specific sectors where there are particularly large stakes. The report explicitly names sectors such as transportation, healthcare, energy, employment, and remote biometric identification, but others like financial services could be included.

Within these sectors, only especially impactful AI applications would receive the label “high-risk” and accompanying oversight. So, while a healthcare allocation algorithm may be included, a hospital’s AI-enabled scheduling software would probably not qualify.

The report details a series of possible oversight mechanisms for applications deemed high-risk AI. Some of these would set standards for the use of AI, such as using representational training data and meeting defined levels of model accuracy and robustness. Others require storage of data and documentation, potentially enabling government auditing of AI models. Transparency measures are also under consideration.

These might require reporting to regulatory authorities (e.g. an analysis of bias for protected classes) or directly to consumers affected by the model (e.g. an individualized explanation for their model outcome). Not all these requirements would apply to all high-risk AI, but instead some subset of these mechanisms would be paired with each high-risk application.

In weighing how these mechanisms might work, it’s valuable to contemplate how various interventions might affect prominent instances of AI harms. For instance, would enabling audits slow the proliferation of pseudoscientific hiring software across human resources departments? Would reporting requirements help identify discriminatory patient treatment in healthcare allocation algorithms?

Would a more rigorous testing process of Tesla’s autonomous driving have made them more resistant to the stickers that trick the vehicles into driving at dangerous speeds? These are questions that the EC paper is raising—questions that the U.S. policy-makers should be asking, too. Given a type of algorithm being used for a particular high-risk purpose, what oversight mechanisms might ensure that it functions in a legal and ethical way?

While the EC paper is exploring new requirements, it also makes clear that enforcing extant law is difficult due to the complexity and opacity of AI. It takes specific expertise in programming and statistics to evaluate the fairness and robustness of AI models, which regulatory agencies across the EU may not yet have.

This is very likely an issue in the United States, too. AI models can easily run afoul of many federal requirements, such as the Civil Rights Acts, the Americans with Disabilities Act, the Fair Credit Reporting Act, the Fair Housing Act, and financial modeling regulations. It is not clear that U.S. regulatory agencies are staffed to handle this emerging challenge.

The EC paper notes that investing in its ability to enforce AI safeguards has real advantages for industry, too. The European approach argues that responsible regulation will build public trust in AI, allowing companies to build automated systems without losing the confidence of their customers. Broadly speaking, the EC’s perspective is positive about the emergence of AI as a general-purpose technology.

It presents AI as a powerful tool to improve scientific research, drive economic growth, and make public services more efficient. They seek to attract €20 billion ($21.7 billion USD) in annual funding for AI, some of which would come from expanding EU spending. This effort would also be bolstered by an ambitious strategy to incentivize data sharing and expand access to cloud infrastructure.

To view the full blog, click here.

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We are on the cusp of colossal changes. But you don’t have to take Mr. Putin’s word for it, nor mine. This is what Erik Brynjolfsson, director of the MIT Initiative on the Digital Economy and a serious student of the effects of digital technologies, says:

“This is a moment of choice and opportunity. It could be the best 10 years ahead of us that we have ever had in human history or one of the worst, because we have more power than we have ever had before.”

To understand why this is a special time, we need to know how this wave of technologies is different from the ones that came before and how it is the same. We need to know what these technologies mean for people and businesses. And we need to know what governments can do and what they’ve been doing. With my colleagues Wolfgang Fengler, Kenan Karakülah, and Ravtosh Bal, I have been trying to whittle the research of scholars such as David Autor, Erik Brynjolfsson, and Diego Comin down to its lessons for laymen. This blog utilizes the work to forecast trends during the next decade.

4 WAVES, 3 FACTS

It is useful to think of technical change as having come in four waves since the 1800s, brought about by a sequence of “general purpose technologies” (GPTs). GPTs are best described by economists as “changes that transform both household life and the ways in which firms conduct business.” The four most important GPTs of the last two centuries were the steam engine, electric power, information technology (IT), and artificial intelligence (AI).

All these GPTs inspired complementary innovations and changes in business processes. The robust and most relevant facts about technological progress have to do with its pace, prerequisites, and problems:

• Technological change has been getting quicker. While the pace of invention may not have accelerated, the time between invention and implementation has been shrinking. While average implementation lags are difficult to measure precisely, it would not be a gross oversimplification to say that they have been cut in half with each GPT wave. Based on the evidence, the time between invention and widespread use was cut from about 80 years for the steam engine to 40 years for electricity, and then to about 20 years for IT (Figure 1). There are reasons to believe that the implementation lag for AI-related technologies will be about 10 years. With technological change speeding up and first-mover advantages as big as they have always been, the need for large and coordinated investments is growing.
• Leapfrogging is practically impossible. While a special purpose technology such as landline telephones bodog online casino can be skipped in favor of a new technology that does the same thing such as, say, mobile phones, it is difficult for countries to leapfrog over general purpose technologies. For a country to overtake another, it must first catch up. Technological advancement is a cumulative process. Business process innovations needed to utilize the steam engine were necessary for firms to take advantage of electric power. More obviously, electricity was a precondition for information technology. Regulations that facilitate or impede technical progress, education and infrastructure, and attitudes toward the social change that accompanies new technologies matter as much as the technologies, pointing to the need for complementary policies that shape the economy and society.
• Automation is labor-share reducing, not labor displacing. While the most commonly expressed concern today is that the spread of artificial intelligence will replace workers with smart machines, the effects of earlier GPTs are better summarized as reducing the share of labor earnings in value added. But the evidence also suggests that since the 1970s, automation in relatively advanced economies has put pressure on labor earnings. Put another way, the concern should not be widespread unemployment but the fact that incomes are becoming increasingly skewed in favor of capital over labor. This means that countries that have efficient arrangements for addressing distributional concerns have an advantage over those that don’t.

To view the full blog, click here.

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Digital data can be recorded, stored, compressed or transferred without any loss of information and quality. The enhancement of these characteristics has been essential for the development of computing, to the point that the term digital has entered into everyday language to generically refer to computer science applications. The development of ever more sophisticated algorithms, combining this data through calculation, makes it easier to solve problems previously considered as too complex.

The continuously improving power of microprocessors is reducing calculation times. The implementation of common protocols to easily exchange data between computers is redefining the concept of connectivity between people. Information, commands and stimuli are circulating in ever greater numbers and dramatically changing how complex systems interact and operate.

Digital technology: a political issue

Therefore, the trend of long-distance communication, which started with writing and continued with the printing press, telegraph, telephone and radio, carries on.

The digital revolution is dramatically changing large areas of human activity. It is shaping globalization by changing the distances between people. Transport, logistics, energy distribution, international finance and critical infrastructure management systems could not function without its applications. The volume of email exchanges is also impressive: 44.7 billion SMS and MMS messages were sent in France in the first quarter of 2018. As of 12 August 2019, more than 45,584 billion emails had been shared worldwide since the beginning of the year.

In the military field, the most advanced armies have integrated battlefield digitalization into their thinking. Military headquarters operate in a more decentralized way, taking advantage of the resources provided by computerization, materializing the advent of a “revolution in military matters”.

From a cultural point of view, games are played on a network. The most talented players earn their living by participating in media tournaments. Special effects are pervading cinema screens, bringing artificial universes to life. A digital culture is emerging.

Digital technology is at the heart of economic, military and cultural issues. It has entered into the everyday life of all people connected to the Internet worldwide. It provides resources in terms of wealth, power, control of society and privacy. For example, Denmark, which is aware of these issues, appointed a Tech Ambassador in 2017. It is legitimate to talk about digital power.
What is power?

Defining the concept of power is a challenge. Common sense accepts that “power” on the international stage is the equivalent of “authority” within societies. However, such an understanding is of limited use. The national and international stages operate under different rules. Authors seeking to understand it acknowledge that it is one of the most controversial terms in international relations.

However, two major themes regularly recur in discussions. The first attempts to make this concept operative. If power exists, it must be possible to define its components and assess them, to measure them in order to act rationally. In this context, power has long been reduced by the realist school to geographical location and to the sum of military, demographic or economic resources.

The most intangible components, such as national pride, the quality of staff and policy, could also count. This accountable and analytical approach, however, is criticized insofar as it only reveals the potential of power. If a state actor does not combine them effectively, it does not guarantee any results. The Soviet Union had many of these advantages, but collapsed without fighting.

Another theme often recurs in discussions on the nature of power. Power is what decides the outcome of the interaction between two state entities or actors in the international system. It no longer refers to a potential, but “to taking action”. In a seminal article, Robert Dahl defines it as: “A has power over B to the extent that A can get B to do something that B would not have otherwise done”.

Power restricts, but not necessarily in a violent way. It can be exercised through seduction, rather than by the brute imposition of will. Finally, power corresponds to an actor’s ability to change the behavior of other actors on the international stage in a favorable direction.

What is digital power?

How can we describe digital power, sometimes called cyberpower, in this context? We will consider digital power as any actor’s ability to exploit digital data to help change the behavior of other actors on the international stage and to achieve its own ends.
It extends beyond the conventional state framework and reconfigures the standard categories, since all connected actors are theoretically likely to have a part in it.

Furthermore, the sources of digital power lie in the exploitation of a synthetic environment and data. This study aims to understand how “intangible” power manages to influence events in the real world and to describe its potential, its applications, and its restrictions.

Digital power transforms the real world through enhancing cyberspace’s network properties (1) and new practices of domination that are imposed on it (2). Its components can be deduced from this (3). However, it is likely that its exercise will be changed in the future through a more assertive, proactive approach by actors in the real world (4). Finally, it is like a kaleidoscope, with several aspects whose coordination sometimes generates considerable tension.

To view the full report, click here.

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The 4IR will affect how companies produce goods and services and what they will produce. Based partly on interviews with Swedish industrial companies, we have identified the following five major production trends: i) automation of physical and digital processes (eventually possibly resulting in the spreading out of production where computers make the decisions), ii) a move towards mass customisation, iii) accelerated servicification, iv) increased specialisation, and v) disintegration of global value chains (GVCs) and production in ecosystems. The technologies will – in turn – affect trade in the following three ways:

1. Improve trade logistics and lower transaction costs.
2. Change the actual content of what firms trade – moving from goods to services and data.
3. Change production processes and the location of production. Technologies can lead to automation and, in turn, the possibility of dispersed, self-orchestrated production. The impact on trade is likely to be significant.

First, moving production closer to customers to serve local markets will lead to less measured trade. Second, the GVC setup will change when companies no longer produce their goods in one place. Beyond being close to customers, companies want to be close to “hubs”, i.e., centres of coopetition, innovation and collaboration. Again, this will affect the GVC set-up. Third, trade flows will change since reorganised GVCs lead to changed movements of the inputs and regional sourcing. Fourth, trade participation will change, for both for countries and firms. For countries, trade participation will bodog poker review change as new GVC set-ups will make the receiving countries importers of inputs and exporters of the product now produced in that same country. For companies, often SMEs, new technologies allow them to enter the supply chain and participate in production.

The technological opportunities of the 4IR will lower the threshold to enter trade, especially for SMEs. Many SMEs have already stepped over the threshold and more will follow. However, taking the step is generally more difficult for SMEs. One central reason is that the benefits of automation have to be even more certain to small companies. Uncertainty about which direction the 4IR will take is a barrier for companies entering the 4IR.

To read the full report, click here

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Today, that growth and innovation is threatened as countries are considering terminating this agreement and imposing – for the first time ever – customs duties on software, music, film, and other digital products and services transmitted electronically over computer networks. Such duties jeopardize US jobs and exports. US policymakers should encourage countries to vote in favor of an extension of the Moratorium and should resist efforts to negotiate these issues at the World Customs Organization (WCO), which lacks the mandate to set such duties.

Why Does the WTO Moratorium Matter?

Customs duties on electronic transmissions would impact a wide range of US digital exports – potentially including subscription or streaming services for music, film, and publications; cloud and other remote software services; app updates and software security patches; data used in manufacturing plants; and a broad catch-all category of “other digital products.”

Some countries have even begun, or are considering, imposing customs duties and requirements on cross-border electronic transmissions. For example, in 2018, Indonesia issued Regulation No.17/PMK.010/2018 (Regulation 17), which amends the Indonesian Harmonized Tariff Schedule to add Chapter 99: “[s]oftware and other digital products transmitted electronically.” The measure has never been fully implemented, but if the Moratorium is terminated this could very well change.

If implemented around the world, measures imposing customs duties on electronic transmissions would have an immediate impact on the global economy – harming not only American digital exporters and workers, but also local industries, workers, and consumers in the implementing countries.

The United States Stands to Lose Jobs and Exports Across Digital Industries if Countries Impose these Duties

Software contributes $1 trillion to US Gross Domestic Product (GDP) and employs over 10 million Americans in jobs that pay more than two times the national average wage. Ending the Moratorium and imposing customs duties on electronic transmissions of software would jeopardize this economic prosperity. Additional impacts exist for American film, music, and other digital exports too.

Regulation 17 purports to cover a wide array of categories, classified in Indonesia’s tariff schedule between subheadings 9901.10.00 to subheading 9901.90.00, including “multimedia (audio, video or audiovisual)”; operating system software; application software; “support or driver data, including design for machinery system”; and a broad catch-all category covering “other software and digital products.”

Countries Imposing Customs Duties Face the Greatest Economic Risks

Countries imposing these duties have the most to lose: Such duties put at risk those countries’ global competitiveness, exports, exports, jobs, and consumer welfare. For example, a country that levies such duties would increase its own industries’ costs of accessing critical technologies and data, including productivity-enhancing software solutions; scientific, research, and other publications; and manufacturing data, blueprints, and other operational information.

Local industries need cross-border access to best-in-class software and data. Faced with higher software costs, local industries will become less competitive vis-à-vis their foreign competitors – threatening both domestic and export market sales. Furthermore, as customs duties would impose an unnecessary burden on local industries, they would also undermine those countries’ attractiveness as a destination for investment and R&D.

Estimated trade impacts are striking. According to a study recently published by the European Centre for International Political Economy (ECIPE), gross domestic product (GDP) losses would exceed the value of customs duties collected by 160 times for Indonesia, 49 times for India, and over 25 times for South Africa, when the risk of retaliatory or corresponding duties imposed by other countries is taken in to account.

Countries Imposing Customs Duties Also Face Legal Risks

Countries imposing such duties on electronic transmissions would also create unnecessary legal risk for themselves. Some countries have discussed the imposition of duties on digital services provided via the cloud or remote access or the imposition of such duties exclusively on foreign enterprises. These scenarios raise serious questions regarding both differential treatment and the scope of WTO Member authority to impose tariffs on such services.

The nature of electronic transmissions, which often consist of data packets transiting multiple servers in multiple jurisdictions, makes country of origin determinations difficult – if not impossible. Additionally, for those seeking to use the WCO to negotiate these tariffs or to address related legal questions, it is important to recall that the WCO’s mandate is limited to enhancing the effectiveness and efficiency of customs administrations – not tariff negotiations or determinations of the WTO consistency of such tariffs.

Is There Another Way?

Discussions are underway among countries at the Organization for Economic Cooperation and Development (OECD) to reach a multilateral agreement to address the challenges to the international tax system posed by an increasingly digitized global economy. Any such internal taxes would need to be applied on a neutral and nondiscriminatory basis, consistent with WTO and other international obligations.

Conclusion

We respectfully ask the US government to encourage countries to vote in favor of an extension of the Moratorium and to resist efforts to improperly negotiate these issues at the WCO.

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Numerous misconceptions and competing narratives around China’s innovation economy have made it difficult for U.S. policymakers to understand the AI ecosystem in China and its links to AI innovation in the United States. This report seeks to improve this understanding by examining China’s progress toward achieving its four strategic goals. The centerpiece of China’s national AI strategy is the New Generation Artificial Intelligence Development Plan (NGAIDP), released by the State Council in 2017. Part of China’s ambitious Made in China 2025 (MIC2025) initiative, NGAIDP outlines a series of strategic initiatives to make China the world leader in AI by 2030. The plan highlights the four strategic goals China seeks to achieve in its pursuit of global AI leadership:

1. Make China the center of fundamental AI research and AI theory development;
2. Lead applied research and development of cutting-edge AI products and services;
3. Build a world-leading domestic AI industry and
dominate global markets for AI; and
4. Leverage AI to increase efficiency in traditional industries and move up the global value chain.

But China’s approach to AI differs from traditional Chinese state planning. China’s high-tech companies are a new breed of Chinese state champions, not having grown up under the wing of the Chinese Communist Party (CCP). In contrast to other industries like banking or telecommunications, companies like the BATs (Baidu, Alibaba, and Tencent) are not former state-owned enterprises (SOEs) and lack the formal links to the CCP that state champions in other industries possess. As Chinese officials and technologists repeatedly emphasize, NGAIDP, MIC2025, Internet+, and other Chinese industrial policies bodog sportsbook review for high-tech industries serve as guidance and signaling mechanisms to the private sector rather than direct government control Chinese leaders recognize that achieving the four goals requires more than just investment in fundamental research. Rather, they utilize an ecosystem approach, combining workforce development, fundamental and applied R&D, deployment of enabling technologies and infrastructure, and incentives for AI adoption in traditional industries. China’s progress in realizing these goals has become a subject of intense interest as the U.S.-China relationship comes to be increasingly defined by technological competition.

China has made significant progress toward developing homegrown AI talent but still struggles to retain the talent it produces. The Chinese government has helped expand AI programs at universities across the country, making China the world’s second-largest home for AI talent, and has utilized the Thousand Talents Program to draw technologists and researchers to Chinese institutions. However, China continues to struggle to retain elite talent, who tend to prefer U.S. and global institutions because they provide the opportunity to work with global leaders in their field without any of the concerns over intellectual independence, air quality, food safety, or educational quality for their families.
Aggressive investment in AI R&D from both the public and private sectors has helped drive significant progress in China’s AI research and industrial bases, but producing unique research and cutting-edge technologies remains a challenge for China. The United States is still responsible for the highest-impact research, but Chinese scholars are increasingly gaining prominence in the field. Focused investment in strategic AI verticals like autonomous vehicles, facial recognition, and natural language processing has helped to boost industry players in China, and the development of digital platforms by internet giants like the BATs is driving investment in new AI tools and applications.

The development of enabling technologies and infrastructure for AI has benefited from China’s ecosystem approach to AI investment. Major national projects to promote investment in key technologies like the internet of things, 5G networks, cloud computing, and robotics are helping China to advance its AI goals by spurring the growth of the requisite physical and digital infrastructure that success in AI will
depend on.

Finally, while China is working to spur AI adoption in traditional industries, the country faces a number of significant challenges. In some areas, such as consumer apps and digital services, Chinese companies have developed world-leading applications, leveraging their massive consumer base and bundled app ecosystems to build enormous databases on Chinese consumers. But AI’s true potential lies in unlocking significant productivity gains and competitiveness through the integration of AI into enterprises and traditional industries. Low rates of digitization among Chinese enterprises, barriers to accessing public data, lagging cloud adoption, uncertain data quality, lack of data diversity, and protectionist data policies make that difficult. Until these issues are rectified, AI developers in China will struggle to create AI applications that produce value for China’s traditional industries.

Overall, China’s progress toward AI leadership remains uneven, and the global AI ecosystem, led by the United States and key allies like the United Kingdom and Canada, continues to attract the top talent, produce the highest-quality research, and be best-positioned to capture the greatest value from AI deployment throughout the global economy. However, China is utilizing every available lever of state power and investing significant attention and resources to develop its AI ecosystem and become a leader in AI innovation. Led by private companies and researchers and supported by significant funding and enabling policies from the Chinese government, China will almost certainly continue to grow its contributions to AI research and application development, expand its AI industries and increase its exports of intelligent products and services, and perhaps even overcome its legacy challenges to increase Chinese competitiveness in traditional industries.

While many policymakers in the United States react with alarm to China’s growth, AI development should not be seen as zero-sum. The U.S. and Chinese AI ecosystems have benefited heavily from collaboration and competition, and keeping the global AI ecosystem open and vibrant will be the best result for both countries. This does not mean that the United States should sit back and ignore Chinese efforts to steal intellectual property and acquire unique technologies with potential national security applications from US companies. Instead, the United States should be cognizant of the cost of these efforts to the U.S. innovation base and we should be clear about our concerns. That China is growing its innovative base and its contributions to the global AI ecosystem is not the problem: the problem is that China has often engaged in illegal and predatory practices to strengthen its domestic AI industry at the expense of U.S. firms and global innovation. The U.S. response should reflect this. One of the United States’ greatest advantages over China is that China is pouring its elite talent and investment capital into U.S. companies and U.S. institutions. The United States should protect the products of U.S. innovation, but that does not mean it should send these resources back to China to support the growth of China’s domestic AI industry at U.S. expense.

Even more important than combating malicious and illegal practices by Chinese firms, the United States must focus on building its own domestic AI innovation capacity. While China is focusing on building its domestic innovation capacity and shaping domestic incentives to support AI development, U.S. policymakers are instead focused on cutting off China’s access to U.S. innovation. China’s ecosystem approach is based on American ideas. NGAIDP draws heavily on concepts developed in two 2016 reports developed by the Obama administration outlining the key factors needed to support continuing U.S. leadership in AI. But while China has invested significant resources in implementing these ideas, the U.S. government’s commitment has been largely rhetorical.

The Trump administration’s February Executive Order on Maintaining American Leadership in Artificial Intelligence emphasizes the right themes, highlighting the importance of building an AI talent pool, expanding AI R&D, developing enabling technologies and infrastructure, and engaging with international partners. But little has been done to implement the executive order, and in fact, many of the Trump administration’s policies run completely contrary to the order’s stated objectives, for example, by slashing budgets at federal agencies that support scientific research, cracking down on visas for people with advanced education and skills, and slashing the U.S. education budget.
In order to maintain U.S. leadership, the United States must take a page out of China’s book. China is investing significant financial, human, and political capital into its drive for AI leadership, taking a strategic approach that brings together policymakers, business leaders, technologists, and the Chinese public to strengthen domestic innovation and build China’s AI ecosystem. China remains behind the United States in fundamental research and key AI technologies, but unless the United States puts its money where its mouth is, China will continue to catch up. Whoever “leads” in the “AI race” or “dominates AI,” China’s AI industries are growing and innovating, and the Chinese government’s strategic approach will continue to drive growth in its AI industry and its contributions to the global AI ecosystem – for better and for worse.

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The United States leads the world in innovation, research, and technology development. Since World War II, the new markets, industries, companies, and military capabilities that emerged from the country’s science and technology commitment have combined to make the United States the most secure and economically prosperous nation on earth. This seventy-year strength arose from the expansion of economic opportunities at home through substantial investments in education and infrastructure, unmatched innovation and talent ecosystems, and the opportunities and competition created by the opening of new markets and the global expansion of trade. It was also forged in the fire of threat: It was formed and tested in military conflicts from the Cold War to the war in Afghanistan, in technological leadership lost and regained during competition with Japan in the 1980s, and in the internal cultural conflicts over the role of scientists in aiding the Pentagon during the Vietnam War. Confronted with a threat to national security or economic competitiveness, the United States responded. So must it once again.

This time there is no Sputnik satellite circling the earth to catalyze a response, but the United States faces a convergence bodog poker review of forces that equally threaten its economic and national security. First, the pace of innovation globally has accelerated, and it is more disruptive and transformative to industries, economies, and societies. Second, many advanced technologies necessary for national security are developed in the private sector by firms that design and build them via complex supply chains that span the globe; these technologies are then deployed in global markets. The capacities and vulnerabilities of the manufacturing base are far more complex than in previous eras, and the ability of the U.S. Department of Defense (DOD) to control manufacturing-base activity using traditional policy means has been greatly reduced.

Third, China, now the world’s second-largest economy, is both a U.S. economic partner and a strategic competitor, and it constitutes a different type of challenger.1 Tightly interconnected with the United States, China is launching government-led investments, increasing its numbers of science and engineering graduates, and mobilizing large pools of data and global technology companies in pursuit of ambitious economic and strategic goals. The United States has had a time-tested playbook for technological competition. It invests in basic research and development (R&D), making discoveries that radically change understanding of existing scientific concepts and serve as springs for later-stage development activities in private industry and government. It trains and nurtures science, technology, engineering, and mathematics (STEM) talent at home, and it attracts and retains the world’s best students and practitioners. It wins new markets abroad and links emerging technology ecosystems to domestic innovations through trade relationships and alliances. And it converts new technological advances into military capabilities faster than its potential adversaries. Erosion in the country’s leadership in any of these steps that drive and diffuse technological advances would warrant a powerful reply.

However, the United States faces a critical inflection point in all of them. There is a great deal of talk among policymakers, especially in the Defense Department, about the importance of innovation, but the rhetoric does not translate fast enough into changes that matter. The Task Force believes that the government and the private sector must undertake a comprehensive and urgent response to this challenge over the next five years. Failure to do so will mean a future in which other  countries reap the lion’s share of the benefits of technological development, rivals strengthen their militaries and threaten U.S. security interests, and new innovation centers replace the United States as the source of original ideas and inspiration for the world.

The major findings of the Task Force are:

• Countries that can harness the current wave of innovation, mitigate its potential disruptions, and capitalize on its transformative power will gain economic and military advantages over potential rivals.
• The United States has led the world in innovation, research, and technology development since World War II, but that leadership is now at risk.
• U.S. leadership in science and technology is at risk because of a decades long stagnation in federal support and funding for research and development. Private-sector investment has risen, but it is not a substitute for federally funded R&D directed at national economic, strategic, and social concerns.
• Friends, allies, and collaborators tightly link technology ecosystems and create scale in a globalized system of innovation, and thus are a competitive advantage. Washington’s current trade policies needlessly alienate partners, raise costs for American tech firms, and impede the adoption of U.S. technology in foreign markets.
• A central strength of the U.S. innovation environment has been a steady pipeline of domestic STEM talent and the country’s ability to attract the best and brightest students, engineers, and scientists from around the world. A lack of strong education initiatives at home and new barriers to talented foreign students’ and workers’ coming to and remaining in the United States will have long-term negative economic and national security consequences.
• The Defense Department and the intelligence community will fall behind potential adversaries if they do not rapidly access and deploy technologies developed in the private sector.
• The defense community faces severe challenges in attracting and retaining tech talent.
• The defense community faces deteriorating manufacturing capabilities, insecure supply chains, and dependence on competitor nations for hardware.
• A persistent cultural divide between the technology and policymaking communities threatens national security by making it more difficult for the Defense Department and intelligence community to acquire and adopt advanced technologies from the private sector and to draw on technical talent.
• China is investing significant resources in developing new technologies, and after 2030 it will likely be the world’s largest spender on research and development. Although Beijing’s efforts to become a scientific power could help drive global growth and prosperity, and both the United States and China have benefited from bilateral investment and trade, Chinese theft of intellectual property (IP) and its market manipulating industrial policies threaten U.S. economic competitiveness and national security.
• China is closing the technological gap with the United States, and though it may not match U.S. capabilities across the board, it will soon be one of the leading powers in technologies such as artificial intelligence (AI), robotics, energy storage, fifth-generation cellular networks (5G), quantum information systems, and possibly biotechnology.
• Although the Donald J. Trump administration has boosted the budgets of several technology-related organizations within the DOD and issued a number of executive orders, its efforts to accelerate innovation in critical frontier technologies such as AI are too incremental and narrow in scale.
• The United States is ahead of the rest of world in AI, but others are closing the gap—and U.S. failure to compete for global talent could result in the loss of its lead.
• In the race for the next generation of communications technologies, the Trump administration has developed only a few parts of what should be a multifaceted strategy. It has failed to coordinate a response to Huawei’s global expansion, muddied its message about the company’s economic and national security risks, and not sufficiently accelerated domestic efforts to deploy 5G.
• Beijing has often exploited the openness of the American system. Efforts to protect U.S. intellectual property are a necessary complement to, but not a substitute for, innovating faster than China. The administration is over-weaponizing trade and investment policy, with costs to U.S. innovation.

The United States needs a national security innovation strategy that ensures it is the predominant power in a range of emerging and foundational technologies over the next two decades. This Task Force report offers policy recommendations for the federal government, industry, and academia. Progress on this issue will require contributions and creativity from all three sectors if the United States is to maintain its ability to lead the world in the scientific and technological innovations necessary to its security and economic vitality. Some of the recommendations can be implemented in the short term; others will require more systemic change.

A new U.S. innovation strategy should be based on four pillars: funding, talent, technology adoption, and technology alliances and ecosystems. Action is required over the next five years.

The major recommendations of the Task Force are:

Restore Federal Funding for Research and Development

• The White House and Congress should restore federal funding for research and development to its historical average. This would mean increasing funding from 0.7 percent to 1.1 percent of gross domestic product (GDP) annually, or from $146 billion to about $230 billion (in 2018 dollars). Only the government can make the type of investments in basic science that ignite discoveries; such investments are too big and risky for any single private enterprise to undertake.
• Federal and state governments should make an additional strategic investment in universities. The investment, of up to $20 billion a year for five years, should support cross-disciplinary work in areas of pressing economic and national security interest.
• The White House should announce moonshot approaches to society wide national security problems. This would support innovation in foundational and general-purpose technologies, including AI and data science, advanced battery storage, advanced semiconductors, genomics and synthetic biology, 5G, quantum information systems, and robotics.
• The White House, Congress, and academia should develop a twenty first-century National Defense Education Act (NDEA), with the goal of expanding the pipeline of talent in science, technology, engineering, and mathematics. A twenty-first-century NDEA would support up to twenty-five thousand competitive STEM undergraduate scholarships and five thousand graduate fellowships.
• Universities, federal and state government, and business should address the underrepresentation of minorities and women in STEM fields through mentoring, training, research experience, and academic and career advising. They should also provide financial support for room and board, tuition and fees, and books, as well as assessments of job placement opportunities in STEM fields, highlighting employers with clear track records of fairness in hiring, promotion, and pay.
• Federal agencies, the private sector, and universities should work together to support debt forgiveness bodog online casino for students going into specialized technology sectors. The United States needs to make it easier for foreign graduates of U.S. universities in scientific and technical fields to remain and work in the country. Congress should “staple a green card to an advanced diploma,” granting lawful permanent residence to those who earn a STEM master’s degree or doctorate. Congress should also pass the Development, Relief, and Education for Alien Minors (DREAM) Act.
• Congress should pass legislation that permits immigrants to live and work in the United States if they can raise funds to start new companies.
• The federal government should make targeted—rather than sweeping —efforts to prevent the theft of scientific knowledge from American universities.

• Federal agencies and each of the military services should dedicate between 0.5 and 1 percent of their budgets to the rapid integration of technology. The heads of each agency should also hire a domain specialist deputy for fast-track technologies (for example, data sciences, robotics, and genomics) from outside the government for a two- to four-year assignment.
• Congress should establish a new service academy, the U.S. Digital Service Academy, and a Reserve Officer Training Corps for advanced technologies (ROTC-T) to foster the next generation of tech talent.
• Lifelong career paths should be complemented with more short-term, flexible options. The White House and Congress should bring people from the technology industry into all three branches of the government for temporary rotations. They should also develop new fellowships to encourage the circulation of technologists, military officers, and federal officials between the technology sector and the Defense Department.

• The State and Treasury Departments should create a technology alliance to develop common policies for the use and control of emerging technologies.
• The Department of Commerce should work with major trading partners to promote the secure and free flow of data and the development of common technology standards.
• The Department of Commerce and the U.S. International Development Finance Corporation should encourage American start-ups in AI and data science, genomics and synthetic biology, quantum information systems, and other frontier technologies to invest in, export to, and form R&D partnerships with firms in emerging technology ecosystems. The goal would be fostering early adopters, developers, and customers who will build on U.S. technologies.
• The Department of Energy (DOE), Department of State, National Institutes of Health (NIH), National Science Foundation (NSF), Office of Science and Technology Policy (OSTP), and other relevant agencies should develop a network of international cooperative science and technology partnerships, open to governments and the private sector, to apply frontier technologies to shared global challenges, such as climate change. Federal agencies should not only fund efforts that will include cooperation with other nations’ science organizations but should also provide R&D and tax incentives for tech firms to form international collaborative partnerships.
  During the early years of the Cold War, confronted by serious technological and military competition from the Soviet Union, the United States invested heavily in its scientific base. Those investments ensured U.S. technological leadership for fifty years. Faced with the rise of China and a new wave of disruptive technological innovation, the country needs a similar vision and an agenda for realizing it. The United States must once again make technological preeminence a national goal.

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