Matthew Daniels
Ben Chang
Igor Mikolic-Torreira
James Baker
Jack Clark
Remco Zwetsloot
Teddy Collins
Helen Toner
Jack Corrigan
Jeff Alstott
Maura Mccarthy
Alex Friedland
Lynne Weil
David Lasker
Jared Dunnmon
Matt Mahoney
Greg Allen
Fellow. Andrew W Marshall

National Power After AI

ing access to certain resources and the industrial capacity to leverage them. These broader effects take more time to appear, but their impact can be enormous: industrialization was not "revolutionary" because of the rapidity of change, as it unfolded in waves over decades, but because of its ultimate magnitude of change. With AI technologies, progressive substitution of machines for human cognitive labor may eventually have economic and social implications on a scale comparable to the Industrial Revolution. And like the Industrial Revolution, this AI revolution will change some fundamental elements of national power. Of course, these foundational shifts can render some of the current processes and resources of a state obsolete, but they can also make what states are already doing, or already possess, more valuable. For example, the invention of railroads was a boon for those rich in steel precursors.  2  With AI, data-hungry algorithms may advantage authoritarian states, which already surveil and catalogue their own populations with little regard for human rights.  3  We suggest an "evolutionary" view of technological change: major, widely diffused innovations are akin to environmental shifts, affecting the competitive capacity of states based on their existing trends in population, resources, institutions, character, and policies. Some previously "maladaptive" factors may become advantageous, and vice versa; states will adapt their institutions, organizations, and policies to the new environment in different ways and to varying degrees, and consequently gain or lose relative power as a result. Nations that primarily focus on AI technologies as offering marginal improvements in existing capabilities ("helping to build better mousetraps") will eventually miss larger opportunities to adapt. This paper is a first step into thinking more expansively about AI and national power. In what follows, we first explain this evolutionary view in greater detail before applying it to AI. Ultimately, we seek pragmatic insights for long-term U.S. competition with authoritarian governments like that of China. For the foreseeable future, China's population and total economic size will very likely exceed those of the United States, even as its per capita GDP lags. This new challenge differs fundamentally from the United States' Cold War competition with the Soviet Union, and success will require thoughtful and timely diagnosis of modern environmental shifts in how states can produce power. These insights can guide our own investments as well as our approach to alliances. The United States has many sources of advantage and strength, and as Joseph Nye rightly observed, "Our greatest mistake in such a world would be to fall into one-dimensional analysis and to believe that investing in military power alone will ensure our strength."  4  This paper is a first step, intended to provoke new questions and provide a framework for assessing the relationship between AI and national power.* *This work benefitted directly from the early Office of Net Assessment summer study on AI in 2016.
 WHY STATIC, UNIVERSAL MEASURES OF POWER (THAT ARE USEFUL) DO NOT EXIST Power is simply the relative capability of a state to achieve what it wants in international affairs. Power depends on one state's favorable factors relative to another. In one of the founding works of international relations, Hans Morgenthau proposed distinguishing nine elements of national power: geography, resources, industrial capacity, military preparedness, population, national character, national morale, quality of diplomacy, and quality of government.  5  Since Morgenthau's writing, generations of analysts have sought a definitive way to measure national power that would, finally, allow accurate judgment of relative strength without fighting a war.  6  The search has included dozens of books and hundreds of journal articles offering competing methodologies and metrics.  7  For example: Should measures of useful access to resources include both steel and oil, or only steel? How should "soft power" be measured? What about the "latent" power that a state could theoretically draw from its population?  8  Were such a universal, "objective" measure obtainable, the benefits would be enormous. We could easily answer questions such as, "who's ahead?" and "if it's not us, what should we do about it?" This quest, however, has not borne fruit. Proposed measures have tended to perform poorly when generalized. 9 History is full of surprises where states have An Evolutionary Theory of Technological Competition 1 achieved victory even when "objective" metrics would predict their defeat: the United States owes its national existence to victory in the Revolutionary War over the British Empire, the superpower of the time. Why? First and foremost, power is always contextual. 10 This is especially clear in military matters. A large military's skill at high-intensity conflict may not translate to skill at counterinsurgency; and factors that provide one country advantage relative to another can change. The world offers no "power particle" to measure objectively alongside other characteristics of nature-what we intuitively mean by "power" is mostly a generalization from particular observations. 11 Elements of power can also combine in surprising ways. Andrew Marshall offered the reminder that countries with relatively smaller populations and GNPs can pose substantial challenges to larger competitors: in 1938, Japan had roughly half the population and one-tenth the GNP of the United States,  12  but it built a navy that challenged the United States in wartime.  13  In part because of these issues, history is rife with leaders who have had a large gap between their beliefs and the reality of military capabilities.  14  Each competition should be analyzed carefully on its own, distinguishing elements of power, identifying key areas of competition, and working to diagnose the most important problems and opportunities in each area of competition.
 MAJOR INNOVATIONS CHANGE THE SECURITY ENVIRONMENT, CHANGING WHAT GIVES RISE TO POWER Military leaders throughout history are sometimes faulted for preparing to fight the previous war instead of the next one. We should likewise avoid strategizing to "win the previous competition." Just as changing adversaries from the Soviet Union to insurgents in Iraq and Afghanistan represented a new security environment and revealed the non-fungibility of power, major innovations also change the security environment as they are widely adopted. Such innovations do this in part by changing what assets, practices, and strategies give rise to power. Differential impacts of emerging technologies often bring shifts in relative capabilities of individual countries.  15  Thinking about long-term competition in periods of rapid technological change therefore requires assessing how innovations change factors related to military and national power. Major innovations can change the estimations of power in three ways: • First, innovations introduce new elements of power. Major innovations, in changing how states generate power, can create new factors that must be considered in characterizing power. For example, the advent of railroads, internal combustion engines, and nuclear weapons dramatically increased the importance of a state's access to steel, oil, and uranium, respectively.  16  New factors, however, are not only limited to materials. They may also encompass characteristics of a society's culture, organizations, or economic activities.  17  • Second, innovations change the importance of existing elements of power. Major innovations also change the "coefficients" of existing elements of power, causing them to matter more or less than before. For example, Mongol light cavalry, modern navies, and ballistic missiles all changed how geographic barriers affected one's balance of power with geographic neighbors, eroding the effectiveness of simple remoteness, oceans, and armies still in the field, respectively, as shields against coercive power.  18  Industrialization meant the inventiveness of a nation's scientists and engineers became more important. For example, before the Industrial Revolution, potential productivity gains in areas like agriculture and manufacturing were small and stable; this made conquering territory a primary means by which one group could increase its wealth and security.  19  During and after the Industrial Revolution, modern states could also pursue substantial military and economic growth by applying new technologies to increase productivity. The next section discusses how these three changes manifest in the context of AI. Perhaps least obviously, major innovations sometimes broadly alter what policies states pursue, by making certain kinds of behavior more valuable or less costly. e offer early thinking about potential changes caused by AI: new elements of power, shifting importance for existing elements of power, and shifting intermediate goals for states. These are not definitive or complete results, but a starting place for broader thinking.
 NEW ELEMENTS One of the most familiar examples of new elements of power is associated with the Industrial Revolution, when machines began to help humans with physical labor in new and organized ways. The Industrial Revolution led to dramatic changes in the character of war and military power. A simple approximation is that, before the Industrial Revolution, any group's military power correlated most closely with its quantity of fieldable humans under arms, a measure of both taxable population and military potential. After the Industrial Revolution, any estimate of military power had to include a society's industrial capacity and access to resources to enable that capacity, which are measures of a society's ability to produce useful military hardware, such as ships, tanks, planes, and submarines. It is useful to see AI technologies today as part of another large-scale transition: machines are increasingly helping humans with certain kinds of cognitive labor in new and organized ways.  20  This transition will span decades, with potential economic and social implications on a scale comparable to those of the Industrial Revolution. Today, as then, there are Power After AI: New Elements, Changed Factors, and Altered Goals 2 W large questions about the future of economic production, human labor, and military capabilities. These future trends will define new elements of power. U.S. defense leaders believe the rapidly growing military applications of AI technologies will be critical for the years ahead.  21  State power will increasingly hinge on the new factors required to effectively adopt AI. Four such factors often identified by existing literature include data, AI scientists and engineers ("AI talent"), computational power ("compute"), and AI-adapted organizations. Below, we explore the latter two in greater detail.
 Ability to Access and Leverage Compute The United States has historically used large-scale compute capabilities for analysis of nuclear weapons detonations and cryptanalysis.  22  More recently the U.S. government's uses have grown to include climate modeling and a variety of scientific applications. In the years ahead, the United States may also use large compute resources for creating and countering new AI capabilities. For decades, cutting-edge AI systems have used steadily increasing quantities of compute resources, making improvements in compute capabilities a key driver of AI progress. This usage appears to have accelerated across the last decade: the compute used in the largest AI training runs has doubled every 3.4 months since 2012, growing more than 300,000 times from AlexNet in 2012 to AlphaGo Zero in 2018.  23  OpenAI researchers have shown that the 2010s appear to be the beginning of a new computing era for AI technologies, distinct from the preceding 40-50 years.  24  For military applications where limited real-world data is available, techniques leveraging computer simulations instead of large quantities of data may further increase demand for compute.  25  Cloud compute may become vital for rapidly processing and fusing intelligence across platforms, while edge compute will be necessary for autonomous systems deployed in the field tasked with assessing and outthinking adversaries' equivalent systems. As such, a nation's ability to leverage large quantities of computational power could become a new primary term feeding into its ability to influence international U.S. defense leaders believe the rapidly growing military applications of AI technologies will be critical for the years ahead. State power will increasingly hinge on the new factors required to effectively adopt AI. affairs. For example, the key technical precursors required to manufacture cutting-edge AI chips are currently concentrated in the United States and allied countries-though semiconductor manufacturing capabilities more broadly, beyond just the most cutting-edge chips, may further grow the importance of Taiwan and South Korea as international trading partners.  26  Importantly, compute resources must be configured in ways useful for modern AI capabilities. High-performance computing (HPC) systems currently maintained within the U.S. Government, such as in the Department of Energy, tend to be both specialized for non-AI functions and subject to system-specific security measures, posing challenges for broad, standardized utilization by other organizations. Consequently, commercial cloud compute resources may better serve the U.S. Government in deploying certain kinds of AI technologies, although potentially promising efforts to improve the use of U.S. HPC assets for AI are also underway.  27  Effective use will depend, too, on accessible software tools for using cloud compute systemswhich may prove to be comparable to process and tooling approaches developed to make factories effective during industrialization in the United States.  28  Compute resources can flow more easily than many traded goods. As computing infrastructure continues to grow, new ways of sharing access to large, regionally-concentrated quantities of compute, including through space internet constellations, may create new opportunities and incentives for international partnerships.
 Ability to Manage Data and AI Safety & Security Even when states possess the raw resources required to adopt some major innovation, they still must undertake the often-difficult process of institutional and organizational adaptation. Bureaucratic factors in organizations matter greatly: in militaries, competing civilian, interservice, and intra-service actors may promote or resist adoption of new technologies.  29  Resistance can include parochial forces that attempt to stymie adoption: for example, only direct pressure from Eisenhower moved the Air Force to adopt ICBMs instead of focusing solely on less survivable crewed bombers.  30  Organizational culture also has significant impacts: because mass armies threatened the pre-existing hierarchical power structure within many European militaries, many states failed to adopt Napoleon's innovation even after his dramatic string of victories.  31  During periods of rapid change, medium-sized powers may have opportunities to adopt innovations more speedily than larger powers.  32  With AI, demands for organizational adaptations will be significant. Two factors are especially important: effective data pipelines and the effective management of security issues associated with modern AI technologies. The ability to deploy cutting-edge AI applications will increasingly depend on the quality of each organization's data pipeline. Modern machine learning methods are notoriously data-hungry, but simply possessing large quantities of data-collecting sensing platforms will be insufficient-for supervised learning applications, data must be structured, labeled, and cleaned; fusing data from many platforms, sources, and formats will represent its own herculean challenge for many militaries. Finally, these data pipelines must also be dynamic: data management itself must be monitored, in part to detect attacks, because "data poisoning" attacks can manipulate AI behavior by changing what lessons it learns.  33  Consequently, it will be increasingly important for military leaders to successfully implement organizational reforms to create and maintain effective data pipelines. Military leaders must also learn to effectively manage the novel security issues associated with AI technologies. Relying on modern AI systems for safety-or mission-critical tasks carries challenges because many deep learning models are exceptionally hard to interpret.  34  Michael Jordan at UC Berkeley has analogized the creation of early large-scale AI models to building bridges before civil engineering was a rigorous discipline: "While the building blocks are in place, the principles for putting these blocks together are not, and so the blocks are currently being put together in ad-hoc ways. … Just as early buildings and bridges sometimes fell to the ground-in unforeseen ways and with tragic consequences-many of our early societal-scale inference-and-decision-making systems are already exposing serious conceptual flaws."  35  A more developed engineering discipline for AI is needed to manage the risk of accidents from relying on opaque machines in the field.  36  In near-term military settings, effectively integrating new AI technologies will require special investment in test, evaluation, validation and verification (TEVV) processes by competent organizational leaders.  37  More widely, many modern AI systems are not designed to work in the presence of malevolent actors. Potential security issues for deep learning systems include adversarial examples and model inversion, in addition to data poisoning and more traditional computer network and software attacks.  38  Adversarial examples refer to "inputs" (such as visual or audio patterns) to an AI system that cause the system to malfunction; model inversion refers to an ability to reverse-engineer the data used to train an AI system, which may include private or classified information. Despite these challenges, modern machine learning capabilities will be increasingly woven into G20 societies, economies, and military systems.* The U.S. position with *For example, AI technologies will intersect with 5G and networking trends in cities as autonomous systems (like vehicles) in urban areas begin to have large quantities of interactions with other intelligent agents-working on everything from traffic coordination to utilities management and financial investments. The ability for intelligent systems to interact on large scales, safely and securely, will be critical. AI technologies for the next two or three decades appears analogous to the future that faced IT technologies in the 1990s: AI technologies are so valuable that they will be used despite substantial design and security issues. What might the future look like given these vulnerabilities? We can only speculate: in direct military settings, there may be new sub-competitions that resemble the emergence of electronic warfare after the invention of radar.  39  In economic systems, in addition to the potential for the novel security risks discussed previously, there is risk of physical manifestations of the kinds of problems currently seen in high frequency trading systems, such as rapid, unanticipated interactions among automated agents managing services in cities.  40  These issues may open new vulnerabilities to both individual rogue actors and state adversaries. Organizations that are able to adapt early to manage these new security issues will be advantaged. Since states vary in their access to compute, data, AI talent, and useful organizational adaptations, they will also vary in their ability to benefit from modern AI technologies. Any national rankings based on these factors will be debatable, but the nations that generally lead in these metrics is unsurprising, and include: the United States, China, Japan, South Korea, the UK, Canada, Taiwan, Israel, France, Germany, and Russia. Advanced economies should be increasingly expected to focus their own investments and policies on improving their positions in these areas.
 CHANGED FACTORS Industrialization meant that a nation's stock of productive scientists and engineers counted more than it had in the past. With the arrival of AI, various previously recognized elements of national power will become more important, while others may become gradually less so. For illustrative purposes below, we discuss population size and scientific talent as contrasting examples: population size becoming less important, scientific talent becoming more important. The U.S. position with AI technologies for the next two or three decades appears analogous to the future that faced IT technologies in the 1990s: AI technologies are so valuable that they will be used despite substantial design and security issues.
 Population Size As AI technologies increasingly substitute for human labor, total population size may become less important for national military and economic capacity.  41  Just as machines took over rote physical labor during industrialization, AI technologies will automate rote cognitive labor, from diagnosing maintenance needs to exploiting imagery intelligence. This may reduce the total quantity of human labor needed to maintain a military's operational capacity. In major wars, partially or fully autonomous AI platforms may further reduce a country's need to field humans in combat. As militaries rely more on autonomous systems for military operations, defense planners may come to count autonomous systems and their available domestic supply of AI chips the way they once counted soldiers and the available domestic recruiting pool of military-age adults.  42  Downstream, this could help technologically advanced nations compensate for demographic challenges, such as aging populations and low birth rates, a situation the United States, China, Japan, Western Europe, and Russia all face to varying degrees.  43  Population trends continue to matter for national power-but AI technologies, like many other technologies of the past century, may further erode this importance.
 Industrious Scientists and Engineers Harnessing new technologies, both by developing technologies and accessing innovations created elsewhere, is an important means of growing power. Applications of AI can help in both areas, serving as a force multiplier on, and therefore increasing the importance of, productive scientists and engineers. Recently, for example, DeepMind's AlphaFold achieved breakthrough rates of accuracy comparable to experimental methods in the protein-structure prediction challenge known as CASP.  44  By obviating the need for experimental protein structure assessment, a skill-demanding and time-intensive procedure, AlphaFold represents a large augmentation of human scientists' biosciences research. In a different domain of research, modern AI applications are able to help with chip design.  45  Researchers have demonstrated a deep learning system capable of designing the physical layout of computer chips more effectively than human engineers.  46  Google has used this system to design its next generation of Tensor Processing Units (TPUs), the company's specialized AI chips. Likewise, rapid progress in machine translation, automatic literature review, and related tools means a given scientific discipline's state-of-the-art will become increasingly accessible and useful to well-organized groups of human scientists and engineers. Just as the printing press alleviated the need to travel from country to country to accumulate knowledge from different libraries, AI applications can lower the costs for researchers to access state-of-the-art knowledge in any field. There are three ways that modern AI applications will contribute on a large scale to scientific discovery and engineering invention: they will contribute directly to new discoveries and engineered systems, especially in areas that involve searches over large spaces in data or design;  47  automate the physical work of science and engineering, such as "self-driving laboratories" that robotically automate experimental laboratory work;  48  and make global scientific knowledge more accessible to humans, such as by extracting knowledge from millions of articles as well as from articles in many different languages.  49  Finally, there is an old debate about whether science advances most because of new ideas or new tools;  50  AI technologies appear able to contribute both. In the longer-term, AI may enable new and more creative forms of knowledge-generation that function as "pathfinders" for human brains, unlocking otherwise difficult-to-reach innovations. When AlphaGo beat Lee Sedol, its 37th move in the second game surprised human professionals. In the words of Go master Fan Hui, "It's not a human move. I've never seen a human play this move. So beautiful."  51  When AI behavior surprises us, we learn something new. Looking ahead, modern and future AI systems may be able to solve scientific puzzles that have thus far stumped humanity's best minds.  52  Just as railways advantaged nations with access to steel, it appears that AI tools capable of augmenting science and engineering work will favor nations with the best existing "resources" of industrious scientists and engineers. This trend appears likely to deepen the advantages of nations that host, or can attract, a disproportionate fraction of the world's best in those fields.  53
 ALTERED GOALS Finally, major innovations can alter state strategies, as different instrumental goals become more appealing for achieving a state's ultimate ends. The Industrial Revolution again provides a clear example. Before industrialization, conquering territory was a primary way that one group could increase its wealth and security relative to others.  54  During and after the Industrial Revolution, in contrast, states have been able to pursue these ends effectively by increasing productivity-as well as by gaining access to international trading networks and new technologies to enable further military and economic growth. Territorial conquest by states in the modern era is rarer for many reasons-but not simply because states have become more beneficent, instead because changes in technology have reshaped how they can best achieve their goals.  55  In short, major innovations can alter what long-term competitions in each era are fundamentally about. In the standard "ends, ways, means" trichotomy, this corresponds to ways. States have the same ends (security, wealth, prestige, influence, sovereign action), but the ways that competition is best pursued can change, such as through participation in globalized production chains instead of territorial conquest. With AI technologies, there are two worrying possibilities: a broad movement toward authoritarianism and the greater use of advanced forms of population-and economy-targeting information warfare.
 Social Control Temptations A technological innovation rarely tilts intrinsically toward "freedom" or "authoritarianism." It is possible, however, to try to discern how new technologies may affect current social and economic systems in the future. Especially in authoritarian states like China, AI technologies may provide elites with tools that reduce contradictions between maintaining power and promoting economic growth through free markets. By making authoritarianism appear more feasible, this may generate an "authoritarian temptation" for the many states with malleable governance systems. First, AI technologies are likely to reduce the costs of controlling populations under authoritarian rule. Automating mass collection, processing, and analysis of data is likely to decrease the marginal cost of controlling additional citizens, thus reducing the resources required to indefinitely sustain totalitarianism. With access to hundreds of millions of cameras, social media postings, bank accounts, automated analysis of emotions and sentiment, and other data streams, AI-empowered algorithms can perform much of the work previously done by secret police in pre-AI authoritarian states.  56  Automated surveillance methods are likely to scale more effectively than manual surveillance, which requires some amount of human labor per citizen to be controlled. For example, Lichter et al. analyzed official Stasi records from East Germany, finding that more than 1.5 percent of the population was either officially employed or unofficially used as informers by the secret police.  57  Beyond the quantity of people involved in human surveillance operations, automated surveillance may impose lower economic costs on a society than human surveillance.  58  On this matter, China appears poised to benefit from feedback cycles between AI deployment and data aggregation-the Chinese government is already using AI technologies to enhance population control, as well as to profile and control its ethnic minorities.  59  In these early efforts, the Chinese government is collecting large quantities of data, from facial scans to DNA; COVID-19 has only deepened PRC data collection on its citizens.  60  This data will help fuel new AI development for social control in Chinese firms. Future AI applications could, in turn, help China manage its data and drive more expansive collection, continuing the cycle. China will likely export versions of these capabilities to authoritarian governments globally in the 2020s and 2030s, as it has already begun to do. According to recent CSET research, since 2008, over 80 countries have adopted Chinese surveillance technologies.  61  These tools will help authoritarian governments worldwide deepen their holds on power.  62  Second, and more speculatively, AI progress may benefit authoritarian states by reducing the costs and consequences of state interventions into internal markets. The classic critique of centrally planning complex economies is that attempting to do so poses intractable optimization problems.  63  For many practical reasons, from human organizational factors to corruption, AI technologies are unlikely to change this. However, AI technologies could reduce, to some degree, the negative consequences of state interventions in markets. For example, AI applications may help gather and interpret the volumes of information necessary for more effective economic controls. An analogous effect is visible inside large firms in both China and the United States today: companies like eBay, Taobao, Amazon, and Uber apply machine learning to mine large volumes of sales data to better match demand and supply. Modern machine learning tools enable automatic pattern analysis, improved forecasting, and natural language processing for predicting demand and performing sentiment analysis. Google's "Smart Bidding," for example, uses machine learning to optimize conversions for ads; California uses AI to predict electricity demand, more effectively controlling the power grid and reducing blackouts.  64  Walmart's internal logistical management has analogs to a centrally planned micro-economy.  65  There are many challenges to using analogous tools effectively for state economic policy, perhaps most of all the variable goals of planners themselves. But these trends suggest national-level strategic planning may be able to benefit from better information by applying modern machine learning tools to data accessible by states. Leaders of authoritarian states like China may find themselves facing lower costs for sustaining domestic political and economic control; leaders of authoritarian-leaning states may find themselves handed these tools by China. The effects of AI on population control and state interventions in markets are not certain. In the near term, however, it seems likely that Chinese elites at least believe that AI may help them better control their society, and so too may elites in other states. be decisively influenced by the clash between AI influence systems, for example, China may determine its best bet for reabsorbing Taiwan is heavy investment in AI-empowered propaganda. Information attacks can also target economic systems and financial markets, especially AI systems associated with managing equities investments. An unintentional, early demonstration of this possibility occurred in 2013, when U.S. trading algorithms responded to disinformation posted by the AP's Twitter account after it was hacked.  66  Information warfare may be increasingly linked to economic warfare, not just political disruptions. Higher-end, AI-empowered information warfare is a more speculative, longer-term capability. Chris Wiggins has characterized current technical trends as enabling "reality jamming": the potential for synthetic, targeted, and optimized disinformation at web-scale.  67  In this future, current computational propaganda concerns are just the tip of the iceberg. The bigger issue is the potential for large-scale machine-generated information that is highly targeted at particular individuals or subpopulations, evolved to maximally shape particular behaviors, and potentially able to affect anyone with web access.  68  Leveraging these developments, governments may attempt to shape perceptions of other populations more frequently than in the past.  69  OpenAI self-censored full publication of its GPT-2 language-generation model in 2019, for example, because it was concerned that generating close-to-human text would enable nefarious actors to proliferate disinformation. It is easy to imagine states pursuing similar capabilities for their own ends.  70  According to recent CSET research, GPT-2's successor, GPT-3, may be especially potent at generating disinformation at scale when steered by a skilled human operator and editor, opening up the possibility of highly effective human-machine teaming.  71  These trends may pose challenges for democratic societies, though it is still too early to make clear judgments. Three unresolved questions exist today: First, if a long-term risk in authoritarian systems is intellectual conformity, an analogous effect in democracies may be mob majoritarianism.  72  This inherent challenge in democratic societies could turn out to be exacerbated by modern information technologies and make organizational reforms even more difficult. Second, more research is needed to understand the balance between democracies' ability to use disagreements and diverse information to advance new explanations and solutions, and the potential for information attacks to undermine political stability.  73  And third, most fundamentally, Western democracies, and particularly the U.S. system of government, are based on a foundation of individual freedom where individuals are the best judges of their own interests. It is not yet obvious how Western institutions will adapt to machines that can anticipate-or shape-individuals' own preferences, states, and choices better than the individuals themselves can.  74  In the context of international competition, leveraging AI technologies to alter target states' national priorities or political stability through information warfare would represent "winning without fighting" par excellence. In this evolutionary theory of technological competition, AI's effects on national power fall into three categories: new elements of power, changed factors, and altered goals. Exploring new elements required for successful AI adoption, such as compute and organizational adaptations, helps us understand when, how, and why some societies may be better positioned than others to benefit from major innovations. Similarly, the idea of changed factors helps focus on how existing elements of national power may have changing importance, such as population size and industrious researchers. Finally, thinking about altered goals of states in competition shows how major innovations can reshape the ways that states engage in competition, such as enacting new domestic political and economic controls and leveraging AI-enabled information attacks on other states' social and economic systems. This research offers a way to start thinking about these issues together, and hopes to spur new, wider thinking and work. Creating new conceptual tools for U.S. decision-makers and analysts to make sense of AI technologies' effects is vital to American prosperity. Over the long term, these technologies will create significant changes in U.S.-China competition. From this research, we see three early sets of insights into opportunities for U.S. leaders: The scale of possible impacts from major technologies is obvious: the United States benefitted greatly from growth connected to technological and economic changes in the 40 years from 1880 through 1920; and China has also already benefitted from a mix of technological and economic changes in its resurgence from 1980 through 2020.  77  Recent history demonstrates that getting technology right is critical for long-term national flourishing-and determining trajectories for the United States and China over the next 20 to 30 years. Can we sketch the longer-term future? Only speculation is possible today: Broad historical examinations tend to suggest that more successful societies present fewer obstacles to long-term change and, especially, limit the costs of intellectual conformity. They seek to maximize the benefits of pluralism, competition, and mechanisms to share, challenge, and supplement new knowledge.  78  A key challenge for China will be limiting the long-term costs of intellectual conformity induced by an authoritarian government. A favorable factor for China will be the dynamic organizations it has built over the last 20 years, which may remain able to adapt and benefit from organizational learning as the world continues to change over the next 10 to 20 years. In the longer term, however, continued evolution seems increasingly challenging for China under the CCP and absent substantial pluralism; many of its main challenges for net economic-technological growth are likely to persist, while the benefits of its dynamic organizations are likely to decline over time. A likely challenge for the United States will be institutional and organizational sclerosis, which will make organizational learning and adaptation challenging over the next decade. Interactions between AI technologies and democratic institutions increase uncertainty and may exacerbate these challenges. Weighing against these factors is Samuel Huntington's reminder of the United States' multidimensional sources of power and ability for self-renewal.  79  The most favorable factors for U.S. vitality and competition with authoritarian governments coincide with its enduring strengths: areas such as its cultural values and pluralism, overall approach to governance, and access to global talent.  80  In the longer term, the United States' central challenges appear more temporary, and its greatest advantages more enduring-a favorable outlook achievable with thinking and work today. It is useful to distinguish AI from autonomy. The former is defined above; the latter is best thought of as some degree of delegation of decision-making agency to another entity, which could be a human or a machine.  84  Systems can have neither, both, or one of these two things. For example, an autonomous military system can be unintelligent, as in the case of a landmine, or an intelligent system can support humans without autonomy, as in the case of an information system for a pilot. The 2010s were the third period of global excitement about AI. The first period occurred in the 1960s, centered in the United States and the UK, and the second period occurred in the 1980s, centered in the United States and Japan. Both periods were associated with significant investment and optimism for cascading breakthroughs in machine intelligence. Both periods were followed by "AI winters": periods of widespread divestment from AI R&D and the belief that earlier expectations had far exceeded reality.  85  The current period will probably be remembered as being centered in the United States and China, though with substantial activity in the UK, Europe, Canada, Japan, Israel, and South Korea. Since the 2010s, most excitement about AI has focused on machine learning (ML), and, within ML, mostly on applications of neural networks (deep learning). ML is a broad subfield of AI that centers on inference from data and overlaps substantially with statistics and optimization. "Neural networks" refers to a family of statistical models for extracting patterns from large quantities of data, originally inspired by the behavior of biological neurons. While the rediscovery and improvement of neural nets started the current AI wave in the late 2000s, specific trends over the last 20 to 30 years enabled the success of recent applications: global growth and diffusion of compute resources; large quantities of digital data globally; and the connection of these two by the global internet. For this reason, the foundation of modern AI advancements is often called the "triad" of new algorithms, compute resources, and data.  86  population, iron and steel production, energy consumption, military expenditure, and military personnel. (See: Singer, J. David, Stuart Bremer, and John Stuckey, "Capability Distribution, Uncertainty, and Major Power War, 1820-1965," in Bruce Russett (ed.) Peace, War, and Numbers, (Beverly Hills: Sage, 1972), pp. 1948, as well as. https://correlatesofwar.org/data-sets/national-material-capabilities.) More recently, Michael Beckley has argued that traditional measures of power conflate gross resources with net resources, and thus fail to account for a country's burdens in addition to its assets. Thus, he proposes the use of "GDP * GDP per capita.  "    INTRODUCTION 1 |* 1 AN EVOLUTIONARY THEORY OF TECHNOLOGICAL COMPETITION 2 | POWER AFTER AI: NEW ELEMENTS, CHANGED FACTORS, In this work, we use "artificial intelligence" to mean, as per the Defense Innovation Board, "a variety of information processing techniques and technologies used to perform a goal-oriented task and the means to reason in the pursuit of that task." See Appendix.

 • Thinking of long-term competitions in an evolutionary framework makes large, broadly-diffused technology changes akin to environmental shifts. Like a volcanic eruption or the start of an ice age, adaptations are valuable and some states will be better at adapting than others. It is useful to begin thinking about how AI technologies can create new elements of power, change the importance of existing elements of power, and alter the goals of states in competition. Getting a better sense of AI's effects in each of these factors will be critical for major powers. The United States has a number of opportunities: studying the approaches of other countries, especially U.S. competitors and medium-sized, quickly-changing countries; 75  developing strategies for global leadership in producing, using, and sharing compute resources; supporting development of AI engineering as a rigorous discipline in the United States and leveraging humans trained in it; continuing to push DOD and IC organizational reforms for how data is managed and leveraged; and leveraging AI tools, cross-training between AI and other disciplines, and high-skilled STEM immigration to access new breakthroughs in science and engineering more widely. • AI technologies may change not only what states can do, but also what they want. Major innovations can broadly alter intermediate, instrumental objectives that states pursue by making certain kinds of behaviors more valuable or less costly. This can drive dramatic changes in state goals and policies. The United States may look for new opportunities in technolo-For the United States, this means learning from its competitors without mirror imaging them and sharing insights with allies before assuming they should symmetrically match U.S. policies. Perhaps most significantly, it may also mean looking ahead to how AI technologies may affect the aims and interests of U.S. allies and partners. 3 Conclusions and Key Points I gy-related democracy promotion; shaping AI technologies themselves to Creating new con-favor democracies, such as by supporting development of AI technologies ceptual tools for U.S. with less dependence on centralized data; 76 and developing approach- es to more rapidly adapt social and economic institutions to "information decision-makers and analysts to make attacks" by AI systems. sense of AI technolo- gies' effects is vital to American prosperity. Over the long term, these technologies will create significant changes in U.S.-China competition. broad• Finally, effects of technological change can be highly asymmetric: new elements, changed factors, and altered goals may have very different manifestations in different countries.
 See "The Power of Nations: Measuring What Matters," International Security 43.2 (2018): 7-44. 8. The best overview of this quest is Ashley J. Tellis, Janice Bially, Christopher Layne, and Melissa McPherson, "Measuring National Power in the Postindustrial Age," RAND Corporation, 2000. 9. This statement includes whether such measures are used quantitatively to predict who wins a war, or whether war will occur, or whether settlement terms will favor one side or another. See: Ibid., 17. 10. For various discussions of this, see: Stephen Biddle, Military Power: Explaining Victory and Defeat in Modern Battle (Princeton: Princeton University Press, 2004); David A. Baldwin, "Power Analysis and World Politics: New Trends versus Old Tendencies," World Politics 161 (1979): 161-94; Jeffrey Hart, "Three Approaches to the Measurement of Power in International Relations," International Organization 30 (1976), 289-305. 11. Almond and Genco (1977) most famously made this point about how to think about political phenomena in general. See Gabriel A. Almond and Stephen J. Genco, "Clouds, Clocks, and the Study of Politics," World Politics 29.4 (1977): 489-522.

Abstract: is a research organization focused on studying the security impacts of emerging technologies, supporting academic work in security and technology studies, and delivering nonpartisan analysis to the policy community. CSET aims to prepare a generation of policymakers, analysts, and diplomats to address the challenges and opportunities of emerging technologies. CSET focuses on the effects of progress in artifi cial intelligence, advanced computing, and biotechnology.


No Permits, No Fabs The Importance of Regulatory Reform for Semiconductor Manufacturing

Executive Summary The ongoing global chip shortage, coupled with China's heavy investments in indigenizing semiconductor manufacturing capabilities, has brought attention to the importance of semiconductors to the U.S. economy, the fragility of semiconductor supply chains, and the decline of U.S. chipmaking capacity over the past three decades. In part as a result of this attention, Congress has advanced legislation to appropriate $52 billion in funding for the CHIPS for America Act. Approximately $39 billion will likely go toward incentivizing semiconductor manufacturers to build new chipmaking capacity in the United States. But more can be done to improve the resiliency of U.S. access to microelectronics beyond manufacturing incentives. This report outlines infrastructure investments and regulatory reforms that could make the United States a more attractive place to build new chipmaking capacity and ensure continued U.S. access to key inputs for semiconductor manufacturing.
 Key Findings: The United States currently builds fewer fabs * at a slower rate than the rest of the world. Part of the reason for this is permitting regulations which require long assessment timelines. Fabs have extensive infrastructure requirements, which interact with federal, state, and local regulations in complex ways. Modern fabs require access to (1) large plots of (2) seismically inactive land with a reliable, affordable, and stable supply of (3) water, (4) electricity, (5) talent,  (6)  transportation infrastructure, and  (7)  nearby land for co-locating with suppliers essential for constructing and operating a modern fab. The CHIPS Act correctly aims to increase the number of fabs constructed in the United States, but regulatory support and infrastructure investments are needed to ensure that these new fabs are built on time and on budget. The United States government should prioritize regulatory support at the local, state, and federal level to expedite fab construction. In particular, full implementation of several recommendations from the 2017 President's Council of Advisors on Science and Technology related to environmental review and permitting of high technology facility construction are essential.  1  The United States should also make infrastructure investments targeting utilities, transportation, and supply chain networks that will assist semiconductor manufacturers. Engagement with allies will be essential for increasing resilience in the semiconductor materials, gases, and chemicals supply chain. In the medium to long term, increasing domestic production and/or stockpiling should be considered. Increasing domestic United States production of many raw materials and chemicals is contingent on opening new mining and/or refining operations, which would require extensive permitting. Thus, coordination with allies who already have existing production and refining capacity may be more expeditious than attempting to establish new capacity in the United States. Though many of these materials have a limited shelf life, stockpiling of certain materials, modeled after existing United States government programs like those operated by the Defense Logistics Agency Strategic Materials, may be an option. The United States should quantify demand for key material inputs, identify potential alternatives, and support their development. Ongoing efforts supported by the Environmental Protection Agency and the semiconductor industry to develop substitutes for environmentally harmful greenhouse gases used in semiconductor manufacturing could serve as a template for further work to identify substitutes for certain materials, chemicals, and gases used in semiconductor manufacturing for which there is no commercially viable domestic supply.
 Introduction: Fab Infrastructure Requirements and Federal Permitting This paper, in concert with forthcoming companion papers on reshoring semiconductor manufacturing, argues that current semiconductor reshoring efforts should prioritize construction of leading-edge fabrication facilities and increase the resilience of the associated supply chain necessary to support these facilities. The U.S. Department of Commerce's 100-day review of the semiconductor supply chain in response to Executive Order 14017 on Securing America's Supply Chains generally aligns with this argument, finding "federal incentives to build or expand semiconductor facilities are necessary to counter the significant subsidies provided by foreign allies and competitors." 2 However, the United States has many regulations in place which may effectively counteract the purpose of CHIPS Act funds, slowing construction of new leading-edge fabrication facilities. In addition, the semiconductor industry must contend with myriad environmental, health, and safety (EHS) regulations that serve important purposes, but will inevitably slow the development of a more resilient semiconductor supply chain in the United States. Finally, the simple reality is that there are very few leading-edge semiconductor manufacturers in the world, and most of them are headquartered outside the United States. In practice, this means that the United States must craft policies that convince specific foreign companies to build outside of their headquarters country, where presumably they face significant political pressure to build domestically and enjoy easier access to policymakers to facilitate build-out in regulatory environments they can navigate adeptly. Local, state, and federal permitting processes in the United States are beneficial to the general public but present tradeoffs for semiconductor manufacturers. A 2017 report from the White House found that these permitting processes "minimize[d] environmental and community impact, which companies are not always economically incentivized to do. The combination of the current Federal and state permitting and review processes, however, can be slow, unpredictable, and lacking in transparency."  3  The report goes on to note that semiconductor factories are particularly vulnerable to permitting-related delays due to their long construction times, significant geographic footprint, and complex supply chains. In addition, due to the many specialized chemicals and gases used in the semiconductor manufacturing process, unique permits must be acquired, which can further delay, or even halt, operations. Adding to this challenge, the semiconductor industry's transition to a fabless-foundry operating model (in which semiconductor design and semiconductor fabrication are done by separate firms) in the past 20 years largely caught U.S. firms flat-footed. Many leading U.S. companies maintain an Integrated Device Manufacturer (IDM) operating model of doing both design and manufacturing in-house, an increasingly costly proposition, especially given the success of Taiwanese foundries that focus solely on manufacturing. In part as a result of both the U.S. regulatory environment and this ongoing structural shift in the industry, the United States builds fewer fabs at a much slower rate than other countries, and at a greater cost to companies. The United States should recognize the nature and value of indirect EHS regulatory support provided by other countries interested in attracting semiconductor manufacturers, and adopt policies that make it equally attractive to build fabs in the United States. This paper begins by reviewing fab rates of construction worldwide from 1990 to 2020, finding that the United States builds fabs far more slowly than other competitor countries and regions, notably Taiwan and China. Next, this paper reviews fabs' myriad unique infrastructure requirements. Finally, this paper discusses how these infrastructure requirements must contend with U.S. environmental, health, and safety regulatory permitting processes, potentially slowing the construction timeline for fabs and the associated supply chain necessary to support semiconductor manufacturing.
 The United States Builds Fewer Fabs More Slowly Than the Rest of the World It takes a long time (typically two to four years) to build a fab in any country. But analysis in this section shows that fab construction takes much longer in the United States than in the East Asian countries where most chipmaking currently takes place. There are many factors underlying the decline in U.S. chipmaking capacity, but one underappreciated factor may be the longer construction timelines associated with building new ("greenfield") American fabs. In part because of the unique infrastructure requirements of fabs and the regulatory processes these large construction projects must navigate, construction of semiconductor fabs takes several years. Between 1990 and 2020 there were approximately 635 greenfield semiconductor fabs built around the world. The average time between the construction start date and the beginning date of production was 682 days or roughly 1.86 years. This timeline does not include pre-permitting and pre-construction considerations, indicating that fab construction times exceed two years on average. There is considerable regional variation in the time it takes to build a new fab. As Figure  1  shows, Japan (584 days) and South Korea (620 days) build fabs significantly faster than the rest of the world on average. The Americas, of which the United States is the primary site of semiconductor fabrication facilities, build fabs at a significantly reduced speed, taking an average of 736 days, or roughly five months longer than Japan. Only construction of fabs in Southeast Asia takes longer than in the Americas. Until the recent slowing of Moore's Law, this industry introduced a new generation of chips every 12 to 18 months, meaning a five month delay in construction could be damaging to a firm's competitiveness. For context, in a period of five months, leading edge foundries like those operated by Samsung and TSMC could produce roughly 500,000 wafers. This trend is particularly troubling as the U.S. industry's position as a leading-edge manufacturer has been ceded to firms in Taiwan and South Korea. Both of these countries maintain the ability to build the world's most advanced fabs at rates that exceed the United States' ability to build trailing-edge fabs. Source: World Fab Forecast. Sample consisted of 635 greenfield fab construction projects with a "construction start" date between 1/1/1990 and a "production date" no later than 12/1/2020. The difference between "construction start" and "production date" was calculated for each fab project and then averaged by region. Figures  2-4  follow this methodology and further break the analysis out by decade. The United States' ability to expeditiously construct fabs has declined at the same time as the total number of fab projects in the United States has declined. Some of this is due to changes in the global semiconductor value chain, which has concentrated resources in Asia as foundries have risen in prominence, and countries like Taiwan, South Korea, and China have established significant market share in the industry from 1990 to 2020. However, during this same 30-year period, the time required to build a new fab in the United States increased 38 percent, rising from an average of 665 days (1.8 years) during the 1990 to 2000 time period to 918 days (2.5 years) during the 2010-2020 time period (Figure  2 ). At the same time, the total number of new fab projects in the United States was halved, decreasing from 55 greenfield fab projects in the 1990-2000 time period to 22 greenfield fab projects between 2010 and 2020.  The decline in the total number of new fab projects in the United States, as well as the speed with which those projects are completed, is striking when compared to other countries. In China, for example, the total number of new fab projects has increased from 14 during the 1990-2000 time period to 95 during the 2010-2020 time period (Figure  3 ). At the same time, China has seen the average number of days from construction start date to production date for these fab projects decrease from a high of 747 days (2 years) during the 2000-2010 time period to 675 days (1.85 years) during the 2010-2020 time period. China is building more fabs and building them faster.   Comparing average fab construction time across regions while controlling for the size of the fab construction project further illustrates the U.S. deficit in advanced semiconductor manufacturing. As Figure  5  shows, from 1990 to 2020, China built 32 fabs that produce 100,000 or more wafer starts per month (WSpM), while the rest of the world only built 24 during the same time period. * The United States had no greenfield fab projects that involved construction of factories with capacity greater than or equal to 100,000 WSpM during this time period. * High WSpM correlates strongly with advanced fabrication. The newest and most advanced fabs in the world can have WSpM greater than 200k. There are several important caveats to this data. First, this analysis is limited to greenfield projects and thus does not take into account fab expansion projects frequently undertaken by leading firms like Samsung and TSMC. Second, while China builds large advanced fabs faster than any other region in the world, most of these advanced fabs are owned and operated by non-Chinese headquartered firms. For example, Samsung and SK Hynix (South Korea) and TSMC (Taiwan) operate high volume fabs in China. This is also the case in Southeast Asia, where firms like Micron (USA) have built their most advanced and highest-WSpM fabs. The fact that some U.S.-headquartered firms are choosing to build their most advanced fabs outside the United States speaks to the challenge U.S. policymakers face in crafting subsidies, regulatory support, and an infrastructure environment that is competitive with allied and adversary countries in Asia.
 Fab Infrastructure Requirements This section reviews some of the infrastructure constraints facing chipmakers deciding where to establish greenfield fabs. Modern fabs require access to (1) large plots of (2) seismically inactive land with a reliable, affordable, and stable supply of (3) water, (4) electricity, (5) talent, (6) transportation infrastructure, and (  7 )
 Number of Fab Projects by Region China Japan Korea SE Asia Taiwan nearby land for co-locating with suppliers essential for operating a modern fab. These infrastructure requirements touch on construction and permitting processes in complex and sometimes costly ways. This section concludes with a discussion of infrastructure investments that other countries with strong semiconductor manufacturing industries have made, which could provide a model for future U.S. infrastructure investments. (1) Large plots of land. Fabs require large plots of land on which to locate their operations. While the cost of land is not as expensive an input in the semiconductor supply chain as the capital expenditures required to purchase and install semiconductor manufacturing equipment, it can present an obstacle to prospective semiconductor manufacturers. Fab "shells," the physical structures that house semiconductor manufacturing equipment (SME) and all associated materials and supporting operations, can occupy hundreds of acres and account for between 20 and 40 percent of the total capital expenditures associated with a greenfield semiconductor manufacturing facility.  6  For example, Samsung's Austin, TX-based fab occupies 640 acres (1 square mile).  7  Semiconductor manufacturers frequently purchase more land than they initially need in anticipation of future expansion. (2) Low seismic activity. Fabs and the semiconductor manufacturing equipment inside them are extremely sensitive to ambient vibration, meaning that they must be located in regions that are not seismically active, and on plots of land relatively isolated from highways, airports, and rail links.  8  While there are mitigation options available, and the industry has pioneered novel seismic isolation techniques, these unique requirements further limit the overall geographic supply of ideal building sites. (3) Stable supply of water. Some estimates indicate a modern fab consumes around five million gallons of water per day. 9 This reliance on a consistent supply of water was recently highlighted in Taiwan, when a record drought forced the government to institute measures to ensure the country's semiconductor manufacturers had access to adequate supplies of water to continue operations. 10 This intensive water consumption frequently necessitates that individual companies take action. For example, TSMC recently announced plans to establish on-site water storage and treatment facilities to prevent potential disruptions stemming from droughts and impurities.  11  (4) Stable supply of electricity. Fabs rely on a stable electrical grid to sustain their 24/7/365 operations. As wafer processing has increased in complexity and automation, energy consumption has gone up proportionally. Leading edge fabs can now consume as much electricity in one year as 50,000 homes.  12  Once a fab has reached volume production, energy costs can account for up to 30 percent of the fab's operating costs.  13  For smaller countries that are home to significant fab operations like Singapore, Taiwan, and South Korea, these factory operations consume a notable percentage of overall electricity in the country. The OECD estimates that TSMC alone accounted for 7.7 percent of total industrial electricity consumption in Taiwan in 2017.  14  The cost of an electrical grid failure that disrupts fab operations is substantial. A February 2021 power grid failure in Texas shut down Samsung, NXP, and Infineon chip factories for several weeks, costing Samsung alone over $270 million.  15  (5) Talent. Fab sites need to be strategically located in an area nearby a skilled workforce. This has resulted in fab clusters in close proximity to university systems with a consistent talent pool and in relative proximity to metropolitan areas. In the United States, these clusters include California's Silicon Valley, New York's Tech Valley, and Oregon's Silicon Forest, all of which draw technical talent from nearby cities, universities, and firms.  16  (6) Transportation infrastructure. Transportation infrastructure also drives the cost of fab construction around the world. The vast majority of semiconductor-affiliated commerce occurs by air freight, necessitating that fabs be close to an international airport. However, there are some chemicals and materials used in the semiconductor production process which, due to their hazardous nature, low value, or extreme weight, ship via ocean freight. In addition, fabs need adequate last-mile road infrastructure to take delivery of particularly large pieces of semiconductor manufacturing equipment and associated material handling devices. For example, ASML indicates one of its Extreme Ultraviolet Lithography systems "ships in 40 freight containers, spread over 20 trucks and three cargo planes."  17  This combination of air, ocean, and land transportation logistics presents myriad supply chain and regulatory bottlenecks. Specialty logistics services have been developed to facilitate semiconductor transportation. One supplier of transportation logistics services targeting the semiconductor industry advertises that they handle everything from SME and hazardous chemical delivery to air freight distribution of finished products (Figure  6 ).  18  Center for Security and Emerging Technology | 14 (7) Nearby land for co-location with key suppliers. Semiconductor fabrication facilities rely on a vast supply chain. Intel, for example, reports that it has identified over 16,000 suppliers.  19  However there are some suppliers whose products or services are so essential to the operations of modern fabs that they must co-locate production and warehousing facilities with the fabs they are supplying. Suppliers of rare gases and specialty chemicals used intensively in fabs need proximate land to establish production and warehousing facilities. Following the announcement that TSMC will be constructing a new fab in Arizona, several Taiwanese suppliers of specialty chemicals and gases to TSMC indicated they will be establishing operations nearby the new facility in addition to their current locations near TSMC's fabs in Taiwan.  20  In this instance, having additional land nearby prospective greenfield semiconductor fabrication sites is another important consideration.
 Government Policies to Reduce Infrastructure Costs and Accelerate Fab Construction Recognizing the costs that these infrastructure requirements impose on semiconductor manufacturers, many countries offer incentives to offset some of the price of constructing new factories. A joint report from the Semiconductor Industry Association and the Boston Consulting Group found that some countries provide both direct support to individual semiconductor companies and also incentives that are designed to facilitate the creation of a semiconductor ecosystem in close proximity to fabs.  21  The Japanese government has offered tax breaks, subsidies, and investments to attract semiconductor companies to establish joint ventures with Japanese firms, mirroring the sorts of incentives proposed by South Korea.  22  Similarly, the Taiwanese government's Ministry of Economic Affairs offers tax and tariff incentives as well as research and development (R&D) subsidies to attract semiconductor companies. Specifically, Taiwan maintains a business tax rate of 17 percent, allows semiconductor firms to credit up to 15 percent of their research & development expenses against their income tax bill annually, and permits firms to import semiconductor manufacturing equipment tariff-free.  23  Subsidies are also available for up to 50 percent of total spending by semiconductor firms who establish an R&D center in Taiwan. International semiconductor firms are clearly responsive to these incentives. The Taiwanese government notes these incentives have successfully attracted Micron, the U.S. memory chip company, to build a fab in Taiwan, while equipment suppliers like ASML from the Netherlands, as well as Applied Materials and Lam Research from the United States, have all set up R&D centers or training headquarters in Taiwan.  24  In addition, some countries focus on minimizing pre-and postfabrication operating costs for semiconductor manufacturers. A recent OECD report found that some governments support semiconductor manufacturers through the provision of water and electricity at below-market rates via state utilities.  25  Furthermore, the provision of land at below-market prices to semiconductor manufacturers was observed by the OECD to be a form of investment incentive. The OECD highlighted the case of Tsinghua Unigroup, a Chinese semiconductor firm which "purchased land for its foundry in Chengdu for CNY 240 per m^2, while the official average price for industrial land in second-tier cities was CNY 724 per m^2."  26  The Government of Israel also made use of similar land-specific incentives which were used by Intel to expand its operations in the country.  27  Finally, many countries in Asia also provide infrastructure support in the form of utilities and logistics investments, as well as providing for expedited procedural consideration and eased regulations associated with semiconductor factory construction.  28  When Micron first considered establishing a fab in Taiwan, the country's investment authority "assisted Micron in terms of land acquisition…accelerated the administrative process…eliminated investment barriers (such as coordinating underground pipelines and sidewalk construction)  [and]  organized job fairs to help the company recruit talent." 29 Taiwan has also established a series of free trade zones designed to facilitate efficient trading, warehousing, transport, and customs clearance processes that are critical to international semiconductor manufacturers. 30 The government of Singapore has provided myriad infrastructure investments designed to attract semiconductor manufacturers. Through government agencies like the Economic Development Board and JTC Corporation, Singapore has established four industrial estates that provide shovel-ready plots of land for semiconductor manufacturers and their suppliers that come preequipped with basic infrastructure like power, electricity and roads.  31  These estates also include ready-built facilities that feature chilled water, bulk industrial gas supply, high ceilings to accommodate SME, and incorporate vibration-control construction techniques.  32  The results of the Singaporean government's efforts are clear, having successfully attracted 14 global semiconductor firms employing 18,600 workers in the industry across these estates.  33  The value of this infrastructure support is not easily quantified but lowers the cost of doing business for semiconductor manufacturers and decreases construction timelines. And the success of this regulatory facilitation and infrastructure investment is clear: GlobalFoundries, one of the leading foundries in the United States, recently chose to substantially expand its semiconductor manufacturing facility in Singapore rather than doing so at its factory in New York.  34
 Semiconductor Fabrication Regulatory Permitting Considerations Fabs' many infrastructure requirements touch on local, state, and federal EHS regulations. These regulations implicate agencies at each level of government, sometimes with overlapping jurisdictions. As a result, construction must carefully navigate arcane regulatory processes to develop greenfield semiconductor fabs. Recognizing the time delays that these regulations and permitting processes place on semiconductor manufacturers, other countries provide incentives and indirect subsidies to expedite fab construction timelines. To date, the United States government has not provided sufficient local, state, and federal regulatory support to match the efforts offered by peer semiconductor-producing countries. Regulatory support steps could include fully implementing 2017 recommendations from the President's Council of Advisors for Science and Technology, such as identifying where federal permitting regulations for high-technology facilities are redundant with state rules and might therefore be modified or removed.  35  The U.S. Environmental Protection Agency (EPA) could also consider creating a "fast track" process for preconstruction and operating permits related to the Clean Air Act (CAA). State and local environmental agencies perform a first review of these permit applications, but the EPA retains the right to review any draft permit and provide comments to state or local authorities. The EPA has experimented with the use of flexible air permits in the past and should create a program specifically tailored to the needs of U.S. semiconductor firms that would accelerate construction of new fabs and re-tooling of existing fabs. For example, following receipt of a flexible air permit, Intel Corporation used this permits' advance approval to make 150-200 equipment changes and process modifications to its Aloha, Oregon fab that would have otherwise required EPA New Source Review permits and resulted in concurrent permits from the Oregon Department of Environmental Quality.  36  This flexible permit allowed Intel to make changes to its fab without notifying environmental regulators, so long as the changes did not result in the fab's emissions exceeding previously agreed-upon levels. This saved the company "hundreds of business days associated with making operational and process changes to ramp up production."  37  Representatives from Intel stated that, had they not received the flexible air permit, continued permitting-related delays would likely have pushed Intel to redirect its production investment and operating facilities to locations where changes could be made within existing environmental regulations (e.g. other U.S. states or the company's fabs in Ireland or Israel). 38
 United States Federal EHS Regulatory Processes Federal EHS laws and regulations govern both the construction and operation of fabs. These laws and regulations are generally overseen by the EPA, the U.S. Army Corps of Engineers, and the U.S. Department of the Interior. These agencies are tasked with auditing proposed construction projects for compliance with relevant federal regulations that touch on fab utility, transportation, and supply chain infrastructure requirements. For example, a regional economic development association in the state of Washington that sought to increase fab construction in the Pacific Northwest observed that "among local and federal agencies, the Bonneville Power Administration (BPA), the United States Army Corps of Engineers (USACE), and the Environmental Protection Agency (EPA), would be key players in coordinating site reviews with parallel agencies in Washington State."  39   At the federal level, there are many laws designed to maintain environmental quality that are also known to often significantly delay major construction projects. Notably, the National Environmental Policy Act (NEPA) review process governs construction projects deemed to be a "major federal action." 40 If the provision of CHIPS Act incentives are determined to be a "major federal action" 41 then the construction of new semiconductor fabs could be significantly delayed.  42  In 2020 the White House Council on Environmental Quality compiled data on timelines for 1,276 Environmental Impact Statements (EIS) filed between 2010 and 2018 and found that NEPA reviews averaged 4.5 years.  43  This permitting process does not include the average of 1.86 years it takes to physically construct a semiconductor fab. This number also does not reflect other federal environmental reviews, some of which may happen concurrent with the NEPA process or entirely separately. A 2017 report from the White House also identified preconstruction permits and operating permits required under the Clean Air Act as "the primary barrier to responsible and timely facility permitting" finding that "for some large projects
 Suppliers In addition to constructing fabs, a process which takes a minimum of two years, the process of establishing a more resilient semiconductor supply chain in the United States necessitates increased domestic production of critical minerals, materials, chemicals, and gases, all of which require lengthy permitting processes. As a result, ongoing collaboration with international allies may be a more expeditious means of increasing semiconductor supply chain resiliency than attempting to increase domestic production in the short term. Some of the semiconductor supply chain, such as providers of specialty chemicals, would need to construct production facilities that would implicate many of the same regulatory considerations identified in Table  1 . Other parts of the supply chain, such as suppliers of raw minerals, would encounter entirely new regulatory considerations such as mining permits that may slow the ability to ramp up domestic production. The June 2021 White House supply chain report found "establishing strategic and critical material production is an extremely lengthy process. Independent of permitting activities, a reasonable industry benchmark for the development of a mineralbased strategic and critical materials project is not less than ten years." 48 United States-based production of materials, chemicals and gases used in semiconductor manufacturing is, with few exceptions, limited. The United States Geological Survey's 2020 Mineral Commodities survey indicates materials like Arsenic, Beryllium, Bismuth, Boron, Cadmium, Helium, Indium, Rhenium, and Silicon are all used in the semiconductor manufacturing process.  49  The National Institute of Standards and Technology also maintains an index of 49 semiconductor process gases used in semiconductor production.  50  Except for a few materials like Helium and Silicon, U.S. firms do not produce or refine these materials in the United States. For example, Intel reports that it relies on smelters and refiners in China, Japan, Germany, Russia, Vietnam, the Philippines, Austria, and the United States for its supply of Tungsten, a key metal that is used to produce tungsten hexafluoride and tungsten sputter targets, both of which are used in the majority of semiconductor devices.  51  One reason that United States firms are not major suppliers of semiconductor materials is the increased cost of doing business in the United States. A Taiwanese supplier of specialty gases estimates that it costs five to six times more for them to build a factory in the United States than in Taiwan.  52  This price disparity is driven by several factors. In addition to contending with some of the construction permitting described above in Table  1  and higher labor market rates,  53  Taiwanese suppliers of semiconductor materials identified "the role of transportation systems" and a need for "seamless dual supply of electricity and natural gas at a favorable rate for the operation of purification and solvent recovery plants" as important factors, and requested federal and state government help to improve transportation system connectivity and utility provider reliability.  54  Both of these companies are single source suppliers of chemicals for TSMC in Taiwan and expressed interest in supplying TSMC's United States facility, but observe a clear increase in the cost of doing business in the United States. United States-based production of materials, chemicals and gases used in semiconductor manufacturing is also limited because many of these goods are derived from, or contribute to, environmentally harmful practices. For example, the semiconductor industry intensively consumes hydrofluorocarbons in the manufacturing process, a type of gas that is recognized by the EPA as a high global warming potential (GWP) greenhouse gas (GHG).  55  HFCs for semiconductor use are generally not produced in the United States. Recently, The Biden Administration's support for the Kigali Amendment to the Montreal Protocol on Substances that Deplete the Ozone Layer committed the United States to cap, and ultimately reduce, the semiconductor industry's use of HFCs.  56  However, until the semiconductor industry can innovate a substitute for the use of HFCs and qualify suppliers, there is no short-term alternative except to continue importing HFCs. Increasing the domestic resilience of this part of the supply chain in the medium to long term requires finding an international supplier willing to navigate the regulatory bureaucracy to establish new operations in the United States. Several companies and industry associations have highlighted how United States government regulatory decisions may increase the costs of doing business in the United States for semiconductor manufacturers and their suppliers. For example, the EPA has undertaken risk evaluations of several chemicals under the Toxic Substances Control Act that are used in the semiconductor manufacturing process.  57  Depending on the findings of these risk assessments, new regulations may restrict the production and supply of these chemicals in the United States  58  In addition, Executive Order 140083 (January 27, 2021) and the subsequent implementation of a temporary ban on new oil and gas leases under Department of Interior Order No. 3395 may reduce future opportunities for domestic helium development. Helium is recovered from natural gas deposits but exists in economic quantities in only a few places within the United States, mainly on federal lands, and is intensively used in semiconductor manufacturing.  59
 Conclusion This report demonstrates that the United States is building fewer fabs at a slower rate than the rest of the world. CHIPS Act manufacturing incentives correctly aim to increase the number of fabs constructed in the United States, but more policy work is needed to ensure these new fabs are built on time and on budget. Prioritize regulatory support at the local, state, and federal level to expedite fab construction. The United States should make infrastructure investments targeting utilities, transportation, and supply chain networks that will assist semiconductor manufacturers. These policies would make the United States competitive with the "foreign allies and competitors" identified in the June 2021 White House supply chain report, and would align United States incentives to match those already offered abroad. Fully implement several of the recommendations from the 2017 PCAST report: 60 1. The Federal government should review permitting for technology facilities to identify areas where regulations are redundant with state rules and might therefore be modified or removed. 2. The EPA should create additional "fast track" permitting options that allow fabs to make some operational changes without filing environmental permit applications, potentially modeled after the State of Oregon's Plant Site Emissions Limit (PSEL) program. 61 Engage with allies and partners to increase semiconductor supply chain resiliency in materials, gases, and chemicals. Because increasing domestic United States production of many raw materials and chemicals would be contingent on lengthy development of mining and/or refining capacity, coordination with allies who already have existing production and refining capacity is essential. Quantify current and forecasted demand for materials, gases, and chemicals used in United States semiconductor manufacturing. Stockpiling of certain materials, modeled after existing United States government programs like those operated by The Defense Logistics Agency Strategic Materials branch, 62 may be an option. Identify substitutes for environmentally harmful or strategically concentrated resources. The EPA is currently supporting semiconductor industry efforts to develop substitutes for environmentally harmful greenhouse gases used in semiconductor manufacturing. These efforts could serve as a template for further work to identify substitutes for certain materials, chemicals, and gases used in semiconductor manufacturing for which there is no commercially viable domestic supply.  63   Figure 1 . 1 Figure 1. Average Number of Days from Fab Construction Start Date to Production Date, by region 1990-2020
 Figure 2 . 2 Figure 2. Time Required to Build New Fabs in the United States (L) and Total Number of New Fab Projects (R), 1990 -2020
 Figure 3 . 3 Figure 3. Time Required to Build New Fabs in China (L) and Total Number of New Fab Projects (R), 1990 -2020
 Figure 4 . 4 Figure 4. Time Required to Build New Fabs in Taiwan (L) and Total Number of New Fab Projects (R), 1990 -2020
 Figure 5 . 5 Figure 5. Number of >100k WSpM Greenfield Fab Projects (L) and Average Number of Days from Fab Construction Start Date to Production Date for those Projects (R) by Region, 1990-2020
 Figure 6 . 6 Figure 6. Transportation Infrastructure Requirements for Semiconductor Production
 Table 1 . 1 Table 1 describes federal environmental requirements for construction in greater detail. Federal Environmental Requirements for Construction Relevant Law Agency Associated Requirements Regulation Jurisdiction Air Quality Clean Air Act (CAA) Environmental Permit for construction- Protection related pollutant emissions Agency Asbestos Clean Air Act (CAA) Environmental Report of asbestos releases Protection above a threshold Agency Dredged and Section 404 of the CWA Army Corp of Permit for discharge of Fill Engineers or dredged material Material/Water state regulator s Environmental National Environmental Environmental Submit Environmental Impact Policy Act Protection Assessment Agency Submit Environmental Impact Assessment Hazardous Comprehensive Environmental Permit to excavate Substances Environmental Response, Protection contaminated soil Compensation, and Agency Liability Act (CERCLA) Historic National Historic United States Pre-construction Properties Preservation Act Department of consultation for historic the Interior property considerations Polychorinated Toxics Substances Environmental Storage and disposal biphenol (PCB) Control Act (TSCA) Protection requirements Wastes Agency Solid and Resource Conservation Environmental Transporters of hazardous Hazardous and Recovery Act (RCRA) Protection waste must register with Wastes Agency EPA Spill Reporting Maintain a material safety data sheet (MSDS)
 ,[this]   permitting process can take 12-18 months."44  More recently, the EPA has announced a goal to make permitting decisions within six months of receipt. But as discussed earlier, given the tight timelines on which this industry operates, any delay can be costly to a firm's competitiveness.45    U.S. State and Local EHS Regulatory ProcessesState and local EHS regulations and agencies also have a bearing on semiconductor manufacturers. In some cases, the EPA delegates authority to implement regulatory programs to states and other agencies. For example, the U.S. Army Corps of Engineers (USACE) administers Section 404 of the Clean Water Act, which regulates the discharge of dredged and fill material into all waters of the United States. The USACE's Fort Worth, TX District reviewed an application of Samsung Austin Semiconductor LLC in 2014 to expand their fabrication facility in compliance with Section 404 of the CWA. However, this application also invoked reviews being conducted concurrently by the Texas Commission on Environmental Quality and a City of Austin Development Permit.46   Even after federal and state-level concerns are addressed, semiconductor building sites may run into local regulatory barriers. When GlobalFoundries was considering building a new fab in Malta, NY there were lingering zoning changes at the local level that needed to be made by the Town Boards of Malta and Stillwater, NY which delayed the site's initial development.47     United States Regulatory Processes Affecting Semiconductor
			 Stephanie Yang, "The Chip Shortage Is Bad. Taiwan's Drought Threatens to Make It Worse," The Wall Street Journal, April 16, 2021,

Abstract: The author would also like to thank Melissa Deng, Dale Brauner, and Danny Hague for editorial support. The author is solely responsible for any mistakes.