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2. Comparing Pharmaceutical Prices in the United States and Other Countries

Facing criticism over exorbitant prices and monopolistic pricing practices, pharmaceutical companies claim that high average returns are necessary to incentivize pharmaceutical R&D, given its high-risk nature.139 Yet, with pharmaceutical companies ranking among the most profitable,140 pharmaceutical prices have sparked controversy throughout the years.141

The patent system has long been criticized for limiting access to pharmaceuticals. Patents grant inventors a limited period of exclusivity with an attempt to allow recoupment of investments in the invention process. In the pharmaceutical industry, this exclusivity and the resulting lack of competition leads to exorbitant prices. High prices limit access to potentially life-saving medicines and hinder achievement of the “highest attainable standard of health,” which several international instruments recognize as a human right.

The pharmaceutical industry claims patents are essential to encourage innovation in risky, lengthy and costly research and development (R&D) processes. But it has yet to put forward indisputable evidence to the actual effects of patents on innovation.

It’s been another dismal term for the Federal Circuit Court of Appeals. Six of its patent law decisions were reviewed in the US Supreme Court’s 2016-17 term, and the Federal Circuit’s decisions were overturned in all six cases. That, unfortunately, is not surprising. Over the past 15 years, the tribunal once known as the nation’s “patent court” has seen many of its most important patent law decisions reversed by the Supreme Court– sometimes in withering opinions. This has seriously undermined the Federal Circuit’s power, reputation, jurisprudence, and (apparently) self-confidence – causing a major problem for the United States’ patent system.

The Federal Circuit was created in 1982 as a specialized court that would hear all appeals in certain areas of the law, including patent law. And “the court came in like gangbusters,” said Ronald Abramson, a partner in the law firm of Lewis Baach Kaufmann Middlemiss. In its first twenty years, the Federal Circuit issued many landmark rulings that made it easier to obtain and enforce patents.

Similar factors apply to the issue of patents. Much university research in economics is funded by companies with interests in patents. These companies may not do anything as crass as ordering professors to take a particular position, but influence can work more subtly, as stated by Edward Said:

Nothing in my view is more reprehensible than those habits of mind in the intellectual that induce avoidance, that characteristic turning away from a difficult and principled position, which you know to be the right one, but which you decide not to take. You do not want to appear too political; you are afraid of seeming controversial; you want to keep a reputation for being balanced, objective, moderate; your hope is to be asked back, to consult, to be on a board or prestigious committee, and so to remain within the responsible mainstream; someday you hope to get an honorary degree, a big prize, perhaps even an ambassadorship.50

Our patent system is a mess. It’s a fount of expensive litigation that allows aging companies to linger around by bullying their more innovative competitors in court.

Critics have suggested plenty of reasonable reforms, from eliminating software patents to clamping down on ”trolls” who buy up patent portfolios only so they can file lawsuits. But do we need a more radical solution? Would we be possibly be better off without any patents at all?

Piers & Andrew, 08-01-2017, “Existential Risk and Cost-Effective Biosecurity,” Health Security, 15(4), PubMed.

In the decades to come, advanced bioweapons could threaten human existence. Although the probability of human extinction from bioweapons may be low, the expected value of reducing the risk could still be large, since such risks jeopardize the existence of all future generations. We provide an overview of biotechnological extinction risk, make some rough initial estimates for how severe the risks might be, and compare the cost-effectiveness of reducing these extinction-level risks with existing biosecurity work. We find that reducing human extinction risk can be more cost-effective than reducing smaller-scale risks, even when using conservative estimates. This suggests that the risks are not low enough to ignore and that more ought to be done to prevent the worst-case scenarios. How worthwhile is it spending resources to study and mitigate the chance of human extinction from biological risks? The risks of such a catastrophe are presumably low, so a skeptic might argue that addressing such risks would be a waste of scarce resources. In this article, we investigate this position using a cost-effectiveness approach and ultimately conclude that the expected value of reducing these risks is large, especially since such risks jeopardize the existence of all future human lives. Historically, disease events have been responsible for the greatest death tolls on humanity. The 1918 flu was responsible for more than 50 million deaths,1 while smallpox killed perhaps 10 times that many in the 20th century alone.2 The Black Death was responsible for killing over 25% of the European population,3 while other pandemics, such as the plague of Justinian, are thought to have killed 25 million in the 6th century—constituting over 10% of the world's population at the time.4 It is an open question whether a future pandemic could result in outright human extinction or the irreversible collapse of civilization. A skeptic would have many good reasons to think that existential risk from disease is unlikely. Such a disease would need to spread worldwide to remote populations, overcome rare genetic resistances, and evade detection, cures, and countermeasures. Even evolution itself may work in humanity's favor: Virulence and transmission is often a trade-off, and so evolutionary pressures could push against maximally lethal wild-type pathogens.5,6 While these arguments point to a very small risk of human extinction, they do not rule the possibility out entirely. Although rare, there are recorded instances of species going extinct due to disease—primarily in amphibians, but also in 1 mammalian species of rat on Christmas Island.7,8 There are also historical examples of large human populations being almost entirely wiped out by disease, especially when multiple diseases were simultaneously introduced into a population without immunity. The most striking examples of total population collapse include native American tribes exposed to European diseases, such as the Massachusett (86% loss of population), Quiripi-Unquachog (95% loss of population), and the Western Abenaki (which suffered a staggering 98% loss of population).9 In the modern context, no single disease currently exists that combines the worst-case levels of transmissibility, lethality, resistance to countermeasures, and global reach. But many diseases are proof of principle that each worst-case attribute can be realized independently. For example, some diseases exhibit nearly a 100% case fatality ratio in the absence of treatment, such as rabies or septicemic plague. Other diseases have a track record of spreading to virtually every human community worldwide, such as the 1918 flu,10 and seroprevalence studies indicate that other pathogens, such as chickenpox and HSV-1, can successfully reach over 95% of a population.11,12 Under optimal virulence theory, natural evolution would be an unlikely source for pathogens with the highest possible levels of transmissibility, virulence, and global reach. But advances in biotechnology might allow the creation of diseases that combine such traits. Recent controversy has already emerged over a number of scientific experiments that resulted in viruses with enhanced transmissibility, lethality, and/or the ability to overcome therapeutics.13-17 Other experiments demonstrated that mousepox could be modified to have a 100% case fatality rate and render a vaccine ineffective.18 In addition to transmissibility and lethality, studies have shown that other disease traits, such as incubation time, environmental survival, and available vectors, could be modified as well.19-21 Although these experiments had scientific merit and were not conducted with malicious intent, their implications are still worrying. This is especially true given that there is also a long historical track record of state-run bioweapon research applying cutting-edge science and technology to design agents not previously seen in nature. The Soviet bioweapons program developed agents with traits such as enhanced virulence, resistance to therapies, greater environmental resilience, increased difficulty to diagnose or treat, and which caused unexpected disease presentations and outcomes.22 Delivery capabilities have also been subject to the cutting edge of technical development, with Canadian, US, and UK bioweapon efforts playing a critical role in developing the discipline of aerobiology.23,24 While there is no evidence of state-run bioweapons programs directly attempting to develop or deploy bioweapons that would pose an existential risk, the logic of deterrence and mutually assured destruction could create such incentives in more unstable political environments or following a breakdown of the Biological Weapons Convention.25 The possibility of a war between great powers could also increase the pressure to use such weapons—during the World Wars, bioweapons were used across multiple continents, with Germany targeting animals in WWI,26 and Japan using plague to cause an epidemic in China during WWII.27 Non-state actors may also pose a risk, especially those with explicitly omnicidal aims. While rare, there are examples. The Aum Shinrikyo cult in Japan sought biological weapons for the express purpose of causing extinction.28 Environmental groups, such as the Gaia Liberation Front, have argued that “we can ensure Gaia's survival only through the extinction of the Humans as a species … we now have the specific technology for doing the job … several different [genetically engineered] viruses could be released”(quoted in ref. 29). Groups such as R.I.S.E. also sought to protect nature by destroying most of humanity with bioweapons.30 Fortunately, to date, non-state actors have lacked the capabilities needed to pose a catastrophic bioweapons threat, but this could change in future decades as biotechnology becomes more accessible and the pool of experienced users grows.31,32 What is the appropriate response to these speculative extinction threats? A balanced biosecurity portfolio might include investments that reduce a mix of proven and speculative risks, but striking this balance is still difficult given the massive uncertainties around the low-probability, high-consequence risks. In this article, we examine the traditional spectrum of biosecurity risks (ie, biocrimes, bioterrorism, and biowarfare) to categorize biothreats by likelihood and impact, expanding the historical analysis to consider even lower-probability, higher-consequence events (catastrophic risks and existential risks). In order to produce reasoned estimates of the likelihood of different categories of biothreats, we bring together relevant data and theory and produce some first-guess estimates of the likelihood of different categories of biothreat, and we use these initial estimates to compare the cost-effectiveness of reducing existential risks with more traditional biosecurity measures. We emphasize that these models are highly uncertain, and their utility lies more in enabling order-of-magnitude comparisons rather than as a precise measure of the true risk. However, even with the most conservative models, we find that reduction of low-probability, high-consequence risks can be more cost-effective, as measured by quality-adjusted life year per dollar, especially when we account for the lives of future generations. This suggests that despite the low probability of such events, society still ought to invest more in preventing the most extreme possible biosecurity catastrophes.

Excler et al. 21 – Jean-Louis Excler, International Vaccine Institute, Seoul, Republic of Korea; Melanie Saville, Coalition for Epidemic Preparedness Innovations (CEPI), London, UK; Seth Berkley, Gavi, the Vaccine Alliance, Geneva, Switzerland; Jerome H. Kim, International Vaccine Institute, Seoul, Republic of Korea

Jean-Louis Excler, Melanie Saville, Seth Berkley, and Jerome H. Kim, "Vaccine development for emerging infectious diseases," Nat Med 27, 591–600, 4-12-2021, 

Yll Bajraktari , 2021, “The Role of AI Technology in Pandemic Response and Preparedness: Recommended Investments and Initiatives,” https://www.nscai.gov/wp-content/uploads/2021/01/NSCAI_White-Paper_The-Role-of-AI-Technology-in-Pandemic-Response-and-Preparedness.pdf

Below we summarize several ways in which AI can be applied to advance healthcare, biomedicine, and biosecurity. These are broken down across four primary areas: 1) situational awareness and disease surveillance; 2) diagnostics; 3) production of vaccines, therapeutics, and medical equipment; and, 4) ongoing healthcare - protecting the healthy and treating the sick. AI is continually evolving. Investing in these areas will improve existing applications, lead to novel use cases, and offer even greater opportunities to keep our citizens safe. While it's unclear whether AI will significantly affect the course of COVID-19, these initial investigations suggest how AI can be used to enhance pandemic preparedness and response in the future. A. Situational Awareness and Disease Surveillance Understand the threat through disease modeling. AI is being employed to better understand how diseases, including COVID-19, spread and ways to fight them. AI models are predicting the structure of proteins associated with the virus and mapping the spread of infection, enabling researchers to determine the mechanisms the virus 10 employs to infect humans and how they can be inhibited. Natural Language 11 Processing helps researchers gain faster understanding of COVID-19 by combing through vast amounts of medical research literature to find answers and build on the work of other experts. In the future, the application of AI to virology could 12 dramatically expedite our ability to understand and combat emerging viral threats. Enable early outbreak detection and real-time disease surveillance. AI is currently being used to ingest and fuse near real-time data from varied sources––including news feeds, social media, public health data, clinical health data, and digital health tools––to monitor for outbreaks, gauge new hot spots, and measure the progress and severity of the virus. Canadian company BlueDot used an AI-driven tool to detect the COVID-19 13 outbreak in Wuhan, China, doing so before widespread recognition of the disease’s emergence. Boston-based enterprise AI provider DataRobot has builtAI-based models that predict COVID-19 spread down to the county level, creating a tool that can help inform local policy decisions. AI-driven platforms will be 15 increasingly capable of universal data ingestion of unstructured multi-domain data sources. These platforms will provide leaders and public health officials with tailored alerts and real-time situational awareness of emerging threats. Monitor and prevent zoonotic spillovers. AI-enabled predictive tools can help monitor for zoonotic spillovers, identify at-risk environmental areas and inform where, 16 when, and what data to collect; thereby contributing to both research and critical early warning systems. AI has been used to identify new species of virus, as well as animal 17 species that may carry pathogens that could jump to humans. Today’s AI capabilities 18 can already be used to sift through molecular, epidemiological, ecological, and climate data to identify vulnerabilities for such zoonotic spillovers. As more data is generated 19 through this work and as the technology progresses for merging multi-source data and models, zoonotic warning systems could combine with the outbreak detection platforms described above for earlier and more accurate disease detection. Advance bioforensics for threat analysis. When an outbreak occurs, bioforensic analysis plays a key role in determining the cause as natural, intentional, or accidental.20 COVID-19 has highlighted the inherent complexity in identifying the origin of a disease outbreak. Bioforensic capabilities seek to detect high-consequence biothreats and profile pathogen samples during an incident for unique signatures that can aid attribution. AI 21 is enabling advances in key sciences for next generation bioforensics—including genomics, proteomics, and metabolomics —that seek to answer both agent-specific 22 and threat-agnostic questions. AI will further progress bioforensics by enabling 23 inferential and predictive methods for interpreting data and identifying key indicators.24 Detect pathogens with advanced sensing. New intelligent sensor technologies could compile data on new pathogens (including instances of weaponized pathogens), trace exhaled droplets dispersed through the air and deposited on surfaces, detect early 25 onset of infection through wearable sensors, and encourage social distancing through 26 mobile proximity detection. Going forward, AI will likely play an increasing role in identifying novel sensing materials and ways to build new capabilities, as well as serve a functional role within certain sensors.B. Diagnostics Diagnose patients and triage care. AI is helping scientists develop more effective tests for COVID-19 by allowing them to more rapidly and comprehensively infer biological insights that contribute to test design, as well as model and design the 27 antibodies and enzymes that are the components of immunoassay diagnostic tests. 28 AI-enabled tools are also being directly used in diagnostics to assist and inform expert assessments. Tools that analyze chest scans have assisted radiologists in detecting diseases like breast cancer and tuberculosis. Some hospitals have applied similar 29 technology to detect COVID-19 and to assess disease severity and care needs. Others 30 have built novel AI-based tools that aid diagnosis based on clinical symptoms and routine laboratory tests. However, the success of these tools is highly dependent on 31 large amounts of disease-specific training data, making it difficult to rapidly transition AI tools designed for other diseases to help healthcare professionals detect and assess COVID-19. As more data and clinical training enhance diagnostic algorithms, AI will 32 be able to contribute in additional ways to diagnostic test development, and will more reliably support radiologists and emergency care teams in rapidly identifying disease indicators and informing patient care.33 C. Development of Vaccines, Therapeutics, and Medical Equipment Rapidly discover and design vaccines and therapeutics. Researchers are leveraging AI to create simulations of how the coronavirus might interact with different therapeutics and vaccines, vastly accelerating the discovery process by exploring a great number of possibilities and narrowing the field of viable candidates. Others are using 34 AI-driven simulations to assess feasibility of repurposing existing drugs as a first step toward treating COVID-19. Additionally, AI can help speed drug and vaccine 35 production by enabling continuous manufacturing processes and digital twins tosupport clinical trials. As the technology develops, AI has the potential to support 36 automated pipelines for building models that simulate possibilities, and synthesize and validate solutions, allowing researchers to respond to emerging viral threats more rapidly with efficiently designed therapeutics and vaccines.37 Manage supply chains. Today’s supply chains are complex, and in the private sector, AI is being used to create self-correcting, smart supply chains. AI can predict 38 disruptions and vulnerabilities, monitor and prioritize inventory, prompt on-demand manufacturing, order orchestration and fulfillment, and recommend corrective actions. We foresee a future in which AI enables intelligent workflows to manage complex and global supply chains for pandemic response, dynamically managing surges and failures.39 Drive advanced manufacturing. AI has enabled the manufacturing industry to speed production and enable innovative manufacturing techniques for medical equipment, including ventilator components, face shields, and personal protective equipment. AI advances manufacturing capabilities, productivity, and quality by helping manage supply chains for raw materials, predict the need for maintenance (thereby reducing production downtime), facilitate human-machine collaboration, and enable generative design. AI further optimizes 3D-printing, which proves useful in adapting to demands 40 for pandemic-related supplies. In the near future, we believe AI-powered advanced 41 manufacturing can provide the agility needed to manage surges in demand for critical items needed during pandemics. In this new era, AI could be used to optimize manufacturing, optimize logistics and supply chains, drive autonomous equipment and vehicles, empower intelligent robots, and direct next-generation 3D-printing and on-demand manufacturing.42 D. Ongoing Healthcare - Protecting the Healthy and Treating the Sick Manage patient risk and mortality. An existing tool in use in 20 hospitals around the United States predicts which patients will experience cardiac arrest and require intensive care, helping physicians determine which patients to admit to the hospital. AI-driven 43 models are being developed that can help predict a patient’s severity of illness and risk of mortality. Such a capability can inform crucial triage decisions when hospitals 44 become overcrowded, providing decision support tools to inform allocation of limited resources. The reliability of these tools will increase as AI design and engineering 45 principles improve, allowing independent testing with comparable performance metrics.   Reduce transmission rates through use of autonomous robots. AI is being used to limit human interaction by enabling new autonomous robotic capabilities and services. These include assisting clinicians in hospitals, monitoring re-opened public spaces, enabling telehealth services, and processing test samples. A Danish company has 46 developed a line of ultraviolet light emitting robots that can travel through hallways and rooms disinfecting areas with no human intervention. Hospitals in Boston have used 47 AI-enabled robots to diagnose COVID-19 patients remotely, enabling informed allocation of in-person care, minimization of exposure, and preservation of protective equipment. Today’s robots are employed in a limited capacity to carry out a small set 48 of specialized tasks such as relaying communications, delivering supplies and meals, monitoring patients, and disinfecting. In the future, a robot may be able to oversee and complete complex, multi-phased tasks such as laboratory testing pipelines that involve teams of robots conducting sample collection, preparation, test administration, error recovery, results interpretation, and results delivery. Remotely monitor patients. With appropriate sensor data, AI is being developed to help physicians remotely monitor patients, both severe cases in intensive care units and moderately ill patients from their homes, as well as conduct remote medical trials. A 49 hospital in Houston has created a “clinical command center” using high-resolution cameras and an analytics platform that uses machine learning algorithms to assess the state of critical patients based on real-time ingested data feeds from ventilators, electrocardiogram machines and oxygen pumps as well as a patient’s electronic medical record and vital signs. A clinical team in Boston is testing an AI-driven device 50 developed by Massachusetts Institute of Technology’s Computer Science and Artificial Intelligence Laboratory that remotely monitors a COVID-19 patient’s breathing, movement, and sleep patterns using wireless signals. Meanwhile, the 51 Department of Defense (DoD) is working with company PhysIQ to monitor COVID-19 patients and those at high risk using clinical-grade biosensors that share data with a Food and Drug Administration approved, AI-enabled platform. Remote 52 monitoring capabilities will likely become increasingly integrated into treatment programs and medical trials as the technology develops, reducing the risk of disease transmission and the burden on hospitals, as well as accelerating robust clinical testing of new medicines.

II. Patents in the Context of AI Systems and Pharmaceutical Innovation

A. A Brief Primer on Patent Law

Catastrophic climate change outcomes, including human extinction, are not being taken seriously enough by scientists, a new study says.

The authors say that the consequences of more extreme warming - still on the cards if no action is taken - are "dangerously underexplored".

Again, the design of IPR regimes – in developed and developing countries alike – will be an important factor in the success or failure of countries in meeting these objectives.

There are several key intersection points between IPR, climate change and development that policymakers should take into account.

Another initiative incorporated in the strategy document also aroused concern: the claim that an enemy cyberattack on U.S. nuclear command, control, and communications (NC3) facilities would constitute a “non-nuclear strategic attack” of sufficient magnitude to justify the use of nuclear weapons in response.

Under the Obama administration’s NPR report, released in April 2010, the circumstances under which the United States would consider responding to non-nuclear attacks with nuclear weapons were said to be few. “The United States will continue to…reduce the role of nuclear weapons in deterring non-nuclear attacks,” the report stated. Although little was said about what sort of non-nuclear attacks might be deemed severe enough to justify a nuclear response, cyberstrikes were not identified as one of these. The 2018 NPR report, however, portrayed a very different environment, one in which nuclear combat is seen as increasingly possible and in which non-nuclear strategic threats, especially in cyberspace, were viewed as sufficiently menacing to justify a nuclear response. Speaking of Russian technological progress, for example, the draft version of the Trump administration’s NPR report stated, “To…correct any Russian misperceptions of advantage, the president will have an expanding range of limited and graduated [nuclear] options to credibly deter Russian nuclear or non-nuclear strategic attacks, which could now include attacks against U.S. NC3, in space and cyberspace.”1

This syllogistic equating of patent protection and national security, though perhaps initially attractive, appears on closer inspection to be overly simplistic. The purpose of this Article is to challenge this line of reasoning, showing that patent rights, and in particular unbridled assertion of patents, can impair and repeatedly has impaired national security interests. It reaches this conclusion by considering patents and national security through the lens of competition. Patents by definition suppress competition to some degree,1 2 so insofar as competition can enhance national security in certain ways, patents can diminish national security when used or licensed in particularly aggressive ways. To establish the relationship between patents and national security, then, this Article also contemplates how competition relates to national security.

The Article proceeds as follows. Part II reviews how patent policy has recently intersected with national security. It first explains the primary basis for relating innovation policy generally with national security, namely ongoing technological "races" in security-sensitive technologies. It then discusses recent events that have given rise to interest in and arguments over how patent law and policy can affect national security interests, particularly those relating to the aforementioned technology races, and identifies the appearance of the syllogistic argument that patent protection uniformly increases national security.

Right now, extreme weather events are jeopardizing global crops, resulting in crop shortages and price spikes. And in the long run, unchecked climate change threatens a third of the world’s food production, which could completely destabilize global food security and disrupt livelihoods.

There exists a desperate need for innovation in agriculture. But what does innovation look like when it comes to what we eat?

IP on AI Inventions can be a roadblock for rapid technological progress and is therefore not beneficial for society. In general, the expansion of patentable subject matter to emerging technical fields hampers diffusion of technology and is detrimental to follow on innovation, employment and economic growth.110 Expansion diminishes freedom to operate. Patents on AI Inventions such as new medicine and personalized drugs are regarded as contrary to public interest.111 The same may apply to scientific disciplines such as biotechnology, analytical chemistry, plant breeding, quantitative genetics and nutrigenomics, that integrate AI in their research programs.112 There should be no plant variety rights on innovative crops invented by an AI system that crossed the autonomy threshold.

Moreover, there is no empirical data that supports the idea that incentives or (the expectation of) a return of investment are needed in case of ‘pure’ AI Inventions. There is also no evidence of a free riding problem in the sense that non-patented AI Inventions are not embraced by the market because of the fear that successful products might be copied freely by (human or AI) competitors.

It’s called the “world in chains” scenario, where, like the preceding thought experiment, a global totalitarian government uses a novel technology to lock a majority of the world into perpetual suffering. If it sounds grim, you’d be right. But is it likely? Researchers and philosophers are beginning to ponder how it might come about – and, more importantly, what we can do to avoid it.

Existential risks (x-risks) are disastrous because they lock humanity into a single fate, like the permanent collapse of civilisation or the extinction of our species. These catastrophes can have natural causes, like an asteroid impact or a supervolcano, or be human-made from sources like nuclear war or climate change. Allowing one to happen would be “an abject end to the human story" and would let down the hundreds of generations that came before us, says Haydn Belfield, academic project manager at the Centre for the Study of Existential Risk at the University of Cambridge.

Not surprisingly, nascent global AI governance regimes remain ‘unorganized’, ‘immature’, and ‘fragmented’,3 where a range of state and non-state led initiatives and different actors have been competing for influence.4As an ambitious AI player, China has signalled strong interests in shaping, if not making, the emerging global AI order. With the open ambition of becoming a global AI superpower by 2030,5 China is envisioning its leadership role in shaping AI’s future.

This article provides a first in-depth analysis of China’s role in emerging global AI governance. It argues that China’s search for leadership in global AI governance is driven by not only domestic regulatory needs but also the desire to gain international norm and agenda setting power. China’s leadership ambition in global AI governance lies in the wider context of its aspiration to shift from a norm-taker towards a norm-shaper, if not maker. However, despite considerable efforts taken so far, this article suggests that realization of China’s leadership ambition in AI governance is facing enormous challenges especially when nascent global AI governance regimes under the influence of geopolitics and liberal democratic values have in effect allowed China limited room to demonstrate its leadership credentials.

The modernization programs of the United States and its democratic allies at the core of the international system tend to promote international security. On the other hand, the nuclear modernization programs of revisionist autocratic powers intent on challenging the international system tend to threaten global peace and stability. Thus, not all modernization programs are created equal. It is ultimately the underlying geopolitical conditions, and not solely the capabilities themselves, which determine the extent to which modernization programs promote or diminish international security.

Since 1945, the United States has been the leader of a rules-based international order that has brought the world unprecedented levels of peace, prosperity, and freedom.3 U.S. nuclear weapons have provided the security backbone of that order by deterring major power conflict in Europe and Asia.4 Additionally, U.S. extended nuclear security guarantees have protected the entire free world and dissuaded many capable states from developing independent nuclear capabilities. The modernization of U.S. nuclear weapons will therefore continue to reinforce these major sources of geopolitical peace and stability.

Will emerging technology cause nuclear war? For more than 70 years, the world has avoided major-power conflict, and many attribute this era of peace to nuclear weapons.1 In situations of mutually assured destruction, neither side has an incentive to launch a nuclear first strike because doing so will only result in self-annihilation. Maintaining secure, second-strike capabilities—the ability to absorb an enemy nuclear attack and respond with a devastating counterattack—is the key to deterrence.2 Recently, analysts have begun to worry, however, that new military technologies may call into question this model of global strategic stability.3

The world is experiencing a fourth industrial revolution (4IR) in which a wave of new and transformative technologies is being developed, including artificial intelligence (AI), additive manufacturing, quantum information technology, hypersonic missiles, biotechnology, and directed energy.4 While these technologies are expected to have profound implications for societies and economies, most are dual use and will also affect national security, including nuclear strategic stability.

VI. An Alternative Model for Patent Law at the 3A Era - Incentivizing Stakeholders Within the AI Multiplayer Model

A. Rethinking the Incentive Effect of the Current Patent Regime