The Coming Wave

The Coming Wave Plot Summary

Introduction

We stand at the threshold of perhaps the most significant technological transformation in human history. Artificial intelligence that can write essays and create art, genetic engineering tools that can edit DNA with precision, and quantum computers that solve problems beyond classical computing's reach - these aren't science fiction scenarios but technologies emerging in labs and companies worldwide. What makes this moment unique isn't just the power of these innovations but their convergence, creating what experts call "the coming wave" - a tsunami of technological change that will transform every aspect of human life. This wave brings both extraordinary promise and unprecedented peril. The same AI systems that could help solve climate change might enable autonomous weapons beyond human control. The gene editing tools that could cure inherited diseases might also create engineered pathogens more dangerous than anything in nature. As these technologies become cheaper, more powerful, and more accessible, humanity faces what may be its greatest dilemma: how to harness their benefits while preventing catastrophic misuse. Throughout this book, we'll explore why these technologies are fundamentally different from anything that came before, why traditional approaches to governance are failing, and what new paths might lead us through this treacherous but potentially magnificent future.

Chapter 1: The Unstoppable Proliferation of Transformative Technologies

Throughout human history, technology has followed a consistent pattern of proliferation. What begins as expensive, complex, and limited eventually becomes cheap, simple, and ubiquitous. The automobile serves as a perfect example of this trajectory. When first invented in the late 19th century, cars were luxury items accessible only to the wealthy elite. Yet within a few decades, Henry Ford's Model T transformed automobiles into mass-market products. By 1930, nearly 60% of American households owned a car - a remarkable shift from just 10% fifteen years earlier. This pattern repeats across virtually all technologies, from electricity to computers to smartphones. This proliferation follows what appears to be an immutable law of technological development. As technologies mature, they become simultaneously more powerful and more accessible. The first computers filled entire rooms, cost millions of dollars, and required specialized training to operate. Today, the smartphone in your pocket contains computing power that would have been unimaginable to early computer pioneers, yet costs a few hundred dollars and can be operated by a child. This democratization of capability represents one of the most significant trends in human history - the steady transfer of power from centralized institutions to individuals and small groups. What drives this unstoppable proliferation? The answer lies in the dialogue between demand and decreasing costs. As technologies become more useful, demand grows, driving competition to produce cheaper versions with more features. This in turn creates yet more demand, and costs continue to fall. The cycle repeats: experiment, improve, adapt, grow. Consider computing - in the late 1940s, experts predicted minimal demand for computers worldwide. Today, there are approximately 14 billion connected devices, with smartphones reaching global adoption in just a few years compared to the decades required for previous technologies. History demonstrates that attempts to contain technology rarely succeed long-term. The Ottoman Empire banned Arabic printing for nearly three centuries, but eventually adopted it like everyone else. Medieval guilds smashed new looms, but the Industrial Revolution came anyway. Japan and China once rejected Western technologies only to later embrace them wholeheartedly. The Luddites could not stop industrial machinery, just as horse-drawn carriage operators could not prevent automobiles from dominating transportation. Where there is demand, technology inevitably breaks through barriers and finds users. This historical pattern suggests that the coming wave of transformative technologies - AI, synthetic biology, quantum computing - will likewise proliferate globally, regardless of attempts to restrict them.

Chapter 2: AI and Synthetic Biology: The Twin Revolutions

Artificial intelligence and synthetic biology represent twin revolutions that are fundamentally reshaping our world. Unlike previous technologies that extended our physical capabilities, AI extends our cognitive abilities - our capacity to process information, make decisions, and solve problems. Modern AI systems, particularly those based on deep learning, can now perform tasks that were once thought to require human intelligence, from diagnosing diseases to creating art and writing essays. What makes these systems so powerful is their ability to identify patterns in vast amounts of data and use those patterns to make predictions or generate new content. The breakthrough moment for modern AI came in 2012 with a system called AlexNet, which revolutionized computer vision using deep learning. From there, progress accelerated dramatically. In 2016, DeepMind's AlphaGo defeated world champion Lee Sedol at the ancient game of Go - a feat experts had thought was decades away. The system learned not just from human games but by playing against itself millions of times, discovering strategies that had eluded human players for thousands of years. Today, large language models like GPT-4 can generate remarkably human-like text on virtually any topic, having been trained on trillions of words from the internet and books - more text than a human could read in thousands of lifetimes. Alongside AI, synthetic biology is experiencing its own revolution. At its core, synthetic biology is about reading, editing, and writing the code of life - DNA. The Human Genome Project, completed in 2003, marked a turning point by sequencing the three billion letters of genetic information that make up human DNA. Since then, the cost of genome sequencing has fallen from $1 billion to under $1,000 - a millionfold decrease in under twenty years. The CRISPR revolution, sparked by a breakthrough in 2012, has made gene editing remarkably precise and accessible, allowing scientists to cut and modify genes with unprecedented accuracy. The convergence of AI and synthetic biology creates entirely new possibilities. AI systems can analyze vast biological datasets to identify patterns invisible to human researchers, accelerating drug discovery and protein design. DeepMind's AlphaFold solved the protein folding problem - predicting how proteins fold based on their amino acid sequence - a challenge that had stumped scientists for decades. This breakthrough has profound implications for medicine, potentially revolutionizing drug development and our understanding of diseases. However, this convergence also amplifies risks. The same AI tools that can design life-saving drugs could potentially be used to design novel pathogens. As these technologies become more powerful and accessible, the gap between what is technically possible and what society is prepared to handle grows wider.

Chapter 3: Four Features Making the Coming Wave Uncontainable

The coming wave of technologies shares four unique features that make them extraordinarily difficult to contain, control, or regulate - far more so than previous technological revolutions. The first feature is asymmetry - these technologies enable individuals or small groups to wield disproportionate power. In Ukraine, consumer drones modified by small teams have successfully disabled Russian military columns. AI systems trained by small teams can write as much text as all of humanity combined. A single pathogenic experiment could potentially trigger a pandemic. This asymmetry represents a massive transfer of power away from traditional institutions toward anyone with the motivation to deploy these technologies. The second feature is hyper-evolution - these technologies develop and improve at unprecedented speeds. While previous innovations like cars evolved over decades, allowing time for safety standards to catch up, AI systems can make dramatic leaps in capability in months or even weeks. This pace is driven by exponential improvements in computing power, data availability, and algorithmic efficiency. What's more, these technologies are increasingly helping design themselves - AI systems can optimize chip designs, which then enable more powerful AI, creating a self-reinforcing cycle of improvement that outpaces human oversight and regulation. The third feature is that these technologies are omni-use rather than merely dual-use. Traditional dual-use technologies have both civilian and military applications - like GPS or nuclear power. But the coming wave's technologies are fundamentally general in nature. The same AI system that discovers life-saving drugs can be redirected to find deadly toxins. The same gene editing tools that cure diseases can create dangerous pathogens. These technologies tend toward generality because that makes them more valuable - just as smartphones evolved from simple phones to devices that take photos, play games, and navigate cities. This omni-use nature makes it nearly impossible to predict all potential applications or harms. The fourth and perhaps most unsettling feature is autonomy. Throughout history, technology has been a tool under human control. But AI systems are increasingly capable of taking actions without immediate human approval. AlphaGo's famous "move 37" against Lee Sedol wasn't programmed - the system discovered this winning strategy on its own. Today's large language models generate outputs that weren't explicitly coded by their designers. As these systems gain more autonomy, they become harder to predict, explain, or control. The combination of these four features - asymmetry, hyper-evolution, omni-use nature, and autonomy - creates what the authors call "the containment problem" - the challenge of keeping these powerful technologies under meaningful human control.

Chapter 4: The Dilemma Between Catastrophe and Dystopia

The coming wave presents humanity with a terrible dilemma: we face the prospect of either catastrophic or dystopian outcomes, with the narrow path between them growing increasingly difficult to navigate. On one side lies the risk of catastrophe. As technologies become cheaper, more powerful, and more widely accessible, they empower a diverse array of actors to cause disruption, instability, and harm on an unprecedented scale. AI systems could enable devastating cyberattacks that cripple critical infrastructure. Synthetic biology tools could allow the creation of engineered pathogens far more transmissible and lethal than anything found in nature. Autonomous weapons could make warfare more lethal and less controllable. On the other side lies the risk of dystopia. To prevent catastrophic misuse, societies might implement increasingly authoritarian measures. This could involve mass surveillance, restrictions on privacy, and intrusions into private life justified by the need to guard against extreme outcomes. China's social credit system offers a glimpse of this potential future - a world where AI-powered surveillance monitors citizens' every move, rewarding compliance and punishing deviation. Even democratic societies might drift toward such systems in the name of security, creating what some scholars call "the surveillance state paradox" - the more powerful and accessible dangerous technologies become, the more societies feel compelled to monitor and control their citizens. What makes this dilemma so acute is that both pursuing and not pursuing these technologies is fraught with risk. We desperately need these technologies to solve our most pressing problems. The challenges of climate change, aging populations, sustainable food production, and affordable healthcare likely cannot be addressed without the innovations of the coming wave. AI and synthetic biology offer potential solutions to some of humanity's greatest threats. Yet the same technologies that could save us also threaten to destabilize or destroy us if misused or if they malfunction. The difficulty is heightened by what the authors term "pessimism aversion" - the tendency for people, particularly elites, to ignore, downplay, or reject narratives they see as overly negative. When confronted with the potential dangers of new technologies, many respond with dismissal or discomfort rather than serious engagement. This emotional reaction leads us to overlook critical trends unfolding before our eyes. The result is a dangerous form of technological determinism - the assumption that technological development will inevitably lead to positive outcomes without deliberate intervention. History suggests otherwise. The path between catastrophe and dystopia requires active navigation, not passive acceptance of technological trajectories.

Chapter 5: The Challenge of Technological Containment

Containment represents our most urgent challenge in the face of the coming technological wave. It refers to the overarching ability to monitor, curtail, control, and if necessary, close down technologies at any stage of their development or deployment. But is containment even possible? History offers few encouraging examples. Nuclear weapons might seem like a partial success story - they've been used in warfare only twice, and only nine countries possess them today. But this containment came at enormous cost and required extraordinary measures: international treaties, rigorous inspection regimes, and the sobering reality of mutually assured destruction. What makes containment so challenging? First, there's the fundamental nature of technology itself - its tendency to proliferate, become cheaper, and grow more accessible over time. Second, there are powerful incentives driving technological development: geopolitical competition, enormous financial rewards, scientific curiosity, and even human ego. Nations feel an existential need to keep pace with rivals in AI and biotechnology. Companies see trillion-dollar market opportunities. Researchers are rewarded for publishing breakthrough findings. And individuals seek status, recognition, and legacy through technological achievement. These incentives create what the author calls "the pessimism-aversion trap" - the misguided analysis that arises when we're overwhelmed by fear of confronting potentially dark realities. The challenge is compounded by the global, distributed nature of technological development. Research happens across thousands of institutions worldwide, with findings shared openly in journals and conferences. The culture of science values openness, peer review, and publication. Even private companies regularly contribute intellectual property to open-source projects. This openness accelerates innovation but makes controlling or limiting technology nearly impossible. Unlike nuclear weapons, which require rare materials and massive industrial infrastructure, many emerging technologies can be developed with widely available resources and knowledge. Despite these challenges, the author argues that containment must be possible. The alternative - allowing these technologies to proliferate without meaningful controls - risks either catastrophic misuse or dystopian surveillance states. The solution likely involves a nested set of constraints working at multiple levels: from technical safeguards in code and DNA to international treaties governing dangerous applications. This approach to containment isn't about stopping technological progress entirely. Rather, it's about ensuring that technology serves humanity rather than threatening it. Effective containment requires new institutions and governance models. Traditional regulatory approaches move too slowly and lack the technical expertise to oversee rapidly evolving technologies. New governance structures must combine technical understanding with ethical principles and democratic accountability. They must operate at both national and international levels, as unilateral regulations can simply push dangerous research to less regulated jurisdictions. And they must be flexible enough to adapt as technologies evolve, avoiding the trap of regulating yesterday's technologies while tomorrow's emerge uncontrolled.

Chapter 6: Navigating the Path Between Progress and Safety

Finding the narrow path between catastrophic risks and dystopian control systems requires a multifaceted approach that balances innovation with safety. The first essential step is massive investment in safety research - not as an afterthought but as a core component of technological development. For every dollar spent making AI more powerful or synthetic biology more versatile, a comparable investment should go toward making these technologies safer and more controllable. This research must be open and collaborative, avoiding the secrecy that often surrounds security-related work, as safety challenges are too complex and urgent to be solved by isolated teams. Technical safeguards represent another critical element. For AI systems, this means developing robust methods for alignment - ensuring AI objectives remain compatible with human values even as systems become more capable. For synthetic biology, it means creating biological safeguards like kill switches that prevent engineered organisms from surviving outside controlled environments. These technical measures must be complemented by rigorous testing protocols and monitoring systems that can detect problems before they escalate to dangerous levels. International cooperation will be essential, as unilateral approaches to containment are doomed to fail in a globalized world. This doesn't necessarily mean creating new bureaucratic institutions, but rather establishing shared principles, standards, and verification mechanisms that can be adapted to different contexts. The Nuclear Non-Proliferation Treaty and the Montreal Protocol on ozone-depleting substances provide models for how international agreements can effectively govern dangerous technologies while allowing beneficial applications to flourish. The private sector must also transform its approach to innovation. The "move fast and break things" ethos that dominated early digital development is fundamentally incompatible with technologies that could potentially "break" civilization itself. New corporate structures, incentive systems, and governance models are needed to ensure that companies developing these technologies prioritize safety alongside profits. This might include public benefit corporations with explicit safety mandates, industry-wide standards bodies with real enforcement power, and financial incentives that reward responsible innovation. Perhaps most importantly, we need to democratize these decisions. The trajectory of transformative technologies shouldn't be determined solely by technical experts, corporate executives, or government officials. Citizens must be meaningfully involved in setting boundaries and priorities, through mechanisms ranging from participatory technology assessment to citizen assemblies. This democratic engagement isn't just about legitimacy - it's about drawing on diverse perspectives to identify risks and benefits that technical experts might miss. The coming wave of technology cannot be stopped, but its course can be shaped - and that shaping should reflect the values and priorities of humanity as a whole, not just those of a technological elite.

Summary

The coming wave of transformative technologies presents humanity with both extraordinary promise and existential risk. Artificial intelligence and synthetic biology are evolving at breathtaking speed, offering solutions to our greatest challenges while simultaneously creating new vulnerabilities that could undermine the foundations of civilization. What makes this moment unique is not just the power of these technologies but their fundamental characteristics: asymmetry that empowers small groups, hyper-evolution that outpaces governance, omni-use applications that span every domain, and autonomy that reduces human control. The key insight from this exploration is that containment - the practice of developing powerful technologies in ways that preserve their benefits while minimizing their risks - represents our best path forward. This requires reimagining our approach to innovation at every level, from technical design to institutional governance to cultural norms. It demands unprecedented cooperation across national boundaries, economic sectors, and academic disciplines. As we stand at this technological inflection point, the question is not whether we can stop the coming wave, but whether we can learn to navigate it together, harnessing its power while avoiding being swept away by its force. How will you participate in shaping these technologies? What values should guide their development? These questions aren't just for technologists or policymakers - they're for all of us, as we collectively determine the future of humanity in an age of unprecedented technological power.

About Author

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Mustafa Suleyman

Mustafa Suleyman is the co-founder and CEO of Inflection AI. Previously he co-founded DeepMind, one of the world’s leading AI companies. After a decade at DeepMind, Suleyman became vice president of AI product management and AI policy at Google.

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