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You have all seen the reports, whether it is from Gartner, or McKinsey, or the MIT Media Lab, or the OECD, or the PwC Artificial Intelligence Study ... oh, the list goes on. There are lots of studies.
All the studies and reports pretty much run as follows:
It’s 2035, and artificial intelligence is everywhere. AI systems run hospitals, operate airlines, and battle each other in the courtroom. Productivity has spiked to unprecedented levels, and countless previously unimaginable businesses have scaled at blistering speed, generating immense advances in well-being. New products, cures, and innovations hit the market daily, as science and technology kick into overdrive. And yet the world is growing both more unpredictable and more fragile, as terrorists find new ways to menace societies with intelligent, evolving cyberweapons and white-collar workers lose their jobs en masse.
Just a year ago, that scenario would have seemed purely fictional; today, it seems nearly inevitable. Generative AI systems can already write more clearly and persuasively than most humans and can produce original images, art, and even computer code based on simple language prompts. And generative AI is only the tip of the iceberg. Its arrival marks a "Big Bang moment" - the beginning of a world-changing technological revolution that will remake politics, economies, and societies.
Like past technological waves, AI will pair extraordinary growth and opportunity with immense disruption and risk. But unlike previous waves, it will also initiate a seismic shift in the structure and balance of global power as it threatens the status of nation-states as the world’s primary geopolitical actors. Whether they admit it or not, AI’s creators are themselves geopolitical actors, and their sovereignty over AI further entrenches the emerging “technopolar” order—one in which technology companies wield the kind of power in their domains once reserved for nation-states.
For the past decade, big technology firms have effectively become independent, sovereign actors in the digital realms they have created. AI accelerates this trend and extends it far beyond the digital world. The technology’s complexity and the speed of its advancement will make it impossible for governments to make relevant rules at a reasonable pace. People say "Governments must catch up soon!" Pointless. They never will.
Yes, yes, yes. I keep up. I have read that policymakers around the world "have begun to wake up to the challenges posed by AI and wrestle with how to govern it". In May 2023, the G-7 launched the “Hiroshima AI process,” a forum devoted to harmonizing AI governance. In June, the European Parliament passed a draft of the EU’s AI Act, the first comprehensive attempt by the European Union to erect safeguards around the AI industry.
But as I noted last week, the EU’s AI Act is now dead-on-arrival. France and Germany refuse to add rules for foundation models, such as OpenAI Inc.’s GPTs, or any generative AI. And now other EU member states are climbing on board, worried about EU overregulation that will cut off Europe’s chances of creating a local rival to ChatGPT. As if.
And in July, UN Secretary-General Antonio Guterres called for the establishment of a global AI regulatory watchdog. Antonio: try to do something in Ukraine and/or the Middle East and/or Yemen and/or ... oh, forget it. You're ill-equipped to handle anything.
Meanwhile, in the United States, politicians on both sides of the aisle are calling for regulatory action. But many agree with Ted Cruz, the Republican senator from Texas (and I cannot believe I could agree with him on anything) who said the U.S. Congress “doesn’t know what the hell it’s doing, and knows nothing about AI.”
Unfortunately, too much of the debate about AI governance remains trapped in a dangerous false dilemma: leverage artificial intelligence to expand national power or stifle it to avoid its risks. Even those who accurately diagnose the problem are trying to solve it by shoehorning AI into existing or historical governance frameworks.
Yet AI cannot be governed like any previous technology, and it is already shifting traditional notions of geopolitical power.
People . do . not . get it.
So, like it or not, 2035 is coming. It will be defined by the positive advances enabled by AI ... and also by the negative disruptions caused by it.
FASTER! HIGHER! STRONGER!
AI is different - different from other technologies and different in its effect on power. It does not just pose policy challenges; its hyper-evolutionary nature also makes solving those challenges progressively harder. That is the AI power paradox, that is the challenge, that is the dilemma, that is the conundrum.
The pace of progress is staggering. Take Moore’s Law, which has successfully predicted the doubling of computing power every two years. The new wave of AI makes that rate of progress seem quaint.
When OpenAI launched its first large language model, known as GPT-1, in 2018, it had 117 million parameters—a measure of the system’s scale and complexity.
Note to readers: for a short tutorial on parameters click here.
Five years later, the company’s fourth-generation model, GPT-4, is thought to have over a trillion. The amount of computation used to train the most powerful AI models has increased by a factor of ten every year for the last ten years.
Put another way, today’s most advanced AI models - also known as “frontier” models - use five billion times the computing power of cutting-edge models from a decade ago. Processing that once took weeks now happens in seconds. Models that can handle tens of trillions of parameters are coming in the next couple of years. “Brain scale” models with more than 100 trillion parameters - roughly the number of synapses in the human brain - will be viable within five years.
With each new order of magnitude, unexpected capabilities emerge. Few predicted that training on raw text would enable large language models to produce coherent, novel, and even creative sentences. Fewer still expected language models to be able to compose music or solve scientific problems, as some now can. Soon, AI developers will likely succeed in creating systems with self-improving capabilities—a critical juncture in the trajectory of this technology that should give everyone pause.
AI models are also doing more with less. Yesterday’s cutting-edge capabilities are running on smaller, cheaper, and more accessible systems today. Just three years after OpenAI released GPT-3, open-source teams have created models capable of the same level of performance that are less than one-sixtieth of its size - that is, 60 times cheaper to run in production, entirely free, and available to everyone on the Internet. Future large language models will probably follow this efficiency trajectory, becoming available in open-source form just two or three years after leading AI labs spend hundreds of millions of dollars developing them.
As with any software or code, AI algorithms are much easier and cheaper to copy and share (or steal) than physical assets. Proliferation risks are obvious. Meta’s powerful Llama-1 large language model, for instance, leaked to the Internet within days of debuting in March 2023. Although the most powerful models still require sophisticated hardware to work, midrange versions can run on computers that can be rented for a few dollars an hour. Soon, such models will run on smartphones. No technology this powerful has become so accessible, so widely, so quickly.
AI also differs from older technologies in that almost all of it can be characterized as “dual use” - having both military and civilian applications. Many systems are inherently general, and indeed, generality is the primary goal of many AI companies. They want their applications to help as many people in as many ways as possible.
But the same systems that drive cars can drive tanks. An AI application built to diagnose diseases might be able to create - and weaponize - a new one. The boundaries between the safely civilian and the militarily destructive are inherently blurred, which partly explains why the United States has (tried) to restrict the export of the most advanced semiconductors to China.
All this plays out on a global field: once released, AI models can and will be everywhere. And it will take just one malign or “breakout” model to wreak havoc. For that reason, regulating AI cannot be done in a patchwork manner. There is little use in regulating AI in some countries if it remains unregulated in others. Because AI can proliferate so easily.
What is more, the damage AI can do has no obvious cap, even as the incentives to build it (and the benefits of doing so) continue to grow. AI is being used to generate and spread toxic misinformation, eroding social trust and democracy; to surveil, manipulate, and subdue citizens, undermining individual and collective freedom; or to create powerful digital or physical weapons that threaten human lives. AI could also destroy millions of jobs, worsening existing inequalities and creating new ones; entrench discriminatory patterns and distort decision-making by amplifying bad information feedback loops; or spark unintended and uncontrollable military escalations that lead to war.
Nor is the time frame clear for the biggest risks. Online misinformation is an obvious short-term threat, just as autonomous warfare seems plausible in the medium term. Farther out on the horizon lurks the promise of artificial general intelligence, the still uncertain point where AI exceeds human performance at any given task, and the (admittedly speculative) peril that AGI could become self-directed, self-replicating, and self-improving beyond human control.
AI is not the first technology with some of these potent characteristics, but it is the first to combine them all. AI systems are not like cars or airplanes, which are built on hardware amenable to incremental improvements and whose most costly failures come in the form of individual accidents. They are not like chemical or nuclear weapons, which are difficult and expensive to develop and store, let alone secretly share or deploy. As their enormous benefits become self-evident, AI systems will only grow bigger, better, cheaper, and more ubiquitous. They will even become capable of quasi autonomy - able to achieve concrete goals with minimal human oversight - and, potentially, of self-improvement. Any one of these features would challenge traditional governance models; all of them together render these models hopelessly inadequate.
TOO POWERFUL TO PAUSE
As if that were not enough, by shifting the structure and balance of global power, AI complicates the very political context in which it is governed.
AI is not just software development as usual; it is an entirely new means of projecting power. In some cases, it will upend existing authorities; in others, it will entrench them. Moreover, its advancement is being propelled by irresistible incentives: every nation, corporation, and individual will want some version of it.
Within countries, AI will empower those who wield it to surveil, deceive, and even control populations - supercharging the collection and commercial use of personal data in democracies and sharpening the tools of repression authoritarian governments use to subdue their societies. Across countries, AI will be the focus of intense geopolitical competition.
Whether for its repressive capabilities, economic potential, or military advantage, AI supremacy will be a strategic objective of every government with the resources to compete. The least imaginative strategies will pump money into homegrown AI champions or attempt to build and control supercomputers and algorithms. More nuanced strategies will foster specific competitive advantages, as France seeks to do by directly supporting AI startups; the United Kingdom, by capitalizing on its world-class universities and venture capital ecosystem - and the EU, by shaping the global conversation on regulation and norms because that is all the EU can do.
The vast majority of countries have neither the money nor the technological know-how to compete for AI leadership. Their access to frontier AI will instead be determined by their relationships with a handful of already rich and powerful corporations and states. This dependence threatens to aggravate current geopolitical power imbalances. The most powerful governments will vie to control the world’s most valuable resource while, once again, countries in the global South will be left behind.
This is not to say that only the richest will benefit from the AI revolution. Like the Internet and smartphones, AI will proliferate without respect for borders, as will the productivity gains it unleashes. And like energy and green technology, AI will benefit many countries that do not control it, including those that contribute to producing AI inputs such as semiconductors.
At the other end of the geopolitical spectrum, however, the competition for AI supremacy will be fierce. At the end of the Cold War, powerful countries might have cooperated to allay one another’s fears and arrest a potentially destabilizing technological arms race.
But today’s tense geopolitical environment makes such cooperation much harder - well, makes it impossible. AI is not just another tool or weapon that can bring prestige, power, or wealth. It has the potential to enable a significant military and economic advantage over adversaries. Rightly or wrongly, the two players that matter most - China and the United States - both see AI development as a zero-sum game that will give the winner a decisive strategic edge in the decades to come.
From the vantage point of Washington and Beijing, the risk that the other side will gain an edge in AI is greater than any theoretical risk the technology might pose to society or to their own domestic political authority. For that reason, both the U.S. and Chinese governments are pouring immense resources into developing AI capabilities while working to deprive each other of the inputs needed for next-generation breakthroughs.
Note to readers: So far, the United States has been far more successful than China in doing the latter, especially with its export controls on advanced semiconductors, although as I have noted those "controls" are pretty porous and advanced U.S. semiconductors are getting to China. Regulators just do not understand global economics and global supply chains.
This zero-sum dynamic - and the lack of trust on both sides - means that Beijing and Washington are focused on accelerating AI development, rather than slowing it down. In their view, a “pause” in development to assess risks, as some AI industry leaders have called for, would amount to foolish unilateral disarmament.
But this perspective assumes that states can assert and maintain at least some control over AI. This may be the case in China, which has integrated its tech companies into the fabric of the state.
Yet in the West and elsewhere, AI is more likely to undermine state power than to bolster it. Outside China, a handful of large, specialist AI companies currently control every aspect of this new technological wave: what AI models can do, who can access them, how they can be used, and where they can be deployed. And because these companies jealously guard their computing power and algorithms, they alone understand (most of) what they are creating and (most of) what those creations can do. These few firms may retain their advantage for the foreseeable future- or they may be eclipsed by a raft of smaller players as low barriers to entry, open-source development, and near-zero marginal costs lead to uncontrolled proliferation of AI. Either way, the AI revolution will take place outside government.
To a limited degree, some of these challenges resemble those of earlier digital technologies. Internet platforms, social media, and even devices such as smartphones all operate, to some extent, within sandboxes controlled by their creators. When governments have summoned the political will, they have been able to implement regulatory regimes for these technologies, such as the EU’s General Data Protection Regulation, Digital Markets Act, and Digital Services Act.
But such regulation took a decade or more to materialize in the EU (and there are "interpretation holes" big enough to drive a truck through so difficult to enforce) - and it still has not materialized in the United States.
And it won't materialize. Because AI moves far too quickly for policymakers to respond at their usual pace. Moreover, social media and other older digital technologies do not help create themselves, and the commercial and strategic interests driving them never dovetailed in quite the same way: Twitter and TikTok are powerful, but few think they could transform the global economy.
This all means that at least for the next few years, AI’s trajectory will be largely determined by the decisions of a handful of private businesses, regardless of what policymakers in Brussels or Washington do. In other words, technologists, not policymakers or bureaucrats, will exercise authority over a force that could profoundly alter both the power of nation-states and how they relate to each other.
MOVING TARGET, EVOLVING WEAPON
Governments will always be behind the curve. That is just the nature of our exponential times. Most proposals for governing AI treat it as a conventional problem amenable to the state-centric solutions of the twentieth century: compromises over rules hashed out by political leaders sitting around a table. But that will not work, cannot work for AI.
And you just need to laugh. Advocates for international-level agreements to tame AI tend to reach for the model of nuclear arms control. But AI systems are not only infinitely easier to develop, steal, and copy than nuclear weapons - they are controlled by private companies, not governments. As the new generation of AI models diffuses faster than ever, the nuclear comparison looks ever more out of date. Even if governments can successfully control access to the materials needed to build the most advanced models - as the Biden administration is attempting to do by preventing China from acquiring advanced chips - they can do little to stop the proliferation of those models once they are trained and therefore require far fewer chips to operate.
For global AI governance to work, it would need to be specific to the technology, the challenges it poses, and the structure and balance of power in which it operates. But because the evolution, uses, risks, and rewards of AI are unpredictable, AI governance cannot be fully specified at the outset - or at any point in time, for that matter.
The starting point for all of this is quite simple. In the case of AI, the sheer velocity of technological progress will quickly overwhelm any ability of existing governance structures to catch up and keep up. Private technology companies may lack sovereignty in the traditional sense, but they wield real - even sovereign - power and agency in the digital spaces they have created and effectively govern.
And the complexity. AI governance would need to cover the entire supply chain - from manufacturing to hardware, software to services, and providers to users. This means regulation and oversight along every node of the AI value chain, from AI chip production to data collection, model training to end use, and across the entire stack of technologies used in a given application.
Plus, all of that requires a deep understanding and up-to-date knowledge of the technologies in question. Regulators and other authorities would need oversight of and access to key AI models. In effect, they would need an audit system that can not only track capabilities at a distance but also directly access core technologies, which in turn will require the right talent.
I . M . P . O . S . S . I . B . L . E
And it will grow worse. The devolved nature of AI development and core characteristics of the technology, such as open-source proliferation, increase the likelihood that it will be weaponized by cybercriminals, state-sponsored actors, and lone wolves.
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