Attributable to Deputy Secretary of Defense Kathleen Hicks:
The Department of Defense must meet the urgency of today’s threats and tomorrow’s challenges with innovation in all portfolios — including how we build and execute our budget. This is critical not only to maintain the trust of the American taxpayer, but also to ensure that DoD can rapidly transition, integrate, and deliver cutting-edge capabilities to the warfighter at speed and scale.
It’s no secret that DoD’s resource allocation process was born in the industrial age, and the Department has undertaken significant reforms to improve it. The recommendations made in the Commission on Planning, Programming, Budgeting, and Execution (PPBE) Reform’s Interim Report released today will further these efforts. I am directing the Department to adopt all actions that can be implemented now, as recommended by the Commission and within its purview. We look forward to working with Congress on all other proposed recommendations included in this interim report.
The PPBE Reform Commission’s work is immensely important to assisting Congress and DoD in the nation’s efforts to stay ahead of the pacing challenge, ensuring our agility in fielding combat credible forces at speed and scale. I stand ready to provide continued DoD cooperation with the Commission and to receive its final report in March 2024.
September/October 2023 Published on August 16, 2023
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 AIsystems 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 almost impossible for governments to make relevant rules at a reasonable pace. If governments do not catch up soon, it is possible they never will.
Thankfully, 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. And in July, UN Secretary-General Antonio Guterres called for the establishment of a global AI regulatory watchdog. 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, who concluded in June that Congress “doesn’t know what the hell it’s doing.”
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.
The challenge is clear: to design a new governance framework fit for this unique technology. If global governance of AI is to become possible, the international system must move past traditional conceptions of sovereignty and welcome technology companies to the table. These actors may not derive legitimacy from a social contract, democracy, or the provision of public goods, but without them, effective AI governance will not stand a chance. This is one example of how the international community will need to rethink basic assumptions about the geopolitical order. But it is not the only one.
A challenge as unusual and pressing as AI demands an original solution. Before policymakers can begin to hash out an appropriate regulatory structure, they will need to agree on basic principles for how to govern AI. For starters, any governance framework will need to be precautionary, agile, inclusive, impermeable, and targeted. Building on these principles, policymakers should create at least three overlapping governance regimes: one for establishing facts and advising governments on the risks posed by AI, one for preventing an all-out arms race between them, and one for managing the disruptive forces of a technologyunlike anything the world has seen.
Like it or not, 2035 is coming. Whether it is defined by the positive advances enabled by AI or the negative disruptions caused by it depends on what policymakers do now.
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.
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. 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 billiontimes 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. 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 restricted 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, its governance can have no gaps.
What is more, the damage AI might do has no obvious cap, even as the incentives to build it (and the benefits of doing so) continue to grow. AI could be 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. All these dangers need to be factored into governance architecture from the outset.
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.
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. 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—Chinaand 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.
China and the United States both see AI development as a zero-sum game.
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. (So far, the United States has been far more successful than China in doing the latter, especially with its export controls on advanced semiconductors.) 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 it still has not fully materialized in the United States. 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. That makes the challenge of governing AI unlike anything governments have faced before, a regulatory balancing act more delicate—and more high stakes—than any policymakers have attempted.
MOVING TARGET, EVOLVING WEAPON
Governments are already behind the curve. 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 for AI.
Regulatory efforts to date are in their infancy and still inadequate. The EU’s AI Act is the most ambitious attempt to govern AI in any jurisdiction, but it will apply in full only beginning in 2026, by which time AI models will have advanced beyond recognition. The United Kingdom hasproposedan even looser, voluntary approach to regulating AI, but it lacks the teeth to be effective. Neither initiative attempts to govern AI development and deployment at the global level—something that will be necessary for AI governance to succeed. And while voluntary pledges to respect AI safety guidelines, such as those made in July by seven leading AI developers, including Inflection AI, led by one of us (Suleyman), are welcome, they are no substitute for legally binding national and international regulation.
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 must be tailored to the specific nature of 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. It must be as innovative and evolutionary as the technology it seeks to govern, sharing some of the characteristics that make AI such a powerful force in the first place. That means starting from scratch, rethinking and rebuilding a new regulatory framework from the ground up.
The overarching goal of any global AI regulatory architecture should be to identify and mitigate risks to global stability without choking off AI innovation and the opportunities that flow from it. Call this approach “technoprudentialism,” a mandate rather like the macroprudential role played by global financial institutions such as the Financial Stability Board, the Bank of International Settlements, and the International Monetary Fund.Their objective is to identify and mitigate risks to global financial stability without jeopardizing economic growth.
A technoprudential mandate would work similarly, necessitating the creation of institutional mechanisms to address the various aspects of AI that could threaten geopolitical stability. These mechanisms, in turn, would be guided by common principles that are both tailored to AI’s unique features and reflect the new technological balance of power that has put tech companies in the driver’s seat. These principles would help policymakers draw up more granular regulatory frameworks to govern AI as it evolves and becomes a more pervasive force.
The first and perhaps most vital principle for AI governance is precaution.As the term implies, technoprudentialism is at its core guided by the precautionary credo: first, do no harm. Maximally constraining AI would mean forgoing its life-altering upsides, but maximally liberating it would mean risking all its potentially catastrophic downsides. In other words, the risk-reward profile for AI is asymmetric. Given the radical uncertainty about the scale and irreversibility of some of AI’s potential harms, AI governance must aim to prevent these risks before they materialize rather than mitigate them after the fact. This is especially important because AI could weaken democracy in some countries and make it harder for them to enact regulations. Moreover, the burden of proving an AI system is safe above some reasonable threshold should rest on the developer and owner; it should not be solely up to governments to deal with problems once they arise.
AI governance must also be agile so that it can adapt and correct course as AI evolves and improves itself. Public institutions often calcify to the point of being unable to adapt to change. And in the case of AI, the sheer velocity of technological progress will quickly overwhelm the ability of existing governance structures to catch up and keep up. This does not mean that AI governance should adopt the “move fast and break things” ethos of Silicon Valley, but it should more closely mirror the nature of the technology it seeks to contain.
In addition to being precautionary and agile, AI governance must be inclusive, inviting the participation of all actors needed to regulate AI in practice. That means AI governance cannot be exclusively state centered, since governments neither understand nor control AI. 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. These nonstate actors should not be granted the same rights and privileges as states, which are internationally recognized as acting on behalf of their citizens. But they should be parties to international summits and signatories to any agreements on AI.
Such a broadening of governance is necessary because any regulatory structure that excludes the real agents of AI power is doomed to fail. In previous waves of tech regulation, companies were often afforded so much leeway that they overstepped, leading policymakers and regulators to react harshly to their excesses. But this dynamic benefited neither tech companies nor the public. Inviting AI developers to participate in the rule-making process from the outset would help establish a more collaborative culture of AI governance, reducing the need to rein in these companies after the fact with costly and adversarial regulation.
AI is a problem of the global commons, not just the preserve of two superpowers.
Tech companies should not always have a say; some aspects of AI governance are best left to governments, and it goes without saying that states should always retain final veto power over policy decisions. Governments must also guard against regulatory capture to ensure that tech companies do not use their influence within political systems to advance their interests at the expense of the public good. But an inclusive, multistakeholder governance model would ensure that the actors who will determine the fate of AI are involved in—and bound by—the rule-making processes.In addition to governments (especially but not limited to China and the United States) and tech companies (especially but not limited to the Big Tech players), scientists, ethicists, trade unions, civil society organizations, and other voices with knowledge of, power over, or a stake in AI outcomes should have a seat at the table. The Partnership on AI—a nonprofit group that convenes a range of large tech companies, research institutions, charities, and civil society organizations to promote responsible AI use—is a good example of the kind of mixed, inclusive forum that is needed.
AI governance must also be as impermeable as possible. Unlike climate change mitigation, where success will be determined by the sum of all individual efforts, AI safety is determined by the lowest common denominator: a single breakout algorithm could cause untold damage. Because global AI governance is only as good as the worst-governed country, company, or technology, it must be watertight everywhere—with entry easy enough to compel participation and exit costly enough to deter noncompliance. A single loophole, weak link, or rogue defector will open the door to widespread leakage, bad actors, or a regulatory race to the bottom.
In addition to covering the entire globe, AI governance must cover the entire supply chain—from manufacturing to hardware, software to services, and providers to users. This means technoprudential 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. Such impermeability will ensure there are no regulatory gray areas to exploit.
Finally, AI governance will need to be targeted, rather than one-size-fits-all. Because AI is a general-purpose technology, it poses multidimensional threats. A single governance tool is not sufficient to address the various sources of AI risk. In practice, determining which tools are appropriate to target which risks will require developing a living and breathing taxonomy of all the possible effects AI could have—and how each can best be governed. For example, AI will be evolutionary in some applications, exacerbating current problems such as privacy violations, and revolutionary in others, creating entirely new harms. Sometimes, the best place to intervene will be where data is being collected. Other times, it will be the point at which advanced chips are sold—ensuring they do not fall into the wrong hands. Dealing with disinformation and misinformation will require different tools than dealing with the risks of AGI and other uncertain technologies with potentially existential ramifications. A light regulatory touch and voluntary guidance will work in some cases; in others, governments will need to strictly enforce compliance.
All of this requires deep understanding and up-to-date knowledge of the technologies in question. Regulators and other authorities will need oversight of and access to key AI models. In effect, they will 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. Only such measures can ensure that new AI applications are proactively assessed, both for obvious risks and for potentially disruptive second- and third-order consequences. Targeted governance, in other words, must be well-informed governance.
THE TECHNOPRUDENTIAL IMPERATIVE
Built atop these principles should be a minimum of three AI governance regimes, each with different mandates, levers, and participants. All will have to be novel in design, but each could look for inspiration to existing arrangements for addressing other global challenges—namely, climate change, arms proliferation, and financial stability.
The first regime would focus on fact-finding and would take the form of a global scientific body to objectively advise governments and international bodies on questions as basic as what AI is and what kinds of policy challenges it poses. If no one can agree on the definition of AI or the possible scope of its harms, effective policymaking will be impossible. Here, climate change is instructive. To create a baseline of shared knowledge for climate negotiations, the United Nations established the Intergovernmental Panel on Climate Change and gave it a simple mandate: provide policymakers with “regular assessments of the scientific basis of climate change, its impacts and future risks, and options for adaptation and mitigation.” AI needs a similar body to regularly evaluate the state of AI, impartially assess its risks and potential impacts, forecast scenarios, and consider technical policy solutions to protect the global public interest. Like the IPCC, this body would have a global imprimatur and scientific (and geopolitical) independence. And its reports could inform multilateral and multistakeholder negotiations on AI, just as the IPCC’s reports inform UN climate negotiations.
The world also needs a way to manage tensions between the major AI powers and prevent the proliferation of dangerous advanced AI systems. The most important international relationship in AI is the one between the United States and China. Cooperation between the two rivals is difficult to achieve under the best of circumstances. But in the context of heightened geopolitical competition, an uncontrolled AI race could doom all hope of forging an international consensus on AI governance. One area where Washington and Beijing may find it advantageous to work together is in slowing the proliferation of powerful systems that could imperil the authority of nation-states. At the extreme, the threat of uncontrolled, self-replicating AGIs—should they be invented in the years to come—would provide strong incentives to coordinate on safety and containment.
On all these fronts, Washington and Beijing should aim to create areas of commonality and even guardrails proposed and policed by a third party. Here, the monitoring and verification approaches often found in arms control regimes might be applied to the most important AI inputs, specifically those related to computing hardware, including advanced semiconductors and data centers. Regulating key chokepoints helped contain a dangerous arms race during the Cold War, and it could help contain a potentially even more dangerous AI race now.
Few powerful constituencies favor containing AI.
But since much of AI is already decentralized, it is a problem of the global commons rather than the preserve of two superpowers. 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. That is why the world needs a third AI governance regime that can react when dangerous disruptions occur. For models, policymakers might look to the approach financial authorities have used to maintain global financial stability. The Financial Stability Board, composed of central bankers, ministries of finance, and supervisory and regulatory authorities from around the world, works to prevent global financial instability by assessing systemic vulnerabilities and coordinating the necessary actions to address them among national and international authorities. A similarly technocratic body for AI risk—call it the Geotechnology Stability Board—could work to maintain geopolitical stability amid rapid AI-driven change. Supported by national regulatory authorities and international standard-setting bodies, it would pool expertise and resources to preempt or respond to AI-related crises, reducing the risk of contagion. But it would also engage directly with the private sector, recognizing that key multinational technology actors play a critical role in maintaining geopolitical stability, just as systemically important banks do in maintaining financial stability.
Such a body, with authority rooted in government support, would be well positioned to prevent global tech players from engaging in regulatory arbitrage or hiding behind corporate domiciles. Recognizing that some technology companies are systemically important does not mean stifling start-ups or emerging innovators. On the contrary, creating a single, direct line from a global governance body to these tech behemoths would enhance the effectiveness of regulatory enforcement and crisis management—both of which benefit the whole ecosystem.
A regime designed to maintain geotechnological stability would also fill a dangerous void in the current regulatory landscape: responsibility for governing open-source AI. Some level of online censorship will be necessary. If someone uploads an extremely dangerous model, this body must have the clear authority—and ability—to take it down or direct national authorities to do so. This is another area for potential bilateral cooperation. China and the United States should want to work together to embed safety constraints in open-source software—for example, by limiting the extent to which models can instruct users on how to develop chemical or biological weapons or create pandemic pathogens. In addition, there may be room for Beijing and Washington to cooperate on global antiproliferation efforts, including through the use of interventionist cybertools.
Each of these regimes would have to operate universally, enjoying the buy-in of all major AI players. The regimes would need to be specialized enough to cope with real AI systems and dynamic enough to keep updating their knowledge of AI as it evolves. Working together, these institutions could take a decisive step toward technoprudential management of the emerging AI world. But they are by no means the only institutions that will be needed. Other regulatory mechanisms, such as “know your customer” transparency standards, licensing requirements, safety testing protocols, and product registration and approval processes, will need to be applied to AI in the next few years. The key across all these ideas will be to create flexible, multifaceted governance institutions that are not constrained by tradition or lack of imagination—after all, technologists will not be constrained by those things.
PROMOTE THE BEST, PREVENT THE WORST
None of these solutions will be easy to implement. Despite all the buzz and chatter coming from world leaders about the need to regulate AI, there is still a lack of political will to do so. Right now, few powerful constituencies favor containing AI—and all incentives point toward continued inaction. But designed well, an AI governance regime of the kind described here could suit all interested parties, enshrining principles and structures that promote the best in AI while preventing the worst. The alternative—uncontained AI—would not just pose unacceptable risks to global stability; it would also be bad for business and run counter to every country’s national interest.
A strong AI governance regime would both mitigate the societal risks posed by AI and ease tensions between China and the United States by reducing the extent to which AI is an arena—and a tool—of geopolitical competition. And such a regime would achieve something even more profound and long-lasting: it would establish a model for how to address other disruptive, emerging technologies. AI may be a unique catalyst for change, but it is by no means the last disruptive technology humanity will face. Quantum computing, biotechnology, nanotechnology, and robotics also have the potential to fundamentally reshape the world. Successfully governing AI will help the world successfully govern those technologies as well.
The twenty-first century will throw up few challenges as daunting or opportunities as promising as those presented by AI. In the last century, policymakers began to build a global governance architecture that, they hoped, would be equal to the tasks of the age. Now, they must build a new governance architecture to contain and harness the most formidable, and potentially defining, force of this era. The year 2035 is just around the corner. There is no time to waste.
1. As artificial intelligence and machine learning continue to expand, the ability to engage in nuanced decision-making can help humans stay employable.
Amid nonstop technological change, leaders must commit to a program of efficient, continuous, rapid learning, said Vanessa Tanicien, director of client success at LifeLabs Learning, a management training consultancy.
“Machines are going to do a lot for us in the future, but one of the things that they will not be able to do are some of those human-flavored skills,” Tanicien said at the recent EmTech Next conference. “Take the time to double down on learning, because that’s what is going to keep us different [from] the machines.”
Tanicien highlighted two skills that are essential to continuous learning:
• Extraction
- the process of applying learning to diverse situations to understand root causes, events, and results and to identify systemic problems.
• Transfer
- intentionally moving knowledge from short- to long-term memory and then applying the new learning to other business situations.
2. It’s often said that economic advancement comes down to who you know. That might include relatively distant connections.
A recent paper co-authored by MIT Sloan professor Dean Eckles and Eaman Jahani, PhD ’21, details a positive correlation between evidence of economic well-being and a greater number of long ties — people who you know but with whom you share no other mutual connections. This could include a childhood neighbor, a former colleague, or a college roommate.
By examining public interactions among all Facebook users in the U.S. over a six-month period, the researchers found that people who move out of state, attend college out of their home state, or transfer to another high school tend to have more long ties and are more likely to be better off financially as a result.
Maintaining relationships with long ties takes work — and the disruption from moving can be difficult — but it results in a more diverse network and increased access to economic opportunities, the researchers found.
“If a close friend has valuable information, it’s likely the same valuable information that a lot of mutual friends have as well,” Eckles said. “Long ties give you access to information and opportunities you wouldn’t have otherwise.”
3. Would planting a trillion trees help to mitigate global warming? The idea has been touted by House Speaker Kevin McCarthy and other Republican leaders.
But new analysis by MIT Sloan professor John Sterman and Andrew P. Jones, executive director of the nonprofit Climate Interactive, indicates that the plan wouldn’t work, partly because of the long lag time for trees to reach maturity and absorb large amounts of carbon.
As reported in The Washington Post, the pair used the En-ROADS global climate simulator, developed by Climate Interactive and the MIT Sloan Sustainability Initiative, to determine that planting a trillion trees would prevent only 0.15 degrees Celsius (0.27 Fahrenheit) of warming by 2100.
The simulator also indicated that planting a trillion trees would sequester only 6% of the carbon dioxide that the world needs to avoid emitting by 2050 to meet the goal of the Paris climate accord.
“Trees are great,” Sterman told the Post. “But the reality is very simple: You can plant a trillion trees, and even if they all survived, which wouldn’t happen, it just wouldn’t make that much difference to the climate.”
+ IDEAS THAT MATTER
How the industrial metaverse helps solve real-world problems.
The industrial metaverse enables more resilient supply chains and localized manufacturing through the use of existing tools such as digital twins.
While the metaverse has been most closely associated with elevated shopping and entertainment experiences for consumers, the industrial sector has pragmatic designs on using it to improve collaboration, optimize operations, and train manufacturing talent.
The suite of tools for constructing the industrial metaverse includes digital twins, artificial intelligence, extended reality, blockchain, 5G connectivity, and cloud and edge computing.
At a recent event hosted by MIT Technology Review, experts discussed how the industrial metaverse links real and digital worlds to enable collaboration while solving real-world business problems. Potential use cases include:
• Improved design and engineering.
Team members from different departments or locations can work in a collaborative setting. Realistic simulations allow for more extensive testing and validation. •
Virtual commissioning and plant design.
By using immersive digital twins, manufacturers can design shop floors in the metaverse, enabling them to detect and correct errors without disrupting ongoing production or incurring unnecessary investment risks. • Enhanced operations. Through simulations and real-time data collection, manufacturers can garner insights to optimize equipment, minimize downtime, and predict and prevent failures.
• Upskilling of employees.
The metaverse gives employees remote access to expert skills and virtual training regardless of where they are physically located.
Governor Kathy Hochul today announced New York’s first-ever statewide cybersecurity strategyaimed at protecting the State’s digital infrastructure from today’s cyber threats. The Strategy articulates, for the first-time, a set of high-level objectives for cybersecurity and resilience across New York. It clarifies agency roles and responsibilities, outlines how existing and planned initiatives and investments knit together into a unified approach, and reiterates the State’s commitment to providing services, advice, and assistance to county and local governments. New York State’s cybersecurity strategy provides public and private stakeholders with a roadmap for cyber risk mitigation and outlines a plan to protect critical infrastructure, networks, data, and technology systems.
“Our interconnected world demands an interconnected defense leveraging every resource available,” said Governor Hochul. “This strategy sets forth a nation-leading blueprint to ensure New York State stands ready and resilient in the face of cyber threats.”
The strategy unifies New York’s cybersecurity services in order to safeguard critical infrastructure, personal information and digital assets from malicious actors. It also provides a framework to align the actions and resources of both private and public stakeholders, including county and other local governments.
New York’s cybersecurity strategy is not just about protecting our digital assets. It is about ensuring the safety and security of all New Yorkers and maintaining our ability to function and thrive in the digital age. From the State employees who deliver digital services to the residents who access and rely on them, the strength of the State’s cyber defense impacts all New Yorkers. This strategy highlights the Governor’s commitment to cybersecurity, not just for State Government systems but for New Yorkers everywhere, as a core responsibility of the State.
Governor Hochul announced her commitment to bolster New York State’s centralized cybersecurity during this year’s State of the State address. The historic $90 million investment for cybersecurity included in the Fiscal Year 2024 Budget made $30 million in shared services funding available to assist local governments in strengthening their own defenses against cyber threats. This initiative signaled a new and stronger collaboration between the state and its local governments on this critical and evolving issue. A part of this strategy includes providing $500 million to enhance New York State’s healthcare information technology, primarily cybersecurity infrastructure, as well as $7.4 million to expand the New York State Police’s Cyber Analysis Unit, Computer Crimes Unit and Internet Crimes Against Children Center.
The state’s comprehensive cybersecurity strategy is defined by three central principles: Unification, Resilience and Preparedness. When taken together, New York State can lean on these tenets to present a unified and more resilient defense against new and more sophisticated cyber threats; preventing the vast majority of attacks but also isolating, controlling and mitigating potential threats; and preparing, adapting and always being ready for the cyber challenges of the future. This strategy offers a blueprint for cybersecurity stakeholders across New York, from State agencies to local governments, to understand how they fit into a larger plan. The blueprint provides objectives, lines of effort, and a commitment from the Governor that they can use when doing future planning and program design.
Governor Hochul also signed legislation to expand New York’s technology talent pool and provide funding to help ensure that New York-based employers are able to hire and retain necessary cybersecurity personnel. Governor Hochul acknowledged the importance of strengthening this sector during today’s announcement, which was attended by recent graduates of the MTA’s Operational Technology Cybersecurity Program.
This strategy sets forth a nation-leading blueprint to ensure New York State stands ready and resilient in the face of cyber threats.”
Governor Hochul
New York State Chief Cyber Officer Colin Ahern said, “Our vision for unification, resilience, and preparedness addresses the critical need for advanced resources and expertise across the state. We’re ensuring that every New Yorker is equally protected from digital threats.”
Acting National Cyber Director KembaWalden said, “The President’s National Cybersecurity Strategy articulates an affirmative vision for a defensible, resilient, and values-aligned digital ecosystem that benefits all Americans and enables our grandest national ambitions. The strategy calls for bold action to rebalance the responsibility for managing cyber risk onto those entities that are most capable of keeping us all safe, and shifting incentives to drive coordinated investments in long-term resilience. The New York strategy similarly articulates a fundamentally affirmative vision for cyberspace—that is, it is not simply reactive to threat actor behavior—and advances policy in areas such as: (1) public-private operational collaboration, (2) regulation of critical infrastructure, (3) cyber education and workforce development, and (4) IT modernization.”
New York State Division of Homeland Security and Emergency Services Commissioner Jackie Bray said,“Cyber threats are more prevalent than ever as the world relies on digital technology. New York’s strategy positions us strongly in preparing for and responding to attacks. Thanks to Governor Hochul’s vision and historic investment in cybersecurity, New York continues to lead the way.”
MTA Chair and CEO Janno Lieber said,“In recent years, MTA has made cybersecurity one of our top priorities. It is essential to ensure we can deliver service for the 6 million-plus commuters and travelers who depend on us every day.”
Acting New York State Chief Information Officer Jennifer Lorenz said, “Thanks to Governor Hochul, cybersecurity is a priority in New York State – backed up by real funding, real human resources and a real strategy designed to protect the state’s assets from intrusion and attack. The Office of Information Technology Services is proud to be a partner in carrying out this important mission, and know it will result in cyber defenses that are better, stronger and more agile.”
New York State Police Acting Superintendent Steven A. Nigrelli said,“Law enforcement is constantly challenged to keep pace with evolving online technologies that are utilized by criminals to steal from the public or gain access to sensitive information. We want to remind the public that just like you should be aware of your physical surroundings, you should be aware of your online presence too. The State Police will continue to work with our partners in safeguarding our cybersecurity networks.”
Department of Financial Services Superintendent Adrienne A. Harris said, “The Department of Financial Services is a pioneer in recognizing the risk of cyberattacks and the importance of adapting to new threats and more sophisticated cyber criminals. The Department’s first-in-the-nation requirements to protect DFS-regulatedbanks, insurance companies, financial services institutions and the consumers they serve stand as a model and I applaud Governor Hochul for advancing a comprehensive plan to address these issues across government and other critical industries.”
Chair and Chief Executive Officer of the Public Service Commission Rory M. Christian said, “New York is a hub for significant financial, governmental, manufacturing, and transportation infrastructure that has higher than normal risk of cyberattack for either criminal or geopolitical reasons. With her drive and determination, Governor Hochul’s leadership will help ensure that New York has the best cybersecurity protection available.”
SUNY Chancellor John B. King, Jr. said, “SUNY campuses are leading in cybersecurity education, both in preparing our students for jobs, and in providing cutting-edge laboratories for faculty, staff, and student research. Our students are in high demand for jobs, and we are thankful for the Governor’s investment to help us educate more New Yorkers in this field, and, via the Digital Transformation Fund in the 2024 enacted budget, protect our campuses from cyberattacks. We applaud Governor Hochul for leading this comprehensive statewide strategy.”
New York State Health Commissioner Dr. James McDonald said, “Under Governor Hochul’s leadership, New York State has significantly enhanced its cyber defenses, which is critically important to our health care system. This first-ever statewide cybersecurity strategy builds on these achievements by helping protect critical systems from cyber threats. The Department of Health looks forward to continuing to work closely with our agency partners on ensuring New York’s hospitals and health care facilities stay secure.”
Contact the Governor’s Press Office
Contact us by phone:
Albany: (518) 474 – 8418 New York City: (212) 681 – 4640
WASHINGTON — Director of National Intelligence Avril Haines on Thursday released the 2023 National Intelligence Strategy (NIS), focusing on “strategic competition” with China and Russia across the economic, political and military spheres — and calling on the Intelligence Communityto up its game on everything from information warfare to supply chain control to rapid adoption of emerging technologies.
“The United States faces an increasingly complex and interconnected threat environment characterized by strategic competition between the United States, the People’s Republic of China (PRC), and the Russian Federation, felt perhaps most immediately in Russia’s ongoing aggression in Ukraine. In addition to states, sub-national and non-state actors—from multinational corporations to transnational social movements—are increasingly able to create influence, compete for information, and secure or deny political and security outcomes, which provides opportunities for new partnerships as well as new challenges to U.S. interests,” Haines writes in a forward to the document.
“In addition, shared global challenges, including climate change, human and health security, as well as emerging and disruptive technological advances, are converging in ways that produce significant consequences that are often difficult to predict,” she added.
The NIS “is a foundational document for the IC and reflects the input of leaders from each of the 18 intelligence elements, as it directs the operations, investments, and priorities of the collective,” explains the Office of the Director of National Intelligence (ODNI) in a press release announcing the new strategy.
Besides the usual three-letter IC agiencis, those 18 organizations include the National Reconnaissance Office, the National Geospatial-Intelligence Agency and the intelligence arms of the military service, with the most recent addition being the Space Force in early 2021.
The document lays out six goals for the interagency community:
Position the IC for Intensifying Strategic Competition: This includes improving the “ability to provide timely and accurate insights into competitor intentions, capabilities, and actions by strengthening capabilities in language, technical, and cultural expertise and harnessing open source, ‘big data,’ artificial intelligence, and advanced analytics.”
Recruit, Develop, and Retain a Talented and Diverse Workforce that Operates as a United Community: The IC needs an increasingly technical and diverse workforce, the document says. “The Community must overcome long-standing cultural, structural, bureaucratic, technical, and security challenges to reimagine and deliver the IC workforce of the future.”
Deliver Interoperable and Innovative Solutions at Scale: To do so, the strategy says, the IC must establish “unified IC procurement authorities, centralized solicitation systems, and a Community-wide contracting system, all bolstered by automation tools. A Community-wide, data-centric approach based on common standards is crucial to realizing the full promise of new capabilities.”
Diversify, Expand, and Strengthen Partnerships: “Even as we continue to invest in existing partnerships like those with our Five-Eyes partnersand forge new ones, the evolving set of challenges — from cyberattacks and climate change to pandemics and foreign malign influence — also require investing in new and more diverse partnerships, especially with non-state and sub-national actors. From companies to cities to civil society organizations, these actors’ ideas, innovations, resources, and actions increasingly shape our societal, technological, and economic futures.”
Expand IC Capabilities and Expertise on Transnational Challenges: Such challenges, the NIS explains, include “more frequent and intense crises due to the effects of climate change, narcotics trafficking, financial crises, supply chain disruptions, corruption, new and recurring diseases, and emerging and disruptive technologies” that in turn are piquing security crises such as civil unrest and migration.
Enhance Resilience: This includes increasing the IC’s role in protecting critical infrastructure to improve early warning that can allow more robust “recovery and response,” as well as “expanding its role in understanding threats and vulnerabilities to supply chains and helping to mitigate threats to government and industry partners’ infrastructure.”
WASHINGTON — The Pentagon’s latest memorandum on its Joint Warfighting Cloud Capability (JWCC) aims to “lay out the conditions” for how the entire department and military services can leverage the contract “to the greatest extent possible,” according to an official from the Defense Department’s chief information office (CIO).
“So now we really are in a place where we need to make sure that we look at our entire cloud landscape, rationalize our cloud landscape, enable the military departments to make sure that they continue to use their platforms to optimize cloud,” Lily Zeleke, deputy CIO for information enterprise, said at a Defense One Cloud Workshop event on Tuesday.
“However, we want to make sure that JWCC is the prime and optimal contract that we’ve put in place,” she continued. “So the guidance is going to enable that and enable rationalization as well.”
The $9 billion JWCC contract is a multi-vendor, multi-cloud follow-up to the infamous single-source failed Joint Enterprise Defense Infrastructure (JEDI) contract, which was canceled in 2021. The new venture is envisioned as DoD’s premier computing contract and is meant to provide the department “with enterprise-wide, globally available cloud services across all security domains and classification levels, from the strategic level to the tactical edge.”
Last December, the Pentagon awardedGoogle, Amazon Web Services, Microsoft and Oracle all spots on the JWCC contract to build out its key military cloud computing backbone. And then this March, all four vendors won their first task orders under the contract.
But since the project’s inception it’s been unclear if or how individual departments or military services are meant to — or mandated to — use JWCC versus their own cloud options.
The memo [PDF], released publicly on Aug. 2, aimed to provide some clarity and said all Office of the Secretary of Defense components and “defense agencies and field activities” (DAFAs) should use JWCC “for all available offerings to procure future enterprise cloud computing capabilities and services.”
“All cloud capabilities and services currently under contract in OSD Components and DAFAs will transition to the JWCC vehicle upon expiration of their current period of performance,” according to the memo.
Military services (MILDEPs) and combatant commands (COCOMS) are also tasked with using JWCC “for all available offerings for any new cloud computing capabilities and services at the Secret (Impact Level 6) or Top Secret, including all tactical edge and Outside the Continental United States (OCONUS) cloud computing capabilities and services.”
However, the memo also notes that the MILDEPs and COCOMs still can leverage other vehicles besides JWCC to procure other cloud capabilities, effectively not mandating the use of JWCC.
“While not mandating JWCC use for all cloud capabilities and services, DoD CIO will encourage MILDEPs and CCMDs to consider use of JWCC for their needs, especially as trends from OSD Component and DAFA-use provide additional data points in the coming year on price competitiveness and mission efficacy,” according to the memo.
In January, DoD Chief Information Officer John Sherman first revealed to Breaking Defense that his office was developing a memorandum to “rationalize” JWCC. The intent wasn’t to override individual cloud efforts from the military services, but Sherman’s vision would have effectively set JWCC as the primary cloud option that would serve as the “absolute foundation” for the Pentagon’s sprawling Joint All Domain Command and Control effort.
“I’m not gonna do anything capriciously or just with a sledgehammer here,” he said then. “This will be with a surgical knife about where things need to go, and… if I was my boss, I would expect the CIO to be doing this and make sure the government is getting the best value for our dollar and the very best mission outcome. And that’s why rather than just let this kind of run on autopilot, there is going to be some guidance about how this works.”
Speaking at the Defense One event, Zeleke said additional JWCC task orders are in the pipeline right now and that the new memorandum will kickstart a new governance council for JWCC, though that isn’t meant to function “like the gavel and we’re sitting at the head of the table.”
“No, it really means that we have the mechanism to make not just the users and the components accountable, but us as DoD CIO, and [Defense Information Systems Agency] as the service arm and the program office for JWCC — all of us across the board from an acquisition standpoint, from a technical standpoint, from processes standpoint — accountable,” she said.
According to the memo, the governance council, now called the DoD Information Enterprise Portfolio Management, Modernization and Capabilities Council, will provide a “broader forum to continue with existing and expanding digital modernization activities relevant to the Department’s information enterprise, including the current and future cloud initiatives as well as contractual efforts, and review of procurement administrative lead time for cloud initiatives.”
The council will include members from DoD components and agencies, the memo says.
The AI Cyber Challenge asks leading companies to develop advanced AI systems that will contribute to critical infrastructure cybersecurity — with nearly $20 million available in prizes.
In the latest step towards harnessing the power of artificial intelligence for public good, the Biden administration is launching a new, two-year competition between some of the leading AI software companies to develop new code to protect the digital networks of critical infrastructures nationwide.
Led by the Defense Advanced Research Projects Agency, the “AI Cyber Challenge” competition partners with companies — including Google, Microsoft, Anthropic and OpenAI — to leverage advanced AI algorithmic capabilities for national cybersecurity.
The prizes for this competition total about $20 million, and will be awarded to the teams with the best systems.
“AI is the most powerful technology of our time, and we have to get it right for the American people,” Arati Prabharker, director of the White House Office of Science and Technology Policy, told reporters on Tuesday. “That means managing its risks and it means harnessing its tremendous potential.”
Prabharker added that this is a pivotal example of how the public and private sectors can collaborate on national security projects for mutual benefit. Ann Neuberger, the deputy national security advisor for cyber and emerging technology, added this challenge is “critical” and marries automatic software security with AI to quickly identify and remedy network vulnerabilities.
“With this new challenge, teams will now have the power of modern AI to work through these complicated problems in support of our national security,” she said. “This challenge will help us stay ahead in the race against our adversaries’ cyber offensive capabilities. Because fundamentally, there is no national security without cybersecurity.”
While the competition involves larger tech firms, DARPA will also fund seven small businesses with up to $1 million to participate in the competition’s initial phase. Perri Adams, the DARPA program manager for the AI Cyber Challenge, confirmed that the qualifying event will take place in spring 2024, with the top 20 candidates participating.
From there, the remaining top five semi-finalists will be chosen to participate in the final competition at DEFCON in 2025.
“This is a chance to explore what’s possible when experts in cybersecurity and AI have access to a suite of cross-company resources of combined, unprecedented caliber,” Adams said.
The AICC will collaborate with the Open Source Security Foundation, the latter of whom will serve as a challenge advisor. Adams said the collaboration is due to the importance of open source software’s role in the democratization of cybersecurity.
“AICC will also ask the prize winners to open source their system such that the innovations produced by AICC can be used by everyone, from volunteer open source developers to commercial industry,” Adams said. “If we’re successful, I hope to see AICC not only produce the next generation of cybersecurity tools in this space, but show how AI can be used to better society.”
A priority for this challenge will be keeping the winning software products agnostic to all sectors and applicable to a large swath of digital networks.
“We’re trying to design tools that can secure as much software as possible throughout society,” a DARPA official said on Tuesday’s press call.
President Joe Biden has focused his executive efforts on cultivating a level of public and private partnerships amid the growing — and unregulated — anthropomorphic AI industry. With participation from agencies like the National Institute of Security and Technology, Biden has put forward several guidance documents like the AI Bill of Rights and AI Risk Management Framework to bring more oversight and accountability into AI systems.
Moving forward, Biden has said he will continue working with Congress to push bipartisan regulations forward, as well as release an executive order on responsible AI innovation.
A case study for you: The Great Baltimore Fire of 1904 serves as a disastrous example of the need for standards.
Starting on a quiet Sunday morning, the fire spread quickly and overwhelmed the city’s ability to fight it alone. Fire companies from nearby states rushed in to help with more than enough water and people to fight the flames … but with fire hoses that didn’t fit the hydrants.
Ultimately, the fire burned for more than a day and destroyed 1,500 buildings.
More than 600 variations in firehose fittings existed across the U.S., according to a NIST study issued in 1914. That’s why NIST worked with the NFPA to usher in a national standard for fire hydrant connections.
Standards are everywhere if you look for them. See the world around you in a new light with this explainer: https://lnkd.in/gKAk4QN4
Pope Francis issued a warning against artificial intelligence Tuesday, saying in a statement it should be used in “service of humanity” and warning to be vigilant of the “rapidly increasing impact” the technology is having on society.
KEY FACTS
The Vatican released the statement to announce the theme of the next World Day of Peace of the Catholic Church—“artificial intelligence and peace”—which is on New Year’s Day; last year’s theme was “combatting Covid-19 together.”
The Pope called for “an open dialogue on the meaning of these new technologies, endowed with disruptive possibilities and ambivalent effects” and said there is an “urgent need to orient” the use of AI in a responsible way so as to avoid “conflicts and antagonism.”
He said in the statement that AI must be used ethically in the specific fields of education and law, and that the development of the technology shouldn’t come “at the expense of the most fragile and excluded.”
Pope Francis, 86, has said in the past he doesn’t know how to use a computer, though he has been praised as one of the more technologically advanced popes as he’s hosted multiple events online and has an active X, formerly Twitter, account.
SURPRISING FACT
Earlier this year, Pope Francis was the subject of many AI-generated photos. The New York Timesreported that AI-generated images of Pope Francis had more likes and comments than many other AI photos. A “deepfake” series of Pope Francis wearing a Balenciaga coat went viral, and other fake images of him eating fast food, playing guitar and scuba diving also started to circulate the internet.
KEY BACKGROUND
AI and its various developments and uses became a worldwide conversation seemingly overnight after the launch of ChatGPT last November. Since then, concerns about its uses and impacts—especially going into an election year—have permeated conversations as lawmakers in the U.S. and abroaddiscuss how to regulate the new technology. In March, Elon Musk and hundreds of other high-profile technologists, entrepreneurs and researchers called on AI labs to stop work on their systems and urged developers to step back from development while society better assess the risks advanced artificial intelligence poses to humanity. Even Geoffrey Hinton, nicknamed the godfather of AI, left his role at Google to spread word about how AI could soon outperform humans and the dangerous advancements ahead. Pope Francis—who has been called innovative in his role leading the Catholic Church—has spoken about AI and technology in the past with similar messages. Five months ago, he said he was “convinced” the development of the technology and machine learning “has the potential to contribute in a positive way to the future of humanity,” though he cautioned that for positive developments to happen the people creating it need to “act ethically and responsibly.” In February, he warned against technology more broadly, saying it cannot “replace human contact.”
The line between fact and opinion in public discourse has been eroding, and with it the public’s ability to have arguments and find common ground based in fact. We at RAND call this diminishing role of facts and analysis in American public life “Truth Decay.” Everyone can feel how it affects their day-to-day lives—the family member who has fallen down a QAnon rabbit hole, avoiding discussing current affairs with a neighbor, or the fractious discourse on a television program. But this phenomenon is also degrading U.S. national security, in ways more difficult to observe.
Five years ago, RAND published a seminal document describing Truth Decay, and former President Obama put it on his summer reading list. Since then, our RAND colleagues have examined the intersections of Truth Decay with media literacy, individual resistance, and vaccine hesitancy. In our new report, we examine this phenomenon specifically in the context of national security, finding that Truth Decay adversely affects the day-to-day business of national security and major decisionmaking at every level.
Two core drivers of Truth Decay are political polarization and the spread of misinformation—and these are particularly intertwined in the national security arena. Exposure to misinformation leads to increased polarization, and increased polarization decreases the impact of factual information. Individuals, institutions, and the nation as a whole are vulnerable to this vicious cycle.
Exposure to misinformation leads to increased polarization, and increased polarization decreases the impact of factual information. Share on Twitter
National security and foreign policy were, historically, areas somewhat protected from politicization. Politicians and foreign policy professionals were seen as driving the international agenda without much input from domestic audiences, and U.S. foreign policy tended not to fluctuate dramatically from one presidential administration to the next. Over the past two decades, however, popular disillusionment with the U.S. wars in Iraq and Afghanistan, in conjunction with the rise of political movements that espoused a virulent nationalism, has weakened the bipartisan consensus on U.S. foreign policy.
Today, it is better understood that the general public has its own opinions on national security and foreign policy issues. This means, however, that a negative cycle of polarization and Truth Decay can easily take hold. Opinions are shaped by the social cues that the public picks up, such as what is said by a trusted political leader, a military leader, or close peers. Extreme partisanship intensifies the effect: People confidently adhere to views endorsed by their party and ignore any contrary facts.
So polarization makes what leaders say more potent. And politicians are, by tradition, if not by nature, selective in the information they present. Put more bluntly, politicians lie. So just as it is hard to parse fact from opinion in today’s information environment, it is also difficult to discern when politicians are knowingly lying and when they are deceiving themselves. Put all of this into the blender with social media and the 24-hour news cycle, and leaders can spread shameless lies rapidly across the globe.
The fractured media environment further pushes foreign policy opinions to extremes. For example, Pew Research has found that both Republicans and Democrats who, respectively, chose right- or left-leaning “news bubbles” held more negative views of China than others in their own parties.
Even if the U.S. national security apparatus—from civil servants to military service members, who are supposed to hold values like trust and stewardship (PDF) as core to their ethical code—can operate entirely outside of politics, it remains exposed to the effects of Truth Decay. Take intelligence work. In an ideal world, intelligence agencies collect information, assess it for its reliability, and provide it to policymakers without bias or agenda. Members of the intelligence community are respected for their expertise and professionalism and how, to the best of their abilities, they are able to discern what are the facts.
Truth Decay impedes this process in several critical ways. It makes it more difficult for intelligence analysts to perform the core function of their job, collecting and analyzing data. Just as it is hard for ordinary civilians to filter through the increasing volume of opinion to find the facts, so too do national security officials grapple with the challenge, with lots of room for improvement.
Truth Decay also increases the risk that policymakers do not trust or use intelligence community assessments. The United States spends over $80 billion a year on its intelligence apparatus—and that’s money well spent only if policymakers choose to use it. Policymakers are not equal consumers of intelligence; some rely heavily on the intelligence community’s assessments, while others barely cash in on their security clearances, particularly in Congress. If intelligence analyses were our daily vegetables, you could say that we pay to grow them, harvest them, prepare them, and plate them, but nobody is required to eat them. If policymakers lack trust in factual information, or analysis based on factual information, that can lead to national security policies that are based instead on opinion or, worse, conspiracy theory or misinformation possibly manufactured by the nation’s adversaries.
The intelligence community is also an interesting example because of how it has been pulled into public dialogue on foreign policy more often in recent decades. The intelligence community has gone from the shadows—remember that the existence of the National Security Agency, nicknamed “No Such Agency,” was a state secret from 1952 to 1975—to high-profile intelligence failures (PDF) in the early 2000s. In the past decade, policymakers have pushed the intelligence community to establish the facts publicly on issues like the origins of the coronavirus pandemic (PDF) and the shooting down of Malaysia Airlines flight MH17.
Paradoxically, this can result in intelligence agencies being undermined and attacked in the public sphere by decisionmakers. This was particularly evident in 2017 with the public release of portions of the intelligence community’s assessment (PDF) on Russian interference in the 2016 presidential elections, which eventually received bipartisan support, but only after direct questioning of the underlying analytical tradecraft, consistent challenging, and significant suspicion from political leaders. Clearly, national security institutions are being used to counter Truth Decay, but their credibility gets eroded by the phenomenon at the same time.
In our report, we anticipate other ways in which Truth Decay can negatively affect the intelligence community and the military in recruiting and retaining the nation’s best talent. As we mention, Truth Decay affects us at the national and international levels, directly impacting our allies and our relationships with them. Though experts debate the degree to which credibility is important in maintaining alliances, they agree it is a relevant factor. Perceptions that U.S. leaders are not speaking honestly or that U.S. assurances cannot be trusted diminish that credibility. Research shows that domestic accountability is key to the credibility of leadership in foreign policy. Former President Trump, in particular, who relied heavily on opinion rather than fact, was seen with little confidence globally, especially among the United States’ European Union allies. Allies depend on U.S. intelligence and military collaboration, and weakening those institutions undermines the value of that cooperation. Further, the same trends of politicization and misinformation that undermine U.S. national security erode allies’ national security.
Meanwhile, the United States’ adversaries are less vulnerable to the negative impacts of these drivers. Populations in Russia, China, Iran, and North Korea do not expect honesty from their governments, so their leaders’ embrace of misinformation or denial of facts do not similarly erode the social contract. These states have long existed in a post-truth society. Russians describe lying as a nationalpastime. Most recently, Russia has weaponized false narratives about the “Nazification” of Ukraine to justify its illegal invasion and is cultivating a young generation of nationalist zealots. The United States’ greater vulnerability to Truth Decay makes this a lever that adversaries can play upon, incentivizing them to push the United States further into polarization and to spread more misinformation in the public.
The United States’ greater vulnerability to Truth Decay makes this a lever that adversaries can play upon.Share on Twitter
We found that little work is being done to understand how severe the impact of Truth Decay is on national security and, more importantly, how to mitigate it. Media literacy workshops, classes, and messaging may help, although the research literature shows that their effectiveness is mixed. Legal institutions can play a positive role here, by raising the penaltiesfor those who spread harmful false information when that speech specifically threatens or terrifies others. The U.S. system, however, is uniquely protective of speech, so social and political norms play a greater role in countering Truth Decay. Political figures could use their podiums to frame factual information as nonpartisan in order to stall or slow the polarization–Truth Decay cycle. At the same time, the bipartisan January 6 select committee, which spent 18 months interviewing over a thousand people and reviewing countless documents before releasing an 845-page final report (PDF), does not seem to have corrected false opinions that voter fraud changed the outcome of the 2020 election or opinions about President Trump’s role in the events of the January 6 insurrection—suggesting that there are limits to the impact of traditional political mechanisms at truth-finding.
It is particularly important to promote the credibility of the United States’ national security and intelligence systems. Such institutions, once damaged, are not easily rebuilt. Government agencies, private-sector organizations, the media, and nonprofit groups all have a role to play. These efforts do not necessarily need to be coordinated, but they all need to be more robust to stay the pervasive negative effects of Truth Decay.
Heather J. Williams is a senior policy researcher at the RAND Corporation and associate director of the International Security and Defense Policy Program. Caitlin McCulloch is an associate political scientist at RAND.
This commentary originally appeared on Lawfare on August 1, 2023. Commentary gives RAND researchers a platform to convey insights based on their professional expertise and often on their peer-reviewed research and analysis.
healthcarereimagined 