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71. Empires of Exceptionalism: Lessons from the EU AI Act and Attempts at AI Legislation in California

Author:
Hosuk Lee-Makiyama and Claudia Lozano
Publication Date:
11-2024
Content Type:
Policy Brief
Institution:
European Centre for International Political Economy (ECIPE)
Abstract:
The EU AI Act, which passed after three years of negotiations and much ambivalence, sets a comprehensive regulatory framework that reflects the European Union’s unique needs that are not translatable to other jurisdictions. The proposed bill in California (SB 1047) illustrates this case in point. The bill could potentially mislead the public into thinking that AI is already under effective regulatory control. Lawmakers must recognize that the EU differs from other systems. The EU AI Act is not only shaped by the desire to slow down global AI development, allowing Europe to catch up with rivals like the US and China: The EU lacks an enforceable constitution, and the Act prohibits its governments to impose social scoring and discriminatory measures. SB 1047 only addressed humanity-ending disasters and had unclear practical value. Meanwhile, the EU AI Act was passed into law to prevent internal competition and Europe’s history of authoritarianism. Existing laws in California and the EU already regulate most AI use cases. In addition, the EU AI Act reviews existing regulations to ensure they are still fit for purpose, something California failed to do in SB 1047. A critical takeaway is to examine existing obligations or executive powers (including enforcement agencies and public funding) to achieve the desired policy objectives. The diverging outcomes of the two laws show the importance of avoiding mismatches between policy objectives and legislative scope. AI regulation cannot substitute for other policy objectives, like privacy and antitrust. Also, lawmakers must weigh the cost of failed regulation against the risks of non-regulation. California did not see any immediate costs of inaction, whereas delayed action by the EU might have led to the fragmentation of its internal market. Also, given its collective decision-making, the EU can escape accountability for policy failures due to premature laws in a way the leaders in other political systems cannot.
Topic:
European Union, Digital Economy, Legislation, and Artificial Intelligence
Political Geography:
Europe, California, North America, and United States of America

72. AI and India’s National Interest

Author:
Hosuk Lee-Makiyama, Badri Narayanan Gopalakrishnan, Claudia Lozano, and Dyuti Pandya
Publication Date:
12-2024
Content Type:
Policy Brief
Institution:
European Centre for International Political Economy (ECIPE)
Abstract:
AI offers a policy dilemma for India. On the one hand, export competitiveness hinges on the nationwide deployment of productivity-enhancing technologies. Indian services and consultancies must incorporate AI technologies to keep their leading position in the global market. On the other hand, there are also concerns over automation’s impact on social cohesion, discriminatory algorithmic decision-making, and the risks of “deepfakes”. However, the current transitional guidelines have shown a feasible pathway to avoiding overlapping liability or regulatory blindspots by re-interpreting existing legislation. India has a comprehensive framework for antitrust, corporate liability, free speech, and public order that covers AI development and use cases. India may not need AI-specific rules. Currently, only the EU has chosen to legislate through binding laws due to its unique structural deficiencies. The EU lacks a supranational constitution that safeguards human rights and protects citizens against AI-based surveillance or policing by its Member States. The EU must enact binding rules to pre-empt AI laws by national governments that will otherwise fragment its Single Market. Whereas India has previously taken inspiration from the EU or the US laws, India must follow its own paths and pursue its national interests based on its services-driven industrial profile and the two-way competition against China and the US, who have chosen not to impose any regulatory impediments on AI use or development. India’s challenge lies not in whether businesses prefer a local or foreign AI platform but in encouraging rapid adoption and supporting open-source and other alternatives accessible for fine-tuning and transfer learning for its IT industry.
Topic:
Regulation, Digital Economy, Exports, and Artificial Intelligence
Political Geography:
South Asia and India

73. Trade, Jobs and Technological Change: What to Expect in the Next Five Years?

Author:
Lucian Cernat
Publication Date:
01-2024
Content Type:
Policy Brief
Institution:
European Centre for International Political Economy (ECIPE)
Abstract:
This Policy Brief explores the intertwined effects of trade and technological change (notably robotics and AI) on employment, highlighting a growing divergence between the number of jobs supported by exports and the declining labour intensity of exports in recent years. The decline in labour intensity may be sharply accelerated by the rise of robotics and the automation of routine tasks, displacing workers in manufacturing and logistics while enhancing productivity. For many countries that have a strong dependence on the trade-jobs nexus, the historically declining labour intensity of exports combined with the rapid adoption of robotics in key economic sectors, will mean that industries could now rely on fewer workers for their exporting activities. This dual shock suggests that, in the future, the number of jobs that depend on trade may decline. The convergence of these forces may lead to certain sectors or regions bearing the brunt of such potential labour disruptions. To address these challenges, supporting policies will be required to mitigate these adverse effects.
Topic:
Globalization, Science and Technology, Digital Economy, Trade, and Artificial Intelligence
Political Geography:
Global Focus

74. CTC Sentinel: January 2024 Issue

Author:
Haroun Rahimi, Andrew Watkins, Gabriel Weimann, Alexander T. Pack, and Rachel Sulciner
Publication Date:
01-2024
Content Type:
Journal Article
Journal:
CTC Sentinel
Institution:
The Combating Terrorism Center at West Point
Abstract:
In the feature article, Haroun Rahimi and Andrew Watkins assess Taliban rule two and a half years into their renewed control of Afghanistan. They write: “Since their 2021 takeover, the Taliban have consolidated control over an impoverished and austere postwar Afghanistan. Since their victory, the Taliban’s emir has reasserted his status as a ‘supreme leader’ and oriented domestic policy in favor of highly conservative constituencies—which has revealed deep differences among their leadership of visions for the future of the Afghan state and society and how authority is divided among themselves. Yet, the Taliban have persistently prioritized the cohesion of their movement and governing apparatus. This trajectory has earned condemnation from Western states and prompted caution in the entire world’s engagement, which has in turn fueled Taliban motivations to reject foreign demands. After two and a half years of rule, the Taliban’s domestic agenda has become intertwined with their foreign relations impasse.” Gabriel Weimann, Alexander Pack, Rachel Sulciner, Joelle Scheinin, Gal Rapaport, and David Diaz write that “with the arrival and rapid adoption of sophisticated deep-learning models such as ChatGPT, there is growing concern that terrorists and violent extremists could use these tools to enhance their operations online and in the real world. Large language models have the potential to enable terrorists to learn, plan, and propagate their activities with greater efficiency, accuracy, and impact than ever before.” The authors offer “an early exploration of how these large language models could be exploited by terrorists or other violent extremists … to support their efforts in training, conducting operational planning, and developing propaganda.” Georgia Gilroy decodes al-Shabaab’s social media strategy, outlining the “controlled, adaptive, and coordinated approach the terrorist group takes to its online behavior.” She writes that the group’s “continued resilience, even in the face of mounting counterinsurgency efforts, is underpinned by its sophisticated communications architecture.” Christian Jokinen assesses whether left-wing terrorism is making a comeback in Germany in a case study of the violent left-wing Engel – Guntermann network. He writes that “the recent concerning trend among German left-wing extremists is toward greater violence and transnationalism.”
Topic:
Terrorism, Taliban, Violent Extremism, Artificial Intelligence, Leftist Politics, and Al-Shabaab
Political Geography:
Afghanistan, Europe, South America, Germany, and Global Focus

75. CTC Sentinel: February 2024 Issue

Author:
Don Rassler, Sean Morrow, Don Rassler, Kristina Hummel, and Daisy Muibu
Publication Date:
02-2024
Content Type:
Journal Article
Journal:
CTC Sentinel
Institution:
The Combating Terrorism Center at West Point
Abstract:
Long-range aerial attacks by the Iran-backed Houthi terrorist group, including a ballistic missile that traveled at least a thousand miles toward Israel before being intercepted (reportedly in space) on October 31, 2023, are focusing minds on long-range stand-off terrorism. In this month’s feature article, which conceptualizes, outlines, and examines the implications of this emerging threat vector, Don Rassler argues that the notion that terrorists could strike the United States across the oceans with unmanned aircraft systems (UAS) is becoming increasingly less far-fetched. Rassler writes that “over the coming decade, hydrogen fuel cell and solar UAS technology will evolve and mature, and will also likely become more available and accessible to the average consumer, which will make longer ranges more accessible as well. Other disruptive technologies, such as generative artificial intelligence, will also mature and will likely be used by extremists to help them optimize system performance and to overcome, or devise creative solutions to, technical long-range UAS challenges.” He warns that “long-range stand-off terrorism will be attractive to some extremists because it opens-up new attack pathways, can enable surprise, and has the potential to deliver a potent psychological, ‘we can strike you from afar’ punch. Over the next decade advancements in commercial technologies and systems will also make range, and extended range, more accessible for violent non-state-entities, making it likely that in the future long-range terrorism will become even more of a threat.” Rassler’s article is the first in a new recurring series in CTC Sentinel entitled “On the Horizon” that will examine emerging counterterrorism challenges. Our interview is with Christopher Maier, the Assistant Secretary of Defense for Special Operations and Low-Intensity Conflict. “We need to have sustainable CT operations that prevent terrorists’ actions, principally al-Qa`ida and ISIS, to ensure we are not distracted by what we view as the longer-term strategic priorities, such as peer adversaries,” he says. “As the rest of the Department and other parts of the U.S. government are doing less CT, [this] means that those who are doing it have to do it better and, in many respects, do it more proportionally to the rest of the national security enterprise. This is why SOF is looked to as the lead for the CT fight in the Department.” Daisy Muibu examines the state of Somalia’s military campaign against al-Shabaab. She writes that: “A year and five months after the Somali government launched its offensive against al-Shabaab, the initial optimism that characterized its first few months have diminished as the counterinsurgency’s momentum has stalled in the central regions of the country.” She adds that “with only a year left until African Union forces are mandated to fully draw down, significant obstacles remain that cast doubts over the government’s ambitious goals to defeat al-Shabaab and assume full responsibility for securing the country by December 31, 2024.”
Topic:
National Security, Science and Technology, Terrorism, Artificial Intelligence, Houthis, and Al-Shabaab
Political Geography:
Iran, Middle East, Israel, Yemen, Palestine, Somalia, Global Focus, and United States of America

76. Controlling the danger: managing the risks of AI-enabled nuclear systems

Author:
Noah Greene
Publication Date:
11-2024
Content Type:
Special Report
Institution:
NATO Defense College
Abstract:
Research on AI and nuclear weapons often discusses three broad categories of risk: technical risks, pitfalls in human-machine teaming, and strategic stability concerns. The potential solutions for mitigating these risks include international political declarations, United Nations level reporting, and a limited purpose AIenabled nuclear weapons treaty.
Topic:
NATO, Nuclear Weapons, Treaties and Agreements, Weapons, Risk, Artificial Intelligence, and Strategic Stability
Political Geography:
Global Focus

77. The tension between exploding AI investment costs and slow productivity growth

Author:
Bertin Martens
Publication Date:
10-2024
Content Type:
Working Paper
Institution:
Bruegel
Abstract:
This working paper explores the tension between rapidly increasing artificial intelligence investment costs and the slower pace of productivity growth, raising concerns about a potential ‘economic winter’ for AI. AI has shown significant technological progress, particularly with machine learning and generative AI models like ChatGPT. Investment in AI has surged. But there are concerns about whether these investments will yield proportional returns. Training costs for a single frontier AI model are increasing exponentially, , from $1,000 in 2017 to nearly $200 million in 2024, driven by constant returns to scale in AI model training data, compute capacity and model complexity. Costs could reach billions of dollars by 2030, despite a rapid fall in unit costs per computing operation over the same period. Global AI infrastructure costs in hardware could exceed $1 trillion by the mid-2030s. Amortizing these huge fixed costs requires business models that can be rolled out across a very large user market. Estimates about AI’s contribution to productivity growth vary, from a modest 0.5 percent per year to a very optimistic 10 percent per year. Research shows that productivity usually catches up slowly compared to costs. Without significant productivity gains, the current investment cost trajectory is unsustainable. We estimate that 3 percent annual productivity growth across advanced economies would be required to sustain AI model cost extrapolations to 2030. In an optimistic scenario, productivity increases would result in accelerated economic growth.
Topic:
Digital Economy, Economic Growth, Microeconomics, Artificial Intelligence, and Productivity
Political Geography:
Global Focus

78. Why artificial intelligence is creating fundamental challenges for competition policy

Author:
Bertin Martens
Publication Date:
07-2024
Content Type:
Working Paper
Institution:
Bruegel
Abstract:
The rapidly evolving market for artificial-intelligence services is apparently thriving and very competitive, with a growing number of AI start-ups and ever larger and more capable AI models. Investors are pouring large amounts of money into start-ups and into a few big tech firms that have the large financial resources and computing capacity that constitute key inputs to the production and running of AI-driven services. However, exponentially growing AI model training costs create a market entry barrier for AI start-ups, forcing them to cooperate with big tech firms to get access to computing infrastructure and end users. At the same time, their AI models compete with those of the big tech firms. Competition authorities investigate these co-opetition agreements, looking for market-distorting clauses. Beyond computing costs, other competition choke points in the AI supply chain include access to dedicated AI processor chips and training data. Strict enforcement of copyright on data may further tighten an already scarce supply of affordable training data. Policymakers have few, if any, effective tools to deal with these potential competition bottlenecks in AI industries. Co-opetition agreements are necessary to enable AI start-ups to access hyperscale and costly computing infrastructure. At the same time, the agreements give big tech privileged access to the latest AI models. Competition authorities can try to minimise market-distorting provisions in these agreements but there are technical and economic limits to the extent of fragmentation in the AI value chain that can be meaningfully imposed on big tech firms. Licensing fees for copyright-protected data further tighten the already scarce supply of affordable data. It is hard to implement a fair market-clearing mechanism for dedicated AI processors. If model training costs continue to grow exponentially, as appears to be the case for the foreseeable future, the entire competition policy setting for AI industries may need a revision, with collaboration, including between big tech firms, dominating competition to keep the pace of AI innovation going.
Topic:
Science and Technology, Governance, European Union, Microeconomics, and Artificial Intelligence
Political Geography:
Europe

79. Catch-up with the US or prosper below the tech frontier? An EU artificial intelligence strategy

Author:
Bertin Martens
Publication Date:
10-2024
Content Type:
Policy Brief
Institution:
Bruegel
Abstract:
European Union policymakers want to close the artificial intelligence innovation gap with the United States, as a way to accelerate lagging productivity growth. The EU focus is on expanding an existing supercomputer network with more AI hardware and computing infrastructure, with taxpayer support. However, this computing infrastructure is not adapted to AI modelling. The cost of catching up with leading big tech AI computing centres is already prohibitive for EU budgets, and is set to become even more so. The hardware focus overlooks missing EU markets for complementary services that are required to set up a successful AI business: large-scale business outlets for frontier generative AI models to generate sufficient revenues to cover huge fixed model training costs, hyperscale cloud-computing infrastructure and private equity financing for AI start-ups. In the absence of (or with insufficient) complementary services markets in the EU, start-ups are forced to collaborate with US big tech firms. Injecting taxpayer subsidies to make up for these missing markets may further distort EU markets. Regulatory compliance costs, including uncertainty about the implementation arrangements for the EU Artificial Intelligence Act, add to market problems. The EU should address a wider range of market failures in its policy initiatives. It should strive to increase productivity growth below the AI technology frontier, by facilitating investment and applications of AI-driven services produced by derived and specialised generative AI models, or AI-applications that build on top of existing generative AI models. Building these below-frontier AI applications requires far less computing capacity and less heavy investment costs. Promoting the uptake of AI application services across a wide range of industries can substantially stimulate productivity growth. That requires a razor-sharp focus on pro-innovation guidelines, standards and implementation provisions for the EU AI Act, shortening the Act’s regulatory uncertainty horizon as much as possible, and facilitating collaborations between EU AI startups and big tech companies. Widening and deepening the EU private equity and venture capital market would also be very helpful.
Topic:
Markets, Science and Technology, European Union, Investment, and Artificial Intelligence
Political Geography:
Europe and United States of America

80. Generative Artificial Intelligence and Its Implications for Labor Markets in Developing Countries: A Review Essay

Author:
Guillermo Cruces, Verónica Amarante, and Estefanía Lotitto
Publication Date:
12-2024
Content Type:
Working Paper
Institution:
Center for Distributive, Labor and Social Studies (CEDLAS)
Abstract:
The unprecedented developments in artificial intelligence technology and its recent widespread availability hold transformative potential to reshape global economic dynamics and labor markets, though opinions on its effects vary greatly. Transformative or not, the irruption of AI has sparked ample public discussion as well as the rapid development of theoretical and empirical approaches to understand it. This review essay discusses recent perspectives, theories, and empirical evidence on the matter, and adds a perspective of the implications of this technology and of the policy discussion it has sparked, from the perspective of developing countries’ economies. The latter is motivated by the relative scarcity of such perspectives in the current public debate, which seems to have minimized the potential effects on the interaction of labor markets between developing and developed countries, and on the potentially different within-country effects at different levels of development.
Topic:
Economic Development, Artificial Intelligence, Literature Review, Labor Market, and Work
Political Geography:
Global Focus