Artificial Intelligence and International Relations Theories
By Bhaso Ndzendze and Tshilidzi Marwala
Palgrave Macmillan Singapore, 2023
Rapid and substantial advances in machine learning, computer processing, and āBig Dataā have triggered an explosion of global interest and investment in artificial intelligence (AI). AIās allure stems from the prevailing belief that it will radically transform life as we know it, with implications for a wide range of sectors, from healthcare, education, and transportation to defense, weapons development, and cybersecurity. As states scramble to procure this emerging technology, scholars have begun thinking about its implications for the field of international relations (IR). While some scholars are hopeful that AI may be used to improve global health outcomes and facilitate trade, others are more pessimistic, warning of escalation towards conflict and the erosion of democratic norms.Ā Artificial Intelligence and International Relations Theories, contributes to this debate by exploring whether the āworld-transforming developmentā of AI will challenge, undermine, or validate the key assumptions and ideas that form the basis of IR theory (p.8).
The authors begin by identifying the central frameworks and paradigms that have defined the field of IR, providing a brief overview of its intellectual history and inter-paradigmatic debates. Ndzendze and Marwala make the important observation that IR theory has historically āevolvedā alongside major developments or shocks to the international system, suggesting that the āage of AIā could prompt the field to revisit its theoretical foundations.
To appeal to a wide, non-technical audience, the authors provide a sketch of the basic systems, algorithmic processes, and logic behind AI, and outline its trajectory from the 1950s to the contemporary era of āBig Dataā. Here, the authors make two important clarifications about AIās potential implications for IR. First, theyĀ differentiateĀ between ānarrowā AI, which refers to algorithms that can ālearnā a specific task, and artificial āgeneralā intelligence, a hypothetical phenomenon where AI could apply lessons learned in one scenario to an entirely different set of problems (p.36). The authors make the point that the systems currently being deployed are ānarrowā AI; and as such, they do not warrant fears of a dystopian near future where super-intelligent AI replaces traditional actors. This distinction cautions against the type of hyperbolic thinking thatĀ expertsĀ fear could misinform policy. Second, the authors maintain that scientific development and innovation haveĀ alwaysĀ been informed by global politics, pointing to early innovations in AI during the Cold War and the currentĀ competitionĀ between the US and China (p.39). This brief history clarifies that the politicization of emerging technologies is not unique to the current day and age.
Having provided readers with the necessary context, the remainder of the book is organized by paradigm, each chapter examining how the proliferation of AI challenges or supports its theoretical underpinnings. Throughout these core chapters, the authors make several astute observations about the risks, opportunities, and limitations of this technology and its influence on global politics. Indeed, they should be applauded for achieving what is undoubtedly an ambitious task ā probing a fieldās intellectual history to ācomprehensively articulate the implications of the growing ubiquity of AI in international relationsā (p.7). However, Ndzendze and Marwalaās analysis includes notable gaps that reveal a lack of breadth and depth. While the authors cannot be expected to cover every minute detail of IR theory, readers may find themselves searching for more ā more nuance, more examples, and more interpretation of the leading intellectual debates about AIās relevance for the field. Important ideas at the core of IR theory are mentioned in passing, with no real consideration of whether the concepts aptly describe the current state of international politics in the āera of AIā, or whether rethinking is in order. The remainder of this review will outline a few illustrative examples.
The chapter on realism makes meaningful points about AIās role in the ābalance-of-power rationaleā and the offense-defense calculus. However, it misses opportunities for a more thoughtful summary of the potential threats that AI poses to some of realismās principal assumptions. Most notably, the authors overlook ongoing debates about the rise of automated decision-making and the concept of āagencyā. Indeed, scholars such asĀ Kiggins (2017)Ā have argued that the heightened autonomy and decision-making capabilities of weapons systems and other processes require that IR reconsider precisely what constitutes an international āactorā. The question of how to characterize agency has serious implications for realism; it challenges both the classical realist emphasis on the role that āhuman natureā plays in humanityās proclivity for conflict as well as structural realistsā claim that unitary states are the central, ānearly exclusiveā actors in IR (p.59). To their credit, the authors do note that āBig Techā companies, responsible for developing the most cutting-edge applications of AI, are playing an increasingly important role in global politics. Further, AI is not currently capable of independent action beyond its programmed instructions, and therefore cannot be said to have āagencyā. The authors should be commended for their refusal to anthropomorphize AI. Yet, by failing to consider whether forms of non-human agency couldĀ eventuallyĀ challenge the realist assumption that states are the primary actor in international relations, the authors neglect urgent philosophical debates about the realist conception of āpowerā in an era of enhanced machine autonomy.
Perceptions of AI as a valuable instrument of economic and military power have spurred competition for this technology, seemingly validating the realist claim that states are ultimately motivated to pursue relative gains. Given that AI can bolster countriesā status, the authors develop a model that measures and predicts the āAI balance of powerā using statesā innovation scores, their total number of AI patents, and technology exports relative to rivals (p.66). The intuition behind this model accurately reflects the role that domestic industry can play in access to emerging technologies. However, this model obscures the distinct characteristics that undermine the utility of simple quantification through the counting of AI āoutputsā. The immateriality and invisibility of advanced algorithms and software differentiate these tools from conventional arms and industrial goods, which are largely material and therefore receptive to quantification. In the case of AI, however, patents and applications, including those with industrial and military applications, can reveal very distinctive purposes and capabilities; that is, not all AI patents or innovations are equal. By downplaying AIās unique characteristics, the authors miss an opportunity to demonstrate preciselyĀ whyĀ states and non-state actors view AI as particularly concerning ā from attribution problems associated with autonomous weaponry to the covert usage of algorithms for nefarious purposes, it is the immateriality of AI that complicates efforts to predict statesā AI capabilities.
The chapter on liberalism encounters similar issues. For instance, the authors note that the proliferation of AI is occurring alongside broader challenges to the āliberal international orderā, where ādemocracy and artificial intelligence appear to be having a negative correlation with one anotherā (p.76). While this correlation is certainly plausible, the authors do not identify the mechanisms that explainĀ whyĀ orĀ howĀ AI is poised to challenge democracy. This omission will strike readers familiar with this topic as odd, given the large body of literature linking AI toĀ repression,Ā surveillance,Ā inequality, andĀ disinformation. Further, the authors maintain that democratic and authoritarian regimes will differ in their approaches to AI, but they do not specifyĀ how. Again, this is an important differentiation ā variation in authoritarian and democratic approaches to AI could tip the balance towards, or away from, a world marked byĀ ādigital authoritarianismā. Finally, the authors mention AI within the context of international trade, but ignore a rich body of literature linking this technology to the neoliberal emphasis on the pursuit of efficiency, profit, and āprogressā (Lyon 2014;Ā DimitrijeviÄ 2023;Ā Bourne 2019). In doing so, they miss the opportunity to highlight linkages between narratives that frame data-centric policies as ārationalā, or āobjectiveā and neoliberal logic.
These shortcomings continue throughout the second half of the text. The chapter on dependency theory makes no mention ofĀ the exploitation of workersĀ hired to do the precarious work of training AI systems, theĀ near-monopoly of US-based āBig Techā firms on the global tech market, or the risk of instability should automation yield massive and rapidĀ changes in employment. The section on constructivist perspectives makes few references to machine-human interaction, the role of local history and context in technological development, or the mutually constitutive relationship between technological and societal change. It would normally be unfair to criticize a book solely on what it omits. However, in the context of these well-established theories, the omission of core concepts such as identity, norms, and contingency is striking.
Ultimately, Ndzendze and Marwala convince readers that IR scholars must take AI seriously. Just as competition and balance-of-power politics have influenced scientific development and innovation, AIās diffusion will have significant impacts on the fieldās intellectual trajectory. The concluding chapter emphasizes that no single paradigm can comprehensively capture the entirety of AIās implications for war, trade, and international order, and thereby encourage inter-paradigmatic discussion, orĀ āanalytical eclecticismā. This recommendation aligns withĀ skepticismĀ about the utility of stark divides for theory-building and testing, and as such provides scholars with a pragmatic way forward.
This bookās most significant impact will be felt by scholars unfamiliar with the politics of AI or those embarking on new projects that may consider emerging technologies. It is not that it puts forth incorrect, misleading, or unsubstantiated arguments. Instead, its major shortcoming is that it leaves the reader looking for a more comprehensive and thorough analysis of its subject matter. Despite AIās wide-ranging applicability and relevance for world politics, this book only scratches the surface.
References
Birhane, Abeba. 2020. āAlgorithmic Colonization of Africa.āĀ SCRIPTed: A Journal of Law, Technology and SocietyĀ 17(2): 389ā409.
Bourne, C. 2019. āAI Cheerleaders: Public Relations, Neoliberalism and Artificial Intelligence.āĀ Public Relations InquiryĀ 8(2): 109ā25.
Brundage, Miles et al. 2018. āThe Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation.ā
āChina Is Striking Back in the Tech War With the U.S. | Time.āĀ https://time.com/6295902/china-tech-war-u-s/Ā (September 29, 2023).
DimitrijeviÄ, Lazar A. 2023. āSmart City Development Strategies: Data Determinism and Technological Sovereignty.āĀ Š”Š¾ŃŠøŠ¾Š»Š¾ŃŠŗŠø ŠæŃŠµŠ³Š»ŠµŠ“Ā 57(1): 76ā101.
āFEATURE-AI Boom Is Dream and Nightmare for Workers in Global South.ā 2023.Ā Reuters.Ā https://www.reuters.com/article/global-tech-workers-idAFL5N2XI2X8Ā (September 29, 2023).
Feldstein, Steven. 2019. āThe Road to Digital Unfreedom: How Artificial Intelligence Is Reshaping Repression.āĀ Journal of DemocracyĀ 30(1): 40ā52.
Fletcher, John. 2018. āDeepfakes, Artificial Intelligence, and Some Kind of Dystopia: The New Faces of Online Post-Fact Performance.āĀ Theatre JournalĀ 70(4): 455ā71.
Jajal, Tannya D. 2020. āDistinguishing between Narrow AI, General AI and Super AI.āĀ Mapping Out 2050.Ā https://medium.com/mapping-out-2050/distinguishing-between-narrow-ai-general-ai-and-super-ai-a4bc44172e22Ā (September 29, 2023).
Kiggins, Ryan David. 2018. āBig Data, Artificial Intelligence, and Autonomous Policy Decision-Making: A Crisis in International Relations Theory?ā InĀ The Political Economy of Robots: Prospects for Prosperity and Peace in the Automated 21st Century, ed. Ryan Kiggins. Cham: Springer International Publishing, 211ā34.Ā https://doi.org/10.1007/978-3-319-51466-6_10.
Lake, David A. 2011. āWhy āIsmsā Are Evil: Theory, Epistemology, and Academic Sects as Impediments to Understanding and Progress.āĀ International Studies QuarterlyĀ 55(2): 465ā80.
Leavy, Susan, Barry OāSullivan, and Eugenia Siapera. 2020. āData, Power and Bias in Artificial Intelligence.ā
Lyon, D. 2014. āSurveillance, Snowden, and Big Data: Capacities, Consequences, Critique.āĀ Big Data and SocietyĀ 1(2).
Miller, Claire Cain, and Courtney Cox. 2023. āIn Reversal Because of A.I., Office Jobs Are Now More at Risk.āĀ International New York Times.Ā https://proxy.library.cornell.edu/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=edsgin&AN=edsgcl.762153334&site=eds-live&scope=site.
OāShaughnessy, Matt. āHow Hype Over AI Superintelligence Could Lead Policy Astray.āĀ Carnegie Endowment for International Peace.Ā https://carnegieendowment.org/2023/09/14/how-hype-over-ai-superintelligence-could-lead-policy-astray-pub-90564Ā (September 29, 2023).
Sil, Rudra, and Peter J. Katzenstein. 2010. āAnalytic Eclecticism in the Study of World Politics: Reconfiguring Problems and Mechanisms across Research Traditions.āĀ Perspectives on PoliticsĀ 8(2): 411ā31.
āThe Dangers of the Global Spread of Chinaās Digital Authoritarianism.āĀ https://www.cnas.org/publications/congressional-testimony/the-dangers-of-the-global-spread-of-chinas-digital-authoritarianismĀ (September 29, 2023).