The intellectual scene of the modern social sciences is experiencing a structural collapse that mirrors the geopolitical fractures of our time. A recent, thought-provoking essay published on TeknoPolitika, called “Grand Theory in Crisis,” rightly diagnosing the exhaustion of traditional theoretical frameworks in making sense of an era defined by rapid technological disruption, intelligence-driven statecraft, and non-linear systemic shocks. Reading Dr. Arslan’s incisive reflections on how classical paradigms are failing to capture contemporary realities prompted me to look deeper into both the foundational myths of our disciplines and the radical methodological reconstruction now required of us. Starting from thinking on IR theories, limiting to Realism and Liberalism here, to social sciences in general but mostly on history, a groovy flow of thought has sparked. This article has limits and constraints due to its medium and format, despite trying to cover several topics which might seem scattered for some people, but it can bring some ideas to take further steps.
While it is undeniable that mainstream International Relations (IR) theories might be incompatible with today’s paradigm shift, we must push the critique a step further. In evaluating the crisis of grand theory, Dr. Arslan suggests that these mainstream paradigms possessed an explanatory validity within the specific historical epochs from which they emerged. Yet a closer examination of historical reality reveals that these theories tended to be flawed even in their own prime. I do not agree with Dr. Arslan that the classical theories reflect high accuracy in what was really going on. Certain strands of academic theorising have remained detached from practical experience, often privileging conceptual consistency over the complexities of real-world political and strategic developments. I do not totally deny theories because they also propose a way of thinking and perspective, but some approaches became fictive, and people could learn more even from the news since theories were produced to be articulated among a narrow group of people.
Classical and structural Realism, for all its claims to cold-eyed empiricism, was relentlessly reductionist. By treating the state as a unitary, monolithic “billiard ball” navigating an anarchic system solely to maximize power or security, Realism blinded itself to the internal fractures, bureaucratic pathologies, technological shifts, and cognitive biases that actually drive decision-making. Never in history, not in Thucydides’ Athens, Metternich’s Vienna, nor Kissinger’s Washington, was the state a seamlessly rational, monolithic actor. It is also important to keep in mind that some politicians still believe that we live in the world of 1815, where being state-centered and controlling land pieces is central. The forums of congresses are not still the place to solve problems or be involved in the partition of countries. Summits become events where politicians come together and talk about the same things, but those events aim to create an economy instead. Another thing is that diplomacy is not limited to political issues but is more effective on the economy, trade, energy, science, sports, or culture. Structures of institutions and mindset of states should evolve accordingly. Questioning the geopolitics is one important step, but I would like to take a step further from a week ago, when Nvidia and Amazon made agreements with the German government, as a strong reflection that non-state actors increase the capacity of a strong state of the old world, which would seem definitely ironic in the age of geopolitics of the past.
Conversely, certain strands of Liberalism have often blurred the distinction between empirical analysis and normative aspirations, treating institutional cooperation and economic interdependence as more reliable constraints on power politics than historical experience necessarily supports. Detached from the brutal frictions of historical reality, it projected a normative, teleological fantasy onto the global stage, assuming that institutional interdependence, trade, and legal regimes would inevitably tame power politics and bend history toward a uniform model of governance. Where Realism flattened human complexity into a sterile geometry of force, Liberalism mistook its own ideological prescriptions for empirical laws. If these grand theories are completely paralyzed in the face of today’s algorithmic warfare, supply-chain weaponization, and multipolar fragmentation, it is because they were built on brittle abstractions from the very beginning.
To survive and explain the profound rupture of the twenty-first century, social inquiry must undergo a total epistemological and methodological overhaul, one that reckons honestly with artificial intelligence, purges institutional parasitism, and reconnects theory with material reality.
The End of Academic “Labor” and the Rise of Pattern-Weaving
For over a century, the prestige of the social scientist was bound up with the mechanical labor of scholarship: spending months in library stacks, hunting down obscure bibliographic references, summarizing secondary literature, translating texts, and painstakingly drafting prose. Today, artificial intelligence is fundamentally transforming this dimension of academic labor, reducing the time required for routine research tasks while raising new questions about the distinctive value of human scholarly contribution. Advanced artificial intelligence models can retrieve, cross-reference, synthesize, and draft literature reviews across thousands of sources in seconds.
When the mechanical labor of writing and source retrieval is automated, the traditional scholar is stripped of their protective guild barriers. What remains, and what machines cannot autonomously originate with genuine existential stake, is the generation of original thought. The social scientist can no longer justify their existence as a curator of existing texts, but they must become an architect of novel conceptual frameworks.
This shift elevates interdisciplinarity from an academic buzzword to an existential imperative. The crises of our era require further approaches beyond a Fordist academicianism limiting their very knowledge and expertise; an all-related chain of facts such as a shift in semiconductor lithography in East Asia simultaneously alters monetary policy, military deterrence, demographic trajectories, and epistemological security. Consequently, the premier cognitive model for the contemporary scholar must be “pattern-weaving.”
Rather than drilling ever deeper into a microscopic subfield causing a blindness to alternative topics, the pattern-weaver operates across horizontal planes of knowledge, integrating insights from evolutionary biology, complexity economics, cybernetics, classical philology, and geopolitical strategy. When AI handles the vertical retrieval of data within isolated domains, the human intellect must focus on weaving disparate empirical threads into coherent, macro-level tapestries of understanding.
“Patchwork” Academia and Hegemonic Fashions
Once we recognize that AI has absorbed the mechanical labor of literature synthesis, an uncomfortable institutional truth emerges: science does not only belong to the legions of full-time, salaried academics whose primary output consists of “patchwork” articles.
For decades, the modern university industrial complex has incentivized a sterile form of production. Academic incentive structures often encourage repetitive scholarship that repackages existing literature within fashionable theoretical frameworks, sometimes at the expense of genuine intellectual innovation. This patchwork scholarship, a glorified exercise in textual collage, is precisely what large language models execute effortlessly. Maintaining vast, bureaucratic faculties to manually perform a task that silicon accomplishes in milliseconds is an unsustainable misallocation of societal resources.
Compounding this structural redundancy is the ideological capture of the social sciences by fashionable trends engineered within core hegemonic institutions. Over the past few decades, fields like identity studies and hyper-fragmented cultural critiques have been aggressively exported from Western academic centers to the rest of the world as the pinnacle of progressive scholarship. Far from advancing human understanding, these fashionable paradigms have actively regressed science.
By reducing every complex historical, economic, and geopolitical phenomenon to subjective grievances, linguistic policing, and parochial identity categories, these trends have atomized inquiry and blinded scholars to the hard, structural drivers of history. They serve the intellectual hegemony of the core by keeping peripheral scholars occupied with narcissistic, unfalsifiable debates while the material foundations of global power are quietly re-engineered.
As the digital realm becomes saturated with synthetic text and automated analysis, the scarcity value of knowledge shifts dramatically back toward the material world. True scientific breakthroughs require boots on the ground, hands in the dirt, and eyes at the microscope. Archaeological excavations or any other physical lab study become important and real for scientific value until the robots are developed to conduct physical study. The comfortable middle ground of the armchair citation-collector is to vanish.
Toward a “Techno-Rankean” Historiography
While physical excavation retrieves the material past, a parallel revolution awaits our treatment of the written archive. Millions of pages of Ottoman, Imperial Chinese, Habsburg, Russian, and local municipal archives remain unexamined or underutilized, locked away in scripts and dialects that few living humans can read at scale. As mass digitization converges with AI-driven optical character recognition (OCR) and robotic archival scanning, our empirical grasp of the past is poised to expand exponentially.
Yet this technological windfall demands a rigorous philosophical correction. Modern historiography has become deeply corrupted by presentism, the arrogant habit of projecting today’s moral judgments, ideological obsessions, and normative frameworks backward onto historical actors. Historians routinely engage in retrospective “intention-reading,” putting figures from the sixteenth or nineteenth centuries on trial for failing to conform to twenty-first-century sensibilities.
To harness the power of AI in the archives without falling into ideological distortion, we need a “techno-Rankean” approach, first proposed in this article. In the nineteenth century, Leopold von Ranke called for history to be written wie es eigentlich gewesen, as it essentially was, grounded strictly in primary archival evidence rather than philosophical speculation or moralizing teleology.
A techno-Rankean methodology revitalizes Ranke’s empirical austerity with twenty-first-century computational power. By deploying AI and robotic digitization to ingest vast, multilingual archival datasets such as tax registers, climate logs, diplomatic cables, court records, and trade manifests, we can reconstruct the structural realities of the past at an unprecedented resolution. Rather than policing the past with today’s moral judgments or guessing at hidden psychological intentions, techno-Rankeanism shall focus on mapping and learning from the collective human experience. It treats history as a vast, empirical laboratory of human adaptation, institutional design, and survival.
Comparative History and the Anatomy of Collapse
The maturation of AI as an instantaneous, universal polyglot removes the single greatest bottleneck that has historically crippled comparative social science: the barrier of language. Previously, a single scholar could realistically master only a handful of languages, forcing comparative history and comparative political science to rely either on flawed secondary translations or narrow, Eurocentric case studies.
Today, a researcher equipped with advanced neural translation and cross-lingual retrieval models can simultaneously interrogate primary sources. This capability must trigger a renaissance in comparative history and comparative political science. We can finally trace institutional parallels, fiscal crises, and strategic doctrines across civilizations without being trapped in the linguistic silos of area studies.
Moreover, the thematic focus of this comparative turn is dictated by our own historical moment. We are living through a profound global rupture as an era characterized by the erosion of the post-1945 order, sovereign debt exhaustion, demographic contraction, and technological dislocation. In times of stable hegemony, scholars study institutional maintenance; in times of fracture, we must study the history of macro-transformations and civilizational collapses.
By applying techno-Rankean tools to comparative history, we can systematically analyze how past empires and international systems, from the Late Bronze Age collapse and the fall of Rome to the dissolution of early modern agrarian empires and the end of imperial world order in 1918. How do elites behave when fiscal extraction hits diminishing returns? How do information revolutions destabilize existing legitimacy structures? Understanding the comparative anatomy of transformation and collapse is an urgent survival manual for contemporary statecraft.
Transhumanism at the Horizon of Historical Consciousness
As we look backward with greater clarity, we must also recognize that the fundamental subject of history as the human being is undergoing an ontological mutation. For all of recorded history, historiography operated on a stable biological baseline: the cognitive capacities, sensory limits, and mortal lifespan of Homo sapiens in 2000 BC were essentially identical to those of 2000 AD. Technology was an external tool wielded by an unchanging biological agent.
That assumption is rapidly expiring. Transhumanism, as the convergence of biotechnology, neural interfaces, genetic engineering, and symbiotic human-AI cognition, must now be integrated into the theoretical core of historical science. When memory is externalized into algorithmic clouds, when strategic decision-making is co-authored by predictive neural networks, and when biological augmentation begins to stratify human capabilities, the nature of historical agency itself transforms. Along with the technological transformation of human nature, the robots become partners of the biosphere, sharing the life of biological creatures.
Historians and political scientists can no longer write as if the future will merely be populated by traditional humans operating faster machines. We must begin theorizing how the blurring boundary between human consciousness and machine intelligence alters the concepts of sovereignty, collective memory, social stratification, and historical causation. A historiography blind to transhumanism will soon find itself unable to comprehend the very actors making history.
The Practitioner’s Burden: Injecting Reality into IR and Economics
Finally, the reconstruction of social inquiry cannot be left solely to reformed academics. In rapidly mutating, high-stakes domains like International Relations and Economics, the chasm between ivory-tower theory and operational reality has become dangerous. Academic economists spent decades building elegant dynamic stochastic general equilibrium (DSGE) models that completely failed to anticipate financial contagions, supply-chain warfare, or the return of industrial policy. Similarly, academic IR theorists debated constructivist norms while intelligence agencies, sovereign wealth funds, and defense ministries quietly rewrote the rules of global power.
In this environment, practitioners bear a dual responsibility. First, they must relentlessly update their own operational habits, shedding bureaucratic inertia to keep pace with technological and systemic shifts. Second, they must actively intervene in the intellectual sphere, contributing their raw, unfiltered operational experience to the world of thought.
Historically, some of the most enduring insights in strategy and political economy came not from tenured careerists, but from practitioners who stepped back to reflect on the forces they navigated, from Thucydides, Ibn Khaldun, and Machiavelli to George Kennan. Today, we urgently need practitioners who understand how sanctions are actually evaded, how algorithmic liquidity actually moves markets, and how modern deterrence actually functions in cyber and space domains to translate their tacit knowledge into rigorous analytical frameworks. Theory without praxis is sterile and praxis without conceptual reflection is blind.
Inheriting the Past, Unlearning the Dogma
The crisis of grand theory highlighted in Teknopolitika is an invitation to liberation of thought. For too long, the social sciences have been trapped between the reductionist dogmas of the Cold War, like Realism’s monolithic state and Liberalism’s normative illusions, and the postmodern decay of hegemonic identity politics and patchwork citation factories.
The path forward requires a disciplined synthesis of heritage and revolution. We must stand firmly on the accumulated scientific legacy of humanity by honoring empirical rigor, archival fidelity, material verification, and logical coherence while ruthlessly purging the rote memorization, ideological orthodoxies, and institutional laziness that have calcified our disciplines. By embracing AI to eliminate mechanical labor, elevating interdisciplinary pattern-weaving, returning to physical fieldwork, adopting a techno-Rankean approach to comparative global collapses, reckoning with transhumanism, and fusing practitioner realism with theoretical ambition, we can build a science of society worthy of the turbulent century before us.
Ege Barış Kanık is a PhD candidate in International Security. His research interests include cultural history, Byzantine and Russian history, and Ancient Greek. This article is part of Kanık’s ongoing Techno-Politics and Cultural History series, published periodically in TeknoPolitika.
