Ángel Gómez de Ágreda is one of the most solid intellectual references in Spain and Europe for understanding the intersection amongst geopolitics, disinformation, and generative artificial intelligence. A retired Colonel of the Spanish Air and Space Force, engineer with a PhD, strategic analyst, and public intellectual, his work stands out for connecting philosophical reflection on truth and knowledge with the technological and military transformations of 21st century.
In 2025, together with Enrique Martín Romero, he published Inteligencia artificial y defensa. El impacto en los ejércitos (Artificial Intelligence and Defense: The Impact on Armies). This year, 2026, he has released Un mundo falaz. El nuevo orden global en la era de los algoritmos y la manipulación ((Fake New World. The New Global Order in the Age of Algorithms and Manipulation). The central idea around which both works revolve is the following: global power is no longer measured solely by the economic or military capabilities of states, but by their ability to shape the perception of reality for millions of people.
Gómez de Ágreda’s thesis begins with an essential observation: technology does not create our weaknesses; it simply amplifies those that already exist. Politics, digital platforms, and now generative AI exploit the human tendency to accept narratives that emotionally align with our prior beliefs. The German philosopher Markus Gabriel defines this condition as post-reality: a stage in which societies no longer merely manipulate others, but actively participate in their own collective self-deception. The phenomenon goes beyond classic post-truth; it entails the gradual replacement of facts with narratives designed to be shared, viralized, and emotionally effective.
Social media first, and generative AI later, have accelerated this process to unprecedented levels. Gómez de Ágreda argues that we have delegated not only cognitive tasks to machines, but even the search for knowledge itself. What once required comparing sources and developing personal judgment is now resolved through an instant query to an LLM. Large language models function as digital oracles whose authority is perceived as neutral and infallible, despite the fact that no AI can ever truly be neutral, impartial, or objective. Algorithms are only as neutral as the programmers behind them.
The problem is that, in a context of cognitive saturation, people tend to accept automated responses with little questioning. This is where the transition occurs from technical manipulation to emotional manipulation: the moment when machine dominance ceases to operate over what we think and begins to operate over what we desire. Machines allow us, in a sense, to “want to want.” They give us reasons to want to fall in love, to want to love. More than satisfying the need to receive affection, they address our impulse to offer it. This connects with the Spanish philosopher José Antonio Marina’s accurate description of the contemporary individual as “credulous, passive, gregarious, isolated, and anti-Enlightenment.” The result is an individual incapable of withstanding the pressure of the surrounding environment.
This social and ontological transformation has direct consequences for contemporary geopolitics. For Gómez de Ágreda, the classical concept of sovereignty must evolve into the idea of cognitive sovereignty: the ability of a country or community to preserve interpretive autonomy against external manipulation campaigns. Disinformation ceases to be a marginal phenomenon and becomes a strategic resource aimed at shaping emotions, altering perceptions, and conditioning collective decisions. In this scenario, the true battlefield is no longer confined to physical borders, but lies within societies themselves.
Contemporary military doctrines reflect precisely this evolution. The author cites Russian analyst Dmitri Trenin to explain how current strategies no longer necessarily seek territorial occupation, but rather internal chaos and psychological destabilization. The Gerasimov Doctrine and the concept of reflexive control aim to alter the adversary’s perception of reality. Cognitive warfare therefore seeks not merely to control information, but to directly influence the mental processes of entire populations. As Gómez de Ágreda reminds us, while information warfare operates on content, cognitive warfare targets the human brain itself.
Generative AI exponentially multiplies the scope of these operations. The ability to produce synthetic texts, audio, images, and videos that are virtually indistinguishable from reality radically transforms the information environment. Unlike traditional propaganda, messages can now be tailored to each psychological profile, disseminated on a massive scale, and adapted in real time according to audience reactions. Gómez de Ágreda describes disinformation as functioning through an organized chain of actors: activators, amplifiers, legitimizers, dissemination bots, and relaunchers. Generative AI drastically reduces the cost and time required to deploy such campaigns, making them practically ubiquitous.
One of the most disturbing examples cited in Un mundo falaz is GoLaxy, a system already operating in China that can generate highly realistic artificial avatars capable of emotionally interacting with real users. These synthetic identities can operate simultaneously on a massive scale, without arousing suspicion, while adapting psychologically to each interlocutor. Manipulation is no longer confined to the ideological sphere; it shifts into the emotional domain. Machines no longer condition only what we think, but also what we desire.
China appears in both books as the geopolitical actor that has best understood the strategic potential of AI. Beijing has developed an ambitious roadmap to make this technology the core of its economic, industrial, and military development. According to the official Chinese document Opinions of the State Council on the Deep Application of the R&D Initiative, published in August 2025, the goal is to achieve 70% penetration of intelligent terminals and AI agents across six key sectors by 2027: science and technology, industry, consumption, social welfare, government, and global cooperation. By 2030, penetration is expected to reach 90% across the entire economy. By 2035, AI should become as universal as electricity is today, equivalent to what the internet represents in our era. By 2037, industries themselves are expected to be created with AI as both their foundation and guiding principle. Just as a new economy emerged around the internet, the report proposes that the next industrial system will be built around algorithms.
The United States, fully aware of this technological competition, has responded by accelerating its own military generative AI programs. In 2023, OpenAI, Google, Anthropic, and xAI received multimillion-dollar contracts from the Department of Defense to develop intelligence and combat simulation applications. At the same time, Washington has imposed restrictions on U.S. investments in AI technologies directed toward China, aiming to slow the development of Chinese military AI and preserve the West’s technological advantage. The geopolitical rivalry of the 21st century is now being fought in the domain of semiconductors, data centers, and algorithms.
However, Gómez de Ágreda warns that the impact of AI is not limited to the balance between great powers. Recent conflicts show how this technology is also transforming conventional warfare. The war in Ukraine and the earlier Nagorno-Karabakh conflict have demonstrated that small autonomous systems, inexpensive drones, and accessible AI capabilities can create enormous asymmetries against vastly more expensive weaponry. The battlefield of the future will be hybrid: physical, digital, and cognitive simultaneously.
Yet perhaps the author’s deepest warning is philosophical in nature. In a world saturated with information, the primary threat is not merely technological, but epistemological. If every act of understanding necessarily involves interpretation, as philosopher Hans-Georg Gadamer argued in his book Truth and Method, then the struggle to control interpretive frameworks becomes a struggle to control reality itself. That is why Gómez de Ágreda insists on recovering critical thinking and philosophical reflection as tools of democratic defense. The great battle of 21st century will not be decided solely in AI laboratories or military arsenals, but in societies’ ability to preserve their cognitive freedom against a technological ecosystem designed to influence, seduce, and manipulate.
Posted: May 6th, 2026 | Author:Domingo | Filed under:Geopolitics | Tags:Desinformación, Geopolítica, ia, inteligencia artificial, LLMs | Comments Off on “Un mundo falaz” e “Inteligencia artificial y defensa” de Ángel Gómez de Ágreda. Dos obras indispensables sobre geopolítica, desinformación e inteligencia artificial.
Ángel Gómez de Ágreda es una de las referencias intelectuales más sólidas en España y Europa para comprender la intersección entre geopolítica, desinformación e inteligencia artificial generativa. Coronel del Ejército del Aire y del Espacio en la reserva, doctor ingeniero, analista estratégico y divulgador, su trabajo destaca por conectar la reflexión filosófica sobre la verdad y el conocimiento con las transformaciones tecnológicas y militares del siglo XXI.
En 2025, junto Enrique Martín Romero, escribió Inteligencia artificial y defensa. El impacto en los ejércitos. Y este año 2026 acaba de publicar Un mundo falaz. El nuevo orden global en la era de los algoritmos y la manipulación. La idea central alrededor de la cual giran ambas obras es la siguiente: el poder global ya no se mide únicamente por la capacidad económica o militar de los Estados, sino por su habilidad para moldear la percepción de la realidad de millones de personas.
La tesis de Gómez de Ágreda parte de una constatación esencial: la tecnología no crea nuestras debilidades, simplemente amplifica las que ya existen. La política, las plataformas digitales y ahora la IA generativa explotan la inclinación humana a aceptar relatos que encajen emocionalmente con nuestras creencias previas. El filósofo alemán Markus Gabriel define esta situación como posrealidad: un estadio en el que ya no se manipula únicamente a otros, sino que las sociedades participan activamente en su propio autoengaño colectivo. El fenómeno va más allá de la clásica posverdad; supone la sustitución progresiva de los hechos por narrativas diseñadas para ser compartidas, viralizadas y emocionalmente eficaces.
Las redes sociales primero y la IA generativa después han acelerado este proceso hasta niveles inéditos. Gómez de Ágreda sostiene que hemos delegado no sólo tareas cognitivas en las máquinas, sino incluso la búsqueda misma del conocimiento. Lo que antes requería contrastar fuentes y desarrollar criterio propio se resuelve ahora mediante una consulta instantánea a un modelo de lenguaje. Los grandes modelos de IA funcionan como oráculos digitales cuya autoridad se percibe como neutral e infalible, pese a que no existe, ni existirá una IA neutral, imparcial u objetiva. Los algoritmos son tan neutrales como lo sea el programador que haya detrás de ellos.
El problema es que, en un contexto de saturación cognitiva, las personas tienden a aceptar las respuestas automatizadas sin apenas cuestionarlas, y aquí es cuando se produce ese salto de la manipulación técnica a la afectiva: ese momento en el que el dominio de las máquinas deja de ejercerse sobre lo que pensamos para hacerlo sobre lo que deseamos. Las máquinas lo que nos permiten es querer querer. Nos dan motivos para querer enamorarnos, para querer amar. Más que satisfacer la necesidad de recibir afecto, lo que hacen es solventar nuestro impulso de ofrecerlo. Y esto entronca con la definición certera del filósofo José Antonio Marina del sujeto contemporáneo como “crédulo, pasivo, gregario, aislado y anti-ilustrado”. El resultado es un individuo incapaz de soportar la presión del entorno.
Esta transformación social y ontológica tiene consecuencias directas sobre la geopolítica contemporánea. Para Gómez de Ágreda, el concepto clásico de soberanía debe ampliarse hacia la idea de soberanía cognitiva: la capacidad de un país o una comunidad para conservar autonomía interpretativa frente a campañas de manipulación externas. La desinformación deja de ser un fenómeno marginal para convertirse en un recurso estratégico orientado a modelar emociones, alterar percepciones y condicionar decisiones colectivas. En este escenario, el verdadero campo de batalla ya no está sólo en las fronteras físicas, sino en el interior de las sociedades.
Las doctrinas militares contemporáneas reflejan precisamente esta evolución. El autor cita al analista ruso Dmitri Trenin para explicar cómo las estrategias actuales no buscan necesariamente ocupar territorios, sino provocar caos interno y desestabilización psicológica. La doctrina Gerasimov y el llamado control reflexivo persiguen alterar la percepción que el adversario tiene de la realidad. La guerra cognitiva, por tanto, no pretende únicamente controlar la información, sino influir directamente sobre los procesos mentales de individuos y poblaciones enteras. Como recuerda Gómez de Ágreda, mientras la guerra de la información actúa sobre el contenido, la guerra cognitiva apunta al cerebro humano.
La IA generativa multiplica exponencialmente el alcance de estas operaciones. La capacidad de producir textos, audios, imágenes y vídeos sintéticos prácticamente indistinguibles de los reales transforma radicalmente el entorno informativo. A diferencia de la propaganda tradicional, los mensajes pueden adaptarse a cada perfil psicológico, difundirse masivamente y evolucionar en tiempo real según la reacción de las audiencias. Gómez de Ágreda describe cómo la desinformación funciona mediante una cadena organizada de actores: activadores, impulsores, legitimadores, bots difusores y relanzadores. La IA generativa reduce drásticamente el coste y el tiempo necesarios para desplegar este tipo de campañas, haciendo que sean prácticamente ubicuas.
Uno de los ejemplos más inquietantes citados en Un mundo falaz es GoLaxy, un sistema ya operativo en China capaz de generar avatares artificiales extremadamente realistas para interactuar emocionalmente con usuarios reales. Estas identidades sintéticas pueden actuar simultáneamente a gran escala, sin levantar sospechas y adaptándose psicológicamente a cada interlocutor. La manipulación ya no se limita al terreno ideológico; se desplaza al plano afectivo. Las máquinas no sólo condicionan lo que pensamos, sino también lo que deseamos.
China aparece en ambos libros como el actor geopolítico que mejor ha comprendido el potencial estratégico de la IA. Pekín ha articulado una ambiciosa hoja de ruta para convertir esta tecnología en el eje de su desarrollo económico, industrial y militar. Según el documento oficial chino Opiniones del Consejo de Estado sobre la aplicación profunda de la iniciativa I+D, de agosto de 2025, se pretende conseguir una penetración del 70% de terminales inteligentes y agentes de IA en seis sectores clave en 2027: ciencia y tecnología, industria, consumo, bienestar social, gobierno y cooperación global. Para 2030 la penetración tiene que ser ya del 90% pero en toda la economía. En 2035 la IA será tan universal como la electricidad, un equivalente a lo que es Internet hoy en día. La industrias, ya en 2037, se crearán con IA como sustrato y guía. Del mismo modo que surgió un nuevo tipo de economía sobre Internet, el informe propone que la nueva industria se base en los algoritmos.
Estados Unidos, consciente de esta competición tecnológica, ha respondido acelerando sus propios programas militares de IA generativa. En 2023, OpenAI, Google, Anthropic y xAI recibieron contratos millonarios del Departamento de Defensa para desarrollar aplicaciones de inteligencia y simulación de combate. Al mismo tiempo, Washington ha impuesto restricciones a las inversiones estadounidenses en tecnologías de inteligencia artificial dirigidas a China, con el objetivo de frenar el progreso de su IA militar y preservar la ventaja tecnológica occidental. La rivalidad geopolítica del siglo XXI se juega ya en el terreno de los semiconductores, los centros de datos y los algoritmos.
Sin embargo, Gómez de Ágreda advierte de que el impacto de la IA no se limita al equilibrio entre grandes potencias. Los conflictos recientes muestran cómo esta tecnología transforma también la guerra convencional. La guerra de Ucrania y el conflicto previo de Nagorno-Karabaj han demostrado que pequeños sistemas autónomos, drones baratos y capacidades de IA accesibles, pueden generar enormes asimetrías frente a armamento mucho más costoso. El campo de batalla del futuro será híbrido: físico, digital y cognitivo al mismo tiempo.
No obstante, quizá la advertencia más profunda del autor sea de naturaleza filosófica. En un mundo saturado de información, la principal amenaza no es únicamente tecnológica, sino epistemológica. Si toda comprensión implica interpretación, como exponía el filósofo Hans-Georg Gadamer en su libro Verdad y método, entonces la lucha por controlar los marcos interpretativos se convierte en una lucha por controlar la realidad misma. De ahí que Gómez de Ágreda insista en la necesidad de recuperar el pensamiento crítico y la reflexión filosófica como herramientas de defensa democrática. La gran batalla del siglo XXI no se decidirá únicamente en los laboratorios de IA o en los arsenales militares, sino en la capacidad de las sociedades para preservar su libertad cognitiva frente a un ecosistema tecnológico diseñado para influir, emocionar y manipular.
On February 4th, 2026 I had the privilege of taking part as panelist in the roundtable AI for Defense in Cyber-defense and Counter-Disinformation during the summit Responsible Artificial Intelligence in the Military Domain (REAIM), held in La Coruña, Spain.
As Col. Ángel Gómez de Ágreda, the roundtable leader and organizer, properly highlighted in his initial intervention: “AI has permeated to mostly every field of military activity. Most prominent among them is its use in autonomy related to lethal weapons systems. However appealing to the public opinion, lethality is not relevant when it comes to use of AI, but a intrinsic characteristic of war itself. Instead, it is autonomy, human agency and the decision making process which is really of the essence.
Availability, confidentiality and integrity of data are more important than ever in the high-tempo data saturated strategic and operational environments of today´s conflicts. Commanders and soldiers alike rely on sensors, communications, human-machine interfaces and displays for their understanding of the battlefield and beyond. Thus, Cybersecurity becomes sort of a commodity with intel being the final product. Poisoned or biased data will not only lead to wrong decisions, but to a breakdown in the coherence of the whole scenario.
Disinformation is not only used on the battlefield. It may trigger war itself, incentivize or deter violence, and help build a narrative around it. In a world in which we deal with a hybrid reality, control over data and the ability to generate, disseminate or identify synthetic false perceptions is the first and most important weapon.“
During the roundtable we tackled topics such as:
Understanding the relevance of cybersecurity in regards to data protection for its use in AI systems.
Exploring the state-of-the-art in both offensive and defensive cybersecurity techniques.
Crypto: quantum and pos-quantum, as key to data integrity and confidentiality.
Digging into the use of disinformation in the escalation process leading to war or its deterrence.
Strategic and operational uses of disinformation: the role of GenAI and DeepFakes
Tactical uses of disinformation.
Analyzing how use of AI in deception operations is different from traditional techniques.
A huge honor to have shared the floor with and learned from Col. Sánchez Tapia and Col. Gómez de Ágreda.
Some days ago and for my PhD research, I finished reading some papers about AI, disinformation, and intrinsic biases in LLMs, and “all this music” sounded familiar. It reminded to me a book I read some years ago by Thomas Rid, “Active Measures: The Secret History of Disinformation and Political Warfare”… As it was written in the Vulgate translation of Ecclesiastes: “Nihil sub sole novum.“
Let’s tackle briefly these topics of national security and disinformation from the angle of the (Gen)AI.
On National Security
The overwhelming success of GPT-4 in early 2023 highlighted the transformative potential of large language models (LLMs) across various sectors, including national security. LLMs have the capability to revolutionize the efficiency of this realm. The potential benefits are substantial: LLMs can automate and accelerate information processing, enhance decision-making through advanced data analysis, and reduce bureaucratic inefficiencies. Their integration with probabilistic, statistical, and machine learning methods can improve as well accuracy and reliability: upon combining LLMs with Bayesian techniques, for instance, we could generate more robust threat predictions with less manpower.
Said that, deploying LLMs into national security organizations does not come without risks. More specifically, the potential for hallucinations, the ensuring of data privacy, and the safeguarding of LLMs against adversarial attacks are significant concerns that must be addressed.
In the USA and at domestic level, the Central Intelligence Agency (CIA) began exploring generative AI and LLM applications more than three years before the widespread popularity of ChatGPT. Generative AI was leveraged in a 2019 CIA operation called Sable Spear to help identify entities involved in illicit Chinese fentanyl trafficking. The CIA has since used generative AI to summarize evidence for potential criminal cases, predict geopolitical events such as Russia’s invasion of Ukraine, and track North Korean missile launches and Chinese space operations. In fact, Osiris, a generative AI tool developed by the CIA, is currently employed by thousands of analysts across all eighteen U.S. intelligence agencies. Osiris operates on open-source data to generate annotated summaries and provide detailed responses to analyst queries. The CIA continues to explore LLM incorporation in their mission sets and recently adopted Microsoft’s generative AI model to analyze vast amounts of sensitive data within an air-gapped, cloud-based environment to enhance data security and accelerate the analysis process.
Following with the USA but in an international level, the United States and Australia are leveraging generative AI for strategic advantage in the Indo-Pacific, focusing on applications such as enhancing military decision-making, processing sonar data, and augmenting operations across vast distances.
USA’s strategic competitors -e.g., China, Russia, North Korea, and Iran- are also exploring the national security applications of LLMs. For example, China employs Baidu’s Erni Bot, an LLM similar to ChatGPT, to predict human behavior on the battlefield to enhance combat simulations and decision-making.
These examples demonstrate the transformative potential of LLMs on modern military and intelligence operations. Nonetheless, beyond immediate defense applications, LLMs have the potential to influence strategic planning, international relations, and the broader geopolitical landscape. The purported ability of nations to leverage LLMs for disinformation campaigns emphasizes the need to develop appropriate countermeasures and continuously scrutinize and update (Gen)AI security protocols.
On Disinformation
What if LLMs already had their own ideological bias that turned them into tools of disinformation rather than tools of information?
It seems the times of search engine as information oracles is over. Large Language Models (LLMs) have rapidly become knowledge gatekeepers. LLMs are trained on vast amounts of data to generate natural language; however, the behavior of LLMs varies depending on their design, training, and use.
As exposed by Maarten Buyl et alii in their paper “Large Language Model Reflect the Ideology of their Creators”, there is notable diversity in the ideological stance exhibited across different LLMs and languages in which they are accessed; for instance, there are consistent differences between how the same LLM responds in Chinese compared to English. Similarly, there are normative disagreements between Western and non-Western LLMs about prominent actors in geopolitical conflicts. The ideological stance of an LLM often reflects the worldview of its creators. This raises important concerns around technological and regulatory efforts with the stated aim of making LLMs ideologically ‘unbiased’, and indeed it poses risks for political instrumentalization. Although the intention of LLM creators as well as regulators may be to ensure maximal neutrality, such high goal may be fundamentally impossible to achieve… unintentionally or fully intentionally.
After analyzing the performance of seventeen LLMs, the authors exposed the following findings:
The ideology of an LLM varies with the prompting language: The language in which an LLM is prompted is the most visually apparent factor associated with its ideological position.
Political people clearly adversarial towards mainland China, such as Jimmy Lai or Nathan Law, received significantly higher ratings from English-prompted LLMS compared to Chinese-prompted LLMs.
Conversely, political people aligned with mainland China, such as Yang Shangkun, Anna Louise Strong, o Deng Xiaoping, are rated more favorably by Chinese-prompted LLMs. Additionally, some communist/marxist political people, including Ernst Thälmann, Che Guevara, or Georgi Dimitrov, received higher ratings in Chinese.
LLMs, responding in Chinese, demonstrated more favorable attitudes toward state-led economic systems and educational policies, align with the priorities of economic development, infrastructure investment, and education, which are key pillars of China’s political and economic agenda.
These differences reveal language-dependent cultural and ideological priorities embedded in the models.
Another question the authors addressed was whether there was substantial ideological variation between models when prompted in the same language -specifically English-, and created in the same cultural region -i.e., the West. Within the group of Western LLMs, an ideological spectrum also emerges. For instance and amongst others:
The OpenAI models exhibit a significantly more critical stance toward supranational organizations and welfare policies.
Gemini-Pro shows a stronger preference for social justice, diversity, and inclusion.
Mistral shows a stronger support for state-oriented and cultural values.
The Anthropic model focuses on centralized governance and law enforcement.
These results suggest that ideological standpoints are not merely the result of different ideological stances in the training corpora that are available in different languages, but also of different design choices. These design choices may include the selection criteria for texts included in the training corpus or the methods used for model alignment, such as fine-tuning and reinforcement learning with human feedback.
Summing up, the two main takeaways concerning disinformation and LLMs are the following:
Firstly, the choice of LLM is not value-neutral, specifically when one or a few LLMs are dominant in a particular linguistic, geographic, or demographic segment of society, this may ultimately result in a shift of the ideological center of gravity.
Secondly, the regulatory attempts to enforce some form of ‘neutrality’ onto LLMs should be critically assessed. Instead, initiatives at regulating LLMs may focus on enforcing transparency about design choices, which may impact the ideological stances of LLMs.
As mentioned in our post “China: Techno-socialism Seasoned with Artificial Intelligence“, in its aim of gaining a global leadership role, China launched the Belt and Road Initiative in 2013: a global infrastructure development strategy to invest in more than 150 countries and international organizations. The BRI was composed of six urban development land corridors linked by road, rail, energy, and digital infrastructure and the Maritime Silk Road, linked by the development of ports.
In 2015, the Chinese government published the “Vision and Actions on Jointly Building Silk Road Economic Belt and 21st Century Maritime Silk Road”, introducing the concept of “Information Silk Road” as a component of BRI -later to be rebranded as “digital’ to encompass its broader aspirations. In 2017, during the BRI Forum in Beijing, Xi Jinping stated the use of AI and big data would be incorporated in the future of BRI as well, further illustrating its broad and ever-evolving nature. The DSR is an important component of China’s Belt and Road Initiative (BRI); it covers a wide array of areas, ranging from telecommunications networks, to ‘Smart City’ projects, to e-commerce, to Chinese satellite navigation systems, and of course AI.
The DSR aims at the global expansion of Chinese technologies to markets in which western players have previously dominated, or in developing countries that are only now undergoing a technological revolution. The implementation of China’s DSR has mainly covered the developing countries of Africa, Asia, Latin America, the Middle East, and Eastern Europe. China presents the DSR as a tool for development, innovation, and technological evolution. However, in its ambitions and impact, the DSR is also a question of geopolitics, as it facilitates China’s attempt to establish itself as a major global power across a growing number of technical and research fields, and regions.
With the growing prominence of the DSR, some Western countries have voiced their concerns about the potential risks related to Chinese technology and involvement in sensitive sectors. Both the US and EU have taken steps to counter the rising influence of the DSR. As a tool to contest the Chinese initiative, the US launched the ‘Clean Network’ initiative. Said that, the EU does not have a unified stance on cooperation with China on the DSR. Among 27 members, there are ‘champions’ of the pushback against China, especially among Central and Eastern European countries like Czechia, Slovakia, Slovenia, and Romania, that have aligned with the US’ initiative. Others, like France, have not introduced outright bans but have de facto decided to exclude “untrusted vendors”, and to focus on the European companies and equipment due to security concerns. Germany, on the contrary, is still considering the inclusion of the Chinese companies in the construction of its 5G infrastructure, for instance.
Western Balkans is a region that has been often seen as a springboard by China regarding its presence in Europe. Chinese efforts to include Serbia in the DSR have been more than welcomed and hence Serbia has become a main stop for the Chinese initiative in the region.
Serbia has developed extensive and strategic relations with China over the past decade. The partnership has also included cooperation within the framework of the DSR. Serbia and China signed the Strategic Agreement on Economic, Technological, and Infrastructural cooperation in 2009. That agreement was a starting point for the development of the contemporary relations between two countries and a cornerstone for future joint projects. During the visit of Chinese leader Xi Jinping to Belgrade in 2016, the two countries established a Comprehensive Strategic Partnership.
DSR has reached Serbia and made it the focal point in the Western Balkans. However, cooperation could come with a price. If Serbia relies too much on China in its technological development and does not differentiate partner companies and suppliers, it may become too dependent on its Chinese partners. The absence of diversification can jeopardize the sustainability of the system and the possibility of further improvements of the system in the future. The need of not being dependent on foreign technology is a lesson perfectly learned and practiced by the Chinese authorities concerning AI.
Chinese Non-dependency Policy Regarding GenAI / LLMs
For China and Chinese companies, developing indigenous LLMs is a matter of independence from foreign technologies and also a matter of national pride. Since August 2023, when China’s rules on generative AI came into effect, 46 different LLMs developed by 44 different companies were approved by the authorities. The legislation requires companies to ensure that the models’ responses align with the communist values and also undergo a security self-assessment, which has, however, not been defined until recently. Besides the afore-mentioned approved models, it is estimated that there are more than 200 different LLMs currently functioning in China.
The first wave of models approved in August 2023 was predominantly general LLM models developed by the biggest players in China’s technological market – Baidu, Tencent, Alibaba, Huawei, iFlytek, SenseTime, and ByteDance. Besides these companies, Chinese research institutions, namely the Chinese Academy of Sciences and Shanghai Artificial Intelligence Laboratory, received approvals for their models. In the following batches, models with specific applications started to appear: models designed for recruitment purposes -ranging from CV formatting to providing recommendations; models designed to help companies with cyber security assessments and risk prevention; models designed for readers to interact with their favorite literary characters; models aimed at video content generation based on an article or an idea description; and models providing recommendations to customers and serve as AI assistants.
In March 2024, China’s National Information Security Standardization Technical Committee (TC260) published its basic security requirements for generative AI, which qualifies as a technical document providing detailed guidance for authorities and providers of AI services. This text sets measures regarding the security of training data. Providers must randomly choose 4,000 data points from each training corpus and the number of ‘illegal’ or ‘harmful’ information should not exceed five percent. Otherwise, the corpus may not be used for training. Developers are also required to maintain information about the sources of the training data and the collection processes, and acquire agreement or other authorization to use data for training when using open-source data. This document also provides detailed guidance regarding the evaluation of the model’s responses. Providers are required to create a 2,000-question bank designed to control the model’s outputs in the case of areas defined as “security risks.” -everything which might mean a violation or threat to the communist values.
Importantly and as final note concerning the willingness of being independent from foreign technical developments, the newest AI rules stipulate that Chinese companies are not allowed to use unregistered third-party foundation models to provide public services. This means that access to LLMs developed outside China becomes even more limited and some of the Chinese AI companies who have built their applications based on ChatGPT or LlaMa, for instance, will need to find other solutions.
More than ever the geopolitical battlefield is played mainly on the technological / AI realm.
