For years, Europe has been building an arsenal of tools designed to detect, analyze, and blunt the impact of disinformation campaigns. There are algorithms that scan social media for coordinated behavior, platforms that verify images and videos, databases that track false narratives, and fact-checking systems that try to separate truth from fabrication. Yet for all that effort, a basic question has gone largely unanswered: which of these tools actually work when confronted with real-world manipulation and interference? It is one thing to design a system in a laboratory, feed it clean datasets, and watch it perform well under controlled conditions. It is quite another to know whether it will hold up when a hostile state actor launches a sophisticated influence operation across multiple platforms, languages, and time zones. A new European Union research project now aims to provide that answer. FIMI-RESIST, a thirty-month initiative funded by Horizon Europe with approximately 3.5 million euros, will systematically evaluate twenty previously EU-funded counter-disinformation tools under common criteria, producing the kind of comparative evidence that policymakers, journalists, and security experts have long lacked. The project is coordinated by the XplaiNLP Research Group at Johannes Gutenberg University Mainz under the leadership of Professor Vera Schmitt, and it brings together ten partners from research and technology organizations, media outlets, and civil society across nine countries. The ambition is not to invent yet another clever solution, but to look honestly at what already exists and figure out what is worth scaling, what needs improvement, and what may be little more than a promising idea that never survived contact with reality.
The acronym behind the project’s name refers to foreign information manipulation and interference, a term that has increasingly replaced the narrower notion of disinformation in European security discourse. This is not just a semantic shift. Disinformation, as it is commonly understood, tends to evoke false stories and misleading articles, the kind of content that fact-checkers can debunk and platforms can label. FIMI is something broader and more menacing. It encompasses coordinated efforts by external actors to distort the entire information environment, whether through fabricated narratives, manipulated media, coordinated inauthentic behavior, or targeted influence operations. Unlike simple falsehoods, these campaigns are often strategic, adaptive, and designed to exploit societal fault lines. They do not merely want to make people believe something false; they want to deepen polarization, undermine trust in institutions, and create a sense that no one can agree on basic facts. Countering them requires more than fact-checking, which after all is a reactive practice that tries to correct individual claims. It demands technical systems capable of detecting coordinated activity at scale, assessing the provenance and integrity of content, and supporting human analysts who must make rapid judgments under pressure. It is precisely this complex ecosystem of tools and practices that FIMI-RESIST intends to put to the test. The project’s founders understand that the threat is not a single lie but a layered, constantly evolving strategy, and that defending against it requires a similarly layered response.
The timing of the initiative reflects a disinformation landscape that is changing faster than the defenses built to contain it. Generative artificial intelligence has dramatically lowered the barriers to producing synthetic text, images, audio, and video. What once required sophisticated technical skills and significant resources can now be done by anyone with an internet connection and a willingness to experiment. Manipulated media can be created cheaply, scaled rapidly across platforms and languages, and made increasingly difficult to distinguish from authentic content. At the same time, the AI systems that people increasingly rely on to find and assess information, including search assistants and conversational agents, have themselves become targets for manipulation. An adversary who can poison the data or outputs of such systems can reach audiences indirectly, bypassing the traditional defenses of newsrooms and fact-checking organizations. These shifting threat vectors form the backdrop against which the project’s evaluation framework will be constructed. What distinguishes FIMI-RESIST from earlier efforts is its deliberate refusal to build yet another stand-alone tool. The European Union has already funded a broad range of research projects and software solutions aimed at detecting and mitigating disinformation, but these have typically been developed in isolation, each with its own assumptions, datasets, and evaluation metrics. The result is a fragmented landscape in which it is nearly impossible to compare performance or determine which approaches are suited to which problems. The project addresses this gap by establishing a shared evaluation and harmonization framework: a common set of criteria and benchmarks against which twenty existing European tools will be assessed. The objective is to generate robust, comparable evidence about which methods perform best for specific users, operational settings, and threat scenarios.
The scientific foundation for this assessment draws on the coordinating group’s particular expertise. The XplaiNLP Research Group at Mainz combines natural language processing with explainable artificial intelligence and robust information processing, fields that are central to modern content analysis. Natural language processing provides the computational machinery for analyzing text at scale, identifying narrative patterns, and tracing how claims spread across networks. It allows researchers to move beyond individual posts and see the broader structures of influence campaigns, the way a single story mutates as it crosses borders, or the way bots and fake accounts amplify certain themes while drowning out others. Explainable AI addresses a persistent weakness of automated systems: the tendency of machine learning models to function as opaque black boxes whose judgments cannot be easily scrutinized. In a domain where decisions can affect freedom of expression and media pluralism, the ability to explain why a system flagged a piece of content is not a luxury but a requirement. A journalist who receives an alert from an automated tool needs to know whether the alert is based on solid evidence or on a flawed correlation. A platform moderator who removes a post needs to be able to justify that decision in a way that respects users’ rights. Robust information processing, meanwhile, concerns the resilience of these systems against adversarial attempts to deceive or evade them. The same AI technologies used for detection can be used by malicious actors to test the limits of detection, to find blind spots, and to adapt their tactics. A tool that cannot withstand such pressure is not truly secure. Yet the project is not only about improving algorithms. A central focus is practical application rather than laboratory performance. Working with journalists, fact checkers, security stakeholders, and civil society organizations, the consortium will assess how effectively existing tools can be integrated into day-to-day workflows. This user-centered approach recognizes a common failure mode in security technology: a system that performs well on benchmark datasets may prove unusable in a busy newsroom or a crisis-response setting, where time constraints, language diversity, and the sheer volume of content create conditions that benchmarks rarely capture. By testing tools in realistic operational contexts, the project aims to identify not only which systems detect manipulation effectively, but also where gaps remain as AI-driven threats continue to evolve.
The consortium assembled for this task spans a deliberately wide range of competencies and geographies, reflecting the belief that countering foreign information manipulation cannot be done from a single academic silo. Alongside the coordinating group at Johannes Gutenberg University Mainz, it includes the Kempelen Institute of Intelligent Technologies in Slovakia led by Dr. Jakub Šimko, the Centre for Research and Technology Hellas in Greece represented by Dr. Symeon Papadopoulos, and the University of Amsterdam in the Netherlands under Professor Richard Rogers. The technology and industry side is represented by Logically/INSIKT, operating in the United Kingdom and Spain, Factiverse from Norway, Exorde Labs from France, Cyfluence Research Center from Germany, and Gretchen AI, also from Germany, which participates as an associated partner. Media and civil society perspectives come from Deutsche Welle, Germany’s international broadcaster, and VoxUkraine, an organization with direct experience of operating in an information environment shaped by war and foreign interference. The inclusion of Ukrainian and media partners underscores the stakes involved. Ukraine has become, in effect, a live testing ground for foreign information manipulation at scale, and organizations like VoxUkraine bring firsthand knowledge of what interference campaigns look like in practice. Deutsche Welle contributes decades of experience in international journalism and in monitoring disinformation across languages and regions. Civil society and security stakeholders round out the picture, ensuring that the evaluation framework reflects the needs of those who defend democratic discourse rather than purely academic metrics. The project has also drawn political support, with Alexandra Geese, a Member of the European Parliament, backing the initiative, and contributions at its kickoff from Saman Nazari of Alliance4Europe and Sandra Fiene of the European Commission, alongside policy and project officers Ilona von Bethlenfalvy and Alberto Domini. Beyond its technical evaluations, FIMI-RESIST is designed to leave a durable institutional footprint. The project will establish a help desk, a European hub, and a program of training offerings to ensure that validated methods and results remain accessible to practitioners after the funding period ends. This sustainability component reflects a lesson learned from previous research projects, whose tools and findings often faded from view once grant support concluded. By building infrastructure for continued knowledge transfer, the consortium hopes to convert its thirty months of work into a lasting European capability rather than a one-time report.
The findings are also intended to feed directly into the European regulatory debate, where the question of what works is no longer merely academic but urgent. The Digital Services Act, which imposes obligations on large online platforms to address systemic risks including disinformation; the AI Act, which establishes rules for artificial intelligence systems including transparency requirements; and the European Media Freedom Act, which protects pluralism and independence in the media landscape, together form a regulatory architecture whose effectiveness depends on an accurate understanding of which countermeasures succeed in practice. Regulators cannot design sensible rules if they do not know whether the underlying technologies are reliable. Platforms cannot implement meaningful safeguards if they are choosing from a menu of tools without comparative data. Journalists and civil society organizations cannot use these systems effectively if they do not understand their strengths and limitations. By supplying rigorous comparative evidence, FIMI-RESIST aims to inform how these frameworks are implemented and refined. It is an effort to bring a measure of empirical discipline to a field that has often been driven by hype, fear, and good intentions. In an era when the integrity of the information environment has become a matter of democratic security, knowing which defenses actually hold is perhaps the most valuable intelligence Europe can produce. The project will not end the battle against disinformation, nor will it offer a single magic solution. But by asking hard questions, comparing tools honestly, and building a shared foundation of knowledge, it offers something just as important: a way to move forward without being deceived, not only by the disinformation campaigns themselves, but also by the comforting illusion that every tool claiming to fight them is actually working.