NaDI
At NaDI, researchers provide innovative solutions to the new societal challenges posed by the digital revolution (eGov, eHealth, eServices, Big data, etc.). Coming from a variety of disciplines, researchers combine their expertise in IT, technology, ethics, law, management or sociology. Grouping six research centers from various disciplines, the Namur Digital Institute offers a unique multidisciplinary expertise to all areas of informatics, its applications and its social impact.
Among its main competencies are formal methods, man-machine interface, requirement engineering, modeling techniques to reason and design complex software systems, testing, quality insurance, software product lines, data bases, big data, machine learning and more generally artificial intelligence, security, privacy, ethics by design, technology assessment and legal reasoning.
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ESPHIN Institute
Post-truth: What if the truth were no longer the issue?
Democracy
Law
Political science
Post-truth: What if the truth were no longer the issue?
Democracy
Law
Political science
The measles vaccine supposedly causes autism. Global warming is supposedly just a natural phenomenon. Immigrants supposedly eat the neighborhood’s cats. These claims all have one thing in common: they have been disproved by the facts. Yet they continue to circulate, to be shared, and sometimes to influence elections. Even more surprising, some are repeated by figures in the highest political offices. What becomes of our relationship with the truth when opinion is presented as fact, when humor obscures intentions, and when information spreads without going through traditional intermediaries? To understand these changes, four researchers from UNamur share their perspectives. Behind the debates on fake news, they see a deeper shift taking shape: the truth still matters, but it is no longer always enough to convince people.
“There is no established, consensus-based definition of ‘post-truth,’” warns Olivier Sartenaer, director of the Department of Sciences, Philosophy, and Society and a member of the ESPHIN Institute (Namur Philosophical Forum). He prefers to describe four trends that, together, shape the phenomenon.
First observation: our relationship with established consensus is becoming more fragile. Ideas that were once marginal now enjoy unprecedented visibility thanks to social media. Second transformation: the line between opinion and knowledge is blurring. “Everyone’s opinion is considered knowledge.” ” Third change: lying has lost some of its symbolic cost. “Until recently, when a political figure was caught lying shamelessly, they had to pay a price—whether electoral or symbolic. Today, lying can even become a sort of badge of honor.”
The fourth transformation, the most subtle, concerns what philosophers call “rhetoric.” “While a liar knows the truth and conceals it, a rhetorician produces discourse to seduce, frighten, or convince, regardless of whether it is true. ” Thus, when Donald Trump claims that one should drink bleach to treat COVID, the most important thing may not be the content of the statement. “Saying that positions him against the elites and gets people talking about him. Is it true? He doesn’t even ask himself that question.”
Olivier Sartenaer explains the emergence of post-truth through the “epistemic deluge”—this overabundance of information driven in particular by digital technologies. Our critical faculties have not necessarily weakened, but the environment in which they operate has become infinitely more complex. This complexity also poses challenges for the law.
Olivier Sartenaer
The Law in the Face of Information Chaos
While “post-truth” is not a legal category in and of itself, Alejandra Michel, a researcher at CRIDS (Center for Research on Information, Law, and Society) within the NaDI Institute (Namur Digital Institute), approaches the phenomenon through what are known as “information disorders.” A key distinction sheds light on the mechanisms at work: “misinformation” refers to incorrect information disseminated without the intent to deceive; “disinformation,” by contrast, implies an intent to manipulate; and “malinformation” is based on true information that has been taken out of context or used to cause harm. In practice, however, these categories remain difficult to distinguish. Intentionally produced false information can be shared in good faith by thousands of people who believe it to be authentic, and its status then changes as it circulates.
From a legal perspective, the issue is all the more delicate because freedom of expression protects both the speaker and the recipient of the information. Should the authors of false information be punished? It’s not that simple: criminalization could backfire on journalists, whistleblowers, or those who disseminate information that is inconvenient for those in power.
Alejandra Michel is therefore more interested in the right to receive high-quality information—not with an absolute obligation to truth, but with a requirement to strive for accuracy and to comply with the rules governing the collection and dissemination of information.
On the European front, the Digital Services Act addresses the information environment itself, notably by requiring large digital platforms to implement measures related to moderation, transparency, and the adaptation of recommendation systems.
Alejandra Michel
The fight against disinformation cannot, therefore, be solely a legal one. It also requires media literacy, support for quality journalism, and the protection of pluralism. One question remains that the law cannot resolve: when no one seems to regard the truth as a common reference point anymore, what still underpins a person’s credibility?
Authenticity: The New Currency of Credibility
Part of the answer lies in humor, which has become a dominant form of communication on the web. According to Fanny Barnabé, a lecturer at CRIDS/NaDI, memes, parodies, trolling, and shitposting play such a significant role in digital cultures that they, too, blur our relationship with the truth.
In classical irony, the speaker says the opposite of what they mean while leaving their listener enough clues to grasp the message’s true meaning. Irony has now lost its transgressive nature because it has become ubiquitous. To continue to surprise, internet users have therefore developed new levels of ambiguity. Today, the lines are blurred: “We no longer know whether a statement is ironic, sincere, or partly both.” This is what is known as post-irony.
A content creator’s credibility therefore no longer rests on their relationship to the truth, but on their authenticity. Fanny Barnabé observes this shift on the streaming platform Twitch, where the relationship between streamers and their community hinges on a sense of direct and sincere connection: awkward moments, spontaneous reactions, and an unfiltered personality are valued more highly than accuracy.
For Fanny Barnabé, the real question, then, may be whether it’s still possible to be serious on the Internet. On Twitch, the reversal has become so complete that “users sometimes explicitly state that they’re being serious. People no longer indicate that a message is ironic. It’s the literal meaning that now needs to be made clear.”
Fanny Barnabé
When Authenticity Becomes a Political Issue
We see exactly this same mechanism at work in politics. Figures like Donald Trump and Elon Musk now use memes, provocation, trolling, and references to gaming culture to speak directly to their audience. Post-irony offers them powerful rhetorical protection. Serious statements can be made in a joking manner, and if the reaction is negative, all one has to do is say, “I was just kidding.”
For Arthur Borriello, a professor of political science at UNamur and a researcher at the Transitions Institute, credibility in politics is measured the same way as it is on Twitch: by perceived authenticity rather than truthfulness. “Trump can afford to come across as a liar or a crackpot. What matters is that he appears authentic,” explains the political scientist. Insults, extravagance, and the transgression of linguistic norms thus become markers of closeness to ordinary people, as opposed to the polished discourse of the elites.
Arthur Boriello
Authenticity doesn’t promise virtue; it promises closeness. It means standing with ordinary people, with all their flaws, their anger, and sometimes even their transgressions. Facing off against Hillary Clinton, Trump essentially declared: Yes, the Wall Street system is corrupt—since I make use of it myself. He didn’t promise to put an end to it; he promised to be authentic.
The political scientist goes further. He questions the very idea that politics is a matter of truth. “Political discourse is not a discourse of truth. That is not its aim.” Its strength lies rather in its internal coherence and its ability to give meaning to lived experience. Trumpism, for example, links economic decline, unemployment, immigration, and a sense of American decline into a single narrative. “Do immigrants eat pets? It doesn’t matter whether that statement is true or false. What matters is that it fits with the other elements in this coherent narrative,” summarizes the political scientist.
The Cost of Distorting the Truth
For Olivier Sartenaer, the consequences of this new relationship with the truth are not merely rhetorical. “If, for example, one claims that the recommendations of the IPCC (Intergovernmental Panel on Climate Change) are merely the ‘religion’ of bourgeois-bohemian environmentalists and that one prefers the popular common sense that favors coal-fired power plants, one creates a climate that becomes uninhabitable. ” The problem here isn’t just being mistaken about a scientific phenomenon; it’s choosing to ignore available knowledge even when the consequences are predictable.
The same mechanism is at work in debates about vaccination. When scientific knowledge gives way to “common sense” or political convictions, collective decisions can have dramatic consequences. “The resurgence of measles in the United States is directly linked to the spread of doubts about vaccines. Today, children are dying from a disease that had been eradicated long ago,” laments the philosopher.
Beyond poor decision-making, it is the very possibility of living together as a society that is at stake. “To discuss and reach agreement, we need a shared world. If we polarize to the extreme, we lose that shared world. We can no longer understand one another or act together.”
Respond Differently
Beyond fake news and conspiracy theories, the “post-truth” and “post-irony” eras thus reveal a profound transformation in our relationship with the shared world. Authenticity versus expert opinion, humor that obscures intentions: the issue is becoming less one of truth and more one of trust. Hence the importance, for researchers, of rebuilding shared spaces through quality information, media literacy, a vibrant civil society, forums for debate, and collective narratives. For without a shared world, it becomes difficult not only to agree on the facts, but also to form a society. One final, distinctly political question remains: can we even combat this obfuscation with “truth” alone? Arthur Borriello believes not, and explains why in the sidebar.
Arthur Borriello: “You have to fight ideology with ideology.”
According to political scientist Arthur Borriello, we must first distance ourselves from two concepts that have become ubiquitous. “The concepts of ‘post-truth’ and ‘populism’ play the same role in public debate today: they serve as catch-all terms that allow us to broadly describe political developments without always analyzing them with the precision they deserve.”
The dominant definition of populism is based on a contrast between a “virtuous people” and “corrupt elites,” which leads to very different movements—including those on the far right—being labeled as populist. In his book *Populism: The Misnamed Phenomenon*, the political scientist defends a view—which he acknowledges is in the minority—that populism is above all a democratic moment, driven by a desire to deepen democracy and return more power to the people. “This definition effectively excludes the far right, which does not seek to deepen democracy but rather to restrict the circle of those who benefit from it.”
But why is this promise to return power to the people used by so many political movements, including the far right? It responds to a very real experience. Many citizens feel they have lost some of their ability to influence political decisions. Arthur Borriello attributes this to the disintermediation observed since the 1970s: political parties, unions, and associations—which traditionally served to transform individual concerns into collective demands—have lost their significance.
The power of political discourse therefore rests more on its ability to give meaning to lived experience and on its internal coherence. This perspective leads him to question the effectiveness of a strategy that consists solely of “fact-checking” the rhetoric of the far right. He illustrates this with a deliberately radical example: “Faced with Hitler, who claimed that Jews were the cause of all evil, would fact-checking have weakened that discourse? Certainly not. The only way to combat this type of rhetoric is to offer an alternative narrative that is sufficiently convincing and resonates with people’s lived experiences. Ideology must be countered with ideology.”
In practical terms, Arthur Borriello advocates for the rebuilding of spaces for mediation: associations, collective organizations, and forums for debate and mobilization that enable citizens to regain their capacity for action and representation. French-speaking Belgium offers an interesting point for reflection in this regard. While the far right is making significant gains in several European countries, it has so far remained relatively marginal there. He attributes this resilience in particular to the persistence of a dense network of associations and to the local roots of certain political groups, such as the PTB through its youth organizations, community health centers, and so on.
The response to the far right, therefore, is not solely a matter of the accuracy of information. It also hinges on a society’s ability to forge connections and offer collective narratives in which everyone can see themselves reflected.
Further Reading
The Truth in Crisis: Disinformation, Critical Thinking, and the Right to Information
A collective work to be published in the fall of 2026 by Larcier Intersentia. This book brings together several contributions, including texts by Alejandra Michel and Fanny Barnabé.
Arthur Borriello, Populism: The Misnamed
University of Brussels Press, “Débats” series.
In this essay, the political scientist examines contemporary uses of the notion of populism and offers a critical analysis of a concept that has become ubiquitous in public debate.
Denis Saint-Amand, Countering Fascist Laughter: Trolling and Resistance
Éditions Rue de l’Échiquier, “Les Incisives” series.
An analysis of the political uses of humor, trolling, and digital cultures, as well as the forms of resistance they can inspire.
Denis Saint-Amand is a qualified researcher at the FNRS at UNamur and president of the Namur Institute of Language, Text, and Transmediality (NALTT)
“The measles vaccine causes autism”: The topic of fake news in the field of health—and specifically regarding vaccination—was one of the subjects discussed during UNamur’s official 2026 academic year opening ceremony. Watch the video of this presentation.
This article is taken from the "Issues" section of Omalius magazine, Issue #42 (September 2026).
Article
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Faculty of Computer Science
NaDI Institute
A study by VUB and UNamur shows that AI agents develop their own “artificial natural language” to communicate about complex data
Artificial Intelligences (AI)
A study by VUB and UNamur shows that AI agents develop their own “artificial natural language” to communicate about complex data
Artificial Intelligences (AI)
AI systems spontaneously develop their own language, tailored to their sensors, rather than copying human language.
Researchers from the VUB’s Artificial Intelligence Lab and the University of Namur (UNamur) demonstrate, in a new large-scale study, how autonomous AI systems can spontaneously develop, without human intervention, a functional and shared language. Unlike large language models such as ChatGPT, which learn existing human language by heart, these AI agents construct their own communication system, directly rooted in their specific sensors and environment. This discovery represents a major breakthrough for communication between autonomous systems, such as self-driving cars, robots and industrial sensors.
A layer of abstraction for non-human senses
Current AI language models focus on understanding and generating human languages such as Dutch or English. These human languages are historically rooted in our own sensory perceptions. When physical or virtual AI agents are equipped with sensors for which humans have no direct sensory equivalent – such as lidar, sonar, infrared or chemical analysis – existing human language proves insufficient.
Jérôme Botoko Ekila, a PhD student at the VUB’s AI Lab, explains: ‘Instead of forcing AI systems to communicate in a human language that does not correspond to their sensors, we allow them to develop their own “artificial natural language”. They construct effective concepts that correspond exactly to what they perceive via their sensors, even if the data is incomprehensible to humans.’
As, in practice, the sensors on different machines or vehicles can never be calibrated identically, the researchers believe that this language offers the ideal solution.
Paul Van Eecke, professor of artificial intelligence at the VUB: “In industrial or physical applications, it is simply unrealistic to expect all the sensors on different robots or vehicles to be calibrated in exactly the same way. Humans solve this problem through language: if I say I am standing near the ‘red car’, we understand each other without our eyes registering exactly the same colour values. Language provides a layer of abstraction above the sensor readings, and this is precisely what we are now allowing these AI agents to construct autonomously.”
Self-organisation and evolution
Instead of pre-programmed words or fixed codes, the researchers simply provided the agents with the basic mechanisms underpinning the evolution of human language: the local invention of words, the adaptation of conceptual prototypes, and the incorporation of feedback following successful or failed communication.
Image
What’s fascinating is that there’s no central computer imposing the rules. Each time, we let two agents communicate with one another at a local level. It is solely through these individual interactions and updates that a global convention emerges spontaneously across the entire population. This principle of self-organisation allows the language to optimise itself automatically: the agents create exactly the number of categories needed to carry out their tasks efficiently, without superfluous details.
Tested on 37 datasets
The universal applicability of the method has been demonstrated across 37 varied and complex datasets. The agents successfully developed their own vocabulary to communicate, notably regarding physico-chemical analyses of wine, NASA data on exoplanets, visual datasets, and images of birds or faces. In all these situations, the agents successfully synthesised the data into new, shared concepts.
Transparent and adaptive
Transparency is a notable advantage of the systems developed. Unlike many ‘black-box’ AI models, researchers can precisely determine the meaning of a specifically developed word, as the prototype can be directly linked to the values of the underlying sensors.
Furthermore, these evolving linguistic systems are extremely robust. When the environment changes, when sensors produce noise, or when individual agents have a different structure, the language automatically adapts to the new circumstances through continuous interaction.
Reference
Botoko Ekila, J., Verheyen, L., Nevens, J., Beuls, K., & Van Eecke, P. (2026). Emergent Communication in Continuous Worlds: Self-Organization of Conceptually Grounded Vocabularies at Scale. Transactions of the Association for Computational Linguistics, vol. 14, pp. 2234–2257. DOI: 10.1162/TACL.a.799
Funding and collaboration
This research was carried out as part of a collaboration between the Artificial Intelligence Laboratory at the Vrije Universiteit Brussel (VUB) and the Faculty of Computer Science at the University of Namur (UNamur), and was funded by the Research Foundation – Flanders (FWO) and the Belgian National Research Fund (FNRS) as part of the WEAVE project.
Article
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Faculty of Computer Science
NaDI Institute
Research from UNamur Makes Artificial Intelligence Tools More Reliable
Artificial Intelligences (AI)
Computer science (IT)
Digital transition
Research from UNamur Makes Artificial Intelligence Tools More Reliable
Artificial Intelligences (AI)
Computer science (IT)
Digital transition
Researchers at UNamur have developed a new method that has uncovered 32 previously undetected bugs in some of the most widely used software libraries for training artificial intelligence models. Originating from a master’s thesis, this research has already led to fixes in several software programs used by millions of developers around the world.
Before artificial intelligence can recognize an image, understand a text, or answer a question, it must first be trained. To do this, developers and data scientists use specialized software libraries—true “toolboxes” that enable the construction of these AI models.
A research team comprising the University of Namur, the University of Passau (Germany), and TU Delft (Netherlands) has been studying this software. Their goal: to detect bugs that are particularly difficult to spot and that could cause a program to crash suddenly.
A New Method for Detecting Hidden Bugs
To verify that these libraries are functioning properly, researchers use software capable of automatically generating thousands of tests. The purpose of these tests is to push the programs to their limits in order to identify any potential errors.
Until now, however, these tools had a major limitation: whenever a test caused a software library to malfunction, the software responsible for running the tests would also stop working. This made it impossible to pinpoint the exact source of the problem or report it to the developers.
Researchers at UNamur have therefore devised a new method. Now, each test is run separately. If one of them causes a crash, it is isolated: the testing software continues to run, logs the error, and carries on with its analysis. This makes it possible to automatically detect bugs that previously went unnoticed.
32 bugs discovered and already fixed
Using this new method, researchers analyzed 1,648 modules from the leading machine learning libraries and uncovered 32 previously unknown bugs. Several of these affected software that has become indispensable for training artificial intelligence models.
These issues were reported to the development teams. Several have already been acknowledged and fixed. “When a bug is fixed at this level, potentially thousands, or even millions, of users benefit,” notes Xavier Devroey, a professor in the Faculty of Computer Science at UNamur and a member of the PReCISE research center at the Namur Digital Institute (NaDI). Beyond these fixes, this research helps make the software on which so many artificial intelligence applications rely today more reliable.
Research that grew out of a thesis
This breakthrough originated from Lucas Berg’s master’s thesis, completed at UNamur under the supervision of Professor Xavier Devroey. As part of his research internship, Lucas Berg then joined Professor Annibale Panichella’s team at TU Delft to work on Pynguin, the open-source automated test generation tool developed at the University of Passau by Professor Gordon Fraser’s team, mentioned earlier.
Initially, his goal was to improve this tool. By preventing crashes while discovering bugs, this first contribution subsequently caught the attention of researchers at the University of Passau, who were facing the same problem, leading to an international collaboration that would result in a joint scientific publication.
Lucas Berg is currently pursuing a Ph.D. at the Faculty of Computer Science at UNamur under the supervision of Professors Wim Vanhoof and Xavier Devroey. The results of this research were presented at the IEEE International Conference on Software Testing, Verification, and Validation (ICST 2026), one of the most prestigious international conferences in the field of software testing.
This research also received support from the Wallonia Public Service (SPW Research) and Wallonia-Brussels International. This recognition underscores the quality of this work and its significance to the international scientific community.
The Namur Digital Institute (NaDI)
At NaDI, researchers develop innovative solutions to the new societal challenges posed by the digital revolution (eGov, eHealth, eServices, big data, etc.). Drawing from a variety of disciplines, the researchers combine their expertise in computer science, technology, ethics, law, management, and sociology. Comprising six research centers, the Namur Digital Institute offers unique multidisciplinary expertise in all areas of computer science, its applications, and its social impact.
News
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Faculty of Law
NaDI Institute
NaDI doctoral students are launching “What If AI…,” a lecture series aimed at “demystifying artificial intelligence”
Artificial Intelligences (AI)
NaDI doctoral students are launching “What If AI…,” a lecture series aimed at “demystifying artificial intelligence”
Artificial Intelligences (AI)
Through five interdisciplinary lecture-workshops, doctoral students from UNamur NaDI invite the general public to develop a critical perspective on artificial intelligence, which is already transforming our daily lives.
Artificial intelligence is now accessible to everyone. Yet, while many people use it every day, few truly understand how it works, its limitations, or the issues surrounding it. To address this need, the Namur Digital Institute (NaDI) is launching “What If AI…,” a series of lecture-workshops open to the general public, coordinated by doctoral students Elisa De Coster (PReCISE) and Aline Nardi (CRIDS).
“The idea behind the project is to demystify artificial intelligence,” begins Elisa De Coster. “As researchers, we’re fortunate to be aware of the issues raised by AI. We wanted curious members of the public to have access to these keys to understanding as well.”
“Before 2022 and the rise of ChatGPT, these tools were limited to a niche audience,” continues Aline Nardi. “Since then, the use of AI has become widespread at record speed, but reflection on the societal implications of these uses has not kept pace. This series of lectures is an invitation to take a step back and understand what’s happening behind the scenes.”
Different Perspectives for a Better Understanding of AI
Each session, lasting about two hours, will bring together the perspectives of several specialists. A doctoral student in computer science will explain the technical workings of AI, while his counterpart in law will address the legal, ethical, and societal implications.
Speakers from the professional world will share their real-world experience, and an interactive activity will allow the audience to put these concepts into practice. Interactivity, interdisciplinarity, and accessibility to the general public are the three pillars of the project.
Five lectures exploring the challenges of AI
Each event will address a different social issue:
- October 1, 2026 – La Nef
What if AI were your confidant?
Can you confide in a chatbot? What are the risks? - October 22, 2026 – PA02
What if AI were wrong?
How can we recognize errors in artificial intelligence and maintain our critical thinking? - November 19, 2026 – Caméo
What if AI were subjective? Is artificial intelligence
truly neutral, or does it perpetuate certain biases? - February 25, 2027 – Quai 22
What if AI stole your creations?
What challenges does generative AI pose in terms of copyright and intellectual property? - March 18, 2027 – TRAKK
What if AI knew you too well?
What happens to our personal data, and to what extent can AI learn to know us?
While Elisa De Coster and Aline Nardi coordinate the project, they emphasize that it is, above all, a collaborative effort. The lecture series is led by ten doctoral students from the PReCISE and CRIDS research centers: Elisa De Coster, Adélaïde Couplet, Jules Dejaeghere, Pierre Luycx, Pierre Poitier, Aline Nardi, Alix Gobert, Florian Jacques, Martin Rappe, Lionel Goffaux, and Olga Thiry. Together, they aim to help the general public better understand artificial intelligence, without demonizing it or presenting it as a miracle solution.
Research at NaDI-CeRCLe
Agenda
What if AI were as subjective as you are? (ESIA#3)
Artificial intelligence (AI)
19
2026
18:30
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20:30
Université de Namur - rue de Bruxelles, 61 - 5000 Namur
What if AI inherited our biases and blind spots? During this third session of the “What If AI?” series, compare, question, and experiment to uncover the subjectivity hidden behind seemingly neutral answers.
AI is often perceived as neutral and objective. But is that really the case? This third session of the “What If AI?” series examines the biases and discrimination that can be embedded in artificial intelligence systems, drawing on striking examples such as biased recruitment and judicial algorithms.
Through demonstrations and interactive experiments, the session aims to debunk the myth of technological neutrality and explore ways to design more equitable and inclusive systems.
Public Defense of a Doctoral Dissertation in Computer Science - Maxime André
Computer science
26
2026
16:00
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20:00
Université de Namur, Ilot Pedro Arrupe, auditoire PA11 - rue Grandgagnage ou rue de Bruxelles 65-67 (via cour des sciences) - 5000 Namur
Contact person
:
Secrétariat informatique
Understanding Data Manipulation in Evolving Microservices
Abstract
Over the past fifteen years, the microservices architectural style has become a dominant model, particularly for the design of cloud-based applications in the cloud continuum. Supported by agile development methods, it has been adopted by many actors of the modern software industry, including open-source communities as well as major software development companies such as Netflix, Spotify, and Amazon. Unlike the monolithic architectural style, it is praised for its qualities of modularity, heterogeneity, deployability, collaboration, and automation. Facilitating software evolution is one of the main motivations for adopting microservices architectures. Paradoxically, recent studies observe the opposite, especially concerning data manipulation layer. Nowadays, it is considered one of the most pressing challenges. Indeed, this style impacts the data layer, making it heterogeneous and distributed. In practice, developers encounter difficulties obtaining a holistic view of the system, understanding the related data concepts, measuring the impact of changes, and propagating subsequent modifications while preserving inter-microservices and inter-data relationships, which are sometimes implicit. These challenges often lead to manual effort during evolution tasks, for which developers suffer from a lack of support. This thesis aims to fill these gaps by proposing novel methods, techniques, and tools. More specifically, it combines static and dynamic program analysis techniques to perform reverse engineering of microservices and their data manipulation layer, to identify data concepts, and to locate related code fragments while taking into account their heterogeneous and distributed nature. It then visualizes the extracted information from a multi-layered viewpoint. Finally, it introduces techniques for analyzing the data-driven evolution of microservices from a historical perspective.
The members of the jury
- Prof. Dr Katrien BEULS – President of the jury, UNamur, Belgium
- Prof. Dr Anthony CLEVE – Supervisor, UNamur, Belgium
- Prof. Dr Xavier DEVROEY – Internal member, UNamur, Belgium
- Prof. Dr Etienne RIVIERE – Co-supervisor, UCLouvain, Belgium
- Prof. Dr Massimiliano DI PENTA – External member, University of Sannio, Italy
- Prof. Dr Michele LANZA – External member, Università della Svizzera Italiana, Italy
What if AI stole your creations? (ESIA#4)
Artificial intelligence (AI)
25
2027
18:30
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20:30
Université de Namur - rue de Bruxelles, 61 - 5000 Namur
Creating with AI—but at what cost to authors and artists? During this fourth session of the “What If AI?” series, explore the blurred lines between inspiration, reproduction, and appropriation.
Artificial intelligence creates, imitates, and transforms content on a large scale. But who owns these creations? And what happens to the works used to train these models? This fourth session of the “What If AI?” series addresses the intellectual property issues related to generative AI.
Drawing on recent cases involving the use of copyrighted works to train models, the speakers will explain the tensions between technological innovation and respect for copyright.
This session will provide insights into the current challenges facing intellectual property law in the face of these technologies and the implications for creators.