AI in research

Major transformations throughout history have often been accompanied by an essential question: how can we take advantage of the opportunities they offer without losing sight of what we want to preserve? Today, in the face of accelerating technological change, this question is more relevant than ever.

In this video, Dr. Torralba reflects on the need to establish ethical principles, consensus, and governance mechanisms that enable emerging technologies to serve people and societies. A global challenge that invites us to ask not only what these technologies can do, but also how we want them to be used.

When a technology begins to make decisions that affect our lives, it is no longer enough to ask what it is capable of doing. The real question is this: what principles should guide its development and use?

In this video, Dr. Torralba explores the foundations of AI ethics and presents some of the principles that should guide responsible technology: transparency, explainability, fairness, privacy protection, and respect for the environment. An essential reflection on how innovation can be harnessed to serve the common good.

Artificial intelligence is already present in many areas of our lives, but perhaps it is in education where its implications raise the deepest questions. If a machine can provide information instantly, what will be the role of teachers? What does it mean to learn in a context where answers are only a click away?

In this video, Dr. Torralba reflects on the challenges that AI poses to education, from the transformation of learning and assessment to the redefinition of the role of educators. An invitation to consider, calmly and thoughtfully, what technology can do and what remains essentially human.

Research has always advanced through new tools that expand our capabilities. But what happens when a technology not only helps us find information, but is also able to organize it, analyze it, and even generate content?

In this video, Dr. Torralba reflects on the impact of artificial intelligence on research. While exploring the opportunities it offers to streamline processes and broaden access to knowledge, he also raises fundamental questions about authorship, academic rigor, and the responsible use of these tools. A balanced perspective on the challenges and opportunities that AI brings to the creation of knowledge.

Generative artificial intelligence goes far beyond the creation of texts. How does this technology work, and what possibilities does it offer in fields such as scientific research?

Dr. Agell introduces the basic concepts of generative AI and its potential to transform research processes and academic publishing.

Artificial intelligence is becoming an increasingly common tool in scientific research. It can help locate information, summarize studies, organize references, and improve writing, allowing researchers to devote more time to higher-value tasks.

In this presentation, Dr. Agell discusses some of the main applications of generative AI in the preparation of scientific articles and reviews tools that facilitate everyday research work. At the same time, she highlights an essential idea: AI is a valuable support tool, but judgment, oversight, and responsibility for knowledge remain firmly in the hands of researchers.

Artificial intelligence tools can accelerate many research tasks, but speed is not always synonymous with reliability. What risks do we assume when we rely on systems that can also make mistakes, reproduce biases, or generate incorrect information?

In this presentation, Dr. Agell examines some of the main limitations of generative AI in scientific research and emphasizes the importance of maintaining a critical perspective on the results it provides. A reflection on responsibility, human oversight, and the good practices that should accompany the use of these tools in research.

The use of artificial intelligence in scientific research raises an increasingly common question: what should be done when part of the work has been assisted by these tools? As AI becomes integrated into writing and analysis processes, the rules governing its use are also evolving.

Dr. Agell reviews the guidelines adopted by scientific journals and international organizations to ensure transparency and academic integrity. An overview of the main recommendations that support the responsible use of AI in scientific communication.

Generative artificial intelligence has opened up new opportunities for research, but its true value depends less on the tools themselves than on how they are used. How can we harness its potential without compromising scientific rigor or critical thinking?

In this final presentation, Dr. Agell summarizes the main recommendations for integrating AI into research practice in a responsible way. A set of guidelines that remind us that technology can facilitate many tasks, but that oversight, judgment, and responsibility remain fundamentally human.

To understand the current impact of artificial intelligence on research, it is useful to take a step back. What advances have made it possible for algorithm-based tools to generate text, translate languages, or solve increasingly complex problems?

In this introductory presentation, Dr. Vilasís explains some of the key concepts behind language models and their rapid development over recent years.

What would happen if part of the research process that is currently carried out manually could be accelerated, or even automated? This possibility no longer seems far-fetched. Artificial intelligence tools are beginning to play a role in tasks ranging from literature reviews to hypothesis generation and data analysis.

Dr. Vilasís examines how AI can be integrated into the different stages of the research methodology, while also emphasizing that these tools do not replace the role of the researcher. Research remains a process grounded in judgment, dialogue, and human responsibility, even as the tools used to conduct it continue to evolve.

Just a few years ago, identifying the key articles in a field, tracking their citations, or understanding how a line of research had evolved required hours of reading and analysis. Today, new tools have emerged that promise to streamline much of this process and help researchers navigate an ever-growing volume of information.

In this session, Dr. Vilasís presents some of the platforms most widely used by the scientific community and explores how they can contribute to literature analysis, the formulation of research questions, and the identification of new connections between ideas. A practical overview of a constantly evolving ecosystem of research tools.

Artificial intelligence can save time, suggest ideas, and automate many research tasks. But what happens when we begin to rely on it too heavily? Where is the line between making use of a tool and delegating to it tasks that should remain the responsibility of researchers?

In this session, Dr. Vilasís reflects on some of the risks associated with the use of AI in research: the erosion of critical thinking, the tendency to reproduce the same solutions, the pressure to increase productivity, and inequalities in access to these technologies. A realistic perspective that reminds us that, no matter how advanced the tools become, curiosity, judgment, and creativity remain human responsibilities.

Artificial intelligence is transforming scientific research, but this change does not occur in a vacuum. The opportunities offered by these technologies are accompanied by new challenges related to regulation, data protection, and responsibility in their use.

In this final presentation, Dr. Vilasís focuses on Europe's role in this transformation and reviews some of the initiatives aimed at fostering innovative research while upholding ethical and legal safeguards. A look at the framework that should guide the development of artificial intelligence in the years ahead.