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As researchers from diverse scientific fields, we recognize the limitations of research when it is confined to techno-centric models. In response, we adopt an interdisciplinary approach to AI (from the humanities and social sciences to computer science and engineering), aiming to study AI in a way that brings to light the social, cultural, ideological, economic, and political frameworks embedded in new technologies and how they shape everyday life.

At the core of our activities is the dissemination of knowledge and raising public awareness through communication channels that highlight the significant scientific research on AI being conducted across computer science, engineering, as well as the social sciences and the humanities. Central to this effort is dialogue, which we consider a key tool for understanding and co-shaping AI. We aim to empower individuals, collectives, and institutions with the necessary critical thinking skills and digital literacy by intervening in the public sphere, organizing workshops, and promoting science outreach activities in society.

Our goal is for AI to be used as a tool with full awareness of its risks and socio-environmental impacts. We advocate for informed, contextualized, critical, and active engagement with AI, fostering a connection between people and “visible” machines, and understanding our collective participation in these technologies as a society.

The complex questions posed by AI technologies are not purely technical. Thus, our Center’s vision is not only based on the technical implementation and improvement of AI but also on highlighting the complex relationships each machine learning technology has with humans and society.

Our mission is to cultivate a democratic dialogue about technology, ensuring that any transformations serve the interests of a just and equitable society. In this effort, we aim to offer two things:

We envision a different framework of human–machine relations, in which machines are “visible” to society. We explore the conditions under which such artifacts can be realized. Finally, we investigate the social processes that can contribute to lifting the internal opacity of machines and freeing them from the monopolistic control of large corporations and patent-based intellectual property.