Collegium Helveticum
Switzerland
fellow
Bruno Moreschi
2023-2024
Discipline(s)
Arts and arts studies
Theme(s)
Visual Arts
Fellowship dates
›
Biography
Bruno Moreschi (born 1982 in Brazil) is a visual artist, a filmmaker, and an academic researcher. His research focuses on the deconstruction of systems and the decoding of procedures and social practices in the fields of the arts, museums, visual culture, and technology. In recent years, he has moved on to artistic research in the field of machine learning, especially AI and computer vision and its training data. How are we teaching machines to “see” the world? What are we reinforcing and excluding? What are the human practices linked to AI that we are not paying due attention to? These are some of the questions that guide his projects today.
Bruno received his PhD in 2018 from the State University of Campinas, with an exchange at the University of Arts of Helsinki. He was also a postdoctoral fellow at the University of São Paulo. Bruno is a senior researcher at the Center for Arts, Design, and Social Research (CAD+SR) and a member of the project Decay without Mourning: Future Thinking Heritage Practices. His projects have been exhibited and supported by institutions such as ZKM, Van Abbemuseum, 33rd São Paulo Art Biennal, Cambridge University, and Bauhaus Fellowship.
Research Project
Acapulco: Seeing (through) Images from Large-Scale Vision Datasets
The rise of computer vision in society has gained prominence in recent years. Scholars often focus on the social impact of these algorithms, especially as they exacerbate injustices. However, these problems can only be understood—and avoided—if we look not only at the outputs of computer vision, but also at the inputs these machines were offered in the first place.
This emergence of computer vision coincides with the dissemination of so-called “Large Scale Vision Datasets,” short “LSVDs.” In these datasets, everything is intricate: millions of amateur images taken without consent from social media; low resolution files; all assembled through precarious labor carried out by thousands of micro-workers on remote platforms. Challenged by the opacity of such datasets, Bruno created a long-term methodological practice that aims at a deeper understanding of these images together with people directly or indirectly related to images, technology, and/or arts. The resulting material is invaluable for a more in-depth and less normative understanding of such images.
As an early-career fellow at the Collegium, Bruno’s intention is to make an experimental film that allows these training images to finally be seen. Academic outcomes (articles and attending conferences) will also form part of the results of this research.
Research Interests:
computer vision; data; large scale vision