Final Synthesis Design Studio 18

A.Y. 2022–2023

Course website

Syllabus (Politecnico di Milano)

Professors

Michele Mauri

Politecnico di Milano

Angeles Briones

Prof. in Visual Communication

Simone Vantini

Prof. in Mathematics

Politecnico di Milano - Department of Matematics

Gabriele Colombo

Politecnico di Milano

Salvatore Zingale

Prof. in Semiotics

Politecnico di Milano

Final Synthesis Design Studio 18 2022–2023

The 2022/2023 edition of the Final Synthesis Design Studio focused on the role of data, algorithms, and digital platforms in shaping how we understand and represent complex phenomena. Students explored the processes through which data is collected, analyzed, and transformed into visual representations, critically examining the choices, limitations, and biases involved in these processes. The climate crisis provided a common ground for investigating how digital platforms mediate information and influence public understanding of environmental issues.

The course followed a three-phase approach. Students first explored statistical and machine learning algorithms, designing visual explanations of their functioning, strengths, and limitations. They then applied digital methods to investigate how the climate crisis is represented and discussed online, producing printed research reports on topics such as greenwashing, reforestation, fast fashion, climate activism, and AI-generated imagery. In the final phase, students transformed their findings into interactive digital narratives, using archives, collections, and other forms of data republishing to engage specific audiences and encourage critical reflection.

Throughout the course, visualization was approached not only as a means of representing data, but also as a form of mediation that shapes knowledge, constructs narratives, and contributes to the formation of different publics.

Student outputs

The course produced 21 group works and 47 individual assignments, including printed posters, books, interactive websites, videos, and physical installations. The projects are documented on the 2022/2023 course website, organized into three phases:

  1. Visual Explanations: Printed posters explaining statistical and machine learning algorithms, their underlying principles, strengths, and limitations.
  2. Data as Artefact: Printed research reports using digital methods to investigate how online platforms represent and mediate different aspects of the climate crisis.
  3. Data Publics: Interactive websites republishing research findings through digital narratives, archives, and collections to engage audiences and encourage critical reflection.