In the era of artificial intelligence, designers have to reconsider typography and design within a broader ecosystem of designed experiences that exist, not only on screens, but beyond, in augmented, virtual and mixed reality environments. Such new forms may have the capacity to be intelligent, generative and responsive to a constant stream of audience and contextual data. If typography and design were the expressive design of words for maximum readability in print, what future forms of typography will emerge in an era of interactive social multimedia? Thus, the aim of the research is to investigate how artificial intelligence can be incorporated into design processes to develop, discover and evaluate new design opportunities in the era of smart and intelligent applications. This is the creative challenge presented by aityde.

My name is Kushtrim Hamzaj, I am an interaction designer specialising in UX Design, UI Design, Typography, and design thinking. Currently, I am doing my PhD in interactive typography and machine learning methods “responsive type: exploring variable fonts in the era of machine learning (ML)” at the Bauhaus-Universität Weimar. My supervisors are Prof. Markus Weisbeck and Prof. Dr. Christof Windgätter. I am also part of the research project "Prof:inSicht" at the Munich University of Applied Sciences, where I am supporting the team on field of user experience design and programming.

In my work, I aim for researching, analysing, proposing, prototyping and teaching new processes and systems to influence the overall aesthetic, functionality, and user experience of visual communication. In my PhD project, I am researching the intersection of machine learning (ML) and variable fonts (VL) to influence the overall evolution of user interfaces from a non-intelligent design to a smart context-aware entity. To this end, I integrate pre-trained machine learning libraries such as faceapi.js and bodypose.js together with the common web technologies such as p5.js, processing, Javascript and APIs. I firmly believe that this groundbreaking fusion of ML and VF has the potential to revolutionize human-machine interaction across diverse domains (e.g., automotive, healthcare, education, and beyond).