Abstract:

With the current advances in information technology and with the proliferation of smart supports, the current trend towards the delegation of graphic tasks to automated systems is bound to further increase. This tendency has a very relevant impact on graphic design education, moving its focus less towards technical skills that will end up being automated, and more toward skill related to the conceptualization of design tasks in algorithmic terms.

While this rule-based nature of communication design has always been implicit in its pedagogy and in its practice, there is now the urgency to propose an approach to design highlighting its computational dimension in terms of a process that produces, and has always produced, “design programs”. Applying the experiences led by the Ulm School of Design to the current technological context, Communication Design curricula must provide, alongside the synthetic and abductive skills that characterize design thinking, the skills related to modeling, abstraction, and decomposition that allow for its expression in terms of rules that guide the representation and translation of contents, with the necessary level of formalism to allow the development of automatic and autonomous applications.

The advantages of mixing cognitive models, introducing forms of computational thinking to design are multi-dimensional: on the one side, the conversion from manual processes to algorithmic ones requires a formalization step that has a positive influence in the explicitation of the typically implicit cognitive processes that are involved in design practice. On the other, the ability to critically recognize the algorithms that, during the design process, are making decisions on one’s behalf, promotes a new awareness to some common design choices that are very much influenced by the underlying technology, and can free the designer from some “default” software settings that are never questioned, eventually making the design landscape less constrained and more expressive.

While the advantages are relevant, the introduction of computational thinking in the design practice has its risks: the power of automation leads to the tendency to reduce every problem to a computational problem, and the synthetic, abductive and transformative process of design thinking risk being replaced and not augmented by the abstract modeling capabilities of computational thinking. Secondly, the necessarily imperfect process of abstraction, may lead the designer to disregard specific edge cases that are difficult to model, or to reduce the complexity reality in order to account for them more easily.

Keywords:

Computational thinking, design thinking, communication design, graphic design, digital design.