A Case of Genetic Algorithms Supporting the Design of Collaboratively Shaped, Genetically Evolving, Products

Abstract

Recently the role of makerspaces has been studied as a mean to promote citizen-driven innovation in the smart cities. In this paper we discuss the possibility of exploiting Genetic Algorithms, namely algorithms that mimic the mechanisms behind the evolution of live beings, for the implementation of a simple tool for the collaborative and participatory design of public art products that assume no technical background of the users thus better supporting the democratization of the design process. This concept has been initially tested in the context of artisan products during the Maker-Faire festival, likely the most celebrated event in makerspaces, with the main purpose of understanding the ability of the proposed process of actually engage citizens. This experiment has actively involved 369 participants, a number not negligible in experiments requiring the physical participation of users. Results from this trial suggest that this process actually leads, by evolution generation after generation, to the selection of a population of three dimensional products that are better appreciated by end users in average. Although the initial conclusions of this study, on the evolution of the products over the generations, cannot be generalized, the study does provide some initial valid feedback, as first steps of a discussion on the use of generative algorithms in art products . The generative algorithms creative process, as described further in this paper, can be seen as the basis for generative collective art in the context of smart cities, while these ideas have been initially tested in the area of 3d printing for product design.