Track Chair: Dr Marzia Mortati
Human-machine collaborations are a reality. Much of what we build entails the co-existence of human and non-human agents and implies (ab)using data as a new design material. This track calls for a collective exploration about the desirable future we might build making virtuous use of data and engaging with diverse forms of artificial intelligence.
Design research and practice are at an important crossroads. New technologies and the manipulation of data increasingly play a leading role in shaping our everyday lives. As societies and economies become more data-driven, new areas of research and practice are become critically important. These include algorithmic/computational creativity, use of data as a new design material, prototypes of mixed systems of human and artificial intelligence, and the study of the ethical and social biases embodied in algorithms. These matters are pushing researchers and practitioners to imagine new avenues for human-machine collaboration while challenging societal consequences.
Building on this, designers need to reconsider their traditional role as first interface between industry and people, as mediators and interpreters of societal needs, as facilitators of implementation processes and fountains of creativity. The new data available and the possibilities for wider (and more inclusive?) societal collaboration have accelerated the imagination of new scenarios where non-human agents complement human tasks and intelligence in uncharted ways.
A new systemic approach to designing these mixed systems of human and non-human collaboration needs to be developed. Here, several new factors should be considered: the socio-technical nature of the system, its dynamic essence that learns over time, the co-responsibility and co-accountability of human and non-human agents involved, but also the black-box nature of artificial intelligence potentially embodying pre-existing social biases. Further, applied to all the different areas of interest of design, these matters open relevant conversations on future capabilities and competences, evolutions in the design process, impacts on the traditional design innovation paradigm.
Design researchers and practitioners need to be cognizant of this upcoming reality and collectively reflect on their evolving role. They will need more than new competences; rather, a change in mindset is required, one that allows moving beyond the key legacies of the Bauhaus, linked for example to reaching near-perfect outputs and a focus on problem-solving. In addition, designers also need to be educated about how to use data as a new material, both as an input to enhance their creative process and a central element in the final output, be it products, services, interfaces or experiences.