This project is part of a postdoctoral Creative Engagement Research fellowship that aims to develop an iconographic, interactive, and symbolic design language for artificial intelligence and machine learning, and make the case for design in this field which is currently dominated by computer science and legal frameworks.
John Fass’s fellowship work positions practice based design research as a way of developing a set of strategies and tactics intended for the designers of digital products to make the workings of algorithmic intelligence more apparent to users.
The accumulation of enormous quantitative data sets, via digital social media and other systems, paired with recent developments in neural networks and increases in computing power has delivered unexpectedly rapid improvements in what artificial intelligence technologies have been able to achieve (Holmquist, 2017). This means the influence of algorithmic decision making and artificial intelligence on digital products, from social media to financial management, has increased significantly. As these systems start to pervade everyday life, they present a challenge to human understanding. We risk developing highly influential technologies of such complexity and opacity that they surpass our abilities to shape them into forces for the common good.
The consequences for culture and society are profound. Firstly, the ethical implication of personal data that is captured and used to train an algorithm, designed by a private corporation for unknown purposes involves an imbalance of power. Secondly, the invisibility and opacity of machine learning technologies means access to the means of production is limited to the few people trained and skilled in creating them. Finally, the conscious or automatic manipulation of flows of information via digital products has been shown to be a danger to democratic processes and information equity. Involving designers in the development of practices that will help understand and explain what is going on in the interfaces and interactions of digital products that depend on artificially intelligent systems means this research is explicitly participatory in nature. Participatory design research rooted in studio practices is a way of opening the inquiry to the people it is intended to benefit most directly. Design research has not paid detailed attention to this topic in this way although it has been covered in studies related to the ethics and politics of machine learning (de Bruin and Floridi, 2017, Mittelstadt et al, 2016) and in theoretical approaches to interaction design (van Allen and Marenko, 2016). The research will make a contribution to knowledge in the field of design research with respect to strategies and practices for designers of digital products to consider the wider social, moral and political implications of artificial technologies in their designs.