Human creativity has been often aided and supported by artificial tools, spanning traditional tools such as ideation cards, pens, and paper, to computed and software. Tools for creativity are increasingly using artificial intelligence to not only support the creative process, but also to act upon the creation with a higher level of agency. This paper focuses on writing fiction as a creative activity and explores human-AI co-writing through a research product, which employs a natural language processing model, the Generative Pre-trained Transformer 3 (GPT-3), to assist the co-authoring of narrative fiction. We report on two progressive – not comparative – autoethnographic studies to attain our own creative practices in light of our engagement with the research product: (1) a co-writing activity initiated by basic textual prompts using basic elements of narrative and (2) a co-writing activity initiated by more advanced textual prompts using elements of narrative, including dialects and metaphors undertaken by one of the authors of this paper who has doctoral training in literature. In both studies, we quickly came up against the limitations of the system; then, we repositioned our goals and practices to maximize our chances of success. As a result, we discovered not only limitations but also hidden capabilities, which not only altered our creative practices and outcomes, but which began to change the ways we were relating to the AI as collaborator.  

Waking up in a world where everyone carries a miniature supercomputer, interaction designers find themselves in their forerunners dreams. Faced with the reality of planetary-scale we have to confront the task of articulating approaches responsive this accidental ubiquity of computation. This thesis attempts such a formulation by defining computation as a strange material, a plasticity shaped equally by its technical properties and the mode of production by which is its continuously re-produced. The definition is applied through a methodology of excursions — participatory explorations into two seemingly disparate sites of computation, connected in they ways they manifest a labor of care. First, we visit the social infrastructures that constitute the Linux kernel, examining strangle entanglements of programming and care in the world's largest design process. This is followed by a tour into the thorny lands of artificial intelligence, situated in the smart replies of LinkedIn. Here, we investigate the fluctuating border between the artificial and the human with participants performing AI, formulating new Turing tests in the process. These excursions afford an understanding of computation as fundamentally re-produced through interaction, a strange kind of affective work the understanding of which is crucial if we ambition to disarm the critical accidents of our present future.

We present a prototype of a system for machine learning (ML) powered interactive generative literature called Multiverse. The system employs a set of neural networks models to dynamically generate a literary space from an initial writing prompt provided by its user-reader. The user-reader is able to choose the model used to generate the text as a kind of interactive machine learning (IML). The research explores how interaction design and HCI researchers can engage directly with ML by leveraging the powerful, yet accessible, models afforded by new developments in the field. User-readers testing the prototype found the imperfect aesthetics of the ML-generated texts to be entertaining and engaging but struggled to conceptualize the generated work as a navigable interactive literary space.