The following extracts are taken from my final proposal that sets the path for my practical and theoretical research. I’m really happy with the direction I’ve taken and feel it clearly identifies the idea of non-linearity within digitally driven narratives. There is a tension between the recent development in Machine Learning – data driven control – and that of previous experiments in database driven narratives such as Soft Cinema. If you would like to read the full text, it can be viewed here.
Field of Study:
Within Interaction Design this project will work with database driven narratives and the more recent break throughs in Machine Learning. I intend to use this research led project as a way to challenge narrative timelines that exist within digital formats. Although secondary to my major focus – the potential of database driven narratives – the psychology of live performance (such as VJing, and cinema) is an important consideration in relation to audience participation and enjoyment. The wider theories of Generative art – art created either wholly or partially by an autonomous system – touch upon many aspects of this project and therefore it is expected that this will be referred to across both the contextual and practical areas of the project.
There are plenty of possibilities for fun and entertaining interaction via a range of sensory inputs. This research project proposes to take these ideas and apply Machine Learning processes to engage the audience in co-authoured narratives that might include a series of tests combining a range of visual and audio content such as; audio/video shorts, VJ performance or game. The tests will mainly focus around storytelling through interactive technologies. Utilising software and hardware combined with the feedback loop from sensory inputs, for example; face detection, proximity sensors, audio input – it is hoped to transform a narrative experience from one of passive absorption to an active, anecdotal engagement where the act of viewing creates a co-authored narrative.