Audience Intelligence
NPIF studentships in Artificial Intelligence and Data-Driven research
This research opportunity builds on i-DAT’s established history of digital practice-based research and its strengths in cultural computation, ludic data and playful experimentation with creative technology. The project will explore the application of Artificial Intelligence and Machine Learning to enhance audience experiences, increase engagement and inform a discourse around the measurement of cultural value.
The aim is to create playful synergies between audience behaviours, interactive media environments, physical objects (or things) and modern integrative, sub-symbolic, computational techniques. The intention is to couple new interactive ways of engaging with large audiences and then to use machine learning techniques to create new experiences and at the same time generate new insights on audience behaviour.
This research is embedded in a unique transdisciplinary collaboration between software engineers, interaction designers, artists, cultural institutions and a highly active participation with audiences. The methods used will necessarily require a systematic relationship between digital practice, provocative prototyping and draw on established creative technologies production methodologies. This incorporates a reciprocal and participatory process whereby the measurement of audience engagement feeds into the audience experience and the creative events which are generating them. This will require, for instance, the construction of networked devices incorporating Machine Learning algorithms to engage, enhance and measure crowd interactions.
The research builds on i-DAT’s open infrastructure for ‘harvesting’ and visualising data through the incorporation of modern integrative, sub-symbolic, computational techniques which apply Artificial Intelligence and Machine Learning to augment, evaluate and increase public engagement of cultural experiences. This research has produced high impact events at the significant public venues (Tate Modern, Society for Arts and Technology (Montreal)), informed innovative cultural value metrics (Artory, British Arts Festival Association, Culture Counts and the AHRC Cultural Value Project), supported City Council open data initiatives (Plymouth City Council DataPlay and Edinburgh City Scape) and impacted on educational policy (Plymouth Creative School). This has led to further applications of this research through ERDF funding (Impact Lab) and HEFCE funded South West Creative Technology Network.
For an informal discussion about the studentship, please contact M.Phillips@plymouth.ac.uk
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