According to Brooks [2017. “The Big Problem with Self-driving Cars Is People”. IEEE Spectrum: Technology, Engineering, and Science News], artificial intelligence has had a variable track-record of usefulness in situations where context and environmental knowledge are responsible for shaping human interactions. In 2021, providing contextually aware training to supervised machine learning is still a non-trivial task for AI models that involve complex systems. In addition, knowledge held only across distributed members of a community, within culture, or tacitly within the wider environment of the ambient commons [McCullough 2013. Ambient Commons: Attention in the Age of Embodied Information. Cambridge, MA: MIT Press] evades consistent generalizable modelling – even in technical domains such as traffic flow management, atmospheric chemistry, or the prediction of election results. Yet it is precisely these interactions of context, community, culture and environment that also define how music can be created. The creative arts can themselves be thought of as a complex system. Assuming that creativity is non-generalizable, this paper assesses creative processes through a humanities-centric lens of machine learning and robotics, aiming to better understand relationships between context, environment and experimental system in artistic research. These relationships are now themselves significantly digitally mediated, requiring a change in academic discourse away from artefacts which need discrete research justification towards a more holistic, and often non-linear view of networks that require cultural situation. In doing so, issues of creative accountability [Field 2021. “Changing the Vocabulary of Creative Research: The Role of Networks, Risk, and Accountability in Transcending Technical Rationality.” In Sound Work: Composition as Critical Technical Practice, edited by J. Impett, 303–317.Orpheus Institute Series. Leuven: Leuven University Press] and the implications of substituting “creative question” for “research question” are examined within creative research. Early twentieth century ideas related to progressivism which have instrumentalized creative practice, particularly where technology forms part of art making, are challenged by re-thinking change through new models. The Three Horizons change model [Sharpe 2016. “Three Horizons: A Pathways Practice for Transformation.” Ecology and Society 21 (2): 47] originally intended to describe environmental ecosystems, is assessed as a practical tool for designing creative research.
|Journal||Interdisciplinary science reviews|
|Publication status||Published - 17 Mar 2022|
Bibliographical note© 2022 Institute of Materials, Minerals and Mining Published by Taylor & Francis on behalf of the Institute
- AI, Creativity Research