New technologies in Data Science and Artificial Intelligence (AI) are providing unprecedented access to cultural heritage, creating new cultural experiences, offering new ways to respond to key research questions in arts, languages, and cultures, and redefining the media and cultural and creative industries landscape. This highly interdisciplinary area opens up a number of exciting possibilities for research, teaching, knowledge exchange, and business engagement.
This internal event highlighted and mapped out expertise, strengths and possible directions and areas of future development on AI in arts, languages, culture, and heritage at the University of Manchester. Researchers were brought together from across the University of Manchester’s Digital Futures network to spotlight their research in these areas.
Welcome and Context: Dr Kostas Arvanitis, Digital Futures Creative and Heritage Lead
AI Trends, Directions and UoM Strengths: Professor Sophia Ananiadou, Deputy Director of the Institute for Data Science and AI
AURA MACHINE: Machine Learning & Musique Concrete: Vicky Clarke, Artist in Residence, NOVARS, European Art-Science-Technology Network for Digital Creativity
How can concrete materials project future sonic realities? As artist in residence with NOVARS, Vicky is exploring this question working with machine learning and musique concrete techniques for sound generation. In this talk Vicky will share insights into the process of building her concrete music training dataset, composing with AI and creating a live performance combining soundsculpture, electronics and machine learning.
Sad Dog Eating: Composition strategies, hybridisation and distributed creativity with Machine Learning: Zakiya Leeming, Doctoral Composer at the Centre for Practice and Research in Science and Music (PRiSM), Royal Northern College of Music (RNCM)
In this presentation I will discuss the creation of the Audio Visual composition ‘Sad Dog Eating’ - from dataset design and collection, through to the creative processes made possible by the integration of Machine Learning, including iterative composition cycles and hybrid human/machine performance outcomes.
Classifying Biometric Data for Novel Musical Expression within Composition: Chris Rhodes, PhD Candidate in Music Composition at NOVARS Research Centre
Commercial wearable technologies released in the last few years, providing novel biometric information, have changed the way we interact with computers. This biometric information is important for music practice and research because it allows us to interact with and control computers through physical musical behaviours. This talk navigates my doctoral research investigating how biometric information can be used with machine learning and AI towards immersive musical media.
Discovering Novel Pathways through Collections: A Museum Recommender System: Lukas Noehrer, PhD student and Co-Organiser of the Alan Turing Institute AI&Arts Group
Museums contain an abundance of information and knowledge, which are - with the broad roll-out of digitisation projects and the adoption of electronic storage systems - available to be used for computationally intensive methods, such as AI and machine learning. However, to meaningfully use such vast amounts of data as a vital source of public, professional, and scholarly engagement requires the creation of systems that facilitate interaction. Recommender engines can personalise information tailored to the individual user based on previous interactions and personal interest, and can therefore offer a possible solution to navigate collections through novel pathways and help to discover new knowledge within them.
Experimenting with AI in the Library: Pete Morris, Software Developer at The University of Manchester Library, and Ian Gifford, Head of Digital Development, John Rylands Library
In this presentation we’ll talk about some of the areas in which we’ve started to play with AI in the library, including enhancing our live digital dashboards to provide recommending reading items and providing fun ways to interact with our digital collections. We’ll also discuss ideas for future uses of AI in the library.