Ethical and Responsible AI Music Making Workshop 17 July 2024

As part of our MusicRAI project we would like to invite you to take part in a one-day workshop on Responsible Music AI with a focus on bias in AI music generation systems.

The event will be hosted on 17th July 2024 at the Creative Computing Institute, University of the Arts London, Holborn, London. There will be an opportunity to join parts of the workshop online.

Workshop Overview

Many AI Models depend on large datasets and so lack an equitable representation of musical diversity. The rising popularity of tools using such models leads to further marginalisation of musical styles for which big data sets simply do not exist or are very hard to source.

We will bring together an interdisciplinary community of musicians, academics, and stakeholders to collaboratively identify the potential and challenges for using low-resource models and small datasets in musical practice.

The workshop will consist of publicly streamed discussion panels, presentations of participants’ work, and brainstorming sessions on the future of AI and marginalised music. The event will be followed by an evening reception featuring live performances.

In the morning sessions we will focus on sharing and identifying current practices and challenges for AI music making with small datasets. The afternoon we will be dedicated to exploring opportunities and practical solutions to using small and marginalised datasets of music and other audio with AI. This will form the start of an international network and roadmap for a new ecosystem that we will build to rapidly open small music datasets and low-resource AI approaches to more wider use in music making and analysis.

Registration

Please register to the workshop through Eventbrite here: Register

We encourage you to present your music making practice and AI work at the workshop in a format of your choice (short presentation, demo, live performance). You will be able to indicate your willingness to present during registration.

Provisional Agenda

Please note that this is a provisional agenda subject to change. The final agenda will be confirmed closer to the workshop date.

Weds 17th July 2024
10:00 AM - 10:10 AM Opening Remarks
10:10 AM - 10:40 AM Case Study Presentations
10:40 AM - 11:45 AM Brainstorming and discussion summary
Understanding features of marginalised music genres and datasets
11:45 AM - 12:00 PM Break
12:00 PM - 13:00 PM Panel Discussion (hybrid)
Challenges and Opportunities for Music Creation
Panelists:
  • François Pachet (Founder)
  • Rebecca Fiebrink (University of the Arts London)
  • Nuno Correia (Tallinn University)
  • Phoenix Perry (University of the Arts London)
Moderator:
  • Nick Bryan-Kinns (University of the Arts London)
1:00 PM - 2:00 PM Lunch
2:00 PM - 2:30 PM Case Study Presentations
2:30 PM - 3:45 PM Brainstorming and discussion summary
Identifying opportunities of small data approaches in music making
3:45 PM - 4:00 PM Break
4:00 PM - 5:00 PM Panel Discussion (hybrid)
The Future of Music Creation
Panelists:
  • Paul McCabe (Roland and AI For Music)
  • Hazel Savage (SoundCloud and Musiio)
  • Daisy Rosenblum (University of British Columbia)
  • CJ Carr (Dadabots)
Moderator:
  • Nick Bryan-Kinns (University of the Arts London)
5:00 PM - 8:00 PM
5:30 PM - 7:30 PM
Reception
Live performances:
  • CJ Carr (Dadabots)
  • Moisés Horta Valenzuela (hexorcismos)
  • Gabriel Vigliensoni

Contact Information

For any inquiries or further information, please contact:
Anna Wszeborowska a.wszeborowska@arts.ac.uk
Prof. Nick Bryan-Kinns n.bryankinns@arts.ac.uk

We look forward to your participation!

Funded by Responsible Artificial Intelligence (RAI) UK International Partnerships (UKRI EPSRC grant reference EP/Y009800/1)


About the MusicRAI Research Project

This 12 month project "Responsible AI international community to reduce bias in AI music generation and analysis" will build an international community to address Responsible AI (RAI) challenges of bias in AI music generation and analysis.

The aim of the project is to explore ways to tackle current over-reliance on huge training datasets for deep learning leads to AI models biased towards Western classical and pop music and marginalises other music genres. We will bring together an international and interdisciplinary team of researchers, musicians, and industry experts to make available AI tools, expertise, and datasets which improve access to marginalised music genres. This will directly benefit musicians and audiences engaging with a wider range of musical genres and benefits creative industries by offering new forms of music consumption.

Team

Lead: Prof. Nick Bryan-Kinns (University of the Arts London, UK; UAL)
Prof. Rebecca Fiebrink (UAL)
Dr. Phoenix Perry (UAL)
Prof. Zijin Li (Central Conservatory of Music, China; CCoM)
Dr. Nuno Correia (Tallinn University, Estonia; TU)
Dr. Alex Lerch (Georgia Tech, USA; GT)
Prof. Sid Fels (University of British Columbia, Canada; UBC)
Dr. Gabriel Vigliensoni (Concordia University, Canada; CU)
Dr. Andrei Coronel and Dr. Raphael Alampay (Ateneo de Manila University, Philippines; AdMU)
Prof. Rikard Lindell (Dalarna University, Sweden; DU)

Partners

Music Hackspace (UK)
DAACI (UK)
Steinberg (Germany)
Bela (UK)

Objectives

Contact

To get involved please contact Prof. Nick Bryan-Kinns n.bryankinns@arts.ac.uk

Funding

Funded by Responsible Artificial Intelligence (RAI) UK International Partnerships (UKRI EPSRC grant reference EP/Y009800/1)


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