02012nas a2200241   4500000000100000008004100001653002800042653002000070653001300090653002800103653000900131653001100140653001600151653001500167653002500182100001600207700002100223700001400244245011400258856007100372520130200443022002501745                                       d10aArtificial intelligence10aCOVERT RESEARCH10aheritage10aIrish traditional music10aWORK10aethics10aethnography10aInnovation10aresearch methodology1 aElin Kanhov1 aAnna-Kaisa Kaila1 aBob Sturm00aInnovation, data colonialism and ethics: critical reflections on the impacts of AI on Irish traditional music  uhttps://www.tandfonline.com/doi/full/10.1080/09298215.2024.24423593 aBy definition, traditional music is in a constant state of friction with innovation, exemplified by resistance to  outside  influences such as different instruments, different ways of learning, and forces of commercialisation. An emerging external influence is artificial intelligence (AI), which is now capable of synthesising music collections at scales dwarfing those crafted by people and communities. In this paper, we examine the impact of research and development of AI on Irish traditional music through case studies of two generative AI systems: folk-rnn and Suno. How can researchers and engineers (academic or industrial) who develop and apply AI to specific practices of music make meaningful and non-harmful contributions to those practices? To answer this question, we critically reflect on the tensions that arise between tradition and innovation, how Irish traditional music becomes subject to data colonialism, and the interdisciplinary challenges of ethically engaging as researchers with a traditional music community. We ask what perspectives are needed to balance the interests of academic research and value systems in traditional music communities, and provide three ways forward for computer science to deepen the considerations of their impacts on communities of practice.  a0929-8215, 1744-5027