Publication: First Issue Journal "AI Music Studies" & Call for thematic issue proposals
Music and Data is a peer-reviewed, annual, thematic journal that brings music and sound studies into dialogue with data science to examine how new technologies shape music cultures across global contexts, past and present.
The first issue, "AI Music Studies," guest-edited by Bob L. T. Sturm, Elin Kanhov, André Holzapfel, Thomas Hodgson, and Rujing Stacy Huang, gathers seven articles developed from the First International Conference in AI Music Studies (Stockholm, 2024), spanning musicology, music theory, MIR, STS, and the political economy of platforms.
Call for thematic issue proposals. We invite proposals for future issues that engage critically with algorithms, platforms, AI, metadata, archives, and infrastructures; address power, labor, inequality, and data justice; center global and transnational perspectives, especially from the Global South; or experiment with collaborative, practice-based, or multimodal methods.
Proposals should include a provisional title and 1–2 page rationale, a list of proposed contributors (with abstracts where possible), short guest-editor biographies, and an indicative timeline. We welcome early-career and senior scholars, and encourage interdisciplinary editorial teams.
Proposals and enquiries: mad[at]ucpress[dot]edu by December 1 2026.