Ethical Implications of Music Computing

Our project focuses on such ethical issues in the context of music computing, in particular which issues may arise from the use of artificial intelligence when we apply it, for instance, to automatic music composition, recommendation, production, or copyright control.

Value chain that illustrates the remoteness between research in Music Information Retrieval and user communities

Technology is not value-neutral but is influenced by design choices, and so has unintended and ethically relevant implications. These can be invisible unless one considers how the technology relates to wider society. In the recent years, the aspects of transparency, accountability, and fairness have been discussed in relation to artificial intelligence. For instance, it is apparent that search engines incorporate biases that result in excluding particular content, or that automatic profiling may result in discrimination of particular groups for instance in crime prevention or credit allocation. It is an ethical obligation of research to investigate such issues that emerge from the use of artificial intelligence.

Our project focuses on such ethical issues in the context of music computing, in particular which issues may arise from the use of artificial intelligence when we apply it, for instance, to automatic music composition, recommendation, production, or copyright control. We develop a theoretical basis that can inform discussions of ethics in music computing. We call attention to biases that are introduced by algorithms and data used in music computing technology, cultural issues related to copyright, and ethical problems in music computing as a scientific practice. We suggest tentative ethical guidelines for developers, and call for addressing key ethical problems, especially those related to forms of bias and the remoteness of the technology development from end users.

Avoiding such ethical problems is of major importance to safeguard the diversity of musical practice across cultures. Awareness of biases and collaboration with user communities are therefore important to promote social sustainability in terms of diversity of cultural expression and social cohesion within cultural groups.

TEAM

Funding

  • KTH MID Faculty Funding

Durations of The Project: 2016-2020

Publications

[1]
A. Holzapfel, B. Sturm och M. Coeckelbergh, "Ethical Dimensions of Music Information Retrieval Technology," Transactions of the International Society for Music Information Retrieval, vol. 1, no. 1, s. 44-55, 2018.
[2]
R. de Valk et al., "MIRchiving: Challenges and opportunities of connecting MIR research and digital music archives," i DLfM '17 Proceedings of the 4th International Workshop on Digital Libraries for Musicology, 2017.