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Ethical Risk Analysis of the Use of AI in Music Production
KTH, School of Electrical Engineering and Computer Science (EECS).
2022 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

With the growing use of AI within new fields, the ethical problems that arise with AI have become a more prominent topic. Multiple ethical guidelines and frameworks have been proposed to aid companies and researchers to develop ethical products, but it is still lacking in execution. This project is a study into the ethical risks that are prevalent when AI is used for music production tools. The study was done by interviewing five different start-up companies about aspects of their company policies and products from an ethics point of view. The interviews were analysed, and six areas of interest were found. A final risk analysis was then done based on an existing ethical guideline, the Ethics Guidelines for Trustworthy AI by AI HLEG. Multiple risk areas were discovered, the largest ones being in connection to Diversity, Bias, Explainability, and Privacy. Another discovery was that multiple companies do not currently have an ethical framework, but that it was something that they were positive about implementing in the future.

Abstract [sv]

Med den växande användningen av AI inom nya områden har de etiska problem som uppstår med AI blivit ett stort diskussionsämne. Flera förslag på riktlinjer som företag och forskare kan använda för att utveckla etiska produkter har lagts fram, men de är sällan implementerade. Detta projekt är en studie av de etiska risker som förekommer vid användningen av AI för musikproduktionsverktyg. Studien gjordes genom att intervjua fem olika startups om deras företagspolicys och produkter utifrån en etisk synvinkel. Intervjuerna analyserades och sex intresseområden hittades. En slutgiltig riskanalys gjordes sedan utifrån en befintlig etisk riktlinje, Ethics Guidelines for Trustworthy AI av AI HLEG. Flera riskområden relaterade till Diversity, Bias, Explainability och Privacy upptäcktes. Ytterligare en upptäckt var att flera företag för närvarande inte använder ett etiskt ramverk, men att de var positiva till att implementera ett i framtiden.

Place, publisher, year, edition, pages
2022. , p. 21
Series
TRITA-EECS-EX ; 2022:736
Keywords [en]
Artificial Intelligence, AI Ethics, Music Informatics
Keywords [sv]
Artificiell intelligens, AI-etik, Musikinformatik
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:kth:diva-321589OAI: oai:DiVA.org:kth-321589DiVA, id: diva2:1711711
Supervisors
Examiners
Available from: 2023-01-03 Created: 2022-11-17 Last updated: 2023-01-03Bibliographically approved

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CiteExportLink to record
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Citation style
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Output format
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