University of Twente Student Theses


Perception and Bias towards AI-Music

Zenieris, R. (2023) Perception and Bias towards AI-Music.

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Abstract:The advent of new information technology (IT) has brought about a profound transformation in the realm of music production and consumption. Notably, Artificial Intelligence (AI) has emerged as a significant catalyst in this process. AI's influence extends to various facets of music, including the completion of Schubert's unfinished symphony and the creation of original compositions by machines. Moreover, AI is even involved in the selection of our next musical preferences. It is evident that the impact of AI extends beyond music, encompassing other artistic domains such as painting. The awareness that certain artistic works are generated by AI systems has been found to alter people's perception. Consequently, it becomes crucial to explore the presence of bias in these contexts. The objective of this paper is to conduct an analysis of pertinent literature to ascertain the existence of bias but also the perspective of the audience towards AI-generated music. Additionally, we propose the implementation of two distinct surveys, one with disclosed artist identity and the other with undisclosed artist identity. Two musical compositions were meticulously chosen to serve as subjects for the conducted surveys. Notably, the AI generated song was deliberately selected to possess a heightened level of auditory appeal in accordance with the personal preference of the author. This deliberate choice was made with the intention of subsequently identifying and examining any potential bias that may arise during the survey analysis phase. Participants will be divided into two groups, each assigned to complete only one of the surveys. The aim of this approach is to confirm the presence of bias, if any, within the surveyed groups and collect the beliefs of the participants towards AI-generated music. The outcomes of this investigation hold significant potential in the scientific realm, as they can be compared with findings from different branches of the art world, thereby illuminating patterns regarding the perceptions of the audience.
Item Type:Essay (Bachelor)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:05 communication studies
Programme:Business & IT BSc (56066)
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