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- All Subjects: artificial intelligence
- All Subjects: Spotify
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
- Member of: Theses and Dissertations
Music streaming services have affected the music industry from both a financial and legal standpoint. Their current business model affects stakeholders such as artists, users, and investors. These services have been scrutinized recently for their imperfect royalty distribution model. Covid-19 has made these discussions even more relevant as touring income has come to a halt for musicians and the live entertainment industry. <br/>Under the current per-stream model, it is becoming exceedingly hard for artists to make a living off of streams. This forces artists to tour heavily as well as cut corners to create what is essentially “disposable art”. Rapidly releasing multiple projects a year has become the norm for many modern artists. This paper will examine the licensing framework, royalty payout issues, and propose a solution.
The sudden turn to artificial intelligence has been widely supported because of the several proposed positive outcomes of using such technologies to support or replace humans. Automating tedious processes and removing potential human error is exciting for society, but some concerns must be addressed. This essay aims to understand how artificial intelligence can automate domains that likely significantly impact underprivileged and underrepresented groups. This essay will address the potentially devastating effects of algorithmic biases and AI’s contribution to perpetual economic inequality by surveying different domains, such as the justice system and the real estate industry. Without society broadly understanding the potential negative side effects on systems that matter, the rapid growth of artificial intelligence is a recipe for disaster. Everyone must become educated about AI’s current and potential implications before it is too late to stop its damaging effects.
Song Sift is an application built using Angular that allows users to filter and sort their song library to create specific playlists using the Spotify Web API. Utilizing the audio feature data that Spotify attaches to every song in their library, users can filter their downloaded Spotify songs based on four main attributes: (1) energy (how energetic a song sounds), (2) danceability (how danceable a song is), (3) valence (how happy a song sounds), and (4) loudness (average volume of a song). Once the user has created a playlist that fits their desired genre, he/she can easily export it to their Spotify account with the click of a button.