BEGIN:VCALENDAR
PRODID:-//Grails iCalendar plugin//NONSGML Grails iCalendar plugin//EN
VERSION:2.0
CALSCALE:GREGORIAN
METHOD:PUBLISH
BEGIN:VEVENT
DTSTAMP:20260522T153050Z
DTSTART;TZID=Australia/Melbourne:20260527T123000
DTEND;TZID=Australia/Melbourne:20260527T140000
SUMMARY: Algorithmic Recommendation and Changes in Musical Taste
UID:20260604T121011Z-iCalPlugin-Grails@philevents-web-6b96c54f56-bljdq
TZID:Australia/Melbourne
LOCATION:La Trobe University\, Bundoora\, Melbourne\, Australia\, 3086
DESCRIPTION:<p><strong>Online attendance:&nbsp\;</strong>if you want to join the talk online please email Yuri Cath at y.cath@latrobe.edu.au to ask for the zoom link.<strong><br></strong> <strong></strong></p>\n<p><strong><br></strong></p>\n<p><strong>Abstract:</strong> <strong><br></strong><br>Suppose a listener---let&rsquo\;s call him Jack---is an avid music fan\, and regularly seeks out recommendations as to new music to listen to. On the basis of a recommendation of some kind\, Jack encounters a piece of music\, M. M is deemed highly valuable by fans of the genre to which it belongs. But M is outside Jack&rsquo\;s comfort zone: it doesn&rsquo\;t immediately appeal to him. What are the chances that Jack's encounter with M will lead to a change in his musical taste? &nbsp\; In this talk\, I argue that the answer to this question depends in part on the <em>mode of recommendation </em>by means of which Jack has encountered M.Specifically\, I will consider the following two modes of recommendation:</p>\n<ul>\n<li>Case 1: Jack is recommended M by a radio DJ whose specialist music show he regularly listens to (a dominant mode of music recommendation pre-streaming)</li>\n<li>Case 2: Jack is recommended M by his Discover Weekly playlist on Spotify\, which he regularly listens to (a dominant mode of music recommendation in the streaming age)</li>\n</ul>\n<p>I will argue that the chances are higher in Case 1 (compared to Case 2) that Jack's encounter with M will lead to a change in his musical taste. This is because Jack has a greater chance of eventually having an <em>aesthetic experience </em>of M in Case 1 than he is in Case 2. The different likelihoods here\, I will claim\, owe in large part to the intersubjective features that Case 1 has\, but Case 2 lacks. &nbsp\; Now\, people today tend to rely far more on Spotify's recommender system to seek out musical recommendations than they do on radio DJs. It is therefore plausible that the average music listener has fewer real chances of having her musical tastes changed today than she used to (or would have done) in the heyday of specialist radio shows. In the final part of the talk\, I will explore whether this is in fact a bad thing\, and if so\, why.&nbsp\; &nbsp\;</p>
ORGANIZER;CN=Yuri Cath:
METHOD:PUBLISH
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