

Nick Seaver, "Computing Taste: Algorithms and the Makers of Music Recommendation" (U Chicago Press, 2022)
6 snips Feb 2, 2023
Chapters
Transcript
Episode notes
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Introduction
00:00 • 4min
Are You the Type Who Really Values Music Technology or Discovering Music That I Haven't Heard of Before?
03:55 • 2min
Is There a Target Audience for Your Book?
05:38 • 2min
Anthropology - The Concept of Myth
07:41 • 5min
How to Do Ethnography of Powerful People
13:10 • 1min
What Is an Algorithm?
14:33 • 3min
The Human Element in These Systems Is Really Important
17:38 • 3min
What's the Point of Music Recommender Systems?
21:07 • 4min
What Is Going on With Taste?
25:18 • 2min
I Have No Idea, Right?
26:58 • 5min
What Is the Role of Technology on Taste?
32:02 • 5min
The Singularity of the Algorithm
36:50 • 2min
Why Do You Need a Music Recommender?
38:41 • 6min
The Myth of Information Overload
44:22 • 3min
How Do I Know if a Recommended System Works?
47:03 • 6min
The Pairing of Animal Trapping to a Recommendation System
52:40 • 4min
Using a Specialization Metaphor in Machine Learning
56:51 • 6min
Parson Recommendation - The Humanization of the Music Streaming System
01:02:42 • 5min
Is There Wildness in Music?
01:08:06 • 4min
What's Your Favorite Part of the Book?
01:12:21 • 3min
Is There a Future for Machine Learning?
01:15:20 • 3min
The Life of Attention in Machine Learning
01:17:56 • 3min
Is It a Key Symbol of Attention?
01:21:24 • 3min