The Next Great YouTube: Improving Content ID to Foster Creativity, Cooperation, and Fair Compensation

By Benjamin Boroughf. 2014

13 citations recorded by the source corpus.

Subfields: AI Ethics, Fairness & Society

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In AI Ethics, Fairness & Society

1. Percy Liang
2. Dan Jurafsky
3. Mark A. Lemley
4. Tatsunori B. Hashimoto
5. Xuechen Li
6. Peter Henderson

Citations in the corpus

• Foundation Models and Fair Use (2023, background): “Similarly, YouTube’s content ID system, a large-scale filtering approach, has been criticized for not following fair use standards and being overaggressive in its filtering (Bartholomew, 2014; Boroughf, 2015).”