Name
Abstract | ||
|---|---|---|
Recommendations are meant to increase sales or ad revenue, since this is the first priority of those who pay for them. As recommender systems match their recommendations with inferred preferences, we should not be surprised if the algorithm optimises for lucrative preferences and thus co-produces the preferences they mine. In this talk I will explain how the GDPR will help to break through this vicious circle, by constraining how people may be targeted.
|
Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3298689.3346980 | Proceedings of the 13th ACM Conference on Recommender Systems |
Field | DocType | ISBN |
Recommender system,World Wide Web,Computer science,Artificial intelligence,Machine learning | Conference | 978-1-4503-6243-6 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mireille Hildebrandt | 1 | 13 | 2.76 |