The Hazards and Benefits of Condescension in Social Learning
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , , , , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2023
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866916128884785152 |
|---|---|
| author | Arieli, Itai Babichenko, Yakov Müller, Stephan Pourbabaee, Farzad Tamuz, Omer |
| author_facet | Arieli, Itai Babichenko, Yakov Müller, Stephan Pourbabaee, Farzad Tamuz, Omer |
| contents | In a misspecified social learning setting, agents are condescending if they perceive their peers as having private information that is of lower quality than it is in reality. Applying this to a standard sequential model, we show that outcomes improve when agents are mildly condescending. In contrast, too much condescension leads to worse outcomes, as does anti-condescension. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2301_11237 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | The Hazards and Benefits of Condescension in Social Learning Arieli, Itai Babichenko, Yakov Müller, Stephan Pourbabaee, Farzad Tamuz, Omer Theoretical Economics Computer Science and Game Theory In a misspecified social learning setting, agents are condescending if they perceive their peers as having private information that is of lower quality than it is in reality. Applying this to a standard sequential model, we show that outcomes improve when agents are mildly condescending. In contrast, too much condescension leads to worse outcomes, as does anti-condescension. |
| title | The Hazards and Benefits of Condescension in Social Learning |
| topic | Theoretical Economics Computer Science and Game Theory |
| url | https://arxiv.org/abs/2301.11237 |