ORES-Inspect: A technology probe for machine learning audits on enwiki
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , , , , , , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2024
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866916283883192320 |
|---|---|
| author | Levonian, Zachary Hagen, Lauren Li, Lu Lilleboe, Jada Wastvedt, Solvejg Halfaker, Aaron Terveen, Loren |
| author_facet | Levonian, Zachary Hagen, Lauren Li, Lu Lilleboe, Jada Wastvedt, Solvejg Halfaker, Aaron Terveen, Loren |
| contents | Auditing the machine learning (ML) models used on Wikipedia is important for ensuring that vandalism-detection processes remain fair and effective. However, conducting audits is challenging because stakeholders have diverse priorities and assembling evidence for a model's [in]efficacy is technically complex. We designed an interface to enable editors to learn about and audit the performance of the ORES edit quality model. ORES-Inspect is an open-source web tool and a provocative technology probe for researching how editors think about auditing the many ML models used on Wikipedia. We describe the design of ORES-Inspect and our plans for further research with this system. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_08453 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | ORES-Inspect: A technology probe for machine learning audits on enwiki Levonian, Zachary Hagen, Lauren Li, Lu Lilleboe, Jada Wastvedt, Solvejg Halfaker, Aaron Terveen, Loren Human-Computer Interaction K.4.2 Auditing the machine learning (ML) models used on Wikipedia is important for ensuring that vandalism-detection processes remain fair and effective. However, conducting audits is challenging because stakeholders have diverse priorities and assembling evidence for a model's [in]efficacy is technically complex. We designed an interface to enable editors to learn about and audit the performance of the ORES edit quality model. ORES-Inspect is an open-source web tool and a provocative technology probe for researching how editors think about auditing the many ML models used on Wikipedia. We describe the design of ORES-Inspect and our plans for further research with this system. |
| title | ORES-Inspect: A technology probe for machine learning audits on enwiki |
| topic | Human-Computer Interaction K.4.2 |
| url | https://arxiv.org/abs/2406.08453 |