Ai explainability 360: An extensible toolkit for understanding data and machine learning models
- Vijay Arya
- Rachel Bellamy
- et al.
- 2020
- JMLR
Publications
78 results for Rachel Bellamy
Introduction to explainable AI
- Q. Vera Liao
- Moninder Singh
- et al.
- 2020
- CHI EA 2020
Introduction to AI fairness
- Yunfeng Zhang
- Rachel Bellamy
- et al.
- 2020
- CHI EA 2020
Joint optimization of AI fairness and utility: A human-centered approach
- Yunfeng Zhang
- Rachel Bellamy
- et al.
- 2020
- AIES 2020
Effect of confidence and explanation on accuracy and trust calibration in AI-assisted decision making
- Yunfeng Zhang
- Q. Vera Liao
- et al.
- 2020
- FAccT 2020
AI Explainability 360 Toolkit
- Vijay Arya
- Rachel Bellamy
- et al.
- 2021
- CODS-COMAD 2021
AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias
- Rachel Bellamy
- Aleksandra Mojsilovic
- et al.
- 2019
- IBM J. Res. Dev
FactSheets: Increasing trust in AI services through supplier's declarations of conformity
- Matthew Arnold
- David Piorkowski
- et al.
- 2019
- IBM J. Res. Dev
Think Your Artificial Intelligence Software Is Fair? Think Again
- Rachel Bellamy
- Kuntal Dey
- et al.
- 2019
- IEEE Software
Exploring rural community practices in HIV management for the design of technology for hypertensive patients living with HIV
- Erick Oduor
- Carolyn Pang
- et al.
- 2019
- DIS 2019