Presentation Open Access
Algorithmic Impact Assessment: Fairness, Robustness and Explainability in Automated Decision-Making
Koshiyama, Adriano; Engin, Zeynep
The workshop session focuses on the following topics:
- Introduction to AI & Machine Learning (Algorithms)
- Key Components of Algorithmic Impact Assessment
- Algorithmic Explainability
- Algorithmic Fairness
- Algorithmic Robustness
Files
(5.0 MB)
| Name | Size | |
|---|---|---|
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A - Algorithmic Impact Assessment - Adriano Koshiyama.pdf
md5:8cb0eb115d5a665657fbaefe1aad0454 |
4.0 MB | Download |
|
AI Assessment Canvas - Clean.pdf
md5:ddfda804b395d5ffd4d09b2a07b829f4 |
109.0 kB | Download |
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AI Assessment Canvas - Clean.png
md5:cc6f78c50b95fa28eac2151c8f54ba34 |
133.1 kB | Download |
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AI Assessment Canvas.pdf
md5:5816a86558b6d6c72dcefb5496028f1e |
204.8 kB | Download |
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AI Assessment Canvas.png
md5:c2c1d51c5b8f075422a05c262a724ccd |
185.8 kB | Download |
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Diversity, non-discrimination and fairness checklist.docx
md5:a0992a52ae05048798f498fe8dae474f |
16.9 kB | Download |
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Explainability checklist.docx
md5:b8dbb88ed44208d45cc46a9b048ee527 |
16.5 kB | Download |
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Fairness, Transparency and Robustness in Automated Decision Making - V0.docx
md5:73a93da3052259064db7f2873d2a344b |
338.3 kB | Download |
1,280
2,594
views
downloads
| All versions | This version | |
|---|---|---|
| Views | 1,280 | 852 |
| Downloads | 2,594 | 1,745 |
| Data volume | 4.8 GB | 3.4 GB |
| Unique views | 1,150 | 774 |
| Unique downloads | 1,977 | 1,384 |
Indexed in
- Publication date:
- June 8, 2019
- DOI:
-
- Keyword(s):
- algorithm impact assessment robustness fairness explainability artificial intelligence
- Meeting:
- Data for Policy 2019: Digital Trust and Personal Data (Data for Policy 2019) (DFP), London, 10-12 June 2019
- Communities:
- License (for files):
- Creative Commons Attribution 4.0 International