Impact of Legal Requirements on Explainability in Machine Learning
July 10, 2020 ยท Declared Dead ยท ๐ International Conference on Machine Learning
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Adrien Bibal, Michael Lognoul, Alexandre de Streel, Benoรฎt Frรฉnay
arXiv ID
2007.05479
Category
cs.AI: Artificial Intelligence
Cross-listed
cs.CY,
cs.LG
Citations
10
Venue
International Conference on Machine Learning
Last Checked
4 months ago
Abstract
The requirements on explainability imposed by European laws and their implications for machine learning (ML) models are not always clear. In that perspective, our research analyzes explanation obligations imposed for private and public decision-making, and how they can be implemented by machine learning techniques.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
๐ Similar Papers
In the same crypt โ Artificial Intelligence
๐
๐
The Cartographer
R.I.P.
๐ป
Ghosted
Explanation in Artificial Intelligence: Insights from the Social Sciences
R.I.P.
๐ป
Ghosted
Federated Machine Learning: Concept and Applications
R.I.P.
๐ป
Ghosted
Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR
R.I.P.
๐ป
Ghosted
DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks
R.I.P.
๐ป
Ghosted
Rainbow: Combining Improvements in Deep Reinforcement Learning
Died the same way โ ๐ป Ghosted
R.I.P.
๐ป
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
๐ป
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
๐ป
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
๐ป
Ghosted