Reuben Binns

Artificial Intelligence · 2017–2020

A researcher in the Science corpus: 11 papers; trusts 116 researchers and is trusted by 39 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 132 citations into it; #12,276 of 35,345 by trust here, #5,424 by citations
• Safety, Robustness & Interpretability — 98 citations into it; #428 of 2,251 by trust here, #915 by citations
• Safety Research — 68 citations into it; #269 of 5,829 by trust here, #270 by citations
• Sociology and Political Science — 55 citations into it; #17,586 of 22,756 by trust here, #5,110 by citations
• AI Ethics, Fairness & Society — 48 citations into it
• Information Systems — 36 citations into it
• Political Science and International Relations — 19 citations into it; #349 of 4,701 by trust here, #876 by citations
• Communication — 15 citations into it; #3,458 of 3,460 by trust here, #2,267 by citations

Whom Reuben Binns trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Cynthia Dwork
2. Faisal Kamiran
3. Toon Calders
4. Moritz Hardt
5. Nicholas A. Diakopoulos
6. Richard S. Zemel
7. Richard J. Arneson
8. R. Huseby
9. Michael Veale
10. Marco Tulio Ribeiro

Who trusts Reuben Binns overall

1. Emilio Ferrara
2. Won Ik Cho
3. Shubham Sharma
4. Andreas Tsamados
5. Jessica Morley
6. David Leslie
7. Jiwon Kim
8. Vincent C. Müller
9. Josh Cowls
10. Nitin Kohli

Papers from Reuben Binns's perspective

Ordered by how strongly the researchers Reuben Binns trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. ImageNet: A large-scale hierarchical image database
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Learning Multiple Layers of Features from Tiny Images
9. Going deeper with convolutions
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Fairer machine learning in the real world: Mitigating discrimination without collecting sensitive data (2017) — 419 citations
• Fairness and Accountability Design Needs for Algorithmic Support in High-Stakes Public Sector Decision-Making (2018) — 500 citations
• Algorithms that remember: model inversion attacks and data protection law (2018) — 238 citations
• Human-Centered Approaches to Fair and Responsible AI (2020) — 58 citations
• Algorithmic content moderation: Technical and political challenges in the automation of platform governance (2020) — 855 citations
• Decentralized Privacy-Preserving Proximity Tracing (2020) — 366 citations
• On the apparent conflict between individual and group fairness (2019) — 385 citations
• 'It's Reducing a Human Being to a Percentage': Perceptions of Justice in Algorithmic Decisions (2018) — 779 citations
• Fairness in Machine Learning: Lessons from Political Philosophy (2017) — 1,041 citations
• Algorithmic Accountability and Public Reason (2017) — 275 citations
• Like Trainer, Like Bot? Inheritance of Bias in Algorithmic Content Moderation (2017) — 180 citations