D. Shin

Safety Research · with Park · 2019–2021

A researcher in the Science corpus: 3 papers; trusts 14 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Safety Research — 22 citations into it; #1,146 of 5,829 by trust here, #2,596 by citations
• Artificial Intelligence — 19 citations into it; #30,012 of 35,345 by trust here, #27,551 by citations
• Sociology and Political Science — 16 citations into it; #9,102 of 22,756 by trust here, #14,364 by citations
• Computer Science Applications — 10 citations into it
• AI Ethics, Fairness & Society — 9 citations into it
• Information Systems — 7 citations into it; #3,924 of 8,771 by trust here, #6,770 by citations
• Health Informatics — 6 citations into it; #156 of 240 by trust here, #170 by citations
• Safety, Robustness & Interpretability — 6 citations into it; #2,116 of 2,251 by trust here, #2,205 by citations

Whom D. Shin trusts overall

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

1. Nicholas A. Diakopoulos
2. Rob Kitchin
3. David Beer
4. Jenna Burrell
5. Kai-Fu Lee
6. Andreas Holzinger
7. Andrew F. Hayes
8. Bryce Goodman
9. Donghee Don Shin
10. Mike Ananny

Who trusts D. Shin overall

1. Donghee Shin
2. Hyesun Choung
3. Prabu David
4. Davinder Kaur
5. Arun Ross
6. Xavier Parent-Rocheleau
7. Daniel Omeiza
8. Nithya Sambasivan
9. Tita Alissa Bach
10. Suleyman Uslu

Papers from D. Shin's perspective

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

1. How the machine ‘thinks’: Understanding opacity in machine learning algorithms
2. AI Superpowers: China, Silicon Valley, and the New World Order
3. Accountability in algorithmic decision making
4. ImageNet classification with deep convolutional neural networks
5. ImageNet: A large-scale hierarchical image database
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
8. The Black Box Society: The Secret Algorithms That Control Money and Information
9. Long Short-Term Memory
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Role of fairness, accountability, and transparency in algorithmic affordance (2019) — 491 citations
• Toward Fair, Accountable, and Transparent Algorithms: Case Studies on Algorithm Initiatives in Korea and China (2019) — 39 citations
• The effects of explainability and causability on perception, trust, and acceptance: Implications for explainable AI (2021) — 1,208 citations