Warren J. von Eschenbach

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 9 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 7 citations into it; #18,594 of 35,345 by trust here, #33,294 by citations
• Safety Research — 6 citations into it; #2,160 of 5,829 by trust here, #5,396 by citations
• Safety, Robustness & Interpretability — 5 citations into it

Whom Warren J. von Eschenbach trusts overall

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

1. Arun Rai
2. Jenna Burrell
3. Paul Humphreys
4. Carlos A. Zednik
5. John Danaher
6. Davide Castelvecchi
7. Karen Jones
8. Luciano Floridi
9. Marcello D'Agostino
10. Riccardo Miotto

Who trusts Warren J. von Eschenbach overall

1. Saleh Afroogh
2. Ali Akbari
3. Emmie Malone
4. Mohammadali Kargar

Papers from Warren J. von Eschenbach's perspective

Ordered by how strongly the researchers Warren J. von Eschenbach trusts endorse each paper. Same corpus, a different order for every researcher.

1. How the machine ‘thinks’: Understanding opacity in machine learning algorithms
2. A Survey of Methods for Explaining Black Box Models
3. Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor
4. The philosophical novelty of computer simulation methods (Synthese)
5. Introduction: the Governance of Algorithms
6. Deep Patient: An Unsupervised Representation to Predict the Future of Patients from the Electronic Health Records
7. Solving the Black Box Problem: A Normative Framework for Explainable Artificial Intelligence (Philosophy & Technology)
8. Can we open the black box of AI?
9. Trust as an Affective Attitude
10. Explainable AI: from black box to glass box (Journal of the Academy of Marketing Science)

Their papers

• Transparency and the Black Box Problem: Why We Do Not Trust AI (2021) — 644 citations