Effy Vayena
Artificial Intelligence · 2018–2020
A researcher in the Science corpus: 6 papers; trusts 4 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 37 citations into it
- Safety Research — 32 citations into it; #2,020 of 5,829 by trust here, #366 by citations
- AI Ethics, Fairness & Society — 12 citations into it
- Safety, Robustness & Interpretability — 12 citations into it
Whom Effy Vayena trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Who trusts Effy Vayena overall
- Raquel Dias
- Ali Torkamani
- Pouyan Esmaeilzadeh
- Inioluwa Deborah Raji
- Jessica Morley
- Daniel S. Schiff
- S. Lo Piano
- Astrid Schepman
- Juan Manuel Durán
Papers from Effy Vayena's perspective
Ordered by how strongly the researchers Effy Vayena trusts endorse each paper. Same corpus, a different order for every researcher.
- Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings
- Energy and Policy Considerations for Deep Learning in NLP
- Artificial intelligence in healthcare: a critical analysis of the legal and ethical implications
- The ethics of information transparency
- Ethics Guidelines for Trustworthy AI
- How AI can be a force for good
- Scoping studies: towards a methodological framework
- AI Now 2017 Report
- The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation
- The Social and Economic Implications of Artificial Intelligence Technologies in the Near-Term
Their papers
- On the responsible use of digital data to tackle the COVID-19 pandemic (2020) — 425 citations
- Explainability for artificial intelligence in healthcare: a multidisciplinary perspective (2020) — 1,677 citations
- The global landscape of AI ethics guidelines (2019) — 2,263 citations
- Artificial Intelligence: the global landscape of ethics guidelines (2019) — 2,720 citations
- AI4People—An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations (2018) — 3,306 citations
- Machine learning in medicine: Addressing ethical challenges (2018) — 708 citations