SOTAVerified

Ethics

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 551–600 of 832 papers

TitleStatusHype
A Principles-based Ethics Assurance Argument Pattern for AI and Autonomous Systems—0
Why we need biased AI -- How including cognitive and ethical machine biases can enhance AI systems—0
Robotic Speech Synthesis: Perspectives on Interactions, Scenarios, and Ethics—0
Cross-model Fairness: Empirical Study of Fairness and Ethics Under Model MultiplicityCode0
Moral Dilemmas for Moral Machines—0
Toward Ethical AIED—0
Towards an Accountable and Reproducible Federated Learning: A FactSheets Approach—0
The four-fifths rule is not disparate impact: a woeful tale of epistemic trespassing in algorithmic fairness—0
Automated Extraction of Energy Systems Information from Remotely Sensed Data: A Review and Analysis—0
Are There Exceptions to Goodhart's Law? On the Moral Justification of Fairness-Aware Machine Learning—0
Seeing Like a Toolkit: How Toolkits Envision the Work of AI Ethics—0
State of AI Ethics Report (Volume 6, February 2022)—0
PrivPAS: A real time Privacy-Preserving AI System and applied ethics—0
Ethics, Rules of Engagement, and AI: Neural Narrative Mapping Using Large Transformer Language Models—0
Technology Ethics in Action: Critical and Interdisciplinary Perspectives—0
A Non-Expert's Introduction to Data Ethics for Mathematicians—0
MORAL: Aligning AI with Human Norms through Multi-Objective Reinforced Active LearningCode0
Democratising Risk: In Search of a Methodology to Study Existential Risk—0
Generation of Synthetic Rat Brain MRI scans with a 3D Enhanced Alpha-GAN—0
Prescriptive Machine Learning for Automated Decision Making: Challenges and Opportunities—0
Filling gaps in trustworthy development of AI—0
Artificial Intelligence Ethics and Safety: practical tools for creating "good" modelsCode1
AI Ethics Principles in Practice: Perspectives of Designers and Developers—0
A Framework for Fairness: A Systematic Review of Existing Fair AI Solutions—0
Scaling Language Models: Methods, Analysis & Insights from Training GopherCode2
Ethics and Creativity in Computer Vision—0
Reduced, Reused and Recycled: The Life of a Dataset in Machine Learning Research—0
A German Corpus of Reflective Sentences—0
P4AI: Approaching AI Ethics through Principlism—0
Software Engineering for Responsible AI: An Empirical Study and Operationalised Patterns—0
Confucius, Cyberpunk and Mr. Science: Comparing AI ethics between China and the EU—0
The MAIEI Learning Community Report—0
A Word on Machine Ethics: A Response to Jiang et al. (2021)—0
AI and Blackness: Towards moving beyond bias and representation—0
AI Ethics Statements -- Analysis and lessons learnt from NeurIPS Broader Impact Statements—0
‘Just What do You Think You’re Doing, Dave?’ A Checklist for Responsible Data Use in NLP—0
AUTO-DISCERN: Autonomous Driving Using Common Sense Reasoning—0
COVID-19 Detection in Chest X-ray Images Using Swin-Transformer and Transformer in Transformer—0
Designing Language Technologies for Social Good: The Road not Taken—0
Can Machines Learn Morality? The Delphi ExperimentCode1
Ego4D: Around the World in 3,000 Hours of Egocentric VideoCode1
Towards AI Logic for Social Reasoning—0
Artificial intelligence for Sustainable Energy: A Contextual Topic Modeling and Content Analysis—0
PASS: An ImageNet replacement for self-supervised pretraining without humansCode1
Towards a Governance Framework for Brain Data—0
AI-HRI 2021 Proceedings—0
Some Critical and Ethical Perspectives on the Empirical Turn of AI Interpretability—0
Actionable Approaches to Promote Ethical AI in Libraries—0
Ethics Sheet for Automatic Emotion Recognition and Sentiment AnalysisCode1
A Logic-based Multi-agent System for Ethical Monitoring and Evaluation of DialoguesCode0
Show:102550
← PrevPage 12 of 17Next →
All datasetsETHICSEthics (per ethics)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1RuGPT-3 LargeAccuracy68.6—Unverified
2RuGPT-3 MeduimAccuracy68.3—Unverified
3RuGPT-3 SmallAccuracy55.5—Unverified
4Human benchmarkAccuracy52.9—Unverified
#ModelMetricClaimedVerifiedStatus
1Human benchmarkAccuracy67.6—Unverified
2RuGPT-3 SmallAccuracy60.9—Unverified
3RuGPT-3 LargeAccuracy44.9—Unverified
4RuGPT-3 MediumAccuracy44.1—Unverified