SOTAVerified

Ethics

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 701–750 of 832 papers

TitleStatusHype
A Framework for Fairer Machine Learning in Organizations—0
A New Screening Method for COVID-19 based on Ocular Feature Recognition by Machine Learning Tools—0
Landscape of Machine Implemented Ethics—0
Precision Health Data: Requirements, Challenges and Existing Techniques for Data Security and Privacy—0
Intelligence Primer—0
Report prepared by the Montreal AI Ethics Institute In Response to Mila's Proposal for a Contact Tracing App—0
A Recommendation and Risk Classification System for Connecting Rough Sleepers to Essential Outreach ServicesCode0
Ethics of Artificial Intelligence in Surgery—0
The societal and ethical relevance of computational creativity—0
Green Lighting ML: Confidentiality, Integrity, and Availability of Machine Learning Systems in Deployment—0
Teaching the Foundations of Machine Learning with Candy—0
Good AI for the Present of Humanity—0
Fairness in machine learning: against false positive rate equality as a measure of fairness—0
Integrating Ethics into the NLP Curriculum—0
The State of AI Ethics Report (June 2020)—0
Towards Contrastive Explanations for Comparing the Ethics of Plans—0
A blindspot of AI ethics: anti-fragility in statistical prediction—0
A Comprehensive Review of Deep Learning Applications in Hydrology and Water Resources—0
Response by the Montreal AI Ethics Institute to the European Commission's Whitepaper on AI—0
Ethical Considerations for AI Researchers—0
The Tragedy of the AI Commons—0
Equality of Learning Opportunity via Individual Fairness in Personalized Recommendations—0
An optimizable scalar objective value cannot be objective and should not be the sole objective—0
Repr\'esentation du genre dans des donn\'ees open source de parole (Gender representation in open source speech resources 1 With the rise of artificial intelligence (AI) and the growing use of deep-learning architectures, the question of ethics and transparency in AI systems has become a central concern within the research community)—0
Explainable deep learning models in medical image analysis—0
How good is good enough for COVID19 apps? The influence of benefits, accuracy, and privacy on willingness to adopt—0
Approaches to the Anonymisation of Sign Language Corpora—0
The Moral Burden of Ambiguity Aversion—0
A Philosophy of Data—0
Applying Transparency in Artificial Intelligence based Personalization Systems—0
Combating The Machine Ethics Crisis: An Educational Approach—0
On the Ethics of Building AI in a Responsible Manner—0
Gender Representation in Open Source Speech Resources—0
Ethics in the digital era—0
Trust dynamics and user attitudes on recommendation errors: preliminary results—0
Whose Side are Ethics Codes On? Power, Responsibility and the Social Good—0
Implementations in Machine Ethics: A Survey—0
Expecting the Unexpected: Developing Autonomous-System Design Principles for Reacting to Unpredicted Events and Conditions—0
Beyond Near- and Long-Term: Towards a Clearer Account of Research Priorities in AI Ethics and Society—0
Perspectives and Ethics of the Autonomous Artificial Thinking Systems—0
On Consequentialism and Fairness—0
Mining Disinformation and Fake News: Concepts, Methods, and Recent AdvancementsCode0
On Quantified Modal Theorem Proving for Modeling Ethics—0
Where Are We? Using Scopus to Map the Literature at the Intersection Between Artificial Intelligence and Research on Crime—0
Teaching Responsible Data Science: Charting New Pedagogical Territory—0
Lessons from Archives: Strategies for Collecting Sociocultural Data in Machine Learning—0
Building Discourse Parser for Thirukkural—0
FairPrep: Promoting Data to a First-Class Citizen in Studies on Fairness-Enhancing Interventions—0
Kernel Dependence Regularizers and Gaussian Processes with Applications to Algorithmic Fairness—0
AI Ethics for Systemic Issues: A Structural Approach—0
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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