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Quantitative AI Risk Assessments: Opportunities and Challenges
Although AI-based systems are increasingly being leveraged to provide va...
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Evaluating a Methodology for Increasing AI Transparency: A Case Study
In reaction to growing concerns about the potential harms of artificial ...
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Using Document Similarity Methods to create Parallel Datasets for Code Translation
Translating source code from one programming language to another is a cr...
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AI Explainability 360: Impact and Design
As artificial intelligence and machine learning algorithms become increa...
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Perfection Not Required? Human-AI Partnerships in Code Translation
Generative models have become adept at producing artifacts such as image...
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Quality Estimation Interpretability for Code Translation
Recently, the automated translation of source code from one programming ...
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Towards evaluating and eliciting high-quality documentation for intelligent systems
A vital component of trust and transparency in intelligent systems built...
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A Methodology for Creating AI FactSheets
As AI models and services are used in a growing number of highstakes are...
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Business (mis)Use Cases of Generative AI
Generative AI is a class of machine learning technology that learns to g...
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Experiences with Improving the Transparency of AI Models and Services
AI models and services are used in a growing number of highstakes areas,...
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One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques
As artificial intelligence and machine learning algorithms make further ...
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AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias
Fairness is an increasingly important concern as machine learning models...
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