22 citations · 39 across the 4 of their papers we have counts for
4 papers
PADTHAI-MM: Principles-based Approach for Designing Trustworthy, Human-centered AI using MAST Methodology
Myke C. Cohen, Nayoung Kim, Yang Ba +7
Despite an extensive body of literature on trust in technology, designing trustworthy AI systems for high-stakes decision domains remains a significant challenge, further compounde…
Evaluating Trustworthiness of AI-Enabled Decision Support Systems: Validation of the Multisource AI Scorecard Table (MAST)
Pouria Salehi, Yang Ba, Nayoung Kim +10
The Multisource AI Scorecard Table (MAST) is a checklist tool based on analytic tradecraft standards to inform the design and evaluation of trustworthy AI systems. In this study, w…
Multisource AI Scorecard Table for System Evaluation
Erik Blasch, James Sung, Tao Nguyen
The paper describes a Multisource AI Scorecard Table (MAST) that provides the developer and user of an artificial intelligence (AI)/machine learning (ML) system with a standard che…
Artificial Intelligence Strategies for National Security and Safety Standards
Erik Blasch, James Sung, Tao Nguyen +2
Recent advances in artificial intelligence (AI) have lead to an explosion of multimedia applications (e.g., computer vision (CV) and natural language processing (NLP)) for differen…