… as trustworthy machine learning (trustworthy ML). This article describes an architecture to
support scalable trustworthy ML and … into the ML techniques to ensure that they are trustworthy. …

… trustworthy person and a trustworthy machine learning system. However, the final trust of
the trustor, subject to cognitive biases, may be quite different for a human trustee and machine …

… categories of trustworthiness technologies for machine learning, … trustworthiness technologies
in all stages of the life cycle. In so doing we establish the ways in which machine learning …

… , and fairness are essential for high stakes use of machine learning (1). Eshete starts with
security as the key to machine learning, which we strongly agree with. This paper explores the …

… What is the current state of machine learning, and how do we make it more trustworthy?
What are the analogs to natural ingredients, sanitary preparation, and tamperresistant …

… of trustworthy ML. For the first element, we used three possible variations – machine learning,
deep learning, … As an example, the first query was machine learning robustness. Exclusion …

… With the advent of machine learning (ML) and deep learning (… robustness challenges that
hinder the trustworthiness of ML, we … We also describe how explainable and trustworthy ML can …

… Speech-centric machine learning systems have … need to be considered more trustworthy
for broader deployment. … to ensure these ML systems are trustworthy, especially private, safe…

… a big picture for machine learning security practitioners. … and trustworthiness technologies
for machine learning systems. … needed for robust and trustworthy ML system development, and …

… In recent years, there are active and ongoing efforts aimed at making machine learning … to
trustworthy AI by improving reliability and user-perceived trustworthiness of machine learning …