Abstract Purpose of Review To assess the state-of-the-art in research on trust in robots and
to examine if recent methodological advances can aid in the development of trustworthy …

Important decisions about people are increasingly made by algorithms: Votes are counted;
voter rolls are purged; financial aid decisions are made; taxpayers are chosen for audits; air …

Vehicle automation has been in the works for a long time now. Automatic brakes, cruise
control, GPS satellite navigation, etc. are all common features seen in today's automobiles …

We present a rigorous methodology for auditing differentially private machine learning by
adding multiple carefully designed examples called canaries. We take a first principles …

The iterative consensus problem requires a set of processes or agents with different initial
values, to interact and update their states to eventually converge to a common value …

Bug-fixes are widely used for predicting bugs or finding risky parts of software. However, a
bug-fix does not contain information about the change that initially introduced a bug. Such …

The widespread acceptance of differential privacy has led to the publication of many
sophisticated algorithms for protecting privacy. However, due to the subtle nature of this …

Differential privacy is a notion of confidentiality that protects the privacy of individuals while
allowing useful computations on their private data. Deriving differential privacy guarantees …

Differential privacy provides a way to get useful information about sensitive data without
revealing much about any one individual. It enjoys many nice compositionality properties not …

Over the last decade, differential privacy has achieved widespread adoption within the
privacy community. Moreover, it has attracted significant attention from the verification …