If a user is presented an AI system that portends to explain how it works, how do we know
whether the explanation works and the user has achieved a pragmatic understanding of the …

The question addressed in this paper is: If we present to a user an AI system that explains
how it works, how do we know whether the explanation works and the user has achieved a …

Abstract Previous research in Explainable Artificial Intelligence (XAI) suggests that a main
aim of explainability approaches is to satisfy specific interests, goals, expectations, needs …

Medical artificial intelligence is cost-effective and scalable and often outperforms human
providers, yet people are reluctant to use it. We show that resistance to the utilization of …

Ensuring fairness of machine learning systems is a human-in-the-loop process. It relies on
developers, users, and the general public to identify fairness problems and make …

This chapter discusses common concerns that researchers have with Mechanical Turk
(MTurk), reviewing the evidence that bears upon each concern. It suggests that readers are …

Computer algorithms are increasingly being used to predict people's preferences and make
recommendations. Although people frequently encounter these algorithms because they are …

It is common for researchers discovering a significant interaction of a measured variable X
with a manipulated variable Z to examine simple effects of Z at different levels of X. These …

How to assess critical aspects of cognitive functioning that are not measured by IQ tests:
rational thinking skills. Why are we surprised when smart people act foolishly? Smart people …

The Cognitive Reflection Test (CRT; Frederick, 2005) is designed to measure the tendency
to override a prepotent response alternative that is incorrect and to engage in further …