Crowdsourcing data collection from research participants recruited from online labor
markets is now common in cognitive science. We review who is in the crowd and who can …

Quality improvement methods are essential to gathering high-quality crowdsourced data,
both for research and industry applications. A popular and broadly applicable method is task …

The power of human language and thought arises from systematic compositionality—the
algebraic ability to understand and produce novel combinations from known components …

The many successes of deep neural networks (DNNs) over the past decade have largely
been driven by computational scale rather than insights from biological intelligence. Here …

With machine learning models being increasingly used to aid decision making even in high-
stakes domains, there has been a growing interest in developing interpretable models …

Abstract In recent years, Mechanical Turk (MTurk) has revolutionized social science by
providing a way to collect behavioral data with unprecedented speed and efficiency …

Theories of reward learning in neuroscience have focused on two families of algorithms
thought to capture deliberative versus habitual choice.'Model-based'algorithms compute the …

One of the most striking features of human cognition is the ability to plan. Two aspects of
human planning stand out—its efficiency and flexibility. Efficiency is especially impressive …

The data explosion of the last few years from social media and 'big'data, along with the
impact of disruptive technologies, like blockchain and machine learning, have changed the …

Most recent gains in visual recognition have originated from the inclusion of attention
mechanisms in deep convolutional networks (DCNs). Because these networks are …