Over the last few years the sharing economy has been changing the way that people share
and conduct transactions in digital spaces. This research phenomenon has drawn scholars …

Although large language models (LLMs) have demonstrated impressive potential on simple
tasks, their breadth of scope, lack of transparency, and insufficient controllability can make …

Despite recent concerns about data quality, various academic fields rely increasingly on
crowdsourced samples. Thus, the goal of this study was to systematically assess …

Crowdsourced data acquired from tasks that comprise a subjective component (eg opinion
detection, sentiment analysis) is potentially affected by the inherent bias of crowd workers …

The promise AI's proponents have made for decades is one in which our needs are
predicted, anticipated, and met-often before we even realize it. Instead, algorithmic systems …

The internet is empowering the rise of crowd work, gig work, and other forms of on-demand
labor. A large and growing body of scholarship has attempted to predict the socio-technical …

We ideate a future design workflow that involves AI technology. Drawing from activity and
communication theory, we attempt to isolate the new value that large AI models can provide …

Crowdworkers regularly support their work with scripts, extensions, and software to enhance
their productivity. Despite their evident significance, little is understood regarding how these …

Visualization researchers have been increasingly leveraging crowdsourcing approaches to
overcome a number of limitations of controlled laboratory experiments, including small …

Paid crowdsourcing platforms have evolved into remarkable marketplaces where requesters
can tap into human intelligence to serve a multitude of purposes, and the workforce can …