TY - RPRT T1 - Imagine All the People: Citizen Science, Artificial Intelligence, and Computational Research Y1 - 2021 A1 - Lea A. Shanley A1 - Lucy Fortson A1 - Tanya Berger-Wolf A1 - Kevin Crowston A1 - Pietro Michelucci AB -

Machine learning, artificial intelligence, and deep learning have advanced significantly over the past decade. Nonetheless, humans possess unique abilities such as creativity, intuition, context and abstraction, analytic problem solving, and detecting unusual events. To successfully tackle pressing scientific and societal challenges, we need the complementary capabilities of both humans and machines. The Federal Government could accelerate its priorities on multiple fronts through judicious integration of citizen science and crowdsourcing with artificial intelligence (AI), Internet of Things (IoT), and cloud strategies.

JF - A Computing Community Consortium (CCC) Quadrennial Paper PB - Computing Community Consortium (CCC) CY - Washington, DC UR - https://cra.org/ccc/wp-content/uploads/sites/2/2021/03/CCC-TransitionPaperImagine-All-the-People.pdf ER - TY - JOUR T1 - Stages of motivation for contributing user-generated content: A theory and empirical test JF - International Journal of Human-Computer Studies Y1 - 2018 A1 - Kevin Crowston A1 - Fagnot, Isabelle AB -

User-generated content (UGC) projects involve large numbers of mostly unpaid contributors collaborating to create content. Motivation for such contributions has been an active area of research. In prior research, motivation for contribution to UGC has been considered a single, static and individual phenomenon. In this paper, we argue that it is instead three separate but interrelated phenomena. Using the theory of helping behaviour as a framework and integrating social movement theory, we propose a stage theory that distinguishes three separate sets (initial, sustained and meta) of motivations for participation in UGC. We test this theory using a data set from a Wikimedia Editor Survey (Wikimedia Foundation, 2011). The results suggest several opportunities for further refinement of the theory but provide support for the main hypothesis, that different stages of contribution have distinct motives. The theory has implications for both researchers and practitioners who manage UGC projects.

PB - Syracuse University CY - Syracuse, NY VL - 109 ER - TY - Generic T1 - Amazon Mechanical Turk: A research tool for organizations and information systems scholars T2 - IFIP Working Group 8.2 Conference: Shaping the Future of ICT Research: Methods and Approaches Y1 - 2012 A1 - Kevin Crowston ED - Anol Bhattacherjee ED - Brian Fitzgerald JF - IFIP Working Group 8.2 Conference: Shaping the Future of ICT Research: Methods and Approaches T3 - IFIP AICT PB - Springer CY - Tampa, FL VL - 389 SN - 978-3-642-35141-9 ER -