Skip to main content

Award: CrowdCO-OP: Sharing Risks and Rewards in Crowdsourcing

Award: CrowdCO-OP: Sharing Risks and Rewards in Crowdsourcing

Dr Alessandro Checco

A joint work between the University of Queensland, the University of Hanover, and the University of Sheffield titled CrowdCO-OP: Sharing Risks and Rewards in Crowdsourcing has received an Honorable Mention Award at the prestigious Conference on Computer-Supported Cooperative Work and Social Computing (CSCW 2020).

The work focused on paid micro-task crowdsourcing. This type of labour has gained in popularity mainly because of the increasing need for large-scale manually labelled datasets which are often used to train and evaluate Artificial Intelligence systems. Modern paid crowdsourcing platforms use a piecework approach to rewards, meaning that workers are paid for each task they complete, given that their work quality is considered sufficient by the requester or the platform. Such an approach creates risks for workers: their work may be rejected without being rewarded, and they may be working on poorly rewarded tasks, in light of the disproportionate time required to complete them. As a result, recent research has shown that crowd workers may tend to choose specific, simple, and familiar tasks and avoid new requesters to manage these risks.

In this work, we propose a novel crowdsourcing reward mechanism that allows workers to share these risks and achieve a standardized hourly wage equal for all participating workers. Reward-focused workers can thereby take up challenging and complex HITs without bearing the financial risk of not being rewarded for completed work. We experimentally compare different crowd reward schemes and observe their impact on worker performance and satisfaction. Our results show that 1) workers clearly perceive the benefits of the proposed reward scheme, 2) work effectiveness and efficiency are not impacted as compared to those of the piecework scheme, and 3) the presence of slow workers is limited and does not disrupt the proposed cooperation-based approaches.

A pre-print of this work is available at this link.

For any questions feel free to contact Alessandro Checco at a.checco@sheffield.ac.uk.

Comments

Popular posts from this blog

Raspberry Pi Weather Project now live

A project to create a raspberry pi weather station is currently live in the Information School.  The Sheffield Pi weather station has been created by Romilly Close, undergraduate Aerospace Engineering student at the University of Sheffield.  The project was funded by the Sheffield Undergraduate Research Experience (SURE) scheme and is being supervised by Dr Jo Bates, Paula Goodale and Fred Sonnenwald from the Information School. Information about the Sheffield Pi station and how to create your own can be found on the project website .  You can also see live data from the Sheffield Pi station on Plot.ly , and further information can also be found on the Met Office Weather Observations Website .    This work compliments the School’s existing project entitled ‘The Secret Life of a Weather Datum’ which explores socio-cultural influences on weather data.  This project is funded under the AHRC’s Digital Transformations Big Data call.  It ...

Our Chemoinformatics Group wins Jason Farradane Award

The Information School's Chemoinformatics Research Group has been awarded the 2012 UKeiG Jason Farradane Award , in recognition of its outstanding 40 year contribution to the information field. The prize is awarded to the three current members of the group,  Professor Val Gillet , Dr John Holliday and Professor Peter Willett . The judges recognised the Group's status as one of the world's leading centres of chemoinformatics research, a major contributor to the field of information science, and an exemplar in raising the profile of the information profession. The School has a long association with the Farradane prize. Its second recipient was long time member of staff Professor Mike Lynch in 1980.

Generative AI paper authored by Dr Kate Miltner among British Academy's 13 discussion papers on "good" digital society

 The British Academy has today published thirteen discussion papers from a range of expert perspectives across the ‘SHAPE’ disciplines (Social Sciences, Humanities and the Arts for People and the Economy) to explore the question: ‘What are the possibilities of a good digital society?’  The papers explore a wide range of issues, from the environmental impacts of digitalised daily life to the possibilities of ‘good’ Generative AI in the cultural and creative industries, to examining more closely what we mean by a ‘good digital society’. Among the papers is one authored by information School Lecturer Dr Kate Miltner, with Dr Tim Highfield from the Department of Sociological Studies. Their paper focuses on "good" uses of generative AI in the cultural & creative industries. Alongside the papers is an introductory summary that provides a thematic overview of the papers and points to how we might conceptualise the principles that underpin these diverse visions of a good digital ...