The goal of this symposium is to analyze both existing human biases in hybrid systems, and methods to manage bias via crowdsourcing and human computation. We will discuss different types of biases, measures, and methods to track bias, as well as methodologies to prevent and solve bias.
We will provide a framework for discussion among scholars, practitioners, and other interested parties, including industry, crowd workers, requesters, and crowdsourcing platform managers. We expect contributions combining ideas from different disciplines, including computer science, psychology, economics, and social sciences.
Topics of interest include (but are not limited to):
Biases in Human Computation and Crowdsourcing
Human sampling bias
Effect of cultural, gender, and ethnic biases
Effect of human in the loop training and past experiences
Effect of human expertise vs interest
Bias in experts vs. bias in crowdsourcing
Bias in outsourcing vs bias in crowdsourcing
Bias in task selection
Task assignment/recommendation for reducing bias
Effect of human engagement on the bias
Responsibility and ethics in human computation and bias management
Preventing bias in crowdsourcing and human computation
Creating awareness of cognitive biases among human agents
Measuring and addressing ambiguities and biases in human annotation
Human factors in AI
Using Human Computation and Crowdsourcing for Bias Understanding and Management
Biases in Human-in-the-loop systems
Identifying new types of cognitive bias in data or content
Measuring bias in data or content
Removing bias in data or content
Dealing with algorithmic bias
Fake news detection
Diversification of sources by means
Provenance and traceability
Long-term crowd engagement
We welcome the submission of research papers and abstracts which describe original work that has not been submitted or is currently under review, has not been previously published nor accepted for publication elsewhere, in any other journal or conference.
Submissions of the research papers must be in English, in PDF format, and be in the current CEUR-WS single-column conference format.
We will follow CEUR-WS guidelines, meet their preconditions, and expect to get the proceedings published. However, note that there is no guarantee that our volume will get published at CEUR-WS.
We welcome the submission of the following types of contributions:
Full papers should be at most 10 pages in length (including figures, tables, appendices, and references);
Short papers should be at most 5 pages in length (including figures, tables, appendices, and references);
Abstracts should be at most 1 page in length (including figures, tables, appendices, and references), should contain just a title and the abstract, and should detail demos or relevant work or ideas which are under development. They can not contain references.
Full, Short, and Abstract papers due: 1 September 2022 AoE (firm deadline)
Notifications: 10 September 2022
Conference: 12, 13, and 14 October 2022