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Event: BHCC 2020 - 2nd Symposium on Biases in Human Computation and Crowdsourcing

BHCC 2020 - 2nd Symposium on Biases in Human Computation and Crowdsourcing Dr Alessandro Checco Human Computation and Crowdsourcing have become ubiquitous in the world of algorithm augmentation and data management. However, humans have various cognitive biases that influence the way they make decisions, remember information, and interact with machines. It is thus important to identify human biases and analyse their effect on complex hybrid systems. On the other hand, the potential interaction with a large pool of human contributors gives the opportunity to detect and handle biases in existing data and systems. The goal of this symposium is to analyse 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. An interdisciplinary approach is often required to capture the broad effects that these processe...

Alessandro Checco & Jo Bates win Best Paper at HCOMP 2018

From Director of Research Professor Paul Clough: I am delighted to announce that Alessandro Checco and Jo Bates (together with Gianluca Demartini) have won the Best Paper award at the prestigious Human Computation or HCOMP 2018 conference for the following paper: Checco A, Bates J & Demartini G (2018) All That Glitters is Gold -- An Attack Scheme on Gold Questions in Crowdsourcing. Proceedings of the AAAI Conference on Human Computation and Crowdsourcing. Abstract here; http://eprints.whiterose.ac.uk/130654/ Not only is it a significant achievement to even be accepted at this conference it is an outstanding achievement to be nominated for Best Paper and then to win it is incredible. Alessandro and Gianluca were awarded the prize at HComp 2018 . Alessandro had this to say about the paper and reviews: "Feedback from chairs was that they really liked the fact we opened a new direction (that is having workers using ML solutions on the employers). We will have the opportu...