Conference paper Open Access

Social Cues, Social Biases: Stereotypes in Annotations on People Images

Jahna Otterbacher

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  "inLanguage": {
    "alternateName": "eng", 
    "@type": "Language", 
    "name": "English"
  "description": "<p>Human computation is often subject to systematic biases. We consider the case of linguistic biases and their consequences<br>\nfor the words that crowd workers use to describe people images in an annotation task. Social psychologists explain that when describing others, the subconscious perpetuation of stereotypes is inevitable, as we describe stereotype-congruent people and/or in-group members more abstractly than others. In an MTurk experiment we show evidence of these biases, which are exacerbated when an image&rsquo;s &ldquo;popular tags&rdquo; are displayed, a common feature used to provide social information to workers. Underscoring recent calls for a deeper examination of the role of training data quality in algorithmic biases, results suggest that it is rather easy to sway human judgment.</p>", 
  "license": "", 
  "creator": [
      "affiliation": "Faculty of Pure and Applied Sciences, Open University of Cyprus and Research Centre on Interactive Media Smart Systems and Emerging Technologies Nicosia, CYPRUS", 
      "@id": "", 
      "@type": "Person", 
      "name": "Jahna Otterbacher"
  "headline": "Social Cues, Social Biases: Stereotypes in Annotations on People Images", 
  "image": "", 
  "datePublished": "2018-07-08", 
  "url": "", 
  "version": "Accepted pre-print", 
  "@type": "ScholarlyArticle", 
  "keywords": [
    "linguistic biases", 
    "social stereotypes", 
    "social cues", 
    "social biases"
  "@context": "", 
  "identifier": "", 
  "@id": "", 
  "workFeatured": {
    "url": "", 
    "alternateName": "HCOMP 2018", 
    "location": "Zurich, Switzerland", 
    "@type": "Event", 
    "name": "Sixth AAAI Conference on Human Computation and Crowdsourcing"
  "name": "Social Cues, Social Biases: Stereotypes in Annotations on People Images"
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