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Challenges in Machine Generation of Analytic Products from Multi-Source Data Proceedings of a Workshop (2017) / Chapter Skim
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8 Session 7: Humans and Machines Working Together with Big Data
Pages 28-30

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From page 28...
... He added that system-level improvements also have the potential to reduce cognitive bias, increase system assessments, and allow analysts to evaluate the trustworthiness of the system's products. When human beings interact with information, Pirolli explained, phenomena occur at multiple time scales, each having their own laws.
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From page 29...
... CROWDSOURCING FOR NATURAL LANUGAGE PROCESSING Chris Callison-Burch, University of Pennsylvania Chris Callison-Burch, University of Pennsylvania, defined crowdsourcing as hiring people to accomplish small tasks as low cost; Amazon's Mechanical Turk is the most common platform for crowdsourcing. Here, humans 1  For information on the ICArUS program, see IARPA, "Integrated Cognitive-Neuroscience Architectures for Understanding Sensemaking (ICArUS)
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From page 30...
... Callison-Burch performed a number of experiments to study the capabilities of human language technologies on Mechanical Turk. He researched how to create bilingual parallel text for a variety of low resource languages; completed a large-scale demographic study in which the list of languages represented by Mechanical Turk workers increased; and used crowdsourcing to identify cases of written Arabic dialect and create an Arabic-to-English parallel corpus that could be used to train a machine translation system.
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  • pirolli explained
  • human language
  • mechanical turkers
  • machine translation
  • intelligence advanced

  • imagenet mechanical
  • soft bots
  • annotation tasks
  • performance capabilities
  • interaction techniques

  • arabic dialect
  • learning programming
  • data changes
  • emerging field
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  • common platform
  • medical decision
  • pirolli stated
  • pirolli believes
  • technology allowed


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