Data Literacy to Support Human-centred Machine Learning

Wolff, Annika; Gooch, Daniel and Kortuem, Gerd (2016). Data Literacy to Support Human-centred Machine Learning. In: CHI 2016, 7-12 May 2016, San Jose California, USA.

URL: http://www.doc.gold.ac.uk/~mas02mg/HCML2016/HCML20...

Abstract

In the past, machine learning applications were mostly developed and deployed in specialist situations where the outputs would be either read by experts, or else interpreted for the public, with the methods hidden from view. In the current data driven society, the general public are increasingly interacting with complex data sets and the outputs of machine learning technologies. Within the domain of the smart city, non-experts are also being brought closer to the design process itself. This paper explores whether improving the overall data literacy of a society can instill within that society a set of core competences that improve the capacity of non-experts in machine learning to engage with machine learning outputs in a more knowledgeable way, or to provide insight and differing perspectives into the design of machine learning applications.

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About

• Item ORO ID
• 46463
• Item Type
• Conference or Workshop Item
• Extra Information
• Paper was presented at the workshop 'Human Centred machine learning', 5 May 2016 at CHI 2016
• Keywords
• H.1.2. Information systems; User/Machine Systems; Human factors
• Academic Unit or School
• Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
  Faculty of Science, Technology, Engineering and Mathematics (STEM)
• Related URLs
• • http://hcml2016.goldsmithsdigital.com/pr...
• Depositing User
• Annika Wolff