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Final published version
Research output: Contribution to conference - Without ISBN/ISSN › Abstract › peer-review
Research output: Contribution to conference - Without ISBN/ISSN › Abstract › peer-review
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TY - CONF
T1 - Researching and Designing Uncanny AI to Legible AI
AU - Pilling, Franziska
AU - Akmal, Haider Ali
AU - Coulton, Paul
PY - 2020/11/13
Y1 - 2020/11/13
N2 - The sociotechnical landscape has become more reliant on artificial intelligence (AI) operating via the Internet of Things (IoT). Technology is typically designed to ease users’ interactions, consequently concealing functionality, leading to various misconceptions regarding AI and how data is processed (Pilling and Coulton, 2019). However, obscuring functions and the incognito collection of data is profitable for companies (Bryson and Winfield, 2017; Mosco, 2014). Though, this intrusion of technology is questioned by users, concerning the security,privacy and the unknown implications of use (Bostrom, 2014; Bridle, 2018). Labelling AI as uncanny and illegible to users, either purposefully or as a result of AI’s unintelligible coded decision logic (Burrell, 2016). Using a Research through Design methodology, we attempt to make AI operations legible through iconography (Lindley et al., 2020; Pilling et al., 2020). We are currently gathering research through workshops, enabling us to test the rigour and disrupt the current iteration of iconography to provoke further iterations. The participants of the workshop complete game-like tasks using cards, which depict the icons and their associated text labels separately, as a medium to engage—in a tangible manner—the intangible and functions of these technologies. We have already had success in participants using with ease our initial iconography system, while also highlighting and exposing icons of interest; which are worth further research and discussion.
AB - The sociotechnical landscape has become more reliant on artificial intelligence (AI) operating via the Internet of Things (IoT). Technology is typically designed to ease users’ interactions, consequently concealing functionality, leading to various misconceptions regarding AI and how data is processed (Pilling and Coulton, 2019). However, obscuring functions and the incognito collection of data is profitable for companies (Bryson and Winfield, 2017; Mosco, 2014). Though, this intrusion of technology is questioned by users, concerning the security,privacy and the unknown implications of use (Bostrom, 2014; Bridle, 2018). Labelling AI as uncanny and illegible to users, either purposefully or as a result of AI’s unintelligible coded decision logic (Burrell, 2016). Using a Research through Design methodology, we attempt to make AI operations legible through iconography (Lindley et al., 2020; Pilling et al., 2020). We are currently gathering research through workshops, enabling us to test the rigour and disrupt the current iteration of iconography to provoke further iterations. The participants of the workshop complete game-like tasks using cards, which depict the icons and their associated text labels separately, as a medium to engage—in a tangible manner—the intangible and functions of these technologies. We have already had success in participants using with ease our initial iconography system, while also highlighting and exposing icons of interest; which are worth further research and discussion.
M3 - Abstract
T2 - International Transdisciplinary Conference
Y2 - 13 November 2020 through 15 November 2020
ER -