A Right Time to Give:Beyond Saving Time in Automated Conditional Donations

Bidwell, Nicola J. and Elsden, Chris and Trotter, Ludwig and Hallwright, Josh and Moore, Sadie and Jeite-Delbridge, Kate and Harding, Michael and Shaw, Peter and Davies, Nigel and Speed, Chris and Vines, John (2021) A Right Time to Give:Beyond Saving Time in Automated Conditional Donations. In: CHI '21: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. ACM, JPN, pp. 1-20. ISBN 9781450380966

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Abstract

Smart Donations is a blockchain-based platform that offers users ‘contracts’ that donate funds to certain causes in response to real-world events e.g., whenever an earthquake is detected or an activist tweets about refugees. We designed Smart donations with Oxfam Australia, trialled it for 8-weeks with 86 people, recorded platform analytics and qualitatively analysed questionnaires and interviews about user experiences. Temporal qualities emerge when automation enforces conditions that contributed to participants’ awareness of events that are usually unconscious, and senses of immediacy in contributing to crisis response and ongoing involvement in situations far-away while awaiting conditions to be met. We suggest data driven automation can reveal diverse temporal registers, in real-world phenomena, sociality, morality and everyday life, which contributes to experiencing a ‘right time’ to donate that is not limited to productivity or efficiency. Thus, we recommend a sensitivity to right time in designing for multiple temporalities in FinTech more generally.

Item Type:
Contribution in Book/Report/Proceedings
Additional Information:
© ACM, 2021. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in PCHI '21: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems http://doi.acm.org/10.1145/3411764.3445371
ID Code:
155764
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Deposited On:
04 Jun 2021 11:35
Refereed?:
Yes
Published?:
Published
Last Modified:
24 Oct 2021 00:59