Rights statement: © ACM, 2019. 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 Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems,Paper No. 379 https://dl.acm.org/citation.cfm?id=3300609
Accepted author manuscript, 1.87 MB, PDF document
Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License
Final published version
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
}
TY - GEN
T1 - Programmable Donations
T2 - ACM CHI Conference on Human Factors in Computing Systems
AU - Elsden, Chris
AU - Trotter, Ludwig Korbinian
AU - Harding, Michael Paul
AU - Davies, Nigel Andrew Justin
AU - Speed, Chris
AU - Vines, John
N1 - © ACM, 2019. 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 Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems,Paper No. 379 https://dl.acm.org/citation.cfm?id=3300609
PY - 2019/5/4
Y1 - 2019/5/4
N2 - This paper reports on a co-speculative interview study with charitable donors to explore the future of programmable, conditional and data-driven donations. Responding to the rapid emergence of blockchain-based and AI-supported financial technologies, we specifically examine the potential of automated, third-party ‘escrows’, where donations are held before they are released or returned based on specified rules and conditions. To explore this we conducted pilotworkshops with 9 participants and an interview study in which 14 further participants were asked about their experiences of donating money, and invited to co-speculate on a service for programmable giving. The study elicitedhow data-driven conditionality and automation could be leveraged to create novel donor experiences, however also illustrated the inherent tensions and challenges involved in giving programmatically. Reflecting on these findings, ourpaper contributes implications both for the design of programmable aid platforms, and the design of escrow-based financial services in general.
AB - This paper reports on a co-speculative interview study with charitable donors to explore the future of programmable, conditional and data-driven donations. Responding to the rapid emergence of blockchain-based and AI-supported financial technologies, we specifically examine the potential of automated, third-party ‘escrows’, where donations are held before they are released or returned based on specified rules and conditions. To explore this we conducted pilotworkshops with 9 participants and an interview study in which 14 further participants were asked about their experiences of donating money, and invited to co-speculate on a service for programmable giving. The study elicitedhow data-driven conditionality and automation could be leveraged to create novel donor experiences, however also illustrated the inherent tensions and challenges involved in giving programmatically. Reflecting on these findings, ourpaper contributes implications both for the design of programmable aid platforms, and the design of escrow-based financial services in general.
U2 - 10.1145/3290605.3300609
DO - 10.1145/3290605.3300609
M3 - Conference contribution/Paper
SN - 9781450359702
BT - ACM CHI Conference on Human Factors in Computing Systems
PB - ACM
CY - New York
Y2 - 4 May 2019 through 9 May 2019
ER -