Opportunities for Automating Email Processing: A Need-Finding Study
Name
mailbot.pdf
Description
Accepted version
Size
895.16 KB
Format
Adobe PDF
Checksum (MD5)
2b17a2906be7da5b729dc71d585c5fda
Author(s)
Park, Soya
Zhang, Amy Xian
Murray, Luke S.
Karger, David R
Date Issued
May 2019
Journal
Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
Publisher
Association for Computing Machinery (ACM)
Citation
Park, Soya et al. "Opportunities for Automating Email Processing: A Need-Finding Study." Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, May 2019, Glasgow, Scotland, Association for Computing Machinery, May 2019. © 2019 Association for Computing Machinery
Version
Author's final manuscript
Abstract
Email management consumes significant effort from senders and recipients. Some of this work might be automatable. We performed a mixed-methods need-finding study to learn: (i) what sort of automatic email handling users want, and (ii) what kinds of information and computation are needed to support that automation. Our investigation included a design workshop to identify categories of needs, a survey to better understand those categories, and a classification of existing email automation software to determine which needs have been addressed. Our results highlight the need for: a richer data model for rules, more ways to manage attention, leveraging internal and external email context, complex processing such as response aggregation, and affordances for senders. To further investigate our findings, we developed a platform for authoring small scripts over a user’s inbox. Of the automations found in our studies, half are impossible in popular email clients, motivating new design directions.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/3290605.3300604
