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  4. Resonance: Drawing from Memories to Imagine Positive Futures through AI-Augmented Journaling

Resonance: Drawing from Memories to Imagine Positive Futures through AI-Augmented Journaling

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Author(s)
Zulfikar, Wazeer
•
Chiaravalloti, Treyden
•
Shen, Jocelyn
•
Picard, Rosalind
•
Maes, Pattie
Date Issued
October 9, 2025
Publisher
ACM|The Augmented Humans International Conference 2025
Citation
Wazeer Zulfikar, Treyden Chiaravalloti, Jocelyn Shen, Rosalind Picard, and Pattie Maes. 2025. Resonance: Drawing from Memories to Imagine Positive Futures through AI-Augmented Journaling. In The Augmented Humans International Conference 2025 (AHs 2025), March 16–20, 2025, Masdar City, Abu Dhabi, United Arab Emirates. ACM, New York, NY, USA, 17 pages.
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Final published version
Abstract
People inherently use experiences of their past while imagining their future, a capability that plays a crucial role in mental health. Resonance is an AI-powered journaling tool designed to augment this ability by offering AI-generated, action-oriented suggestions for future activities based on the user’s own past memories. Suggestions are offered when a new memory is logged and are followed by a prompt for the user to imagine carrying out the suggestion. In a two-week randomized controlled study (N=55), we found that using Resonance significantly improved mental health outcomes, reducing the users’ PHQ8 scores, a measure of current depression, and increasing their daily positive affect, particularly when they would likely act on the suggestion. Notably, the effectiveness of the suggestions was higher when they were personal, novel, and referenced the user’s logged memories. Finally, through open-ended feedback, we discuss the factors that encouraged or hindered the use of the tool.
Description
AHs 2025, Masdar City, Abu Dhabi, United Arab Emirates
MIT Department
Massachusetts Institute of Technology. Media Laboratory
Terms of Use
Creative Commons Attribution
https://creativecommons.org/licenses/by/4.0/
Persistent DSpace Link
https://hdl.handle.net/1721.1/164076
DOI of Published Version
https://doi.org/10.1145/3745900.3746099
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