Workshop Paper
Kazi Sinthia Kabir, Jason Wiese
CHI 2022 Workshop on the Grand Challenges in Personal Informatics and AI, 2022 May
CHI 2022 Workshop on the Grand Challenges in Personal Informatics and AI, 2022 May
View PDF
Cite
Cite
APA
Click to copy
Kabir, K. S., & Wiese, J. (2022, May). The Challenge for Just-in-Time Adaptive Interventions: Incomplete or Missing Data. CHI 2022 Workshop on the Grand Challenges in Personal Informatics and AI.
Chicago/Turabian
Click to copy
Kabir, Kazi Sinthia, and Jason Wiese. “The Challenge for Just-in-Time Adaptive Interventions: Incomplete or Missing Data.” CHI 2022 Workshop on the Grand Challenges in Personal Informatics and AI, May 2022.
MLA
Click to copy
Kabir, Kazi Sinthia, and Jason Wiese. The Challenge for Just-in-Time Adaptive Interventions: Incomplete or Missing Data. CHI 2022 Workshop on the Grand Challenges in Personal Informatics and AI, May 2022.
BibTeX Click to copy
@misc{kabir2022a,
title = {The Challenge for Just-in-Time Adaptive Interventions: Incomplete or Missing Data},
year = {2022},
month = may,
publisher = {CHI 2022 Workshop on the Grand Challenges in Personal Informatics and AI},
author = {Kabir, Kazi Sinthia and Wiese, Jason},
month_numeric = {5}
}
Just-in-Time Adaptive Interventions (JITAIs) are AI-based personal informatics systems that provide users with personalized feedback based on their self-tracked data. The performance of these systems is influenced by how users engage with these systems. Therefore, this position paper aims to facilitate discussion about addressing user interactions that may lead to missing or incomplete data and, subsequently, impact the personalization aspect of JITAIs. We posit open questions about two such interactions: episodic abandonment and retrospective tracking. As one approach to answering these questions, we suggest that the algorithms in these systems require active human engagement for more accurate information about the users’ current state and their desired personalization.
