Samenvatting
Current data representations in AI-powered self-tracking wearable systems convey an objective, one-fits-all and top-down perspective
over tracked activities, often leading to tensions between subjective experience and objectified self, unintended effects, and abandonment
of devices. Scholarly design guidelines suggest moving towards more personalized experiences integrating subjective stance in both the
data collection and consequent prediction and data representation, however, this is an underexplored field.We argue that multistability
and ambiguity could be adopted as research approaches to explore individuals’ multiple interpretations of self-tracking data with
respect to their personal goals, values and needs. The ultimate goal is to customize data representations through AI.
over tracked activities, often leading to tensions between subjective experience and objectified self, unintended effects, and abandonment
of devices. Scholarly design guidelines suggest moving towards more personalized experiences integrating subjective stance in both the
data collection and consequent prediction and data representation, however, this is an underexplored field.We argue that multistability
and ambiguity could be adopted as research approaches to explore individuals’ multiple interpretations of self-tracking data with
respect to their personal goals, values and needs. The ultimate goal is to customize data representations through AI.
| Originele taal-2 | Engels |
|---|---|
| Status | Gepubliceerd - 1 mei 2022 |
| Evenement | CHI 2022 Workshop on Grand Challenges for Personal Informatics and AI - Duur: 11 mei 2022 → 11 mei 2022 |
Workshop
| Workshop | CHI 2022 Workshop on Grand Challenges for Personal Informatics and AI |
|---|---|
| Periode | 11/05/22 → 11/05/22 |