aiqbench analysis
This research presents a novel AI framework for inferring users' long-term life goals directly from unstructured computer usage patterns, moving beyond surface-level activity tracking. By integrating human feedback loops into the inference process, the system addresses the ambiguity of user intent and enhances personal agency in digital environments. This work represents a significant step toward deeply understanding user motivations within the intersection of artificial intelligence and human-computer interaction.
"What Are You Really Trying to Do?": Co-Creating Life Goals from Everyday Computer Use
arXiv:2605.00497v2 Announce Type: replace-cross Abstract: Recent advances in user modeling make it feasible to conduct open-ended inference over a person's everyday computer use. Despite longstanding visions of systems that deeply understand our actions and the purposes they serve in our lives, existing systems only capture what a person is doing in the moment, not why they are doing it, limiting these systems to surface-level support. We introduce striving co-creation, a process for inferring broader life goals from unstructured observations of computer use. Grounded in Activity Theory and Emmons' personal strivings framework, our system progressively constructs a hierarchical representation of a person's activities. Strivings are, however, difficult to fully resolve from observation alone, as the same action can be driven by many different goals. Our system therefore supports an editing interface that gives people agency over how they are understood by the system, feeding their corrections back into subsequent rounds of striving induction. In a week-long field deployment (N=14), we find that our co-creation process produces strivings that participants recognize as representative of their long-term goals and gives them greater agency than baseline methods.
Title:"What Are You Really Trying to Do?": Co-Creating Life Goals from Everyday Computer Use
Abstract:Recent advances in user modeling make it feasible to conduct open-ended inference over a person's everyday computer use. Despite longstanding visions of systems that deeply understand our actions and the purposes they serve in our lives, existing systems only capture what a person is doing in the moment, not why they are doing it, limiting these systems to surface-level support. We introduce striving co-creation, a process for inferring broader life goals from unstructured observations of computer use. Grounded in Activity Theory and Emmons' personal strivings framework, our system progressively constructs a hierarchical representation of a person's activities. Strivings are, however, difficult to fully resolve from observation alone, as the same action can be driven by many different goals. Our system therefore supports an editing interface that gives people agency over how they are understood by the system, feeding their corrections back into subsequent rounds of striving induction. In a week-long field deployment (N=14), we find that our co-creation process produces strivings that participants recognize as representative of their long-term goals and gives them greater agency than baseline methods.
Human-Computer Interaction (cs.HC); Artificial Intelligence (cs.AI); Computation and Language (cs.CL)
arXiv:2605.00497 [cs.HC]
(or arXiv:2605.00497v2 [cs.HC] for this version)
https://doi.org/10.48550/arXiv.2605.00497 Focus to learn more arXiv-issued DOI via DataCite
https://doi.org/10.1145/3830398.3830630 Focus to learn more DOI(s) linking to related resources
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Full text under the publisher's open licence · 301 words
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