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This article covers three practical approaches for studying agentic AI when the system’s behavior is a moving target. Trust is inherently longitudinal over time. A snapshot study capturing the moment alone describes almost nothing about how the relationship is changing, which misses the evolving relationship arc. The author discusses using modified diary studies, longitudinal trust measurement, and relationship arc research to study trust. The article also includes guidance on getting started with a first longitudinal study.
[See the full post at: Researching What Changes: UX Methods for AI Systems That Learn Over Time]
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