Behavior latticing synthesizes connections across unstructured user interactions to generate insights into underlying motivations, yielding deeper and more accurate user understanding than task-only models.
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Accurate individual predictions by AI recommenders produce societal harms through functional misalignment with human reflective goals, driven by fast-signal bias, feedback loops, and collective dynamics.
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Behavior Latticing: Inferring User Motivations from Unstructured Interactions
Behavior latticing synthesizes connections across unstructured user interactions to generate insights into underlying motivations, yielding deeper and more accurate user understanding than task-only models.
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Functional Misalignment in Human-AI Interactions on Digital Platforms
Accurate individual predictions by AI recommenders produce societal harms through functional misalignment with human reflective goals, driven by fast-signal bias, feedback loops, and collective dynamics.