Personalize with permission, not surprise
Design a chatbot personalization path that makes data use visible and controllable.
Trust risk A career bot wants to use past feedback to recommend a learning path. The recommendation can be useful and still feel invasive if the source is hidden. Consent path Source -> Reason -> Control Personalization needs a visible data trail. Tell users what you are using, why it changes the answer, and how they can change it. Surprise rec High relevance, low trust. Personalization becomes legible and reversible. Use personal data only when the user can understand and steer the effect. 01 Source 02 Reason 03 Control Make data visible The bot has access to manager feedback and…
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