Abstract: Systems and methods are disclosed herein for protecting and managing usage of user data for artificial intelligence (AI) model training. More particularly, systems and related methods are disclosed for collecting user data by tracking interactions with a user interface of a user device in accordance with user defined consent parameters. Further, the collected data may be stored in a training database and leveraged to train an AI model for the user. However, upon receiving an input to delete data from the training database, either explicitly or from deleting an application installed on (or otherwise accessed via) a user device, the data may be removed from the training database and new AI model weights are calculated and provided to the AI model to fine tune the AI model.

Abstract: Systems and methods are disclosed for modifying content items based on eye tracking data, which may be indicative of saccadic suppression of a user. A plurality of content items is displayed on a device, including a first content item displayed at a first region. In an example, based on eye tracking data of the user, the onset of a saccade of the user is detected. An end location and duration of the saccade may be predicted based at least in part on the eye tracking data. A saccadic suppression window is identified based on the predicted duration. Based at least in part on the predicted end location, the display of the first content item is modified at a time that is within the saccadic suppression window.

Abstract: Systems and methods are disclosed for modifying content items based on eye tracking data, which may be indicative of saccadic suppression of a user. A plurality of content items is displayed on a device, including a first content item displayed at a first region. In an example, based on eye tracking data of the user, the onset of a saccade of the user is detected. An end location and duration of the saccade may be predicted based at least in part on the eye tracking data. A saccadic suppression window is identified based on the predicted duration. Based at least in part on the predicted end location, the display of the first content item is modified at a time that is within the saccadic suppression window.