Abstract: Classification of the user of an attention application is moved from the cloud, where the classification is performed by advertisers based on trackers that follow a user, to the attention application itself. A user of the attention application controls inputs to the classification model and can exclude sensitive privacy information from inclusion in the classification model. The classification model is applied locally at the attention application to a catalog of advertisements and without revealing to trackers and advertisers whether attention was paid to particular ads. An analytics provider may have increased access to attention applications and can form ad campaigns and provide performance data thereon to advertisers without infringing attention user privacy. The system directs value away from trackers and advertisers and to attention application users and publishers.

Abstract: To provide user data to third-party services in a privacy compliant manner, an edge computing device within a content delivery network receives user data generated based on user interactions with web or application content from a client device proximate to the edge computing device, stores user biographical information, and performs a consent validation of the user data with respect to at least one third-party service. In response to determining that the user data passes the consent validation with respect to the third-party service, the edge computing device provides the user data to the third-party service.

Abstract: Classification of the user of an attention application is moved from the cloud, where the classification is performed by advertisers based on trackers that follow a user, to the attention application itself. A user of the attention application controls inputs to the classification model and can exclude sensitive privacy information from inclusion in the classification model. The classification model is applied locally at the attention application to a catalog of advertisements and without revealing to trackers and advertisers whether attention was paid to particular ads. An analytics provider may have increased access to attention applications and can form ad campaigns and provide performance data thereon to advertisers without infringing attention user privacy. The system directs value away from trackers and advertisers and to attention application users and publishers.

Abstract: Classification of the user of an attention application is moved from the cloud, where the classification is performed by advertisers based on trackers that follow a user, to the attention application itself. A user of the attention application controls inputs to the classification model and can exclude sensitive privacy information from inclusion in the classification model. The classification model is applied locally at the attention application to a catalog of advertisements and without revealing to trackers and advertisers whether attention was paid to particular ads. An analytics provider may have increased access to attention applications and can form ad campaigns and provide performance data thereon to advertisers without infringing attention user privacy. The system directs value away from trackers and advertisers and to attention application users and publishers.

Abstract: An attention application includes a digital asset wallet. The attention application can estimate the attention a user has spent such as on media content created by a publisher or ads sent by an advertiser. The attention application can pay an amount of the digital asset to the publishers based on the attention spent by the user or receive a payment of the digital asset if the user devoted sufficient attention to a paying advertiser.