Generating adaptive textual explanations of output predicted by trained artificial-intelligence processes

A computer-implemented method, comprising:

• using at least one processor, training adaptively an artificial intelligence process based on a plurality of training datasets associated with a first temporal interval, and validating the trained artificial intelligence process based on a plurality of validation datasets associated with a second temporal interval, wherein the second temporal interval is subsequent to the first temporal interval;
• receiving, using the at least one processor, an input dataset based on elements of first interaction data associated with a third temporal interval and a temporal identifier characterizing a fourth temporal interval, the fourth temporal interval being subsequent to the third temporal interval, and the input dataset comprising feature values of a plurality of input features corresponding to the first interaction data;
• using the at least one processor, and based on the application of a trained artificial intelligence process to the input dataset, generating output data representative of a predicted likelihood of an occurrence of an event during the fourth temporal interval;
• using the at least one processor, training an explainability process based on the plurality of validation datasets;
• using the at least one processor, provisioning pairs of the feature values and Shapley feature values to the trained explainability process, where each pair comprises a corresponding one of the feature values and a Shapley feature value associated with the corresponding feature value;
• using the at least one processor, and based on an application of the trained explainability process to the pairs of the feature values and Shapley feature values, generating a first element of textual content that characterizes an outcome associated with the predicted likelihood of the occurrence of the event, the first element of textual content being associated with the corresponding feature value;
• and
• using the at least one processor, transmitting a portion of the output data and the first element of textual content to a computing system, wherein the computing system is configured to generate or modify second interaction data based on the portion of the output data, and to provision notification data comprising the first element of textual content to a device associated with the first interaction data.

A tangible, non-transitory computer-readable medium storing instructions that, when executed by at least one processor, cause the at least one processor to perform a method, comprising:

• training adaptively an artificial intelligence process based on a plurality of training datasets associated with a first temporal interval, and validating the trained artificial intelligence process based on a plurality of validation datasets associated with a second temporal interval, wherein the second temporal interval is subsequent to the first temporal interval;
• receiving an input dataset based on elements of first interaction data associated with a third temporal interval and a temporal identifier characterizing a fourth temporal interval, the fourth temporal interval being subsequent to the third first temporal interval, and the input dataset comprising feature values of a plurality of input features corresponding to the first interaction data;
• based on an application of the trained artificial intelligence process to the input dataset, generating output data representative of a predicted likelihood of an occurrence of an event during the fourth temporal interval;
• training an explainability process based on the plurality of validation datasets;
• provisioning pairs of the feature values and Shapley feature values to the trained explainability process, where each pair comprises a corresponding one of the feature values and a Shapley feature value associated with the corresponding feature value;
• based on an application of the trained explainability process to the pairs of the feature values and Shapley feature values, generating an element of textual content that characterizes an outcome associated with the predicted likelihood of the occurrence of the event, the element of textual content being associated with the corresponding feature value;
• and
• transmitting a portion of the output data, and the element of textual content to a computing system, wherein the computing system is configured to generate or modify second interaction data based on the portion of the output data, and to provision notification data comprising the element of textual content to a device associated with the first interaction data.