Auditable authorship attribution with event tracking and mock content
OwnerSoumitri Kolavennu, Raj Bharadwaj +5inventors
InventorsSoumitri Kolavennu, Raj Bharadwaj, Lavanya Basavaraju, Jayant Chawla, Christopher Ziolkowski, Valerie Lancelle, Christopher Davis
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Abstract
A content editor or a plugin thereto automatically generates authorship tokens that identify content authored by a human author or an artificial author. The authorship tokens are applied to the work while the work is being produced. Thus, subsequent review of the work can identify regions produced by a human author and other regions produced by an artificial intelligence.
Claims20
A method comprising:
- obtaining initial content that was generated during a content editing session;
- generating a prompt based on the initial content;
- selecting at least one generator from among a set of generators based, at least in part, on a content type of the initial content;
- for each selected generator:
- using the prompt to produce new content;
- comparing the new content to the initial content;
- and
- making a respective determination whether the new content and the initial content are similar based on whether a similarity threshold is satisfied;
- using the respective determination for each selected generator, ensuring that an authorship token is associated with the initial content,
- wherein the authorship token includes a form indicating that an associated content region has human rather than an artificial authorship or artificial rather than human authorship.
A non-transitory computer-readable storage medium storing instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising:
- one or more processors communicatively coupled to a memory subsystem storing instructions which, when executed, cause the one or more processors to perform:
- obtaining initial content that was generated during a content editing session;
- generating a prompt based on the initial content;
- selecting at least one generator via an artificial intelligence model from among a set of generators based, at least in part, on a content type of the initial content determined by the artificial intelligence model;
- for each selected generator:
- using the prompt to produce new content;
- comparing the new content to the initial content;
- and
- making a respective determination whether the new content and the initial content are similar based on whether a similarity threshold is satisfied;
- using the respective determination for each selected generator, ensuring that an authorship token is associated with the initial content,
- wherein the authorship token includes a form indicating that an associated content region has human rather than an artificial authorship or artificial rather than human authorship.
Dependencies are inferred from the claim text.