LLM Generating Obfuscated Employee Feedback Summaries and Modification Suggestions
Summary
USPTO published patent application US20260099625A1 filed by Recep Colak, Daniel Perry, and Serena Jeblee on October 4, 2024. The application discloses systems and methods for using large language models to generate obfuscated summaries of employee feedback data and to provide modification suggestions based on that feedback. The system includes a manager feedback interface that displays obfuscated summaries to managers without revealing individual employee identities.
What changed
USPTO published patent application US20260099625A1 disclosing a system that uses large language models to generate obfuscated summaries of employee feedback data and provide modification suggestions. The system receives employee feedback, generates a prompt for an obfuscation LLM to create anonymous summaries, displays these summaries via a manager feedback interface, and can generate modification suggestions based on the underlying feedback data.
For compliance officers and legal professionals, this patent application signals emerging technology for HR data anonymization using AI. Organizations developing similar systems should consider data privacy compliance, employment law requirements, and employee consent obligations when implementing LLM-based feedback processing tools.
What to do next
- Monitor for patent grant status
Archived snapshot
Apr 14, 2026GovPing captured this document from the original source. If the source has since changed or been removed, this is the text as it existed at that time.
UTILIZING LARGE LANGUAGE MODELS TO GENERATE OBFUSCATED SUMMARIES OF EMPLOYEE FEEDBACK DATA AND MODIFICATION SUGGESTIONS BASED ON THE EMPLOYEE FEEDBACK DATA
Application US20260099625A1 Kind: A1 Apr 09, 2026
Inventors
Recep Colak, Daniel Perry, Serena Jeblee
Abstract
The present disclosure relates to systems, non-transitory computer-readable media, and methods for utilizing machine learning to generate an obfuscated summary for employee feedback data and generating a modification suggestion based on the employee feedback data. In particular, in one or more embodiments, the disclosed systems generate a prompt for an obfuscation and summary generation large language model to generate an obfuscated summary of employee feedback data and provide the obfuscated summary within a manager feedback interface on a manager client device. Moreover, in one or more embodiments, the disclosed systems receive a request to generate a modification suggestion from the manager feedback interface, then utilize a recommendation large language model to generate a modification suggestion based on the employee feedback data. Further, the disclosed systems provide the modification within the manager feedback interface on the manager client device.
CPC Classifications
G06F 21/6245 G06Q 10/0639
Filing Date
2024-10-04
Application No.
18906980
Related changes
Get daily alerts for USPTO Patent Applications - Business Methods (G06Q)
Daily digest delivered to your inbox.
Free. Unsubscribe anytime.
Source
About this page
Every important government, regulator, and court update from around the world. One place. Real-time. Free. Our mission
Source document text, dates, docket IDs, and authority are extracted directly from USPTO.
The summary, classification, recommended actions, deadlines, and penalty information are AI-generated from the original text and may contain errors. Always verify against the source document.
Classification
Who this affects
Taxonomy
Browse Categories
Get alerts for this source
We'll email you when USPTO Patent Applications - Business Methods (G06Q) publishes new changes.
Subscribed!
Optional. Filters your digest to exactly the updates that matter to you.