Invention Application
- Patent Title: MACHINE LEARNING TRACEBACK-ENABLED DECISION RATIONALES AS MODELS FOR EXPLAINABILITY
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Application No.: US17379937Application Date: 2021-07-19
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Publication No.: US20220237509A1Publication Date: 2022-07-28
- Inventor: John Frederick Courtney , Kenneth Paul Baclawski , Dieter Gawlick , Kenny C. Gross , Guang Chao Wang , Anna Chystiakova , Richard Paul Sonderegger , Zhen Hua Liu
- Applicant: Oracle International Corporation
- Applicant Address: US CA Redwood Shores
- Assignee: Oracle International Corporation
- Current Assignee: Oracle International Corporation
- Current Assignee Address: US CA Redwood Shores
- Main IPC: G06N20/00
- IPC: G06N20/00 ; G06N5/04 ; G06F11/32

Abstract:
Techniques for providing decision rationales for machine-learning guided processes are described herein. In some embodiments, the techniques described herein include processing queries for an explanation of an outcome of a set of one or more decisions guided by one or more machine-learning processes with supervision by at least one human operator. Responsive to receiving the query, a system determines, based on a set of one or more rationale data structures, whether the outcome was caused by human operator error or the one or more machine-learning processes. The system then generates a query response indicating whether the outcome was caused by the human operator error or the one or more machine-learning processes.
Public/Granted literature
- US2165821A Hand cabbage setter Public/Granted day:1939-07-11
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