17550401. URGENCY DRIVEN DYNAMIC EXPLAINABILITY simplified abstract (INTERNATIONAL BUSINESS MACHINES CORPORATION)

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URGENCY DRIVEN DYNAMIC EXPLAINABILITY

Organization Name

INTERNATIONAL BUSINESS MACHINES CORPORATION

Inventor(s)

Gandhi Sivakumar of Bentleigh (AU)

Kushal S. Patel of Pune (IN)

Luke Peter Macura of Lucas (AU)

Sarvesh S. Patel of Pune (IN)

URGENCY DRIVEN DYNAMIC EXPLAINABILITY - A simplified explanation of the abstract

This abstract first appeared for US patent application 17550401 titled 'URGENCY DRIVEN DYNAMIC EXPLAINABILITY

Simplified Explanation

The patent application describes a computer-implemented method that uses a machine learning model to generate answers to user queries. It determines the urgency level of the query and generates an explanation of the answer based on this urgency level. The answer and explanation are then presented to the user.

  • The method receives a query from a user device.
  • It uses a machine learning model to generate an answer to the query.
  • The urgency level of the query is determined.
  • An explanation of the answer is generated based on the urgency level.
  • The answer and explanation are presented to the user via the user device.

Potential Applications

  • Customer support systems that provide quick and accurate answers to user queries.
  • Virtual assistants that can understand and respond to user questions in real-time.
  • Chatbots that can provide explanations for their answers to improve user understanding.

Problems Solved

  • Improves the efficiency of answering user queries by using a machine learning model.
  • Provides explanations for answers to enhance user understanding.
  • Helps prioritize urgent queries and provide appropriate responses.

Benefits

  • Faster response times to user queries.
  • Improved user satisfaction and understanding.
  • More efficient use of computing resources.
  • Enhanced user experience with personalized explanations.


Original Abstract Submitted

A computer-implemented method includes: receiving, by a computing device, a query from a user device; generating, by the computing device and using a machine learning model, an answer to the query; determining, by the computing device, an urgency level of the query; generating, by the computing device, an explanation of the answer based on the determined urgency level; and presenting, by the computing device, the answer and the explanation to a user via the user device.