AGENT TO BOT TRANSFER
    5.
    发明申请

    公开(公告)号:US20210160374A1

    公开(公告)日:2021-05-27

    申请号:US16695401

    申请日:2019-11-26

    Abstract: A method, a computer program product, and a computer system determine when to transfer a communication session from an agent to a bot. The method includes monitoring the communication session between the agent and a user. The method includes determining a continuing utility value indicating a predicted continuing cost to maintaining the communication session with the agent. The continuing utility value is indicative of a predicted continuing benefit to maintaining the communication with the agent. The method includes determining a transferring utility value indicating a predicted transferring cost to transferring the communication session from the agent to the bot. The transferring utility value is indicative of a predicted transferring benefit to transferring the communication session from the agent to the bot. The method includes, as a result of the predicted transferring benefit being greater than the predicted continuing benefit, transferring the communication session from the agent to the bot.

    PROMOTING REFLECTIVE ENGAGEMENT WITH RANKED ALTERNATIVES PRODUCED BY AN ARTIFICIAL INTELLIGENCE SYSTEM

    公开(公告)号:US20200226483A1

    公开(公告)日:2020-07-16

    申请号:US16248927

    申请日:2019-01-16

    Abstract: One or more alternatives are received. Each of the one or more alternatives has an associated weight. An advocate-agent corresponding to each of the one or more alternatives is generated in which each advocate-agent is configured to advocate for the corresponding alternative. An interaction characteristic is determined for each advocate-agent based on the associated weight and an engagement model. An engagement metric associated with each advocate-agent is received in which the engagement metric is indicative of an attention level of a user towards the particular alternative associated with the particular advocate-agent. The interaction characteristic a particular advocate-agent is adjusted based upon the engagement metric associated with the particular advocate-agent according to the engagement model.

    Mitigating statistical bias in artificial intelligence models

    公开(公告)号:US11586849B2

    公开(公告)日:2023-02-21

    申请号:US16745872

    申请日:2020-01-17

    Abstract: Techniques regarding mitigating bias in one or more machine learning models are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise a model component that can evaluate a machine learning model at a plurality of threshold settings to generate a sample set and can define a relationship between a fairness metric and a utility metric of the machine learning model based on the sample set.

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