US 2025/0063394 A1Published application

Detection of and recovery from failures of artificial intelligence/machine learning based algorithms

AssigneeAT&T Intellectual Property I, L.P.

InventorsFarooq Bari, Muhammad Umar Bin Farooq

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Abstract

Aspects of the subject disclosure may include, for example: building a computer-usable model; performing automated testing on the computer-usable model to determine whether the computer-usable model successfully handles a plurality of test scenarios; performing fault injection by injecting a plurality of faults into the computer-usable model to determine whether the computer-usable model successfully handles the plurality of faults, and facilitating deployment of the computer-usable model. Other aspects of the subject disclosure may include, for example: the deployed computer-usable model detecting and/or experiencing deviations, inconsistencies and/or anomalies; and activating one or more backup methods in response to the deployed computer-usable model detecting and/or experiencing deviations, inconsistencies and/or anomalies. The one or more backup methods can be implemented in a preferred order (e.g., depending upon the type of the deviations, inconsistencies and/or anomalies). Other embodiments are disclosed.

Claims20

Dependent claims

A device, comprising:

a processing system including a processor;
and
a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations, the operations comprising:
building a first computer-usable model that characterizes a system, wherein the building is based at least in part upon a defined plurality of performance metrics associated with the first computer-usable model;
obtaining a validation dataset;
utilizing the first computer-usable model and the validation dataset to establish a baseline performance of the first computer-usable model;
performing automated testing on the first computer-usable model to determine whether the first computer-usable model successfully handles a plurality of test scenarios, wherein the automated testing results in a first determination;
responsive to the first determination being that the first computer-usable model successfully handles the plurality of test scenarios, performing fault injection by injecting a plurality of faults into the first computer-usable model and determining whether the first computer-usable model successfully handles the plurality of faults, wherein the fault injection results in a second determination;
and
responsive to the second determination being that the first computer-usable model successfully handles the plurality of faults, facilitating deployment of the first computer-usable model.

7 more elements

A non-transitory machine-readable medium comprising executable instructions that, when executed by a processing system including a processor, facilitate performance of operations, the operations comprising:

deploying a computer-usable model that characterizes a system, resulting in a deployed model;
obtaining input data related to operation of the system;
generating a failure flag in response to a detecting, via use of the deployed model and the input data, of:
one or more input parameters in live data diverging significantly from training data;
one or more deviations in a performance of the deployed model;
one or more key performance indicators (KPIs) in a live network falling below a defined KPI threshold;
one or more artificial intelligence (AI) based abnormal behaviors via use of an AI model other than the deployed model;
one or more machine learning (ML) based abnormal behaviors via use of an ML model other than the deployed model;
or
any combination thereof;
and
activating, responsive to the generating of the failure flag, a backup mechanism that facilitates:
replacing the deployed model;
or
supplementing the deployed model.

12 more elements

A method, comprising:

detecting, by a processing system including a processor, one or more unexpected results associated with use of a deployed computer-usable model that characterizes a system;
responsive to the detecting of the one or more unexpected results, generating by the processing system a failure indicator;
responsive to the generating of the failure indicator, selecting by the processing system a backup mechanism to replace or supplement the deployed computer-usable model, wherein the selecting results in a selected backup mechanism, and wherein the selected backup mechanism is one of a plurality of potential backup mechanisms from which selection is made;
and
responsive to the selecting of the selected backup mechanism, activating by the processing system the selected backup mechanism in order to replace the deployed computer-usable model or in order to supplement the deployed computer-usable model.

2 more elements

Dependencies are inferred from the claim text.