US-20260129121-A1 - DEVICE, SYSTEM AND METHOD FOR CONTROLLING ARTIFICIAL INTELLIGENCE USAGE

US20260129121A1US 20260129121 A1US20260129121 A1US 20260129121A1US-20260129121-A1

Abstract

A computing device determines a relative weightage of human-in-the-loop component usage to artificial intelligence component usage in a computing process that includes human decision-making and artificial intelligence decision-making. When the relative weightage is below a given range, such that the human-in-the-loop component usage is low relative to the artificial intelligence component usage: the computing device adjusts the computing process to increase the human-in-the-loop component usage relative to the artificial intelligence component usage. When the relative weightage is above the given range, such that the human-in-the-loop component usage is high relative to the artificial intelligence component usage: the computing device adjusts the computing process to decrease the human-in-the-loop component usage relative to the artificial intelligence component usage

Inventors

BING QIN LIM
Brian J. Frommelt
Brandon Christensen

Assignees

MOTOROLA SOLUTIONS, INC.

Dates

Publication Date: 20260507
Application Date: 20241107

Claims (20)

1 . A method comprising: determining, at a computing device, a relative weightage of human-in-the-loop component usage to artificial intelligence component usage in a computing process that includes human decision-making and artificial intelligence decision-making; when the relative weightage is below a given range, such that the human-in-the-loop component usage is low relative to the artificial intelligence component usage: adjusting, via the computing device, the computing process to increase the human-in-the-loop component usage relative to the artificial intelligence component usage; and when the relative weightage is above the given range, such that the human-in-the-loop component usage is high relative to the artificial intelligence component usage: adjusting, via the computing device, the computing process to decrease the human-in-the-loop component usage relative to the artificial intelligence component usage.
2 . The method of claim 1 , wherein adjusting the computing process to increase the human-in-the-loop component usage relative to the artificial intelligence component usage comprises: increasing a threshold in the computing process for implementing an artificial intelligence component.
3 . The method of claim 1 , wherein adjusting the computing process to increase the human-in-the-loop component usage relative to the artificial intelligence component usage comprises: deactivating one or more given artificial intelligence based features of the computing process.
4 . The method of claim 1 , wherein adjusting the computing process to increase the human-in-the-loop component usage relative to the artificial intelligence component usage comprises one or more of: changing a type of artificial intelligence algorithm used in the computing process from a theory-of-mind type artificial intelligence algorithm to a limited-memory artificial type intelligence algorithm or a reactive type artificial intelligence algorithm; changing the type of artificial intelligence algorithm used in the computing process from the limited-memory type artificial intelligence algorithm to the reactive type artificial intelligence algorithm; changing the type of artificial intelligence algorithm used in the computing process from a deep learning type artificial intelligence algorithm to a machine-learning type artificial intelligence algorithm; changing the type of artificial intelligence algorithm used in the computing process from a continuous-learning type artificial intelligence algorithm to a pre-trained type artificial intelligence algorithm; changing the type of artificial intelligence algorithm used in the computing process from an unsupervised-learning type artificial intelligence algorithm to a supervised-learning type artificial intelligence algorithm; and replacing the artificial intelligence algorithm with a programming-based algorithm.
5 . The method of claim 1 , wherein adjusting the computing process to decrease the human-in-the-loop component usage relative to the artificial intelligence component usage comprises: decreasing a threshold in the computing process for implementing an artificial intelligence component.
6 . The method of claim 1 , wherein adjusting the computing process to decrease the human-in-the-loop component usage relative to the artificial intelligence component usage comprises: activating one or more given artificial intelligence based features of the computing process.
7 . The method of claim 1 , wherein adjusting the computing process to decrease the human-in-the-loop component usage relative to the artificial intelligence component usage comprises one or more of: changing a type of artificial intelligence algorithm used in the computing process from a reactive type artificial intelligence algorithm to a limited-memory artificial type intelligence algorithm or a theory-of-mind type artificial intelligence algorithm; changing the type of artificial intelligence algorithm used in the computing process from the limited-memory type artificial intelligence algorithm to the theory-of-mind type artificial intelligence algorithm; changing the type of artificial intelligence algorithm used in the computing process from a machine-learning type artificial intelligence algorithm to a deep learning type artificial intelligence algorithm; changing the type of artificial intelligence algorithm used in the computing process from a pre-trained type artificial intelligence algorithm to a continuous-learning type artificial intelligence algorithm; changing the type of artificial intelligence algorithm used in the computing process from a supervised-learning type artificial intelligence algorithm to an unsupervised-learning type artificial intelligence algorithm; and replacing a programming-based algorithm with the artificial intelligence algorithm.
8 . The method of claim 1 , wherein adjusting the computing process to increase or decrease the human-in-the-loop component usage relative to the artificial intelligence component usage comprises: controlling a notification device to provide an indication of the adjusting; receiving, from a client device associated with the notification device, an acceptance of the adjusting; and implementing the adjusting in response to receiving the acceptance.
9 . The method of claim 1 , further comprising: adjusting the given range based on one or more factors associated with implementing the computing process.
10 . The method of claim 1 , further comprising one or more of: generating a dashboard at a display screen, the dashboard providing indications of the adjusting; and generating an incident report at the display screen, the incident report providing one or more indications at text of the incident screen that describe respective human actions that were assisted by the artificial intelligence component.
11 . The method of claim 1 , wherein the relative weightage comprises an average relative weightage, based on average, or total, human-in-the-loop component usage to average, or total, artificial intelligence component usage for a plurality of computing processes, including the computing process, that occur at different stages of an incident response, and the method further comprises: adjusting one or more the plurality of computing processes to increase or decrease respective human-in-the-loop component usage relative to respective artificial intelligence component usage, to bring the average relative weightage, for the plurality of computing processes, to within the given range.
12 . The method of claim 1 , wherein the relative weightage comprises an average relative weightage, based on average, or total, human-in-the-loop component usage to average, or total, artificial intelligence component usage for a plurality of computing processes, including the computing process, that occur at different stages of an incident response, and the method further comprises: adjusting one or more the plurality of computing processes to increase or decrease respective human-in-the-loop component usage relative to respective artificial intelligence component usage, to bring the relative weightage, for the plurality of computing processes, to within the given range.
13 . A computing device comprising: a controller; and a computer-readable storage medium having stored thereon program instructions that, when executed by the controller, causes the controller to perform a set of operations comprising: determining a relative weightage of human-in-the-loop component usage to artificial intelligence component usage in a computing process that includes human decision-making and artificial intelligence decision-making; when the relative weightage is below a given range, such that the human-in-the-loop component usage is low relative to the artificial intelligence component usage: adjusting the computing process to increase the human-in-the-loop component usage relative to the artificial intelligence component usage; and when the relative weightage is above the given range, such that the human-in-the-loop component usage is high relative to the artificial intelligence component usage: adjusting the computing process to decrease the human-in-the-loop component usage relative to the artificial intelligence component usage.
14 . The computing device of claim 13 , wherein adjusting the computing process to increase the human-in-the-loop component usage relative to the artificial intelligence component usage comprises one or more of: increasing a threshold in the computing process for implementing an artificial intelligence component; deactivating one or more given artificial intelligence based features of the computing process. changing a type of artificial intelligence algorithm used in the computing process from a theory-of-mind type artificial intelligence algorithm to a limited-memory artificial type intelligence algorithm or a reactive type artificial intelligence algorithm; changing the type of artificial intelligence algorithm used in the computing process from the limited-memory type artificial intelligence algorithm to the reactive type artificial intelligence algorithm; changing the type of artificial intelligence algorithm used in the computing process from a deep learning type artificial intelligence algorithm to a machine-learning type artificial intelligence algorithm; changing the type of artificial intelligence algorithm used in the computing process from a continuous-learning type artificial intelligence algorithm to a pre-trained type artificial intelligence algorithm; changing the type of artificial intelligence algorithm used in the computing process from an unsupervised-learning type artificial intelligence algorithm to a supervised-learning type artificial intelligence algorithm; and replacing the artificial intelligence algorithm with a programming-based algorithm;
15 . The computing device of claim 13 , wherein adjusting the computing process to decrease the human-in-the-loop component usage relative to the artificial intelligence component usage comprises one or more of: decreasing a threshold in the computing process for implementing an artificial intelligence component; activating one or more given artificial intelligence based features of the computing process; changing a type of artificial intelligence algorithm used in the computing process from a reactive type artificial intelligence algorithm to a limited-memory artificial type intelligence algorithm or a theory-of-mind type artificial intelligence algorithm; changing the type of artificial intelligence algorithm used in the computing process from the limited-memory type artificial intelligence algorithm to the theory-of-mind type artificial intelligence algorithm; changing the type of artificial intelligence algorithm used in the computing process from a machine-learning type artificial intelligence algorithm to a deep learning type artificial intelligence algorithm; changing the type of artificial intelligence algorithm used in the computing process from a pre-trained type artificial intelligence algorithm to a continuous-learning type artificial intelligence algorithm; changing the type of artificial intelligence algorithm used in the computing process from a supervised-learning type artificial intelligence algorithm to an unsupervised-learning type artificial intelligence algorithm; and replacing a programming-based algorithm with the artificial intelligence algorithm.
16 . The computing device of claim 13 , wherein adjusting the computing process to increase or decrease the human-in-the-loop component usage relative to the artificial intelligence component usage comprises: controlling a notification device to provide an indication of the adjusting; receiving, from a client device associated with the notification device, an acceptance of the adjusting; and implementing the adjusting in response to receiving the acceptance.
17 . The computing device of claim 13 , wherein the set of operations further comprises: adjusting the given range based on one or more factors associated with implementing the computing process.
18 . The computing device of claim 13 , wherein the set of operations further comprises one or more of: generating a dashboard at a display screen, the dashboard providing indications of the adjusting; and generating an incident report at the display screen, the incident report providing one or more indications at text of the incident screen that describe respective human actions that were assisted by the artificial intelligence component.
19 . The computing device of claim 13 , wherein the relative weightage comprises an average relative weightage, based on average, or total, human-in-the-loop component usage to average, or total, artificial intelligence component usage for a plurality of computing processes, including the computing process, that occur at different stages of an incident response, and the method further comprises: adjusting one or more the plurality of computing processes to increase or decrease respective human-in-the-loop component usage relative to respective artificial intelligence component usage, to bring the average relative weightage, for the plurality of computing processes, to within the given range.
20 . The computing device of claim 13 , wherein the relative weightage comprises an average relative weightage, based on average, or total, human-in-the-loop component usage to average, or total, artificial intelligence component usage for a plurality of computing processes, including the computing process, that occur at different stages of an incident response, and the method further comprises: adjusting one or more the plurality of computing processes to increase or decrease respective human-in-the-loop component usage relative to respective artificial intelligence component usage, to bring the relative weightage, for the plurality of computing processes, to within the given range.

Description

BACKGROUND OF THE INVENTION The increasing integration of artificial intelligence (AI) in public safety (PS) agencies, and other types of agencies, has introduced complex technical challenges in managing AI usage. PS agencies may rely on AI to assist with decision-making in high-stakes environments such as 911 dispatch centers and law enforcement operations. Similarly, medical personnel may rely on AI to assist with medical diagnoses, and the like. However, how often AI is used, especially in critical situations, such as public safety incidents, remains a significant technical challenge. BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS The accompanying figures, where like reference numerals refer to identical or functionally similar elements throughout the separate views, together with the detailed description below, are incorporated in and form part of the specification, and serve to further illustrate embodiments of concepts that include the claimed invention, and explain various principles and advantages of those embodiments. FIG. 1 is a system for controlling artificial intelligence usage, in accordance with some examples. FIG. 2 is a device diagram showing a device structure of a computing device for controlling artificial intelligence usage, in accordance with some examples. FIG. 3 is a flowchart of a method for controlling artificial intelligence usage, in accordance with some examples. FIG. 4 depicts a portion of the system of FIG. 1 implementing aspects of a method for controlling artificial intelligence usage, in accordance with some examples. FIG. 5 depicts the portion of the system of FIG. 1 continuing to implement aspects of a method for controlling artificial intelligence usage, in accordance with some examples. FIG. 6 depicts the portion of the system of FIG. 1 continuing to implement aspects of a method for controlling artificial intelligence usage, in accordance with some examples. FIG. 7 depicts a dashboard providing indications of adjustments of artificial intelligence usage for a plurality of computing processes and at different stages of an incident response. Skilled artisans will appreciate that elements in the figures are illustrated for simplicity and clarity and have not necessarily been drawn to scale. For example, the dimensions of some of the elements in the figures may be exaggerated relative to other elements to help to improve understanding of embodiments of the present invention. The apparatus and method components have been represented where appropriate by conventional symbols in the drawings, showing only those specific details that are pertinent to understanding the embodiments of the present invention so as not to obscure the disclosure with details that will be readily apparent to those of ordinary skill in the art having the benefit of the description herein. DETAILED DESCRIPTION OF THE INVENTION Ensuring human oversight in AI-driven decisions may be crucial to prevent errors in scenarios that impact public safety environments and/or in other environments. Additionally, the balance between human involvement and AI assistance must be carefully controlled. Over-reliance on AI may result in inappropriate actions, while insufficient use of AI can reduce the efficiency of operations. Thus, there exists a need for an improved technical method, device, and system for controlling artificial intelligence usage. In particular, provided herein is a device, system and method for controlling artificial intelligence usage, and in particular for controlling a relative weightage of human-in-the-loop component usage to artificial intelligence component usage in a computing process that includes human decision-making and artificial intelligence decision-making. An aspect of the present specification provides a method comprising: determining, at a computing device, a relative weightage of human-in-the-loop component usage to artificial intelligence component usage in a computing process that includes human decision-making and artificial intelligence decision-making; when the relative weightage is below a given range, such that the human-in-the-loop component usage is low relative to the artificial intelligence component usage: adjusting, via the computing device, the computing process to increase the human-in-the-loop component usage relative to the artificial intelligence component usage; and when the relative weightage is above the given range, such that the human-in-the-loop component usage is high relative to the artificial intelligence component usage: adjusting, via the computing device, the computing process to decrease the human-in-the-loop component usage relative to the artificial intelligence component usage. Another aspect of the present specification provides a computing device comprising: a controller; and a computer-readable storage medium having stored thereon program instructions that, when executed by the controller, causes the controller to perform a set of operat