Abstract: Techniques regarding the governing of use by a consumer of an artificial intelligence technology are described. 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 include an analyzing component that can, based on an artificial intelligence usage policy, analyze a proposed use by a consumer of an artificial intelligence technology, resulting in an analyzed use of the artificial intelligence technology. The computer executable components can further include a governing component that can, based on the analyzing, govern use by the consumer of the artificial intelligence technology.

Abstract: An autonomous agent operating method, system, and computer program product, including launching a first autonomous agent for a task with an initial update interval and adjusting the initial update interval for a second autonomous agent based on a second task for the second autonomous agent being similar to the task over time in relation to a trust level of a human user in a performance of the first autonomous agent.

Abstract: One or more systems, devices, computer program products and/or computer-implemented methods provided herein relate to risk assessment for artificial intelligence models, and more specifically, to the generation of customized risk scores and converted comparable scores. In an embodiment, the customized risk assessment scores can be based on a risk profile determined from risk assessment requirements and measurements of an artificial intelligence model. In another embodiment, one or more customized risk assessment scores can be converted to a converted risk assessment score that is comparable to a customized risk assessment score or another converted risk assessment score.

Abstract: Provided are techniques for dynamic fact contextualization in support of AI model development. A template from a plurality of templates is selected, where the template includes definitions for identifying facts. The facts are retrieved from a facts repository based on the definitions. It is determined that that the facts are valid based on one or more policies. A FactSheet is generated using the template and the facts. A machine learning model is used to identify one or more deficient facts from the FactSheet. The FactSheet is displayed in a preview with the one or more deficient facts. One or more facts corresponding to the one or more deficient facts are located. The FactSheet is updated to correct the one or more deficient facts with the corresponding facts.

Abstract: A method, computer program, and computer system is provided for testing a user interface. A previously trained machine learning model trained with traces of interactions between one or more users and a user interface is accessed. The interactions include one or more timestamps of user interactions with the user interface, actions by each user associated with the user interface, and metadata associated with user interactions. A simulated interaction of a simulated agent utilizing the user interface is generated using the previously trained machine learning model. The simulated interaction is encoded as an input trace to a user interface. The encoded simulated interaction is input into the user interface for automated testing of the user interface. Results of the automated testing of the user interface are received.

Abstract: An autonomous agent operating method, system, and computer program product, including launching a first autonomous agent for a task with an initial update interval and adjusting the initial update interval for a second autonomous agent based on a second task for the second autonomous agent being similar to the task over time in relation to a trust level of a human user in a performance of the first autonomous agent.

Abstract: Embodiments relate to interactive graphical display. A request is processed by a generative system to generate multiple hypotheses of an output in response to the request, a primary hypothesis of the multiple hypotheses having a highest confidence for the output, multiple secondary hypotheses of the multiple hypotheses having a lower confidence than the highest confidence. At least one region of divergence is determined from the primary hypothesis by the multiple secondary hypotheses, the at least one region of divergence having alternatives in the multiple secondary hypotheses, the alternatives in the multiple secondary hypotheses differing from the primary hypothesis. A graphical user interface displays the at least one region of divergence in the primary hypothesis and alternatives in the multiple secondary hypotheses for the at least one region of divergence, the alternatives and primary hypothesis for the at least one region of divergence being displayed as selectable options for a user.

Abstract: An autonomous agent operating method, system, and computer program product, including configuring an autonomous agent for a task, launching the autonomous agent with an initial update interval, the update interval determining a frequency of the autonomous agent reporting results to a human user for review, measuring the trust level of human user in a performance of the autonomous agent, and dynamically adjusting the update interval based on this measured trust.

Abstract: Embodiments relate to interactive graphical display. A request is processed by a generative system to generate multiple hypotheses of an output in response to the request, a primary hypothesis of the multiple hypotheses having a highest confidence for the output, multiple secondary hypotheses of the multiple hypotheses having a lower confidence than the highest confidence. At least one region of divergence is determined from the primary hypothesis by the multiple secondary hypotheses, the at least one region of divergence having alternatives in the multiple secondary hypotheses, the alternatives in the multiple secondary hypotheses differing from the primary hypothesis. A graphical user interface displays the at least one region of divergence in the primary hypothesis and alternatives in the multiple secondary hypotheses for the at least one region of divergence, the alternatives and primary hypothesis for the at least one region of divergence being displayed as selectable options for a user.

Abstract: A method of using artificial intelligence to provide source code from an original programming language in a target programming language showing regions of low confidence. The method includes receiving, by a computing device, a code base in an original programming language. The computing device further provides the code base in the original programming language to a target programming language using an artificial intelligence tool. The computing device additionally displays the code base in the target programming language using a visualization tool in a visual interface. The computing device still further displays the regions of uncertainty to a human user in the visual interface. The regions of uncertainty provide low confidence regions of the code base in the target programming language for targeted user intervention. The regions of low confidence correlate with violations to provide displayed actionable insight regions.

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.

Abstract: An automated analytic tool (AAT) apparatus analyzes a machine learning system (MLS). The tool comprises a processor configured to receive experiment parameters associated with an experiment performed on the MLS, and captures information from a plurality of stages of the experiment. The information comprises information regarding MLS results and choices made during the experiment. The tool automatically revise the captured information into revised information utilizing a knowledge base comprising information from prior experiments. The tool then presents the revised information to a user.

Abstract: An autonomous agent operating method, system, and computer program product, including configuring an autonomous agent for a task, launching the autonomous agent with an initial update interval, the update interval determining a frequency of the autonomous agent reporting results to a human user for review, measuring the trust level of human user in a performance of the autonomous agent, and dynamically adjusting the update interval based on this measured trust.

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.

Abstract: A method and apparatus for displaying information on a display device of limited display area. More specifically, an array of elements is formed on the display where each of the elements represents an attribute and has graphical information indicating the state of the attribute. Further, the position of each element in the array represents its position in a collection of attributes. Each element is also user selectable, so that when the element is selected, further information on the attribute is displayed.