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: 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 implicit bias monitoring system is provided. The system receives sensor data including video and audio that are captured during an interaction between a first individual and a second individual. The system determines a set of attributes associated with the interaction based on the received sensor data, the set of attributes comprising at least one of race and gender of the second individual. The system detects an implicit bias based on a combination of the determined set of attributes and a bias profile. The system generates an alert based on the detected implicit bias.

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, system, and computer program product for motion-based user interfaces are provided. The method identifies a navigation mode indication. A navigation interface is generated at a display device and configured based on the navigation mode indication to include a first graphical content. At least a portion of the navigation interface is modified based on one or more movements of the mobile computing device. A portion of the navigation interface is selected based on detecting a pressure change on at least a portion of a mobile computing device. The method presents a second graphical content on the display device based on the selected portion of the navigation interface.

Abstract: A method, system, and computer program product for motion-based user interfaces are provided. The method identifies a navigation mode indication. A navigation interface is generated at a display device and configured based on the navigation mode indication to include a first graphical content. At least a portion of the navigation interface is modified based on one or more movements of the mobile computing device. A portion of the navigation interface is selected based on detecting a pressure change on at least a portion of a mobile computing device. The method presents a second graphical content on the display device based on the selected portion of the navigation interface.

Abstract: An implicit bias monitoring system is provided. The system receives sensor data including video and audio that are captured during an interaction between a first individual and a second individual. The system determines a set of attributes associated with the interaction based on the received sensor data, the set of attributes comprising at least one of race and gender of the second individual. The system detects an implicit bias based on a combination of the determined set of attributes and a bias profile. The system generates an alert based on the detected implicit bias.

Abstract: A video stream control method, system, and a computer program product include analyzing a video stream to identify a section of the video stream where a condition will occur, delivering a notification that the condition will occur in the section of the video stream and modifying the video stream before the section of the video stream is played, and selecting a type of delivery of the section of the video stream based on a set of rules factoring the condition and user data at a time of the notification.

Abstract: A method, system and apparatus for source code auto-suggestion, including receiving and processing source code from a source code repository, extracting one or more features from the source code received from the source code repository, extracting one or more features from the source code within a development environment, comparing the one or more features from the source code received from the source code repository with the one or more features extracted from the source code within the development environment, and providing a segment of source code from the received and processed source code repository according to a similarity to the source code within the development environment.

Abstract: A system includes a processor and logic integrated with the processor, executable by the processor, or integrated with and executable by the processor. The logic is configured to train a participant model on video streams of a participant and train the participant model on environmental parameters. The logic is also configured to store the trained participant model. The trained participant model is usable to generate a synthetic video representation of the participant. A computer-implemented method includes generating, by the computer, a synthetic video representation of a participant based on at least a trained participant model corresponding to the participant and live audio input. In response to a trigger event, the method includes replacing, by the computer, live video transmission with a synthetic video transmission that is based at least in part on the synthetic video representation.

Abstract: A method for checking against transmitting a message to an unintended recipient, includes developing, using a processor on a computer, a training model of a linguistic profile of messages previously transmitted electronically by a user to a recipient, by iteratively computing a composite feature vector over a set of all messages previously transmitted electronically to the recipient, the iterations for developing the training model continuing until summed proportional changes across all features falls below a first preset threshold value.

Abstract: A video stream control method, system, and a computer program product include analyzing a video stream to identify a section of the video stream where a condition will occur, delivering a notification that the condition will occur in the section of the video stream and modifying the video stream before the section of the video stream is played, and selecting a type of delivery of the section of the video stream based on a set of rules factoring the condition and user data at a time of the notification.

Abstract: A video stream control method, system, and a computer program product include analyzing a video stream to identify a section of the video stream where a condition will occur, delivering a notification that the condition will occur in the section of the video stream and modifying the video stream before the section of the video stream is played, and selecting a type of delivery of the section of the video stream based on a set of rules factoring the condition and user data at a time of the notification.

Abstract: A method for checking against transmitting a message to an unintended recipient, includes developing, using a processor on a computer, a training model of a linguistic profile of messages previously transmitted electronically by a user to a recipient, by iteratively computing a composite feature vector over a set of all messages previously transmitted electronically to the recipient, the iterations for developing the training model continuing until summed proportional changes across all features falls below a first preset threshold value.

Abstract: A method (and structure) for developing a linguistic profile of a message to be transmitted, using a processor on a computer. The linguistic profile is compared with at least one linguistic profile of messages previously transmitted to other persons.

Abstract: A video stream control method, system, and a computer program product include analyzing a video stream to identify a section of the video stream where a condition will occur, delivering a notification that the condition will occur in the section of the video stream and modifying the video stream before the section of the video stream is played, and selecting a type of delivery of the section of the video stream based on a set of rules factoring the condition and user data at a time of the notification.

Abstract: A method (and structure) for developing a linguistic profile of a message to be transmitted, using a processor on a computer. The linguistic profile is compared with at least one linguistic profile of messages previously transmitted to other persons.