XR Explainable AI Content for User Trust in Headsets
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Users in extended reality environments often lack understanding of the reasoning behind AI-generated content, leading to potential disablement or disregard of beneficial content.
Innovation Solution
An extended reality system that includes a head-mounted device with sensors and processors to capture input data, determine virtual content, and provide explainable artificial intelligence (XAI) content describing the rationale behind the virtual content presentation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If AI-generated content is provided in extended reality environments, then the functionality and personalization of the system is improved, but user understanding and trust of the content deteriorates due to lack of explanation
Solution Approach 1:
The patent introduces XAI content as an intermediary element that mediates between the AI-generated virtual content and the user. This intermediary provides contextual explanations, reasoning, and transparency about how the virtual content was generated, thereby maintaining both the functionality of AI content delivery and the user's understanding of it.
Solution Approach 2:
The patent segments the information presentation into distinct components: the virtual content itself and the XAI explanatory content. This segmentation allows the system to deliver personalized AI-generated content while separately providing transparent explanations, enabling users to understand both what is being presented and why.
2Loss of information
If XAI content is added to explain AI-generated content, then user understanding is improved, but system complexity increases
Solution Approach 1:
The patent implements a multi-functional XAI content generation system that can provide multiple types of explanations (reasoning, context, transparency) through a unified framework. This universal approach handles various AI-generated content types and user needs through a single system architecture, managing complexity while delivering comprehensive explanations.
Solution Approach 2:
The system incorporates feedback mechanisms where XAI content is generated based on user interactions, preferences, and contextual factors. This feedback loop allows the system to adapt explanations to user needs dynamically, improving understanding without requiring permanently complex system structures.
3Adaptability or versatility
If personalized virtual content is generated using machine learning environments, then content relevance to user is improved, but computational requirements and processing time increases
Solution Approach 1:
The patent employs pre-trained machine learning models and pre-computed user profiles that capture user preferences and characteristics in advance. This preliminary action allows the system to generate personalized virtual content more efficiently during runtime, reducing processing time while maintaining high content relevance.
Solution Approach 2:
The system optimizes processing by dynamically adjusting parameters such as the level of personalization, complexity of XAI explanations, and selection of ML models based on contextual factors and user preferences. This allows the system to balance computational requirements with content relevance and explanation quality in real-time.
Data Source
AI summary
Features described herein generally relate to providing explainable artificial intelligence (XAI) within extended reality. Particularly, after obtaining input data, including environmental information, user state information, and user profile information, an extended reality system determines virtual content to be presented to a user via a head-mounted device. The extended reality system also identified additional contextual factors associated with this virtual content, including system goals, user goals, a current state of the user, a user's location, a current time, and a current environment of the user. These additional contextual details are then used to determine XAI content that describes one or more aspects of the virtual content (such as how the virtual content was determined based on the input data). The virtual content and the XAI content are then presented to the user by the extended reality system.