Best-Practice Input Guidance for Intelligent Computing Interactions
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Solution Overview
Problem
User inputs to intelligent computing systems often do not conform to best practices, leading to inefficient use of computing resources and potential safety hazards, such as dangerous vehicle actions.
Innovation Solution
A system that guides users to interact with intelligent computing systems using best practices by modifying user inputs to fit predefined rules, reducing resource usage and enhancing safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the system processes user inputs that do not conform to best practices, then the system can handle diverse user interactions, but computational resources are wasted and processing efficiency decreases
Solution Approach 1:
The system performs preliminary validation of user inputs against best practice rules before full processing. The best practice determiner checks inputs upfront to identify non-conforming interactions, allowing the system to either correct them or handle them differently, thus avoiding wasted computational resources on invalid inputs while maintaining versatility in handling diverse interaction types
Solution Approach 2:
The best practice determiner acts as an intermediary component between the user input interface and the main processing system. It intercepts user inputs, evaluates them against best practices, and either modifies or flags them before they reach the main processing pipeline, thereby protecting the system from inefficient processing while preserving the ability to handle various input types
2Ease of operation
If the system processes unclear or non-conforming user inputs extensively, then it may eventually understand user intent, but computational resources are tied up and response time increases
Solution Approach 1:
The system performs preliminary validation of user inputs against best practice rules before full processing. The best practice determiner checks inputs upfront to identify non-conforming interactions, allowing the system to either correct them or handle them differently, thus avoiding wasted computational resources on invalid inputs while maintaining versatility in handling various interaction types
Solution Approach 2:
The system provides feedback to users when their inputs do not conform to best practices. By presenting modified user interactions that align with best practices, the system guides users toward more effective input patterns, reducing the need for iterative processing and improving overall response time while maintaining ease of operation
3Adaptability or versatility
If the system accepts user interactions that do not follow best practices, then user freedom is maintained, but safety hazards may occur in critical applications
Solution Approach 1:
The system applies preliminary anti-action by proactively identifying and correcting user inputs that could lead to safety hazards before they are executed. The best practice determiner evaluates inputs against safety-critical best practices and presents modified interactions that prevent potential harm, thereby maintaining user freedom while eliminating safety risks through preventive correction
Solution Approach 2:
The best practice determiner acts as an intermediary safety layer between the user and the system's critical functions. It intercepts potentially harmful inputs, evaluates them against safety best practices, and either blocks or modifies them before they can cause harm, thus preserving user freedom while preventing safety hazards in critical applications
Data Source
AI summary
A plurality of best practice rules pertaining to best practices for interacting with a system can be received. A first user interaction from a user can received. A best practice determiner can determine whether the first user interaction fits at least one of the best practice rules. Responsive to determining, by the best practice determiner, that the first user interaction does not fit the at least one of the best practice rules, a modified user interaction can be generated by modifying the first user interaction based, at least in part, on the received plurality of best practice rules. The modified user interaction can be presented to the user.