Automated Command Verification for Misinterpretation Risks

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Solution Overview

Problem

Automated recognition systems, such as speech and visual recognition, often misinterpret user commands, leading to undesirable or dangerous consequences due to recognition errors, particularly in critical applications like car control and military systems.

Innovation Solution

Implementing a method within automated systems to evaluate the ambiguity of user commands, predict potential consequences of executing these commands, and take preventative actions such as seeking user confirmation or suspending execution to prevent dangerous outcomes.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If automated recognition systems execute commands without verification, then system productivity and response speed are improved, but recognition errors lead to undesirable or dangerous consequences

Engineering Contradiction:

Improvecommand execution speedVSAvoidcommand execution safety

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system performs preliminary evaluation of command ambiguity and potential consequences before executing the command. By assessing whether a command is ambiguous and predicting harmful outcomes in advance, the system can prevent dangerous executions without requiring verification for every command, thus maintaining productivity while improving reliability.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements a feedback mechanism where command processing results are evaluated to determine ambiguity, and potential consequences are assessed before execution. This feedback loop allows the system to identify risky commands and either request clarification or prevent execution, thereby reducing recognition errors while maintaining efficient operation for clear commands.

Inventive Principle:

Principle #23Feedback

2Measurement precision

If the system evaluates ambiguity and consequences for all commands, then recognition accuracy and safety are improved, but system complexity and processing time increase

Engineering Contradiction:

Improvecommand recognition accuracyVSAvoidcommand processing system complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system applies different levels of evaluation to different commands based on their characteristics. Rather than uniformly evaluating all commands, the system focuses detailed ambiguity assessment and consequence prediction on commands that are likely to be ambiguous or potentially harmful, while processing clear, low-risk commands more efficiently. This localized approach improves accuracy for critical commands without unnecessarily increasing overall system complexity.

Inventive Principle:

Principle #3Local quality

3Reliability

If the system requests user confirmation for ambiguous commands, then command execution safety is improved, but response time and user interaction complexity increase

Engineering Contradiction:

Improvecommand execution safetyVSAvoidcommand processing time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system takes preliminary anti-action by predicting harmful consequences of ambiguous commands before execution. When potential harm is identified, the system proactively prevents execution or seeks clarification, thereby avoiding dangerous outcomes. This approach improves safety by addressing potential issues before they manifest, rather than reacting to errors after they occur.

Inventive Principle:

Principle #9Preliminary anti-action

Data Source

PatentUS7437297B2Systems and methods for predicting consequences of misinterpretation of user commands in automated systems

Publication Date: 2008.10.14 HYUNDAI MOTOR CO LTD

AI summary

Systems and methods are provided for processing and executing commands in automated systems. For example, command processing systems and methods are provided which can automatically determine, evaluate or otherwise predict consequences of execution of misrecognized or misinterpreted user commands in automated systems and thus prevent undesirable or dangerous consequences that can result from execution of misrecognized/misinterpreted commands.