On-device Offensive Content Detection Using Neural Analysis
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Solution Overview
Problem
The rapid connectivity provided by network-enabled mobile devices can lead to the transmission of messages in emotional states that may skew intended messages, resulting in the inclusion of offensive content, which existing technologies fail to effectively detect and manage.
Innovation Solution
A method and system on user devices that analyze message content for offensive triggers, considering context and sentiment, generate alerts, and provide options to edit or discard such messages, utilizing a neural network trained on labeled content and a custom keyboard with integrated message analysis units.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If instant connectivity is provided by network enabled mobile devices, then communication speed and accessibility are improved, but the risk of transmitting offensive content increases due to emotional states
Solution Approach 1:
The system performs preliminary analysis of message content before transmission by scanning for offensive trigger words and evaluating contextual factors. This pre-transmission check allows the system to identify potentially offensive content while the user is still composing the message, enabling intervention before harm occurs.
Solution Approach 2:
The messaging system acts as an intermediary between the user and the communication network, inserting an automated analysis layer that evaluates message content. This intermediary function filters and monitors communications without replacing human judgment, allowing offensive content detection while preserving user autonomy.
2Measurement precision
If message content is analyzed for offensive triggers, then detection accuracy is improved, but processing time and computational resources increase
Solution Approach 1:
The analysis system is divided into separate functional modules: trigger word detection, contextual evaluation, and decision-making. This segmentation allows each component to operate independently and efficiently, processing different aspects of message analysis in parallel rather than sequentially, thereby reducing overall processing time.
Solution Approach 2:
The system adjusts analysis parameters dynamically based on message characteristics. For example, it can modify the stringency of trigger word matching or the depth of contextual analysis required, allowing faster processing for low-risk messages while maintaining high detection accuracy for potentially offensive content.
3Reliability
If contextual analysis is performed to determine offensiveness, then false positives are reduced, but computational complexity increases
Solution Approach 1:
The system applies different levels of analysis to different parts of the message based on local context. Trigger words surrounded by neutral or positive context receive lighter analysis, while those in potentially harmful contexts undergo more rigorous evaluation. This localized approach improves reliability without uniformly increasing complexity across all messages.
Solution Approach 2:
The contextual evaluation module serves multiple functions: it identifies offensive intent, determines severity levels, and provides recommendations for message modification. This multi-functionality reduces the need for separate specialized systems, managing complexity while improving determination reliability through comprehensive analysis.
4Object-affected harmful factors
If users are provided with options to edit or discard messages, then harmful content transmission is reduced, but user communication efficiency decreases
Solution Approach 1:
The system applies preliminary countermeasures by presenting edit or discard options only when offensive content is detected, rather than blocking all messages or requiring review of every transmission. This targeted approach prevents harmful content while maintaining efficient communication for benign messages, minimizing the impact on overall communication productivity.
Solution Approach 2:
Users retain control over their messages through self-service options to edit or discard content flagged by the system. This approach empowers users to make final decisions about their communications, maintaining efficiency by allowing them to quickly accept or modify messages without requiring system intervention for every transmission.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on computer storage medium, to facilitate interception of messages that include offensive content. In one aspect, a method includes actions of receiving input on a user device that includes message content, determining, on the user device, whether the message content includes offensive content, and in response to determining, on the user device, that the message content includes offensive content, generating an alert message for display on the user device that provides an indication that the message includes offensive content.