Tendency Detection System for Proactive Bias Analysis
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Solution Overview
Problem
Current bias training methods for institutions, such as police forces, are largely reactive and lack proactive tools to detect and address biases in real-time, especially when dealing with incidents monitored by audio and video analytics, which limits their effectiveness in preventing unfair treatments.
Innovation Solution
A computer-implemented method and system that generates tendency scores from incident data, using a database with fields for rights-protected persons and additional data, to dynamically provide workflow actions within a graphical user interface, enabling users to select and initiate actions based on identified biases, leveraging neural networks for anomaly detection and bias score generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If reactive bias training methods are used, then institutions can respond to complaints after they occur, but they cannot proactively detect or prevent biases in real-time
Solution Approach 1:
The system performs preliminary actions by continuously analyzing incident data and generating tendency scores before bias incidents escalate into complaints. The automated monitoring and scoring system proactively identifies potential bias patterns, allowing institutions to intervene early rather than waiting for reactive complaints.
Solution Approach 2:
The system implements continuous feedback loops where incident data is constantly analyzed, tendency scores are generated and updated, and workflow actions are triggered based on threshold exceedances. This real-time feedback mechanism enables dynamic bias detection and response, improving both reliability and reducing response time.
2Extent of automation
If automated tendency score generation is implemented, then proactive bias detection is enabled, but system complexity increases
Solution Approach 1:
The system segments the complex bias detection task into distinct components: incident data collection, data processing, tendency score generation, threshold comparison, and workflow action triggering. Each component operates independently but contributes to the overall automated detection system, making the complexity manageable and maintainable.
Solution Approach 2:
The system employs universal components that serve multiple functions. For example, the incident data database stores structured information that serves both as raw data for analysis and as the basis for generating tendency scores. The same processing infrastructure handles both data storage and analytical computations, reducing overall system complexity.
3Loss of information
If structured incident data with multiple fields is collected, then comprehensive bias analysis is possible, but data management complexity increases
Solution Approach 1:
The incident data is segmented into distinct structured fields including rights-protected person class, individual person identification, and additional data. This segmentation organizes complex information into manageable, queryable units that can be systematically analyzed for bias patterns without overwhelming data management complexity.
Data Source
AI summary
Tendency detecting and analysis in support of generating one or more workflows via user interface interactions is disclosed. In accordance with the user interface interactions, processing user selection of one or more icons may generate at least one user-selectable option within a graphical user interface, where the user-selectable option corresponds to at least one workflow action. The workflow action may relate to an identified tendency of a person or a group of people.