Bias-Corrected Visual Representation for Provider Communication Sessions
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Solution Overview
Problem
Providers in customer service centers exhibit bias towards certain user categories based on demographic information, leading to increased call times, transfers, and repetitive application submissions, which are difficult to detect and correct using existing automated methods.
Innovation Solution
A device determines an interaction profile for the provider using a machine learning model trained on interaction data, and generates a visual representation that depicts a person without characteristics associated with the one or more categories of users, which are absent from the face of the person.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If demographic information is displayed to providers during communication sessions, then providers can identify user categories, but provider bias towards certain user categories increases leading to longer call times and more transfers
Solution Approach 1:
The patent extracts and removes the harmful demographic characteristics from the visual representation displayed to providers. By generating images that deliberately exclude race, age, gender, and other demographic features, the system prevents providers from identifying user categories visually, thereby reducing bias-related call times and transfers while maintaining operational effectiveness.
Solution Approach 2:
The patent converts the potentially harmful effect of visual demographic identification into a beneficial outcome by intentionally designing visual representations that lack demographic characteristics. This approach transforms what could be a source of bias into a tool for promoting equitable treatment across all user categories.
2Ease of operation
If demographic information is displayed to providers, then user category identification is possible, but provider bias increases leading to more repetitive application submissions
Solution Approach 1:
The system extracts and removes demographic characteristics from visual representations, preventing providers from identifying user categories through visual cues. This reduction in visual identification capability decreases provider bias, leading to fewer repetitive application submissions and improved processing efficiency.
Solution Approach 2:
The patent converts the potential harm of demographic-based discrimination into a benefit by designing visual representations that intentionally exclude demographic features. This approach promotes equitable decision-making and improves application processing efficiency by reducing bias-driven rejections and resubmissions.
3Difficulty of detecting and measuring
If existing automated methods are used to detect provider bias, then detection capability is limited, but bias correction remains difficult and ineffective
Solution Approach 1:
The patent applies preliminary action by proactively preventing bias before it can manifest in provider decisions. By generating visual representations that exclude demographic characteristics before the interaction begins, the system preemptively eliminates the root cause of bias, making detection and correction unnecessary.
Solution Approach 2:
The patent introduces an intermediary mechanism - the modified visual representation - that mediates between the user and the provider. This intermediary element (the demographic-free image) blocks the transmission of demographic information that would otherwise trigger biased responses, thereby improving both detection and correction of provider bias.
Data Source
AI summary
In some implementations, a device may determine an interaction profile for a provider that is to engage with a user in a communication session. The interaction profile may be based on interaction data relating to interpersonal interactions involving the provider during one or more previous communication sessions. The interaction profile may indicate a bias of the provider in connection with one or more categories of users. The device may generate, based on the interaction profile, a visual representation that depicts at least a face of a person for presentation to the provider during the communication session. One or more characteristics associated with the one or more categories of users may be absent from the face of the person. The device may cause presentation of the visual representation to the provider during the communication session.