Anonymized Connection Facilitation with Relationship Scoring
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Solution Overview
Problem
Existing systems fail to effectively facilitate connections within organizations while preserving the privacy of individuals, as they often reveal internal connections without consent, leading to pressure on potential introducers and inefficiencies in identifying relevant relationships.
Innovation Solution
A system and method that anonymize user identities until they accept introduction requests, using a server to identify connections based on electronic records, calculate relationship-strength scores, and automatically schedule meetings, preserving privacy until consent is given.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If user identities are revealed to facilitate connections, then connection effectiveness is improved, but user privacy is compromised
Solution Approach 1:
The system segments the connection facilitation process into distinct phases: initial connection identification with anonymized data, user consent solicitation, and post-consent identity revelation. This segmentation allows the system to protect privacy during early stages while enabling effective connections after user approval.
Solution Approach 2:
The system performs preliminary actions by identifying potential connections and calculating relationship-strength scores before revealing user identities. This allows the system to prepare connection opportunities in advance while maintaining privacy, then reveal identities only when users consent to be approached.
2Adaptability or versatility
If all internal connections are revealed, then connection opportunities are maximized, but user pressure and discomfort increase
Solution Approach 1:
The system applies local quality by providing different information states to different parties: requesters see anonymized connection data and relationship scores, while potential introducers see consent requests. This differentiated information presentation maximizes connection opportunities while reducing user pressure by maintaining anonymity until consent is given.
Solution Approach 2:
The system inverts the traditional approach by not revealing identities first and then seeking consent, but rather seeking consent first through anonymized channels and only revealing identities after approval. This inversion fundamentally reduces user pressure while maintaining connection effectiveness.
3Object-affected harmful factors
If manual connection identification is used, then privacy control is maintained, but system efficiency decreases
Solution Approach 1:
The system implements self-service by automatically identifying connections, calculating relationship-strength scores, and managing the consent process without requiring manual privacy controls. Users passively maintain privacy through the anonymized interface while the system efficiently processes connection identification and matching.
Solution Approach 2:
The system uses anonymized connection data and relationship-strength scores as intermediaries between privacy protection and efficient connection identification. These intermediaries allow automated processing to maintain privacy control while achieving high system efficiency in identifying and facilitating connections.
4Measurement precision
If detailed connection information is collected, then connection accuracy is improved, but data processing complexity increases
Solution Approach 1:
The system extracts only the essential elements needed for connection accuracy: relationship-strength scores calculated from electronic records. By extracting and focusing on these key metrics while anonymizing other details, the system achieves high connection accuracy without requiring complex processing of all available data.
Solution Approach 2:
The system changes parameters by transforming detailed connection information into aggregated relationship-strength scores. This parameter transformation maintains connection accuracy by preserving the essential relationship metrics while simplifying data processing through anonymization and aggregation of underlying details.
Data Source
AI summary
Systems and methods for privacy-preserving enablement of connections within organizations are disclosed. In one embodiment, a method may include (1) receiving, at a server comprising a computer processor, an identification of a target to contact from a requester in an organization; (2) the computer processor identifying, in a connection database, at least one user within the organization having a connection with the target; (3) the computer processor communicating anonymized information representing the at least one user having the connection and a relationship-strength score for the connection; (4) the computer processor communicating a request for introduction assistance to the at least one user; (5) the computer processor receiving acceptance of the request for introductory assistance from the at least one user; and (6) the computer processor identifying the at least one that accepted the request to the requester.