Cognitive Message Analysis for Skill Gap Annotation
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Solution Overview
Problem
Senders lack the ability to determine whether recipients possess the necessary skills to comprehend the content of messages, particularly in cases where the content is technically or domain-specific, leading to potential misunderstandings due to mismatched skill levels.
Innovation Solution
A method that analyzes message content characteristics, computes the required skill factors, and annotates recipients with a gap analysis, allowing senders to adjust or reconsider message distribution based on tolerance thresholds, using natural language processing and question-and-answer systems to assess recipient expertise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If senders distribute technical or domain-specific content to recipients, then information sharing efficiency is improved, but recipient comprehension reliability deteriorates when skill levels are mismatched
Solution Approach 1:
The system performs preliminary analysis of recipient skill levels and content complexity before message distribution. By computing skill factors for each recipient and comparing them against content requirements in advance, the system identifies potential comprehension gaps before they occur, allowing senders to adjust content or recipient selection proactively
Solution Approach 2:
The system provides feedback to senders about recipient comprehension suitability by computing and displaying skill gap analyses. This feedback mechanism enables senders to understand whether recipients have adequate skill levels for the content being shared, allowing them to make informed decisions about message distribution
2Measurement precision
If senders compose messages with technical or domain-specific content, then content precision is improved, but ease of operation deteriorates due to inability to assess recipient suitability
Solution Approach 1:
The system performs self-service by automatically analyzing content characteristics and recipient skill levels without requiring manual assessment by the sender. The cognitive analytics engine independently computes skill factors, evaluates comprehension suitability, and provides annotations, freeing the sender from the complex task of manually assessing recipient expertise
3Reliability
If cognitive analytics is applied to analyze message content and recipient skills, then recipient comprehension suitability is improved, but device complexity increases
Solution Approach 1:
The system introduces a cognitive analytics engine as an intermediary component that bridges the gap between senders and recipients. This intermediary automatically performs the complex tasks of content analysis, skill factor computation, and suitability evaluation, isolating the complexity from the sender and recipient while providing simple feedback interfaces
Data Source
AI summary
A set of characteristics is constructed corresponding to a content of a message. For a characteristic in the set of characteristics, a skill factor is computed that is needed to achieve a degree of comprehension of the content having the characteristic. A gap is computed between the skill factor corresponding to the characteristic and a skill factor associated with a recipient of the message. An annotation is selected in response to evaluating that the gap exceeds a tolerance value. The annotation is applied in the message to an identifier of the recipient.