Trust Engine for Automation Calls
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Solution Overview
Problem
There is a lack of trust in automation calls due to the absence of visibility into their trustworthiness, which affects user satisfaction and makes it difficult to intervene during issues, as traditional quality metrics do not account for developer personas and consumer satisfaction.
Innovation Solution
A trust engine and automation database system that provides trustworthiness scores for API calls based on observable properties like performance, process, and purpose, allowing users to understand API trustworthiness and detect misaligned intent, with a graphical user interface for feedback and intervention assistance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional quality metrics (QoS, KPIs) are used for automation calls, then system operation is maintained, but developer trust and visibility into automation trustworthiness are insufficient
Solution Approach 1:
The patent introduces a trust engine as an intermediary component that sits between the automation call execution and the developer. This trust engine collects, processes, and aggregates trust indicators from multiple sources (performance metrics, security logs, compliance data) and presents them through a standardized trust score interface, thereby mediating the information gap between complex automation processes and developer understanding
Solution Approach 2:
The patent segments the trustworthiness assessment into multiple discrete trust indicators (performance, security, compliance, reliability) that can be independently measured, evaluated, and presented. This segmentation allows developers to understand specific aspects of automation trustworthiness rather than receiving a single undifferentiated metric
2Productivity
If outcome-based control automation is implemented, then automation capability is enhanced, but visibility into individual steps and alignment with developer intent is reduced
Solution Approach 1:
The patent implements comprehensive feedback mechanisms that continuously monitor automation call execution and provide real-time trust indicator updates. The system feeds back performance data, security events, and compliance status to both the trust engine and developers, enabling ongoing assessment of automation trustworthiness throughout the execution process
Solution Approach 2:
The patent adds a new dimensional layer of trust assessment that operates parallel to the traditional automation execution flow. Instead of merely tracking whether automation steps complete, the system introduces trust scores and indicators as an additional dimension of measurement that evaluates the quality, safety, and alignment of each automation action
3Ease of operation
If consumer satisfaction measures (CSAT, NPS) are not included in GUIs, then interface simplicity is maintained, but consumer trust and satisfaction visibility are diminished
Solution Approach 1:
The patent applies partial action by selectively presenting trust indicators based on user role, context, and need. Rather than displaying all possible trust metrics simultaneously, the system provides relevant trust information on-demand or based on user permissions, maintaining interface simplicity while ensuring necessary trust visibility is available when needed
Data Source
AI summary
A method for generating a trustworthiness score for an automation call is disclosed. An automation database may return trust information for multiple trust indicators. A current score may also be determined. The trust information provides insight into the trustworthiness of the automation call. When an error is encountered with the call or in a user interface, the trust system may intervene based on the user sentiment. The intervention may be automatic, and computer or human based.