How AI Systems Adjust Their Behavior Based on User Mood
A system that monitors human-AI interactions to build personality profiles and automatically adjust AI responses to improve communication quality.
Original patent title: “Mood detection with intelligence agents”
A system that monitors human-AI interactions to build personality profiles and automatically adjust AI responses to improve communication quality. Granted to International Business Machines Corp in 2019 with 17 claims.
Key facts
Coverage
What does this patent actually cover?
The system acts like a digital mediator between people and AI agents. It observes interactions by tracking biometric data, facial expressions, and speech tone from the human, while simultaneously gathering sensor and text data from the AI. It then creates a cognitive profile for both parties and maps their history of interactions. Finally, it generates specific action operations—like changing the AI's tone or response style—to make the interaction more effective or positive.
The gap
What does this patent NOT cover?
- Does not cover systems that rely solely on static user settings without real-time biometric or behavioral observation.
- Does not cover manual adjustment of AI parameters by a human administrator.
- Does not cover general sentiment analysis that does not result in a specific 'action operation' to modify the interaction.
These exclusions are unique to PatentBrief — derived from the actual claim language, not patent-office boilerplate.
What made this novel
The system treats the AI agent itself as an entity with a 'cognitive profile' that needs to be mapped and adjusted, rather than just treating the AI as a static tool that interacts with a human.
Schematic visualization of the patent's claim structure. Hand-drawn diagrams in progress for each landmark patent.
Where you've seen this
Real-world examples
AI customer service chatbots that switch to a human agent when frustration is detected.
Adaptive virtual assistants that change their speaking pace or tone based on user stress levels.
Why it matters
The bigger picture
As AI assistants become more integrated into customer service and personal productivity, the ability to detect frustration or confusion in real-time is a key differentiator. IBM's approach attempts to formalize the 'emotional intelligence' of software, moving beyond simple command-response loops into adaptive, relationship-based computing.
Filed
May 25, 2017
Granted
June 11, 2019
Market context
Who's building on this
Companies in this space
IBM continues to lead in enterprise AI through its Watson platform. Other major players like Microsoft with Copilot and Salesforce with Einstein are actively developing similar adaptive interaction models for CRM and productivity software.
Market impact
This patent reflects a broader industry shift toward 'affective computing,' where software is designed to recognize and respond to human emotion. It highlights the move away from rigid, rule-based interfaces toward dynamic systems that prioritize the quality of the user experience over simple task completion.
Claim 1 — Plain English
What this patent covers
The system acts like a digital mediator between people and AI agents. It observes interactions by tracking biometric data, facial expressions, and speech tone from the human, while simultaneously gathering sensor and text data from the AI. It then creates a cognitive profile for both parties and maps their history of interactions. Finally, it generates specific action operations—like changing the AI's tone or response style—to make the interaction more effective or positive.
The clever bit
The system treats the AI agent itself as an entity with a 'cognitive profile' that needs to be mapped and adjusted, rather than just treating the AI as a static tool that interacts with a human.
What it does not cover
- Does not cover systems that rely solely on static user settings without real-time biometric or behavioral observation.
- Does not cover manual adjustment of AI parameters by a human administrator.
- Does not cover general sentiment analysis that does not result in a specific 'action operation' to modify the interaction.
Patent timeline
Application submitted to the patent office
Application published, typically 18 months after filing
Patent officially issued
PatentBrief Score
Impact Score
Early stage
Citation count
0/40
No citations yet
Claim breadth
11/20
Broad claimsclaimsThe numbered statements at the end of a patent that legally define what the inventor owns.Read more →
Recency
10/20
Granted 5–10 years ago
Assignee scale
0/20
Independent or smaller assigneeassigneeThe entity that owns the patent — usually the inventor's employer or a company.Read more →
PatentBrief Impact Score — based on citation count, claim breadth, recency, and assignee scale. Not a legal assessment.
Heuristic Value Estimate
What this patent might be worth
$31K – $100K
Midpoint $62K · 10.9 yr remaining · industry ×1.6
Heuristic only — blends forward/backward citation counts, claim scope, time remaining, litigation history, and CPC-derived industry baseline. Real valuations need a professional appraisal.
The original legal language
Original claims
17 claims as filed with the patent office.
Concepts involved
Citations
Patent lineage
Cite this patent
Whitman, T. R., Pandey, D., Perrino, J. P., & Baughman, A. K. (2019). How AI Systems Adjust Their Behavior Based on User Mood (U.S. Patent No. 10,318,876). U.S. Patent and Trademark Office. https://patentbrief.org/patent/us/10318876/neural-architecture-search-with-rl
Auto-generated from the patent record. Double-check author order and the issue date against the official USPTO document before submitting.
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Common Questions
Frequently Asked Questions
What does How AI Systems Adjust Their Behavior Based on User Mood cover?
A system that monitors human-AI interactions to build personality profiles and automatically adjust AI responses to improve communication quality.
Who owns patent US 10318876?
International Business Machines Corp owns this patent, granted in 2019.
When does this patent expire?
This patent is expected to expire on June 11, 2039, when the invention enters the public domain.
What problem does this patent solve?
As AI assistants become more integrated into customer service and personal productivity, the ability to detect frustration or confusion in real-time is a key differentiator. IBM's approach attempts to formalize the 'emotional intelligence' of software, moving beyond simple command-response loops into adaptive, relationship-based computing.
What does this patent NOT cover?
Does not cover systems that rely solely on static user settings without real-time biometric or behavioral observation.
Same assignee
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