Control the source
Test, verify and constrain harmful, false or biased outputs.
Learn · Map · Trace · Act
See where an AI decision meets the real world
Learn responsible AI, map your project, trace foreseeable consequences and receive practical actions you can use.
P8 responsibility pillarsL6 pathway stagesCReal-world consequences
PPillarsWhat may fail?
LProject lifecycleWhere can it fail?
CConsequencesWho or what is affected?
Accuracy × Deployment × People
A false water-safety warning changes which source a community uses.
Learn the pathway
Move from input and processing to action and consequence.
Decode S, P and R
Understand how source, pathway and receptor interact to form risk.
Explore consequences
Combine pillar, affected level and severity.
Lesson 1 · Output to outcome
Responsible AI follows the decision pathway.
Foreseeable consequences need attention before, during and after AI use. A technically small output may become important when people trust it and act on it.
Foreseeable issue
No AI output is inherently consequential or inconsequential. Its significance depends on context, audience, reliance and the action that follows.
Lesson 2 · Risk decoder
Risk emerges where Source, Pathway and Receptor meet.
The environmental Source–Pathway–Receptor model provides a practical way to examine AI risk. Adjust each component to see why no single feature determines the consequence.
SPR
Thinking score
27 / 125
Moderate interaction
Risk becomes stronger where source potency, pathway transmissibility and receptor susceptibility overlap.
S 3 × P 3 × R 3 = 27
This is a structured thinking aid, not a statistical probability or formal safety certification.Manage the pathway
Reduce blind reliance, uncontrolled sharing and excessive automation.
Protect the receptor
Build capability, routes for challenge and safeguards for vulnerable users.
Lesson 3 · Three-dimensional consequence matrix
Which pillar may fail, who is affected, and how serious could it become?
The pillars are causal routes to consequences. They matter because of what can happen next.
Selected consequence cell
- Failure route
- Possible consequence
- Interrupt the pathway
Worked example · Water-safety prediction
A rare error may still be unacceptable.
An AI map labels a contaminated source as safe. A local officer trusts the output, the community continues using the source, and exposure leads to illness.
AI predictionSafe→Human interpretationTrusted→ActionSource remains open→ConsequenceExposure and illness
Apply it to your project
Turn principles into a practical action plan.
Describe the role of AI and assess eight safeguards. The tool identifies where further evidence, design or governance is needed.
Answer all 8 questions. 0 answered.
About this framework
Responsible AI becomes meaningful when we ask what may happen next.
This educational tool combines a lifecycle consequence pathway, an adapted Source–Pathway–Receptor risk model and a three-dimensional consequence matrix. It supports reflection and discussion. It does not replace legal, regulatory, ethical or domain-specific assessment.