AI Literacy: The 5-stage event-driven AI Operating & Control model

My objective is for AI users to understand: how information becomes AI intelligence, how intelligence is used to perform tasks & how the entire journey is governed to produce reliable, safe & useful outcomes.

The five-stage event-driven AI Operating & Control model follows the analogy of the Vacuum Cleaner sucking up digital data to Data Refinery t0 Intelligence Engine t0 Intelligent Vehicle to Destination, with governance & controls embedded in every stage.

Each stage is represented by a complete event-driven SIPOC model with a start event, objective, process owner, suppliers, inputs, process, outputs, customers, end event & eventually a key control at subprocess level.

The five stages can be viewed as two connected systems:

AI Capability System: stages 1–3 How Information becomes an AI model with learned capabilities. Main accountability: AI provider

AI Action System: stages 4–5 How AI capabilities become actions & valuable outcomes. Main accountability: Deploying organization & user

1. The Giant Vacuum Cleaner: Acquire Data

Acquire suitable & legally usable information for AI development. Are the data sources legitimate, traceable & authorized for their intended use ?

2. The Data Refinery: Prepare Data

Transform raw information into suitable, quality-controlled AI training data. Has unreliable, inappropriate or sensitive material been appropriately identified & handled ?

3. The Intelligence Engine: Train the LLM

Develop an AI model capable of generating useful & sufficiently reliable responses. Has the model been tested for factual errors, harmful behavior, bias & other foreseeable failures ?

4. The Intelligent Vehicle: Operate AI

Apply AI capabilities to the user's task within appropriate instructions, permissions & safeguards. Does the AI operate within its authorized scope & can humans intervene before consequential actions ?

5. The Destination: Create Human Value

Convert AI-generated information or actions into verified, beneficial outcomes. Is the AI result correct enough for its intended use & did it produce the desired outcome without unacceptable harm ?

Like a car, AI requires more than a powerful engine. It needs trustworthy fuel, a defined destination, reliable navigation, effective brakes & accountable operators.

Event-driven Action model StartEvent >Suppliers >Inputs >Process >Outputs >Customers >EndEvent

Using the following link you can access this sandbox model in the ProcessHorizon web app and adapt it to your needs (easy customizing) and export or print the automagically created visual AllinOne event-driven SIPOC map as a PDF document or share it with your peers: https://app.processhorizon.com/enterprises/hDLiWT3KzvLrkzwsvTWSKQEU/frontend