SIPOC mapping for Intelligent Agents

While AI models are basically functions that map inputs to outputs, the SIPOC model extends this model notion by adding stakeholders in AI applications.

As one and the same model will produce different results in different contexts and under different circumstances, for different individuals and stakeholders, end-to-end SIPOC process mapping will make the AI application context and its impacted stakeholders transparent.   

As LLMs have become an all-purpose or general-purpose technology, all-in-one SIPOC mapping of data input to output, algorithms & stakeholders is a precursor of envisaged AI applications.

LLMs: what you ask is what you get ?

SIPOC model

Suppliers > Input > PROCESS > Output > Customers

SIPOC mapping for AI applications

Data source>Data Input> Algorithm: objective function >Data Ouput>Destination

AI model explained

Who ? Supppliers > Stakeholders upstream

            Customers > Stakeholders downstream

What ? Input data & Output data

How ? Process > algorithmic transparency

When ? Events trigger

Where ? anywhere

Why ? SIPOC map from Suppliers > Input > Process > Output to Customers

SIPOC map for input to output transformation from data source to destination

In an age of complex algorithms and invisible decision-making, SIPOC gives us clarity. It shows us not just what happens but who makes it happen, with what and for whom.

In AI context, SIPOC is a floating signifier leading the way from sophisticated simplicity to a sustainable humanity model (UN SDGs).

Using the following link you can access this sandbox SIPOC model in the ProcessHorizon web app and adapt it to your needs (easy customizing) and export or print the automagically created visual AllinOne SIPOC map as a PDF document or share it with your peers: https://app.processhorizon.com/enterprises/zoQdqZmSmc1vEQUcjgNYDYPD/frontend