PAISE^® – process model for AI systems engineering

Abstract

The application of artificial-intelligence-(AI)-based methods within the context of complex systems poses new challenges within the product life cycle. The process model for AI systems engineering, PAISE®, addresses these challenges by combining approaches from the disciplines of systems engineering, software development and data science. The general approach builds on a component-wise development of the overall system including an AI component. This allows domain specific development processes to be parallelized. At the same time, component dependencies are tested within interdisciplinary checkpoints, thus resulting in a refinement of component specifications.

Explainable AI: introducing trust and comprehensibility to AI engineering

“…1. Similar decompositions can be found in process models like CRISP-DM [18], KDD [5] or PAISE [7]. It can be easily seen that the majority of the stages of this pipeline are concerned with "Instead of focusing on the code, companies should focus on developing systematic engineering practices for improving data in ways that are reliable, efficient, and systematic.…”