gWhy

GWhy is a term used in discussions of explainability and debugging in software systems and artificial intelligence to describe a compact, structured representation of the reasons behind observed outcomes or behaviors. It is commonly imagined as a graph in which nodes represent statements, events, or decisions, and edges represent causal or justificatory relationships that connect these elements.

Origin and usage: The term emerged in academic and industry conversations as a mnemonic for "graph of why." It is not a formal standard or specification, but a conceptual tool used in pedagogy and research to illustrate how a system arrived at a particular result. It can be adapted for different domains, including machine learning, software tracing, and decision pipelines.

Structure: In gWhy representations, node types may include premises (initial inputs or facts), inferences (intermediate conclusions), and outcomes (final results). Edges may carry labels such as justification, evidence, or confidence, and may be weighted to indicate strength or reliability. The graph can be serialized as JSON, YAML, or other formats for interoperability and auditing.

Applications: gWhy is used for explainable AI, debugging complex pipelines, and compliance auditing. It helps developers and auditors identify where assumptions or data quality influence outcomes, and provides a traceable rationale for decisions.

Limitations: As a concept, gWhy does not prescribe a single methodology. Its usefulness depends on the availability of interpretable premises and the ability to capture justifications without oversimplification. It may also introduce overhead in model design and documentation.