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  • Getting Started
  • ๐Ÿ”Taxonomy
    • Introduction
    • Effect (SEP) View
      • Security
      • Ethics
      • Performance
    • Lifecycle View
    • Schema
  • ๐Ÿ“ฆDatabase
    • Introduction
    • Framework
      • Base Classes
      • Auxiliary Classes
    • ๐Ÿ› ๏ธBackend
    • ๐Ÿ› ๏ธEditorial Interface
  • ๐Ÿ‘ทโ€โ™€๏ธDeveloper Tools
    • Python SDK
      • Datamodels
      • Connectors
      • ๐Ÿ› ๏ธIntegrations
        • garak
        • ModsysML (Apollo)
        • ๐ŸขGiskard
        • Inspect AI
      • API Reference
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  1. Taxonomy

Lifecycle View

PreviousPerformanceNextSchema

Last updated 1 month ago

The stages in this view represent high-level sequential steps of a typical ML workflow. Following the widely-used Cross-industry standard process for data mining () framework, we designate six stages in this view.

ID
Stage

L01

Business Understanding

L02

Data Understanding

L03

Data Preparation

L04

Model Development

L05

Evaluation

L06

Deployment

Figure T.2 reconciles the two different views of the AVID taxonomy. We conceptually represent the potential space of risks in three dimensions, consisting of the risk domainโ€”S, E, or Pโ€”a specific vuln pertains to; the (sub)category within a chosen domain; and the development lifecycle stage of a vuln. The SEP and lifecycle views are simply two different sections of this three-dimensional space.

๐Ÿ”
CRISP-DM
Figure T.2. SEP and Lifecycle views represent different sections of the space of potential risks in an AI development workflow.