Developed by Jacob Eli Jimenez

🐙 GitHub 💼 LinkedIn

<aside> 🌳

About this field guide

I built this field guide to make the UC Berkeley taxonomy of AI trustworthiness easier to visualize, explore, and learn from.

</aside>

How to read the tree

The source taxonomy contains 150 properties of trustworthiness organized across seven AI lifecycle stages. Within those stages, properties are grouped under NIST trustworthiness characteristics.

Properties marked with an asterisk are identified by the source as potentially less relevant for AI systems that are not human facing.

graph TD
    A["AI Trustworthiness · 150 properties"]
    A --> S1["1. Plan and Design · 61 properties"]
    A --> S2["2. Collect and Process Data · 13 properties"]
    A --> S3["3. Build and Use Model · 14 properties"]
    A --> S4["4. Verify and Validate · 14 properties"]
    A --> S5["5. Deploy and Use · 12 properties"]
    A --> S6["6. Operate and Monitor · 21 properties"]
    A --> S7["7. Use or Impacted By · 15 properties"]

Lifecycle at a glance

Lifecycle stage Purpose Properties
Plan and Design Articulate and document the system’s concept and objectives, underlying assumptions, context, and requirements. 61
Collect and Process Data Collect and process data, including gathering, validating, cleaning, and documenting dataset metadata and characteristics. 13
Build and Use Model Create, select, and train models or algorithms. 14
Verify and Validate Verify and validate, calibrate, and interpret model output. 14
Deploy and Use Pilot the system, check compatibility with legacy systems, verify regulatory compliance, manage organizational change, and evaluate user experience. 12
Operate and Monitor Operate the AI system and continuously assess recommendations and impacts, both intended and unintended, against objectives and ethical considerations. 21
Use or Impacted By Use the system or technology, monitor and assess its impacts, seek mitigation of impacts, and advocate for rights. 15

Explore the 150 Trustworthiness Properties

The taxonomy can also be explored as a structured property library. I built this view for readers who prefer working with tables and want to compare properties across lifecycle stage, trustworthiness characteristic, human facing relevance, source questions, and NIST AI RMF mappings.

Untitled

AI Trustworthiness Property Library

Full Taxonomy Tree

Expand each lifecycle stage, then each trustworthiness characteristic, to move down the tree into the individual properties. Each property opens into a learning node.

1. Plan and Design

2. Collect and Process Data

3. Build and Use Model

4. Verify and Validate