IEEE use case matrix

As explained in Delivering Machine Learning Projects: From design to deployment

The IEEE use case matrix is a framework for relating artificial-intelligence application contexts to potentially relevant ethical concerns.

The IEEE use case matrix relates an AI application context to likely ethical concerns, helping teams turn an ethics review into project decisions. section 6.6.2

Use the matrix to:

• Classify the application context, such as operational efficiency. section 6.6.2
• Prioritize concerns including data governance and human agency and oversight. section 6.6.2
• Convert concerns into delivery controls, such as insight and interaction tooling, disablement controls, or trend-only forecasts. section 6.6.2
• Record and communicate decisions through an ethics report. section 6.6.2

The Bike Shop assessment

A Bike Shop application contained no identified personal data, but the matrix still highlighted data governance and human agency as significant. The team scheduled controls for sprint 2, including ways to disable predictive analytics and fall back to trend-only or steady-state forecasts. section 6.6.2

Figure 6.9 Ethics assessment matrix for The Bike Shop, based on an IEEE use case matrix

Inspect the ethics assessment matrix for the Bike Shop application. section 6.6.2

How Delivering Machine Learning Projects: From design to deployment covers it

How deep it goes

Maps concerns to sprint actions and governance artifacts, but does not provide a detailed matrix construction method.

Examples

Uses The Bike Shop application, predictive forecasts, disablement controls, and an ethics assessment matrix.

What it assumes

Assumes a defined application, project objectives, and familiarity with its data sources and predictive analytics.

What you can do after

Apply it via an ethics assessment matrix to prioritize concerns and define operational safeguards.

How it connects

Connects operational efficiency with data governance, human agency and oversight, predictive analytics, and data privacy.

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Related concepts

• ethicsproduces · Ethics is the study and application of principles for evaluating morally acceptable conduct, decisions, and outcomes.

This explainer was generated by Manning's knowledge graph from the text of Delivering Machine Learning Projects: From design to deployment. The section links point to the parts of the book it draws on.