Mitigate Machine Bias – Phase 2: Identify Data Biases

Author(s): Natalia Modjeska

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Biases can be introduced into a machine learning (ML) system at any stage of the process, from the data you collect to the way it is collected (or created). This phase will take you through the following content and activities:

  • Where and how data biases originate.
  • How to address or mitigate data biases.
  • The “Datasheets for Datasets” framework being piloted by industry leaders to increase transparency around data set creation and bias mitigation.
  • Create your own template by adapting the datasheets for data sets approach and the template provided.
  • Complete datasheet for selected AI/ML project and data set.

Use this phase as part of the full blueprint, Mitigate Machine Bias.

View the Complete Blueprint:

Mitigate Machine Bias

Control machine bias to prevent discriminating against your consumers and damaging your organization.

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