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Machine biases are not intentional. They reflect cognitive biases, preconceptions, and judgement of the creators of AI systems and societal structures encoded in the data sets used for machine learning. They can have disastrous consequences and they should be actively identified and mitigated. This phase will help you understand the following:

  • Why unchecked machine biases are dangerous.
  • What human cognitive biases are and how they relate to AI.
  • What algorithmic (AI) biases are and why they happen.
  • What AI truly is and how machine learning (ML) is related to AI.
  • What the ML process looks like and how it relates to AI biases.

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

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Mitigate Machine Bias

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

Solution Set Steps

  1. Start here – read the Executive Brief
  2. Understand AI biases
    • Mitigate Machine Bias – Phase 1: Understand AI Biases
  3. Identify data biases
  4. Identify model biases
  5. Mitigate machine biases and risk

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