Mitigate Machine Bias – Phases 1-4

Author(s): Natalia Modjeska

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AI is the new electricity. It is fundamentally and radically changing the fabric of our world and how we conduct business: AI-powered applications help increase internal efficiencies, better engage customers, and make faster, more accurate decisions. They also power disruptive business models.

But like any new technology, AI has a dark side: machine bias. If unchecked, machine bias leads to biased products and services that may treat some of your customers (or employees) differently, based on their race, gender, identity, age, etc., effectively discriminating against them. Bias is also bad for business: it can give rise to missed business opportunities, lost consumer confidence, reputational risk, regulatory sanctions, and lawsuits. Machine bias, therefore, is organizational risk.

This blueprint will help you learn about machine bias, educate your organization on this important topic, create a framework for documenting machine biases in order to mitigate them, and start laying the foundation for AI governance by following our four-phase methodology:

  • Understand AI biases
  • Learn about and identify data biases
  • Learn about and identify model biases
  • Mitigate machine biases and risk

By identifying and mitigating machine biases, you will minimize and control their impact, scope, and associated risks, and reduce your organization’s exposure and liability while reaping the benefits of AI.

View the Complete Blueprint:

Mitigate Machine Bias

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

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