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Manage AI Bias Instead of Trying to Eliminate It
Article

Manage AI Bias Instead of Trying to Eliminate It

To remediate the bias built into AI data, companies can take a three-step approach.



Editorial Rating

8

Qualities

  • Scientific
  • Applicable
  • Insider's Take

Recommendation

Increasingly, businesses are turning to AI systems to automate their processes, data analysis and interactions with employees and customers. As a result, fairness has emerged as a knotty problem. AI systems inherently reflect and perpetuate the pervasive bias in data sets – a flaw that has no mathematical solution. In succinct and implementable fashion, AI risk governance expert Sian Townson recommends a three-phase approach to manage AI systems’ intractable biases.

Take-Aways

  • AI systems inevitably perpetuate bias.
  • Since you can’t eliminate AI bias, compensate for its unfairness in three ways.
  • Bias is difficult to identify because it remains so pervasive.

About the Author

Sian Townson is an expert in AI risk and governance frameworks and holds a doctorate in mathematical modeling from Oxford University. She currently works as a partner for the global consultancy, Oliver Wyman.