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Campaign Business Media Brand of the Year 2020
Travel Media Awards Trade Publication of the Year 2020 - Print & Online

What steps do we take to avoid it?

As a data scientist there is a responsibility to constantly check the models that you design:

 

• Have we intentionally or unintentionally ignored any group?
• Is the feature set relevant to what we’re trying to measure or predict?
• Are the ways we have sorted training data proportionate to the population data as a whole?
• Is the model optimised and methodology appropriate to its purpose?
• Is your model accuracy similar for all groups?
• Are you models meeting the criteria of the use case they were designed for?
• Were the feature set in the training environment similar to the ones experienced with the data in the current environment?
• Is the model’s weighting of certain features what is to be expected?
• Are there any anomalies in predictions or unexpected in the data?

What should you know when you start looking for bias in your business?

  • Realise that bias can happen to any business, big or small
  • Bias isn’t always easily seen so be prepared to dig
  • Be objective. Don’t audit with bias. If you don’t have the resources to do it yourself make sure that partner with a third party who you can trust to be objective
  • Keep an eye on the shape of your people, those you recruit, reward and retain
  • Schedule regular data reviews
  • Audit your customer data, your communications – your target audiences, imagery, and messaging
  • Processes and models are journeys not destinations – regular checking is key

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TTG - Travel Trade Gazette
For Smarter, Better, Fairer Travel
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