Address data bias and ethics

Create a framework or policy for how to gather, use and store data ethically including ways to avoid data bias. Sytems and processes to address bias in data that may result in discriminaton or amplification of stereotypes.

Why the contribution is important

As data becomes used more and more to influence decision making and generate insights, we need to ensure we are not disadvataging anyone. Trustworthy data is free from human bias.

by SarahB on October 30, 2021 at 02:59PM

Current Rating

Average rating: 5.0
Based on: 1 vote


  • Posted by Leeanna November 08, 2021 at 17:36

    Yes, agree. Especially when using automated methods of data collection ie AI. Transparency is important when understanding how the data was collated, interpreted and any analysis and projections would ideally show the methodology (and not hide behind a black box) used.

    An interesting consideration for those developing ML techniques :)
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