Bias in data

Four people are outside on a pavement in front of some railings and lush green foliage. It is a relaxed scene and appears to be viewed through a camera with ‘time log information positioned in the top left and right corners respectively.. One sits on a bench and has an identification box around her bag and head. In original version of this image, identifying features including female and caucasian were displayed, but it has been left blank for use in different languages. Three men are in the centre-right of the image. On the original image one has an identification box with an ID number and identifying features listed as male, black, hoodie. Identifiers can be layered on to this image to show the kind of characteristics biometric systems might identify.
Image by Comuzi / © BBC / Better Images of AI / Surveillance View B / CC-BY 4.0

I’m pulling together a dozen ideas to produce some workshop material next year about improving evaluation practice in learning and development – keep looking out for it early next year.

One area I’ve been focusing on has been bias. There isn’t bias in data per se, just bias in what’s collected, when, how, why, who collects and interprets it and who, how, when, and what is reported.

Bias in data? Not really.

Bias in learning and development. Oh yes.

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