Tackling algorithmic bias by promoting transparency in health datasets
Health data is highly complex and can be challenging to interpret without knowing the context in which it was created. Data biases can be encoded into artificial intelligence (AI) health technologies, worsening existing health inequalities at scale. The STANDING Together recommendations give guidance to those who are creating and using health data on how to minimise this risk. They were developed via an international consensus process involving representatives from 58 countries. In this session, the lead researchers for STANDING Together will talk through the recommendations and how they can be used to develop AI health technologies which are safe and effective for everyone.
Speakers:
Joseph Alderman
Clinical Research Fellow, University of Birmingham
Xiaoxuan Liu
Associate Professor, University of Birmingham
Moderators:
Matthias Groeschel
Resident physician, Charité - Berlin University of Medicine
Eva C. Keller
Carlo Schmid Fellow, International Telecommunication Union (ITU)
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Disclaimer:
The views and opinions expressed are those of the panelists and do not reflect the official policy of the ITU.