FAT in Algo

Algorithm dynamics: Asking Google, Facebook and others to be ‘fair’

What do you learn when learning about Machine Learning? That in personalising services, massive networks like Google, Facebook are promoting extremism and inequality. Two computer scientists have built an antidote in the hope that people will become aware and eventually demand fair personalisation


Pervasive personalisation. Two words that describe how algorithms shape our views and behaviour and determine what we see, buy, read online. There’s so much value in personalisation that tech companies are giving away algorithmic tools for free; the actual money lies in the application, in manipulating large population groups. And as this happens, much of societal biases are reinforced online.

Elisa Celis and Nisheeth Vishnoi, professors at Ềcole Polytechnique Fẽdẽrale de Lausanne, Switzerland, propose a framework to de-bias algorithms. They’ve built a prototype for ‘Balanced Search’, to demonstrate how it’s possible to mitigate extreme views…

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