Full Stack Fest 2018

Adam L Smith

Avoiding Digital Bias

Sep 2018

AI and machine learning introduce complex algorithms which affect our daily life.

Despite all the benefits of machine learning it can be biased, and there are risks that are introduced which can manifest themselves as bias towards customers or users, for example in the form of racism, sexism and other forms of discrimination. This presentation will explain the unique ethical risks that can occur when personal data and machine learning meet, give newsworthy examples where bias has been demonstrated, and discuss practical steps developers and testers can take to mitigate them.


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