With Big Data the digital tracks we are leaving behind us can be exploited, leading to more personalized relationships but also to more fear and distrust. The feeling of being tracked can break the relationship with the customer.
This risk is particularly important in the context of public service organizations for which trust is an essential part of the job.
“Building trust” was the topic of the first panel discussion to be held at the EBU Big Data conference on 21 and 22 March 2017 in Geneva (Switzerland). I was discussing this issue with 4 other experts in the field : Joe Cannataci, Joe McNamee, Lokke Moerel and Alessandro Mantelero whom I had the please to discuss with the week before.
For those interested you can find my presentation below. I’m focusing in this presentation on building ethical and transparent algorithms, on the information and education part, but also on a new class of algorithms that will aim at showing to user how artificial intelligence is working.
Visualizing things, in particular black boxed algorithms, is for me an essential part of the trust building exercise. As I have explained in other articles, we need to open up algorithmic models and make them “auditable”.
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