Ethics and Artificial Intelligence (Part 4)
Channel: Laurent Bugnion
Date: 08/07/2019

This session was given at the DotNet Day conference in Zurich on May 28th, 2019.

*Part 4: The Bias, part 2*

Now Laurent talks about two kinds of biases which have a big impact on some populations in our societies: Racial bias and Gender bias. He illustrates these with examples explaining why this is probably the biggest ethical issues when using AI.

*Links in the video*
- Racial bias in Google Photos: http://gslb.ch/c335v-dotnetday19
- Racial bias in crime profiling: http://gslb.ch/c336v-dotnetday19
- Gender bias: http://gslb.ch/c344v-dotnetday19
- Slides and other information: http://gslb.ch/dotnetday19

*Abstract*
There is no question that Artificial Intelligence and Deep Learning will play an important role in the future (and the present!) of humanity. Taking advantage of faster and faster computers, larger and larger databases, we are able to run very complex algorithms against humongous amounts of data. This allows the creation of tools that can help us in complex areas of our lives. From autonomous vehicles to image and speech recognition, from assisting impaired humans to saving lives in critical situations, from inspecting industrial installations to sending machines in deep space or deep waters, the possibilities are amazing.

But this power comes with big responsibilities. How do we take steps to minimize flaws in the data we use for our models? How do we build machines that act for the greater good? What are the risks? In this session, Laurent Bugnion, a Senior Cloud Developer Advocate for Microsoft will talk about what could happen, and what we can do to try and prevent it.