Show notes

This podcast is episode 2 of 4 recorded at UXLx 2019

People worry that machines are going to get too smart. The bigger problem right now is that they aren’t smart enough. Daryl Weir, mathematician and data scientist joins us to talk about machine learning and AI.

We discuss the impacts of seeding systems with biased data, how our designs and algorithms evolve and impact beyond what we had originally envisaged. We also talk about the new automation revolution and the importance of awareness, self-regulation and care. 

“Everything that is currently referred to as AI is basically statistics from the 1950s

Daryl Weir

(Listening time: 37 minutes)

References:

SaveSave

SaveSave