I am a technical data architect who has a special interest in traditional sciences, trivial facts and general nerdy-ness. Throughout the years I developed a special appreciation for applied mathematics, especially in the field of statistics and machine learning. In everything I do, I like to look beyond the technical implementation and take special care in pragmatic problem-solving. I strive against over-engineering on a daily basis, and help companies on using their data more efficiently and more intelligently.
Killer Robots. Mass surveillance. Fake videos and news. Racist and biased AI. The news is flooded with bad and dangerous applications of machine learning. In this talk, you will learn from a person who makes a living out of developing AI algorithms why they can be dangerous and should be avoided.
This talk will give you a general overview of the state of AI and Machine Learning to date, where its caveats lie and what you currently should and should not do with it.
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