Machine learning requires huge, dynamic data sets. Conclusions are
delivered based on that data. Our models cannot get better than the
data we can give them. However good your AI is, "garbage in, garbage
out".

How do we build balanced models and avoid biased data? Can AI be
trusted? Let's see what industry experts have to say about this.

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Agenda:
Network and Mingle
Introduction to our debaters
Opening Statements
The Debate
Q&A
The Chicago Tech Debate Game
Network with the debaters