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Algorithmic Bias and Fairness #18

Season 1 Episode 18 | 10m 56s

We're going to talk about five common types of algorithmic bias we should pay attention to: data that reflects existing biases, unbalanced classes in training data, data that doesn't capture the right value, data that is amplified by feedback loops, and malicious data.

Aired: 12/12/19
Extras
In our final episode of Crash Course AI, we're going to look towards the future.
Jabril tries to make an AI to settle the question once and for all.
Search engines are just AI systems that try to help us find what we’re looking for.
We need to save Jabril and John Green Bot’s movie nights.
We’re going to talk about recommender systems.
One of the most common ways we interact with computers is through language
We’re going to focus on the benefits of humans and AI working together.
We create a game and then build an AI to destroy it.
One of the best test spaces for building new AI systems are games.
Robots are built to perform specific tasks.
Latest Episodes
In our final episode of Crash Course AI, we're going to look towards the future.
Jabril tries to make an AI to settle the question once and for all.
Search engines are just AI systems that try to help us find what we’re looking for.
We need to save Jabril and John Green Bot’s movie nights.
We’re going to talk about recommender systems.
One of the most common ways we interact with computers is through language
We’re going to focus on the benefits of humans and AI working together.
We create a game and then build an AI to destroy it.
One of the best test spaces for building new AI systems are games.
Robots are built to perform specific tasks.