Facebook succeeded because it was about real people having a presence on the Internet. There were all these other social networking sites people had, but they were all about fictional people.
Peter ThielRead
Machine learning is looking for patterns in data. If you start with racist data, you will end up with even more racist models. This is a real problem.
Interpretation
The quote emphasizes the importance of data quality in machine learning and warns against biases in data.
Oren Etzioni's quote highlights a critical issue in the field of machine learning: the impact of biased data. When the data used to train algorithms contains inherent biases, the models developed as a result will also reflect and potentially amplify these biases, leading to problematic outcomes. This serves as a reminder that the integrity of the data is paramount in developing ethical and fair AI systems.
In practice
In a discussion about AI ethics, this quote can be used to illustrate the consequences of using biased data.
Facebook succeeded because it was about real people having a presence on the Internet. There were all these other social networking sites people had, but they were all about fictional people.
Machines take me by surprise with great frequency.
As soon as I have got flying to perfection, I have got a scheme about a steam engine.
While nations protect their physical borders, tech platforms leave digital borders wide open.
The problem with the Internet is that it gives you everything - reliable material and crazy material. So the problem becomes, how do you discriminate?
Type 'What is th' and faster than you can find the 'e' Google is sending choices back at you: 'What is the cloud?' 'What is the mean?' 'What is the American dream?' 'What is the illuminati?' Google is trying to read your mind. Only it's not your mind. It's the World Brain.
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