The training data of written content, no matter the sources, will always be biased in one way: it doesn't contain thoughts people kept to themselves. Example 1

The training data of written content, no matter the sources, will always be biased in one way: it doesn't contain thoughts people kept to themselves. Example 1: Mr. X is very popular author among a small group, who chat daily about it on various websites. Outside of that group, many people know about Mr. X but don't care much about his works. So the majority of content about Mr. X is positive, even though the majority of opinions are ambivalent. Example 2: Somebody asks for help on StackOverflow. Two replies offer different answers, A and B. So the answers seem like they'd have equal value. If 90% of people think A is the right answer, the written content wouldn't reflect that, because those people won't write duplicate answers. I'm sure there are ways to account for these examples. Assigning different "weights" to content sources could help with #1, and feedback mechanisms like upvotes could help with #2. But I doubt those fixes would cover all the problems with the bias against thoughts that people never shared.