Source: MIT Technology Review
Summary
A new study finds that training AI models on human-generated data can lead to biased and discriminatory outcomes. Researchers analyzed data from a popular chatbot and found that it was trained on a dataset that contained biases against certain groups of people. The study highlights the need for more diverse and representative training data to ensure that AI models are fair and unbiased. According to the researchers, “it also takes a lot of energy to train a human.”
Our Reading
The launch follows a familiar script.
Another study reveals that AI models can perpetuate existing biases if trained on human-generated data. Because, of course, humans are infallible. The study suggests that more diverse training data is needed, because that’s not what we’ve been saying for years. The researchers are shocked, SHOCKED, that biased data leads to biased AI. It also takes a lot of energy to train a human, apparently.
Author: Evan Null
Deja Vu All Over Again
This study sounds like a broken record. We’ve been hearing about the dangers of biased AI training data for years. When will we learn?
The Usual Suspects
The researchers found that the chatbot was trained on a dataset that contained biases against certain groups of people. Who could have seen that coming?
Surprise, Surprise
The study’s findings are about as surprising as a sunrise. Of course, biased data leads to biased AI. What’s next, a study that reveals water is wet?
Training Humans
The researchers’ comment about training humans being energy-intensive is… interesting. Are they implying that humans are inherently flawed and need to be “trained” to be unbiased? That’s a whole can of worms.
More of the Same
This study is just another example of the tech industry’s ” Groundhog Day” problem. We keep repeating the same mistakes, expecting different results. When will we learn?
