Artificial intelligence systems learn from vast datasets, and a recent discussion on Reddit’s r/artificial highlights a crucial point: AI output is directly influenced by its training data. This means inherent biases or skewed perspectives present in the data can be replicated and amplified by the AI, leading to unintended and potentially problematic consequences. The discussion emphasizes the importance of carefully curating training data to mitigate these risks and ensure fairness and accuracy in AI applications. [Original Reddit post: https://old.reddit.com/r/artificial/comments/1nesabq/data_in_dogma_out_ai_bots_are_what_they_eat/]
AI Behavior Mirror Training Data, Reveals Potential Biases
