One of the most pressing concerns with the rise of generative AI is biased outputs. AI learns from datasets, replicating biases such as gender or race, perpetuating stereotypes. Addressing bias requires diverse datasets and algorithms to mitigate bias in content.
Handling bias in AI-generated content may necessitate human intervention. It prompts professionals to identify biases and develop solutions, emphasizing the need for cross-disciplinary collaboration to address issues effectively.
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