Beyond the exciting advancements, a significant, often overlooked negative externality of AI is its substantial environmental footprint, with the immense computational power needed to train large models consuming vast amounts of electricity and contributing heavily to carbon emissions. What's more, AI's reliance on historical data means it can unintentionally perpetuate and even amplify existing societal biases if the datasets aren't meticulously curated and diverse, leading to unfair or discriminatory outcomes in areas like hiring or loan applications. It's a critical challenge to ensure AI develops equitably and sustainably.