This commentary explores three fundamental premises surrounding the human-AI partnership. First, a human-AI collaboration is perhaps superior to either working independently, as AI enhances human capabilities but requires oversight to ensure ethical and accurate outcomes. Second, AI's effectiveness is limited by the quality and biases of its training data, which underscores the need for diverse, unbiased datasets. Without proper data, AI could perpetuate flawed or biased decisions, impacting areas such as hiring, healthcare, and empathy-driven interactions. Finally, generative AI is prone to “hallucinations,” where it produces plausible yet incorrect outputs. These errors pose significant risks in high-stakes sectors like healthcare and security. As AI becomes more ingrained in society, these challenges raise ethical concerns around job displacement, loss of human autonomy, and biased decision-making. Here, we also examine the implications of AI hallucinations and model collapse, stressing the importance of continuous human intervention to mitigate AI-driven inaccuracies. Ultimately, a balanced partnership between human judgment and AI's scalability, along with rigorous oversight, is necessary to unlock AI's potential while safeguarding societal values.