  Generative AI is rapidly transforming medical imaging and text analysis,
offering immense potential for enhanced diagnosis and personalized care.
However, this transformative technology raises crucial ethical, societal, and
legal questions. This paper delves into these complexities, examining issues of
accuracy, informed consent, data privacy, and algorithmic limitations in the
context of generative AI's application to medical imaging and text. We explore
the legal landscape surrounding liability and accountability, emphasizing the
need for robust regulatory frameworks. Furthermore, we dissect the algorithmic
challenges, including data biases, model limitations, and workflow integration.
By critically analyzing these challenges and proposing responsible solutions,
we aim to foster a roadmap for ethical and responsible implementation of
generative AI in healthcare, ensuring its transformative potential serves
humanity with utmost care and precision.
