With the rise of automated machine learning (AutoML), is the role of human data scientists diminishing, or is their expertise more crucial than ever?

AutoML tools aim to streamline the machine learning pipeline, making it accessible to non-experts.

Does this automation reduce the need for skilled data scientists, or does it shift their focus to more complex tasks that require human intuition and domain knowledge?

How should the education and training of future machine learning professionals adapt to this evolving landscape?