As a researcher invested in the development of AI, I see the merits in both requiring explanations and recognizing the limitations some AI systems have in providing them. While transparency is crucial for trust, certain models, like deep learning neural networks, inherently lack straightforward interpretability. At times, pushing for explanations can hinder innovation or misguide policy. Balancing these needs requires cautious evaluation.