Not that I'm necessarily defending this sentiment, I did recently watch a lecture about ML (I think it was fast.ai's Jeremy Howard) with a similar real life example.

He spoke about a project from the 2000's looking to apply an artificial neural net to a medical diagnosis problem. What they did was spend many years of work with domain experts to identify the best features for the net to use. The professor then proceeded to explain that nowadays feature engineering approaches became so much more powerful, that significantly better results could be achieved in a more recent project much faster and without almost any domain expertise.