I'd predict the opposite: 'tabular data' of the usual sort will yield bad human performance. See the clinical prediction literature going back to Paul Meehl: given some tabular data and asked to predict stuff like disease progression or recidivism risk, the expert human will often underperform a simple linear model, never mind 'real' tabular ML. We're really good at stuff like images, yes, but give us a CSV and ask us to predict housing prices in Boston in 1970...