Why is ML research disconnected from reality

In the last two years, there have been a large number of machine learning research papers published on COVID-19. However, the number of these research papers that actually helped in solving ground-level problems form a very small portion. A study analysed 232 algorithms developed for diagnosing or predicting the disease spread. It found that none of these studies was fit for clinic use. Just two of these 232 tools were deemed promising enough for future testing. This is a good indication of how many machine learning and AI research works are disconnected from the ground realities and the real challenges at hand. In his recent tweet, Christoph Molnar, data scientist and author of Interpretable Machine Learning: A Guide for Making Black Box Models Explainable, described the same. He wrote