Troubling Trends in Machine Learning Scholarship

Flawed scholarship threatens to mislead the public and stymie future research by compromising ML’s intellectual foundations. Indeed, many of these problems have recurred cyclically throughout the history of AI and, more broadly, in scientific research. In 1976, Drew McDermott chastised the AI community for abandoning self-discipline, warning prophetically that "if we can’t criticize ourselves, someone else will save us the trouble." The current strength of machine learning owes to a large body of rigorous research to date, both theoretical and empirical. By promoting clear scientific thinking and communication, our community can sustain the trust and investment it currently enjoys.