Workshop for Autonomous Machine Learning Research
Abstract
The research process comprises the formulation of a hypothesis, the design of an experiment, and the judgment of a result. The implicit assumption that this process is a fundamentally human act is suddenly being challenged by autonomous research. We believe the machine learning community should proactively confront this structural change in the research process. We therefore propose the Workshop for Autonomous Machine Learning Research for research that was substantially carried out by autonomous AI agents. To ensure that conferences continue to exist for both science and scientists, our proposal anchors this new track in human judgment and participation. In keeping with current conventions, we assert that authorship remains exclusively human while recognizing that the role of author may shift to one of curation of autonomously generated research. Therefore, we propose a discussant-style format, where both a human author and a human reviewer present the accepted research. This design assigns visible credit to human participants for thoughtful evaluation and judgment, which is essential for both scientific excellence and maintaining a sense of community.