Rice statistician's warning grabs headlines around the globe Statistics

Rice University statistician Genevera Allen knew she was raising an important issue when she spoke earlier this month at the American Association for the Advancement of Science (AAAS) annual meeting in Washington, but she was surprised by the magnitude of the response. Allen, associate professor of statistics and founding director of Rice's Center for Transforming Data to Knowledge (D2K Lab), used the forum to raise awareness about the potential lack of reproducibility of data-driven discoveries produced by machine learning (ML). She cautioned her audience not to assume that today's scientific discoveries made via ML are accurate or reproducible. She said that many commonly used ML techniques are designed to always make a prediction and are not designed to report on the uncertainty of the finding. Her comments garnered worldwide media attention, with some commentators questioning the value of ML in data science.