Thanks for pointing this out. The professor cited most certainly knows the best of ML. I'm guessing the author of this article simply attended the AAAS session

Thanks for pointing this out. The professor cited most certainly knows the best of ML. I'm guessing the author of this article simply attended the AAAS session where Allen gave a talk on recent work on addressing inferential challenges with modern ML and wrote this piece that doesn't do her work justice. See https://aaas.confex.com/aaas/2019/meetingapp.cgi/Session/2159 https://aaas.confex.com/aaas/2019/meetingapp.cgi/Session/215... & list of recent papers https://arxiv.org/search/?query=genevera+allen&searchtype=all&source=header https://arxiv.org/search/?query=genevera+allen&searchtype=al... Nearly all statisticians realize the need for more inferential thinking in modern ML. E.g. http://magazine.amstat.org/blog/2016/03/01/jordan16/ http://magazine.amstat.org/blog/2016/03/01/jordan16/ We still don't do that well in high dimension, low sample size regimes that make up the majority of life science research.