4 ms·

Thanks for sharing that article - I wrote it months ago, and there's been plenty more papers that have come out since, but there's really not much I'd change in

by jph00 6y ago

Thanks for sharing that article - I wrote it months ago, and there's been plenty more papers that have come out since, but there's really not much I'd change in it today. The science has only become more clear. I think the 538 article really under-states the evidence. I'm quoted in it, but only about my thoughts on the political situation. I actually pointed out to the author that the science is stronger than any other intervention we have.

YeGoblynQueenne 6y ago
So you're Jeremy Howard? Hi. Someone on this thread recommended this article by yourself, on The Conversation, that I managed to miss a couple of months ago (I can't find again the post where the link to the article was given, apologies): https://theconversation.com/masks-help-stop-the-spread-of-coronavirus-the-science-is-simple-and-im-one-of-100-experts-urging-governors-to-require-public-mask-wearing-138507 https://theconversation.com/masks-help-stop-the-spread-of-co... From what I can see in the article, you were first convinced that masks should be worn after watching a youtube video. Then, having been convinced by the video you found more evidence to support your conviction. I quote from the article: The research that first convinced me was a laser light-scattering experiment. Researchers from the National Institutes of Health used lasers to illuminate and count how many droplets of saliva were flung into the air by a person talking with and without a face mask. The paper was only recently published officially, but I saw a YouTube video showing the experiment in early March. The results are shockingly obvious in the video. I have to say, this rings all manner of alarm bells. For example, a video on youtube cannot be seen as evidence of anything, even if it's from the NIH; that video could at best be seen as evidence of a likely mechanism for the spread of the virus, but evidence of a mechanism that could produce an effect is not evidence that the mechanism produces that effect; etc. In short, all this is not "strong science", even if it led to strong convictions. In any case, we all have to remember -data scientists first of all- that "data science" is not a "science" in the sense that e.g. epidemiology is a science and in a time of a public health crisis, the stage should be left clear for the relevant experts.

by jph00 6y ago

YeGoblynQueenne 6y ago

So you're Jeremy Howard? Hi. Someone on this thread recommended this article by yourself, on The Conversation, that I managed to miss a couple of months ago (I can't find again the post where the link to the article was given, apologies): https://theconversation.com/masks-help-stop-the-spread-of-coronavirus-the-science-is-simple-and-im-one-of-100-experts-urging-governors-to-require-public-mask-wearing-138507 https://theconversation.com/masks-help-stop-the-spread-of-co... From what I can see in the article, you were first convinced that masks should be worn after watching a youtube video. Then, having been convinced by the video you found more evidence to support your conviction. I quote from the article: The research that first convinced me was a laser light-scattering experiment. Researchers from the National Institutes of Health used lasers to illuminate and count how many droplets of saliva were flung into the air by a person talking with and without a face mask. The paper was only recently published officially, but I saw a YouTube video showing the experiment in early March. The results are shockingly obvious in the video. I have to say, this rings all manner of alarm bells. For example, a video on youtube cannot be seen as evidence of anything, even if it's from the NIH; that video could at best be seen as evidence of a likely mechanism for the spread of the virus, but evidence of a mechanism that could produce an effect is not evidence that the mechanism produces that effect; etc. In short, all this is not "strong science", even if it led to strong convictions. In any case, we all have to remember -data scientists first of all- that "data science" is not a "science" in the sense that e.g. epidemiology is a science and in a time of a public health crisis, the stage should be left clear for the relevant experts.