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科学美国人60秒: 人工智能能“嗅出”不安全的食物

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Artificial Intelligence Sniffs Out Unsafe Foods

人工智能能“嗅出”不安全的食物

The Food and Drug Administration has to recall hundreds of foods every year. Like cookie snack packs with chunks of blue plastic hiding inside, Salmonella-tainted taco seasoning or curry powder laced with lead.

美国食品和药物管理局每年必须召回数百种食品。例如里面藏着大块蓝色塑料的饼干零食包,受沙门氏菌污染的墨西哥卷饼调味料或含有铅的咖喱粉。

It can take months before a recall is issued. But now researchers have come up with a method that might fast-track that process, leading to early detection and, ultimately, faster recalls.

召回可能需要数月时间。但现在,研究人员已经提出了一种方法,可以快速跟踪这一过程,从而实现早期检测,并最终加快召回速度。

The system relies on the fact that people increasingly buy foods and spices online. And people tend to write reviews of products they buy online—which are like bread crumbs to food-safety officials sniffing out dangerous products.

该系统依赖于人们越来越多地在网上购买食物和香料这一事实。人们倾向于对他们在网上购买的产品写评论,这对食品安全官员来说就像面包屑一样,可以嗅出危险产品。

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The researchers linked FDA food recalls from 2012 to 2014 to Amazon reviews of those same products. They then trained machine-learning algorithms to differentiate between reviews for recalled items and reviews for items that had not been flagged.

研究人员将2012年至2014年FDA召回的食品与亚马逊对这些产品的评论联系起来。然后,他们训练了机器学习算法来区分被召回产品的评论和未被标记产品的评论。

And the trained algorithms were able to predict FDA recalls three quarters of the time. They also identified another 20,000 reviews for possibly unsafe foods—most of which had never been recalled. The results are in [JAMIA Open].

经过训练的算法能够在原来四分之三的时间预测FDA的召回。他们还识别了可能不安全的2万条评论——但这些食品多数从未被召回。该研究结果发表在[JAMIA Open]杂志上。

The World Health Organization estimates that 600 million people worldwide get sick annually, and more than 400,000 people die from contaminated food. “So having tools that allow us to detect this faster and hopefully investigate and do recalls faster will be useful not just in the U.S. but in other countries around the world as well.” Study author Elaine Nsoesie of Boston University.

世界卫生组织估计,全世界每年有6亿人患病,40多万人死于受污染的食品。“因此,拥有能够让我们更快发现这一问题、并有望更快进行调查和召回的工具,不仅对美国有用,对世界其他国家也有用。”来自波士顿大学的伊莱恩·恩索西,同时也是该研究的报告者说道。

She did add one caveat: even recalled products can still get five-star reviews. So stars alone don’t tell the whole sickening story. The proof, unfortunately, may still be in the pudding.

但她也提出了一个警告:即使是被召回的产品也可能获得五星评价。因此,单凭评价并不能讲述整个患病的故事。不幸的是,需要我们试试才知道。

Artificial Intelligence Sniffs Out Unsafe Foods

The Food and Drug Administration has to recall hundreds of foods every year. Like cookie snack packs with chunks of blue plastic hiding inside, Salmonella-tainted taco seasoning or curry powder laced with lead.

It can take months before a recall is issued. But now researchers have come up with a method that might fast-track that process, leading to early detection and, ultimately, faster recalls.

The system relies on the fact that people increasingly buy foods and spices online. And people tend to write reviews of products they buy online—which are like bread crumbs to food-safety officials sniffing out dangerous products.

The researchers linked FDA food recalls from 2012 to 2014 to Amazon reviews of those same products. They then trained machine-learning algorithms to differentiate between reviews for recalled items and reviews for items that had not been flagged.

And the trained algorithms were able to predict FDA recalls three quarters of the time. They also identified another 20,000 reviews for possibly unsafe foods—most of which had never been recalled. The results are in [JAMIA Open].

The World Health Organization estimates that 600 million people worldwide get sick annually, and more than 400,000 people die from contaminated food. “So having tools that allow us to detect this faster and hopefully investigate and do recalls faster will be useful not just in the U.S. but in other countries around the world as well.” Study author Elaine Nsoesie of Boston University.

She did add one caveat: even recalled products can still get five-star reviews. So stars alone don’t tell the whole sickening story. The proof, unfortunately, may still be in the pudding.


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