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The 14-Year-Old Who Convinced People to Ban Dihydrogen Monoxide

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Jeff Swensen/Getty Images

In the spring of 1997, a 14-year-old’s school science fair project made a convincing argument to ban a dangerous chemical compound: dihydrogen monoxide, known as DHMO. Nathan Zohner, a junior high school student in Idaho, gave 50 of his fellow students a report called "Dihydrogen Monoxide: The Unrecognized Killer,” which accurately laid out the dangers of DHMO, convincing the majority of students to call for its ban. The experiment caused enough of a splash that it was picked up by The Washington Post.

The compound can corrode and rust metal and cause severe burns, the paper correctly argued. If you consume it, it can cause bloating and excessive urination and sweating. Thousands of people in the U.S. die from its accidental ingestion every year. If you are dependent on it, going through withdrawal can kill you. It’s found in significant quantities in acid rain, tumors, and more. Armed with this information and asked what the world should do about the threat of DHMO, 43 of Zohner’s classmates voted to ban the compound, citing its deadly nature. Lucky for them, no lawmaker would agree: DHMO is the chemical formula for water. Zohner—whose project won the grand prize at the regional science fair that year—wasn’t the first person to drive people into hysterics over the (real) dangers of DHMO, which can in fact burn, drown, and otherwise harm you in its various forms.

One of the earliest iterations of the hoax came from a Michigan paper called The Durand Express, which ran a piece decrying the harms of DHMO as an April Fool’s Day joke in 1983. Zohner’s experiment highlighted how easily young students—even those who had taken chemistry—could be taken in by misleading, fear-mongering scientific information. But scientific illiteracy isn’t just an issue with kids, and the widespread ability to Google basic facts hasn’t kept similar hoaxes and conspiracy theories from taking root in the public imagination today.

People still believe that fluoride in the water is a result of the government trying to poison them (fluoridation has been called one of the greatest public health achievements of the 20th century, causing a major decline in dental cavities and tooth loss across populations) or that vaccines cause autism (an idea, widely disproven, that was based on a 12-person study that used falsified data) or that deodorant can cause breast cancer (no scientific evidence supports this claim, according to the National Cancer Institute).

Consider the recent trend of “detoxing” propagated by publications like Goop. Most people don’t know what “toxins” they’re trying to filter out with their expensive juice cleanses to begin with, but doctors point out that the human body is pretty well equipped to handle the damaging materials you throw at it—like, say, alcohol. With no real scientific evidence to back it up, it’s the modern equivalent of leeching, experts have pointed out.

No doubt Gwyneth Paltrow would be as worried about DHMO as she is about underwire bras causing cancer (don’t worry, they don’t). The lesson of Zohner’s project, two decades later? Chemicals aren’t always bad. Everything is made of chemicals, and just because it has a name you can’t pronounce doesn’t mean it’s dangerous. It’s easy to get taken in by doomsday pseudoscience—because hey, pollution is truly dangerous and most of us haven’t taken a science class in decades. But with a little bit of skepticism and some basic research skills, we can all learn to sort through the false facts. In moderation, a little DHMO is a wonderful thing.

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Google's AI Can Make Its Own AI Now
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iStock

Artificial intelligence is advanced enough to do some pretty complicated things: read lips, mimic sounds, analyze photographs of food, and even design beer. Unfortunately, even people who have plenty of coding knowledge might not know how to create the kind of algorithm that can perform these tasks. Google wants to bring the ability to harness artificial intelligence to more people, though, and according to WIRED, it's doing that by teaching machine-learning software to make more machine-learning software.

The project is called AutoML, and it's designed to come up with better machine-learning software than humans can. As algorithms become more important in scientific research, healthcare, and other fields outside the direct scope of robotics and math, the number of people who could benefit from using AI has outstripped the number of people who actually know how to set up a useful machine-learning program. Though computers can do a lot, according to Google, human experts are still needed to do things like preprocess the data, set parameters, and analyze the results. These are tasks that even developers may not have experience in.

The idea behind AutoML is that people who aren't hyper-specialists in the machine-learning field will be able to use AutoML to create their own machine-learning algorithms, without having to do as much legwork. It can also limit the amount of menial labor developers have to do, since the software can do the work of training the resulting neural networks, which often involves a lot of trial and error, as WIRED writes.

Aside from giving robots the ability to turn around and make new robots—somewhere, a novelist is plotting out a dystopian sci-fi story around that idea—it could make machine learning more accessible for people who don't work at Google, too. Companies and academic researchers are already trying to deploy AI to calculate calories based on food photos, find the best way to teach kids, and identify health risks in medical patients. Making it easier to create sophisticated machine-learning programs could lead to even more uses.

[h/t WIRED]

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Land Cover CCI, ESA
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European Space Agency Releases First High-Res Land Cover Map of Africa
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Land Cover CCI, ESA

This isn’t just any image of Africa. It represents the first of its kind: a high-resolution map of the different types of land cover that are found on the continent, released by The European Space Agency, as Travel + Leisure reports.

Land cover maps depict the different physical materials that cover the Earth, whether that material is vegetation, wetlands, concrete, or sand. They can be used to track the growth of cities, assess flooding, keep tabs on environmental issues like deforestation or desertification, and more.

The newly released land cover map of Africa shows the continent at an extremely detailed resolution. Each pixel represents just 65.6 feet (20 meters) on the ground. It’s designed to help researchers model the extent of climate change across Africa, study biodiversity and natural resources, and see how land use is changing, among other applications.

Developed as part of the Climate Change Initiative (CCI) Land Cover project, the space agency gathered a full year’s worth of data from its Sentinel-2A satellite to create the map. In total, the image is made from 90 terabytes of data—180,000 images—taken between December 2015 and December 2016.

The map is so large and detailed that the space agency created its own online viewer for it. You can dive further into the image here.

And keep watch: A better map might be close at hand. In March, the ESA launched the Sentinal-2B satellite, which it says will make a global map at a 32.8 feet-per-pixel (10 meters) resolution possible.

[h/t Travel + Leisure]

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