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The Man Who Invented Intelligent Traffic Control a Century Too Early

With traffic accidents soaring, Charles Adler imagined an intelligent transportation system that was ahead of its time

12 min read
Adler demonstrates one of his automated safety systems.
Sound Off: Adler demonstrates one of his automated safety systems, which triggered a light when a car passed over a sound detector in the road.
Photo: Charles Adler, Jr. Collection/Archives Center/National Museum of American History, Smithsonian Institution

On a cool December day in 1925, Charles Adler Jr. stood beside Falls Road, a state highway on Baltimore’s north side. He was there to test his latest invention: an electromagnetic apparatus that would automatically slow cars traveling at unsafe speeds. Adler had embedded magnetic plates in the road where it led into a precarious curve, and he was now waiting for a specially prepared car to drive over the magnets. The magnets would activate a speed governor connected to the vehicle’s engine, slowing it to 24 kilometers per hour.

Adler had developed this automatic speed-control system for railroad crossings, the scene of many deadly accidents at the time. But he soon came to imagine all sorts of applications for it: “Dangerous road intersections, streets on which schools are located, bad curves, and even steep down grades,” according to an article in the Baltimore News.

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This Idea Wasn't All Wet: The Sensing Water-Saving Shower Head Debuts

An engineer’s dinner-table invention is finally a consumer product

4 min read
A mounted and running showerhead that says oasense and has a blue light on it.
Oasense

For Evan Schneider, the family dinner table is a good place for invention. “I’m always, ‘Wouldn’t it be cool if this or that,’” he says, “and people would humor me.”

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Can AI’s Recommendations Be Less Insidious?

Artificial intelligence has us where it wants us

5 min read
illustration of hand holding megaphone with different bubbles of computer widgets
iStock

Many of the things we watch, read, and buy enter our awareness through recommender systems on sites including YouTube, Twitter, and Amazon. Algorithms personalize their suggestions, aiming for ad views or clicks or buys. Sometime their offerings frustrate us; it seems like they don’t know us at all—or know us too well, predicting what will get us to waste time or go down rabbit holes of anxiety and misinformation. But a more insidious dynamic may also be at play. Recommender systems might not only tailor to our most regrettable preferences, but actually shape what we like, making preferences even more regrettable. New research suggests a way to measure—and reduce—such manipulation.

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