Later that spring I learned that the food-delivery robots had indeed arrived during the break. A friend of mine who’d spent the winter on campus told me that for several weeks they had roamed the empty university sidewalks, learning all the routes and mapping important obstacles. The machines had neural nets and learned to navigate their environment through repeated interactions with it. This friend was working in one of the emptied-out buildings near the lake, and he said he’d often looked out the window of his office and seen them zipping around below. Once he caught them all congregated in a circle in the middle of the campus mall. “They were having some kind of symposium,” he said. They communicated dangers to one another and remotely passed along information to help adapt to new challenges in the environment. When construction began that spring outside one of the largest buildings, word spread through the robot network—or, as one local paper put it, “the robots remapped and ‘told’ each other about it.”

One day I was passing through campus on my way home from the library. It was early evening, around the time the last afternoon classes let out, and the sidewalks were crowded with students. I was waiting at a light to cross the main thoroughfare—a busy four-lane street that bifurcated the campus—along with dozens of other people. Farther down the street there was another crosswalk, though this one did not have a light. It was a notoriously dangerous intersection, particularly at night, when the occasional student would make a wild, last-second dash across it, narrowly escaping a rush of oncoming traffic. As I stood there waiting, I noticed that everyone’s attention was drawn to this other crosswalk. I looked down the street, and there, waiting on the corner, was one of the delivery robots, looking utterly bewildered and forlorn. (But how? It did not even have a face.) It was trying to cross the street, but each time it inched out into the crosswalk, it sensed a car approaching and backed up. The crowd emitted collective murmurs of concern. “You can do it!” someone yelled from the opposite side of the street. By this point several people on the sidewalk had stopped walking to watch the spectacle.

The road cleared momentarily, and the robot once again began inching forward. This was its one shot, though the machine still moved tentatively—it wasn’t clear whether it was going to make a run for it. Students began shouting, “Now, now, NOW!” And magically, as though in response to this encouragement, the robot sped across the crosswalk. Once it arrived at the other side of the street—just missing the next bout of traffic—the entire crowd erupted into cheers. Someone shouted that the robot was his hero. The light changed. As we began walking across the street, the crowd remained buoyant, laughing and smiling. A woman who was around my age—subsumed, like me, in this sea of young people—caught my eye, identifying an ally. She clutched her scarf around her neck and shook her head, looking somewhat stunned. “I was really worried for that little guy.”

Later I learned that the robots were observed at all times by a human engineer who sat in a room somewhere in the bowels of the campus, watching them all on computer screens. If one of the bots found itself in a particularly hairy predicament, the human controller could override its systems and control it manually. In other words, it was impossible to know whether the bots were acting autonomously or being maneuvered remotely. The most eerily intelligent behavior I had observed in them may have been precisely what it appeared to be: evidence of human intelligence.

From the book God, Human, Animal, Machine: Technology, Metaphor, and the Search for Meaning, by Meghan O’Gieblyn. Published by Doubleday, a division of Penguin Random House LLC.

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