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Raising Them Right: AI and the Internet of Big Things 143

share its data streams publicly—this possibility poses a real challenge. How to
generate enough data to make the bridge useful but not so much that it
becomes the infrastructure equivalent of a neo-Nazi sexbot?

8.4 LEARNING TO LIVE WITH IT

Oneofmycolleagueson thebridgeprojectsuggeststhatsincethestructurewill
have been built by robots we should expect it to be altered by robots too. He
imaginesthemtweakingthedesigninresponsetotheusagepatternsrevealedin
the sensor data, and then coming out at night to add metal here, take it away
there: a virtual update followed by a physical one, both driven by robot intel-
ligence free of human decision making. The idea may seem far-fetched, but
only in its application to the direct amendment of physical objects.
There is reason to believe that Amsterdam as an experience is already
being significantly reshaped by AI. Consider the city’s massive tourist flows:
they are directed to their dinners by Yelp’s AI-powered search and to their
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beds by Booking.com’s. My colleagues and I are trying to understand these
flows by using smart infrastructure to observe them in motion. We may suc-
ceed, but, in a kind of intellectual arms race, the subtlety of AI influence will
probably continue to outstrip our ability to understand that influence over-
all, despite our own use of AI tools to do so. Amsterdam will continue to
change but, beyond a certain point, we may not be able to explain those
changes or influence them with precision.
I am not one of those losing sleep worrying about AI running amok, but
being unable to figure out why something good happened can keep you
awake at night too. I propose again the analogy of parenting. There you
begin by training, progress to teaching, fall back on influencing, and finally
learn yourself to live with your grownup child as best you can. Hopefully
with pride, but perhaps with horror, you eventually get to see that child’s
impact on the wider world.

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Yelp uses AI for much more than just search. Yelp recommendations, for example, begin with AI
interpreting the multitude of photos diners take in the city’s many restaurants. (See https://www.
fastcompany.com/3060884/your-photo-of-a-burrito-is-now-worth-a-thousand-words. This use of
AI was pioneered by an acquaintance of mine who after much thought realized that his hyper-local
recommendation engine was identifying “hipster” bars in part by the disproportionate amount of facial
hair seen in photos of male patrons. His startup was, predictably, purchased by Google.) Booking.com,
which happens to be based in Amsterdam, matches travelers to rooms thousands of times daily across the
city—https://www.booking.com/content/about.html states that “Every day, more than 1,550,000
room nights are reserved on our platform”; the Amsterdam-specific number was provided to me by an
internal source.