was like a child. He said the real secret to
human intelligence is our ability to learn.
Thirty years of developmental cognitive science have shown that children are
the best learners on earth. But how do they
learn so much so quickly? For the last 15
years developmental cognitive scientists
and computer scientists have been trying
to answer this question, and the answers
shape new kinds of machine learning (see
“Kindergarten for Computers,” page 52).
Many of the recent advances in AI
have come through techniques like deep
learning, which can detect complicated
statistical regularities in enormous data
sets. Computers can suddenly do things
that were impossible before, like labeling
images on the Internet.
The trouble with this sort of purely
statistical machine learning, though, is
that it depends on data that’s already been
selected by humans. Machines need gigantic human-generated data sets just to be
able to look at a new picture and say “
kitty-cat!”—something a baby can do after seeing just a few examples.
An alternative in machine learning
and cognitive science—the “
probabilistic models” framework—takes a different
approach. These systems formulate and
test abstract hypotheses. Bayesian inference procedures have been particularly
important. For example, you can mathematically describe a particular causal
hypothesis as a directed graph that systematically generates a particular data pattern, and then calculate just how likely
that hypothesis is to be true, given the data
you see. Machines have become great at
testing hypotheses against the data in this
way, with consequences for everything
from medical diagnosis to meteorology.
We’ve shown that young children use data
to evaluate hypotheses in a similar way.
But there are two things even very
young children do that are still far beyond
the abilities of current computers. We are
trying to understand these abilities both
formally and empirically, and these inves-
tigations may allow us to design more
powerful kinds of AI.
The really hard problem is deciding
which hypotheses, out of all the infinite
possibilities, are worth testing. Even preschoolers are remarkably good at coming
up with brand new concepts and hypotheses in a creative and imaginative way. In
fact, our research has shown that they can
sometimes do this better than grown-ups.
A second area where children outshine
computers is in their ability to go out and
explore and experiment with the world
around them—we call this “getting into
everything.” Developmental cognitive scientists are just beginning to understand
and formalize this kind of active learning.
The wildly creative imaginations and
ceaseless exploration of young children
may be the key to their impressive learning abilities. Studying those children can
give us clues about how to design computers that can pass the more profound
Turing test and be almost as smart as a
Alison Gopnik is a professor of psychology
at the University of California, Berkeley.
The Encryption Myth
Law enforcement has plenty of tools to get
your data, even with encryption.
“The terrorists are going dark”—that
phrase came back into vogue after the
Paris attacks of mid-November, implying
that encryption is enabling attackers to go
undetected. But we’re being given a false
choice: either we allow law enforcement
unfettered access to digital communications or we let the terrorists win. It’s not
It’s true that much of the world’s com-
munication has shifted from easy-to-
intercept text messages and phone calls
to mobile apps that provide improved pri-
vacy and security. But there’s still plenty
of data that is not fully encrypted or not
encrypted at all—the kind of data that
officials say they need to catch the bad
guys. Not all the approaches to getting the
data are clearly legal, and many app devel-
opers (including me) are actively working
to defend against them, since they’re often
used to monitor activists or journalists.
But it’s disingenuous to pretend they don’t
exist. Here are a few:
- If someone carries a mobile phone,
his or her every movement, call, and use of
the Internet is being tracked by the mobile
service provider. Accessing this data often
doesn’t require a warrant.
- Even in well-regarded implementations by WhatsApp and Apple, it’s probably possible to disable access to or reduce
the strength of encryption on a per-user
basis, without the user even knowing.
- An encrypted chat can be monitored
if the app supports group chat or synching
conversations among multiple devices. If
law enforcement can compel the app service provider to add a new device to an
account without notifying existing users,
then they’re in.
- Most cloud data is encrypted to protect it from attackers, not from the service provider itself. Some services say they
encrypt data in the cloud, but the user
doesn’t hold the key—the service does.
Law enforcement can thus get access to a
cloud backup of all the messages, contacts,
calendars, photos, location data, and more
that users often unwittingly store there.
Whether we’re aware of it or not, we’re
all constantly generating and exposing our
private data, and the opportunities for targeted surveillance are vast—within both
clearly legal and legally gray areas.
Nathan Freitas leads the Guardian Project, which develops open-source mobile