INNOVATOR OF THE YEAR Josh Tenenbaum
at the MIT Quest
launch in March
2018. Credit: Kris
“That’s my job, and my colleagues, to
really work on that,” he said.
His team has made some strides in this
area, particularly in the study of what he
refers to as “common sense.”
A three month-old child doesn’t look out
into the world and see patterns and pixels
like a machine-learning algorithm, explained
Tenenbaum. Instead they see things,
objects and people and understand that
these are what make up the world.
“That in some form seems to be built into
the brain and we’ve made some progress
using probabilistic programming tools to
but it wasn’t anything like the phenomena
that it is now with the level of resources
it has. I would take a computer science
class or two, but I was really thinking about
wanting to build models of the mind and
create theories of human intelligence.”
Eventually, his career shifted into a
subfield of cognitive science known as
computational cognitive science—the
idea of using the tools and language of
computer science and AI to think about
the human mind.
Children’s minds as models
It requires “baby steps,” to better understand the human mind, said Tenenbaum.
“What is currently most exciting to me,
and what has driven a lot of my work
recently, is thinking a lot about human
children. If you like, we are taking baby
steps starting from actual babies,” said
Tenenbaum. “You could argue that the old-
est dream of AI is this one—the idea that
you could build a machine that grows into
intelligence the way a person does, that
This concept is not new, said Tenenbaum.
Computer science-pioneer Alan Turing
proposed the idea years ago, asserting that
the only way to develop human-like intelli-
gence in a machine was to build something
that started off like a child because it was
presumably simpler, and then teach it in a
similar manner as a child is taught.
“That sounds great but it hasn’t really
worked until now and we are still far
from making it work because of one
key thing—children’s brains and minds
turned out to not be as simple as Turing
thought,” said Tenenbaum.
There is currently some understanding
of how babies learn, said Tenenbaum, but
most of this comes from the study of cognitive development and is not in the form
of math models or engineering.
Josh Tenenbaum (first row, far left) with colleagues from the Curious Minded Machine
program, a new interdisciplinary collaboration designed to imbue robots with human-like
curiosity led by Honda Research Institute. Credit: Honda Research Institute.