|Chapter 13: Information and Education
Originally published by Henry Holt and Company 1999. Published on KurzweilAI.net May 15, 2003.
Nicholas Negroponte is the visible face of the Media Lab, an articulate
advocate of being digital. Far fewer people know of Jerome Wiesner's
role. Jerry was MIT's president, and Kennedy's science advisor.
He's been described as the member of the administration during that
exceptional era who was not only smart, but also wise.
As I started attending faculty meetings I soon discovered that
Jerry was even more bored with them than I was. If I sat next to
him he would tell me stories, like how the debate in the meeting
we were ignoring mirrored a fight he had had in the Cabinet. Through
these discussions I learned a secret: the Media Lab is really a
front for an even more interesting project.
After a lifetime of shaping science, Jerry felt that there was
a big hole in the middle of academia in general, and at MIT in particular.
Disciplines were kept apart, basic and applied research happened
in different places at different times, and industrial interaction
was based on handing off results rather than intimate collaboration.
Most serious of all, content of many kinds had no place on campus.
As a physicist in a normal department I could look at transistors,
but not toys. I might see industrialists, but not artists.
The Media Lab was his last grand project, a meta-experiment in
organizing inquiry for a new era. He knew that this goal was so
interesting and important that he could never really discuss it
openly. There would be too many conflicting interests for it ever
to be accomplished by a committee. Instead, Nicholas and his colleagues
at the predecessor to the Media Lab, the Architecture Machine Group,
provided the perfect research agenda and working style to create
a laboratory laboratory.
It took me a long time to recognize this hidden project. When I
started visiting, I didn't see the Media Lab as a place to do serious
science; it was an entertaining diversion from the real work that
I was doing elsewhere. I expected to eventually go to an industrial
laboratory to set up my research group (I had found that I was too
practical to be happy in a traditional academic setting). And Nicholas
certainly didn't see the Media Lab as a place for something as dry
and remote as a physics lab.
When we finally sat down to talk, he told me a story to explain
his surprise at the prospect of my coming to the Media Lab. He said
that if there was a monastery on top of a hill, and a brothel down
in a valley, he wouldn't expect there to be too much traffic between
the two institutions. I was struck by this image, but for the life
of me I couldn't figure out which lab was which. I'm even less sure
The more we spoke, the more we realized that it did make sense
for the Media Lab to have a physics group. For me, it would provide
the support to work on physics in the new domains where it is needed.
I knew how to do physics; the hard thing was getting access to the
emerging context. For Nicholas, it would provide the tools and techniques
to help open up computers and move information out into the world
where it is needed.
In retrospect I'm embarrassed by how long it took me to decide
that it was okay to have fun for a living. I had been trained to
believe that the sorts of things I had been doing in the Media Lab,
like working on Yo-Yo's cello, were done on the side by serious
scientists, not as part of their day job. I thought that trying
to do physics outside of a Physics department was going to be a
radical and uncertain step.
I realized that it was going to work when students started showing
up, explaining that they loved physics, but that they knew they
did not want to study it in a traditional department. They were
unwilling to disconnect their personal passions from their intellectual
pursuits, and they did not want to follow a conventional academic
career path with limited prospects for funding and employment. This
was brought home one day by a headline in MIT's campus newspaper,
"Cutbacks Announced in Dance and Physics."
I was also concerned about where my students would publish their
research papers; I had expected that we would have to dissect out
the pure academic nuggets from the impure context. Here again I
realized that this was not going to be a problem when journal editors
started showing up in my lab to solicit submissions. They recognize
that the world is changing, and they don't want to keep publishing
the same kinds of papers.
As my lab grew, my biggest surprise was watching how my students
were reinventing the organization of their education. Scientific
training has traditionally been based around extensive classwork,
illustrated by occasional labs. My students were turning that inside
That they were in my lab at all was due to Edwin Land, the founder
of Polaroid. He felt that MIT's undergrads should be in working
laboratories participating in real research as it happened, rather
than doing rote repetitions in lab classes long after the fact.
He provided the seed funding for a very successful program to do
The undergrads in my lab used it for far more than what Land originally
envisioned. It became their home, the place where they learned to
work with people and use disciplines to solve hard problems. Their
classes took on a supporting role, providing the raw material that
got shaped into an education in my lab. Over and over they told
me that they had no idea why they were being taught something until
they got to use it in one of our projects. For them, this experience
was more like being in a studio than a classroom.
I found that one of the best predictors of a student's success
working this way was their grades: I look to make sure they have
a few F's. Students with perfect grades almost always don't work
out, because it means they've spent their time trying to meticulously
follow classroom instructions that are absent in the rest of the
world. Students with A's and F's have a much better record, because
they're able to do good work, and also set priorities for themselves.
They're the ones most able to pose—and solve—problems
that go far beyond anything I might assign to them.
The present system of classes does not serve the students, or their
teachers, very well. One week an MIT undergrad, and independently
an MIT professor, asked me the same question: how does the bandwidth
of a telephone line relate to the bit rate of a modem? The bandwidth
is the range of frequencies a phone line can pass, which is set
by the phone companies and regulatory agencies. The bit rate is
how fast data gets sent, all too noticeable as the speed with which
a Web page loads. They were wondering how the bandwidth affects
the bit rate that can be achieved, and what the prospects were for
This is the problem that Shannon solved in the 1940s with his theory
of information: the maximum possible bit rate is the bandwidth times
the logarithm of one plus the ratio of the strength of the signal
to the amount of noise. The bit rate can be improved by using more
frequencies, by sending a stronger signal, or by decreasing the
noise. Modems are now near the limit of a conventional phone channel,
although the wires themselves can handle data much faster.
I was surprised to find that someone could be at MIT as long as
both the student and professor had been, studying communications
in many forms, and never have heard of a result as important as
this. Not only that, both were unprepared to understand where it
came from and what conclusions might be drawn from it.
Entropy shows up in two places in their question, in analyzing
the noise that is intrinsic to the materials in a telephone, and
in analyzing the information that can be carried by a message sent
through the telephone. Although these two calculations are closely
related, physicists learn how to do the former in one part of campus,
and engineers the latter in another. Very few students manage to
be sufficiently bilingual to be able to do both. Those who are either
take so many classes beyond the usual load that they manage to squeeze
in a few different simultaneous degrees, or take so few classes
that they have enough time to put these pieces together on their
own. Either path requires unusual initiative to answer such a reasonable
Faced with students who knew a lot about a little, I decided that
I had to teach everything. This took the form of two semester-long
courses, one covering the physical world outside of computers (The
Physics of Information Technology), and the other the logical world
inside computers (The Nature of Mathematical Modeling). My students
loved them; some of my peers at MIT hated them. This was because
each week I would cover material that usually takes a full semester.
I did this by teaching just those things that are remembered and
used long after a class has ended, rather than everything that gets
thrown in. This starts by introducing the language in an area so
that the students, for example, know that bit rate and bandwidth
are related by Shannon's channel capacity. Then I cover enough of
each subject to enable students to be able to understand where the
results come from and how they are used; at this point they would
know how to calculate the channel capacity of a simple system. Each
week ends with pointers into the specialized literature so that,
for example, students learn that Shannon's limit effectively can
be exceeded by taking advantage of quirks of human perception. Although
this brisk pace does a disservice to any one area, unless I teach
this way most people won't see most things. It is only by violating
the norms of what must be taught in each discipline that I can convey
the value of the disciplines.
What connects the work in the Media Lab is a sensibility, a style
of working, a set of shared questions and applications. It's not
a discipline, a distinct body of knowledge that has stood the test
of time and that brings order to a broad area of our experience.
Progress on the former relies on the latter.
In many places computers are studied in separate departments, meaning
that students who like computers get less exposure to mathematics
and physics, and hence can have less insight into how computers
work. This can result in their using the wrong tool for the wrong
problem, and in their being unable to distinguish between hard things
that look easy and easy things that look hard.
A number of computer scientists have told me that they want to
mount display screens in glasses. They know that the eye cannot
focus on something so close, so they intend to be clever and blur
the image in just the right way to compensate for the optics of
the eye. Unfortunately, this nice idea has no chance at all of working.
The light passing through a lens must be specified by both its intensity
and direction; the image on a display can control only the intensity.
There is no pattern that can change the direction that light is
emitted from a conventional display.
Or, some computer scientists were looking for a source of random
numbers for cryptography, which depends for security on having a
steady supply of random keys. They hit on the idea of aiming the
camera connected to their computer at a 1960s lava lamp, and using
the motion of the blobs as a source of randomness. In fact, a lava
lamp is appealing to watch precisely because it is not completely
random; there is a great deal of order in the motion. The electrical
noise from a simple resistor is not only much easier to measure,
it is one of the most random things that we know of. A far more
convenient device can solve their problem far better.
One more computer scientist showed me the automated cart he developed
for delivering mail. With great pride he turned it on and together
we watched it crash into the wall. He was measuring the position
of the cart by counting the revolutions of its wheels; if they slip
at all it gets completely lost. I explained that there were techniques
for measuring location inside a building, something like the GPS
system used outside of a building. His instant response was, "Oh,
that's hardware." It was the wrong level of description for him,
so he was going to struggle on with software patches for a device
that could never work reliably.
An education that forces people to specialize in hardware, or software,
sends them out into the world with an erroneous impression that
the two are easily separated. It is even embodied in our legal code,
in the workings of the U.S. Patent Office. A patent must scrupulously
distinguish between apparatus claims, on hardware, and method claims,
on software. This means that "the medium is the message" is actually
illegal: the message must be separated from the medium for patent
The best patent examiners recognize that new technology is stretching
the boundaries of old rules, and are flexible about interpreting
them. The worst examiners refuse to accept that a single entity
can simultaneously embody a physical apparatus and a logical method.
I've spent years winding my way through the legal system with a
particularly obtuse examiner who insists on trying to split an invention
into its component hardware and software, even though the function
of the device cannot be seen in either alone but arises only through
Companies can't help but notice that these kinds of distinctions
no longer make sense. I realized that we're living through a new
industrial revolution when I saw how many senior executives visiting
my lab said that they had no idea what business they were in. A
newspaper company gathers and creates information, annotates and
edits it, sells advertising, runs printing presses, and has a delivery
fleet. As digital media make it possible to separate these functions,
which of them are core competencies and which are legacy businesses?
The answer is not clear, but the question certainly is.
One morning I met with a company that explained that they had reached
the limit of complexity in what could be designed with a computer,
and given the development cost of their product they needed better
interfaces for designers to interact with large amounts of information.
That afternoon a company explained that they had reached the limit
of complexity in what could be designed with a computer, and given
the development cost of their product they needed better interfaces
for designers to interact with large amounts of information. The
former made video games; the latter jet engines.
In the face of such rapid and uncertain change, a few lessons are
emerging about how companies can respond. Instead of storing up
large inventories of supplies and products, raw materials should
arrive just in time to make products on demand. Management and computing
should be done close to where the business happens, not in a central
office. And production should be organized in flexible workgroups,
not in regimented assembly lines or narrow departments.
Many of the same constraints apply to education, but few of these
lessons have been learned. Universities go on filling students with
an inventory of raw knowledge to be called on later; this is sensible
if the world is changing slowly, but it is not. An alternative is
just-in-time education, drawing on educational resources as needed
in support of larger projects.
One of the best classes I ever taught at MIT was at one in the
morning in Penn & Teller's warehouse in Las Vegas. We had gone
out with a group of students to finish debugging the spirit chair
prior to its first performance. In the middle of the night all of
the hardware finally came together. Before the music could be tested,
a computer had to combine the raw signals from the sensors to determine
where the player's hands were. This is a classic data analysis problem.
So I gave an impromptu lecture on function fitting to students who
were eager (desperate, really) to learn it, and who then retained
the ideas long after the performance was over.
The big new thing on campuses now is distance learning, using videoconferencing
and videotapes to let people far from a place like MIT take classes
there. This is an awful lot like mainframe computing, where there
is a centralized learning processor to which remote learning peripherals
get attached. Just like management or information processing, the
most valuable learning is local. Far more interesting than letting
people eavesdrop from a distance is providing them with tools to
Some of this is happening naturally, as the Web lowers the threshold
to make information widely available. More and more articles get
shared through servers such as http://xxx.lanl.gov
without needing to travel to research libraries to read expensive
journals. Through the working notes my group puts on the Web, I
discovered that we have virtual collaborators who use our results
and provide thoughtful feedback long before the notes are formally
And some of this is happening through the tools. The same technology
that lets us embed surprisingly sophisticated and flexible sensing
and computing into children's toys or consumer appliances helps
make the means for meaningful scientific experimentation much more
widely accessible. A Lego set today can make measurements that were
done only in specialized labs not too long ago.
Academics visiting the Media Lab usually start by asking what department
we are in. They have a hard time understanding that the Media Lab
is our academic home, not an appendage to another department. Uniquely
at MIT, it both grants degrees and manages research. Learning and
doing elsewhere are separated into departments and laboratories.
Military types visiting want to see an organizational chart, and
are puzzled when we say that there isn't one. I spent a day with
a Hollywood studio executive who kept asking who gets to green-light
projects. He was completely perplexed when I told him that more
often than not projects get initiated by the undergrads. Most every
day I come to work knowing exactly what we should do next, and most
every day they show me I'm wrong.
The reality is that there are many different ways to view the organization
of the Media Lab, all correct: by projects, by disciplines, by levels
of description, by industrial consortia, by people. It functions
as an intellectual work group that can easily be reconfigured to
tackle new problems. Once visitors understand this (lack of) structure,
the next question they ask is how the Media Lab can be copied, and
why there aren't more already.
In part, the answer is that it just requires getting these few
organizational lessons right, but few institutions are willing to
make that leap. We've had an unblemished record of failure in helping
start spin-offs from the Media Lab elsewhere. What always happens
is that when it comes time to open the new lab, whoever is paying
for it expects to run it, choosing the projects and controlling
the intellectual property. They're unwilling to let go of either,
letting the research agenda trickle up from the grassroots, and
eliminating intellectual property as any kind of barrier to collaboration.
In part, the answer is that there are a few unique features of
the environment of the Media Lab that don't show up on any formal
documents. To start, running the Media Lab is a bit like driving
a bumper car at an amusement park. While we're more or less in control,
the rest of MIT provides a great deal of enabling physical and intellectual
infrastructure. This leads to steady jostling, but it would be impossible
for the Media Lab to function in isolation outside of that less-visible
Even that has a hidden piece. It was only after spending time at
both Harvard and MIT that I realized that Cambridge has one university
with two campuses, one for technology and one for humanities. While
of course there are plenty of exceptions, broadly MIT's strength
as a technology school frees Harvard from even trying to lead the
world in bridge building, and because of Harvard's strengths MIT
can be less concerned about Classics. Since MIT does not have a
school of education, or a film school, there is not a turf battle
over the Media Lab working on those things.
Then there are the students. It's not that they're any smarter
than students elsewhere; it's that they're so desperate to make
things work. I've never seen any group of people anywhere so willing
to go without eating and sleeping to reduce something to practice.
It almost doesn't even matter what it is.
One day I came in and found that my lab had been co-opted to make
a grass display, a lawn mounted on mechanical pixels that could
move to make an ambient agricultural information channel. The students
building it labored heroically to make the drive circuits that could
handle that much power, and fabricate the structure to merge the
drive solenoids with the sod. The only thing they couldn't do is
tell me why they were doing it. Once they realized that it was possible,
they could not conceive of not making one.
About a month later I came in and found that my students had been
up many nights in a row, hacking an interface into a global satellite
system to get sensor data off the summit of Mount Everest for an
expedition that Mike Hawley was putting together. They developed,
debugged, and deployed a satellite terminal in a few days, slept
for a few days, then went back to whatever else they had been doing.
No one had ever been able to collect weather data from on top of
Everest, since most people there are just trying to stay alive.
The data from their probe went via satellite to the Media Lab, and
from there it went to planetary scientists as well as to base camp
to be relayed up to climbers on the mountain.
When the designer of the satellite link, Matt Reynolds, showed
up in my lab as a freshman he was already the best radiofrequency
engineer I'd ever met, including during my time as a technician
at Bell Labs. This is a technical specialty that few people really
master, and usually then only after a lifetime of experience. It's
hard not to believe that Matt's knowledge is genetic, or comes from
a past life. He as much as confirmed that one evening after we attended
a conference in San Francisco, when we were happily sitting on a
deck in Big Sur watching a memorable sunset. I casually asked him
how he chose to come to MIT. The conversation ground to a halt;
it was almost as if I had said something inappropriate. He paused,
struggled to answer, and then said that he had known he was going
to go to MIT since he was a fetus. He didn't choose to go to MIT,
he had a calling to serve.
Another freshman, Edward Boyden, appeared one day with a ten-page
manifesto for the future of all research. It was the most interesting
nonsense I've read; he didn't have any of the details right, but
the spirit and sensibility were wise far beyond his limited scientific
experience. He came in with almost no relevant skills. I set him
to work helping a grad student; in January Edward learned computer
programming, in February he learned how to do 3D graphics and digital
video, in March how to numerically model the behavior of electric
fields, so that in April he could put all the pieces together and
render the physics underlying the sensors we were developing to
see with fields. Having caught up to the grad student, Ed's only
reaction was to be frustrated by his own slow pace.
It makes no sense to funnel that kind of raw problem-solving ability
through a conventional curriculum. Edward learns too quickly, and
is too intellectually omniverous, to be content following a prescribed
path through knowledge. Matt spends a tiny fraction of each day
taking care of the formal requirements of his classes, then gets
back to learning things that go far beyond the classes. They arrived
understanding a lesson that it usually takes students longer to
learn: the goal of classes is to get you to not want to take classes.
Once students know how to read the literature, and teach themselves,
and find and learn from experts, then classes should take on a supporting
role to help access unfamiliar areas.
One of the most meaningful moments in my life came in an airport
lounge. I was waiting to fly back from my brother's wedding, and
ended up sitting with our family rabbi. In this informal setting,
with time before the plane and no distractions, I screwed up my
courage to say something that I had wanted to tell him for a long
time. I explained that I found the morality, and history, and teachings
of Judaism to be deeply significant, but that I had a hard time
reciting formal rituals I didn't believe in. He beamed, and said
that the same was true for him. Letting me in on a secret, he told
me that he saw many of the ceremonial aspects of Jewish observance
as a formal scaffolding to engage people's attention while the real
meaning of the religion got conveyed around the edges. The formal
structure was valuable, but as a means rather than an end.
Rather than start with the presumption that all students need most
of their time filled with ritual observance, the organization of
the Media Lab starts by putting them in interesting environments
that bring together challenging problems and relevant tools, and
then draws on more traditional classes to support that enterprise.
The faster the world changes, the more precious traditional disciplines
become as reliable guides into unfamiliar terrain, but the less
relevant they are as axes to organize inquiry.
WHEN THINGS START TO THINK by Neil Gershenfeld. ©1998 by
Neil A. Gershenfeld. Reprinted by arrangement with Henry Holt and