it's very difficult to find a black cat in a dark room,

especially when there is no cat.

I find this a particularly apt description of science

and how science works --

bumbling around in a dark room, bumping into things,

trying to figure out what shape this might be,

what that might be,

there are reports of a cat somewhere around,

they may not be reliable, they may be,

and so forth and so on.

Now I know this is different than the way most people

think about science.

Science, we generally are told,

is a very well-ordered mechanism for

understanding the world,

for gaining facts, for gaining data,

that it's rule-based,

that scientists use this thing called the scientific method

and we've been doing this for 14 generations or so now,

and the scientific method is a set of rules

for getting hard, cold facts out of the data.

I'd like to tell you that's not the case.

So there's the scientific method,

but what's really going on is this. (Laughter)

[The Scientific Method vs. Farting Around]

And it's going on kind of like that.

[... in the dark] (Laughter)

So what is the difference, then,

between the way I believe science is pursued

and the way it seems to be perceived?

So this difference first came to me in some ways

in my dual role at Columbia University,

where I'm both a professor and run a laboratory in neuroscience

where we try to figure out how the brain works.

We do this by studying the sense of smell,

the sense of olfaction, and in the laboratory,

it's a great pleasure and fascinating work

and exciting to work with graduate students and post-docs

and think up cool experiments to understand how this

sense of smell works and how the brain might be working,

and, well, frankly, it's kind of exhilarating.

But at the same time, it's my responsibility

to teach a large course to undergraduates on the brain,

and that's a big subject,

and it takes quite a while to organize that,

and it's quite challenging and it's quite interesting,

but I have to say, it's not so exhilarating.

So what was the difference?

Well, the course I was and am teaching

is called Cellular and Molecular Neuroscience - I. (Laughs)

It's 25 lectures full of all sorts of facts,

it uses this giant book called "Principles of Neural Science"

by three famous neuroscientists.

This book comes in at 1,414 pages,

it weighs a hefty seven and a half pounds.

Just to put that in some perspective,

that's the weight of two normal human brains.

(Laughter)

So I began to realize, by the end of this course,

that the students maybe were getting the idea

that we must know everything there is to know about the brain.

That's clearly not true.

And they must also have this idea, I suppose,

that what scientists do is collect data and collect facts

and stick them in these big books.

And that's not really the case either.

When I go to a meeting, after the meeting day is over

and we collect in the bar over a couple of beers with my colleagues,

we never talk about what we know.

We talk about what we don't know.

We talk about what still has to get done,

what's so critical to get done in the lab.

Indeed, this was, I think, best said by Marie Curie

who said that one never notices what has been done

but only what remains to be done.

This was in a letter to her brother after obtaining

her second graduate degree, I should say.

I have to point out this has always been one of my favorite pictures of Marie Curie,

because I am convinced that that glow behind her

is not a photographic effect. (Laughter)

That's the real thing.

It is true that her papers are, to this day,

stored in a basement room in the Bibliothèque Française

in a concrete room that's lead-lined,

and if you're a scholar and you want access to these notebooks,

you have to put on a full radiation hazmat suit,

so it's pretty scary business.

Nonetheless, this is what I think we were leaving out

of our courses

and leaving out of the interaction that we have

with the public as scientists, the what-remains-to-be-done.

This is the stuff that's exhilarating and interesting.

It is, if you will, the ignorance.

That's what was missing.

So I thought, well, maybe I should teach a course

on ignorance,

something I can finally excel at, perhaps, for example.

So I did start teaching this course on ignorance,

and it's been quite interesting

and I'd like to tell you to go to the website.

You can find all sorts of information there. It's wide open.

And it's been really quite an interesting time for me

to meet up with other scientists who come in and talk

about what it is they don't know.

Now I use this word "ignorance," of course,

to be at least in part intentionally provocative,

because ignorance has a lot of bad connotations

and I clearly don't mean any of those.

So I don't mean stupidity, I don't mean a callow indifference

to fact or reason or data.

The ignorant are clearly unenlightened, unaware,

uninformed, and present company today excepted,

often occupy elected offices, it seems to me.

That's another story, perhaps.

I mean a different kind of ignorance.

I mean a kind of ignorance that's less pejorative,

a kind of ignorance that comes from a communal gap in our knowledge,

something that's just not there to be known

or isn't known well enough yet or we can't make predictions from,

the kind of ignorance that's maybe best summed up

in a statement by James Clerk Maxwell,

perhaps the greatest physicist between Newton and Einstein,

who said, "Thoroughly conscious ignorance

is the prelude to every real advance in science."

I think it's a wonderful idea:

thoroughly conscious ignorance.

So that's the kind of ignorance that I want to talk about today,

but of course the first thing we have to clear up

is what are we going to do with all those facts?

So it is true that science piles up at an alarming rate.

We all have this sense that science is this mountain of facts,

this accumulation model of science, as many have called it,

and it seems impregnable, it seems impossible.

How can you ever know all of this?

And indeed, the scientific literature grows at an alarming rate.

In 2006, there were 1.3 million papers published.

There's about a two-and-a-half-percent yearly growth rate,

and so last year we saw over one and a half million papers being published.

Divide that by the number of minutes in a year,

and you wind up with three new papers per minute.

So I've been up here a little over 10 minutes,

I've already lost three papers.

I have to get out of here actually. I have to go read.

So what do we do about this? Well, the fact is

that what scientists do about it is a kind of a controlled neglect, if you will.

We just don't worry about it, in a way.

The facts are important. You have to know a lot of stuff

to be a scientist. That's true.

But knowing a lot of stuff doesn't make you a scientist.

You need to know a lot of stuff to be a lawyer

or an accountant or an electrician or a carpenter.

But in science, knowing a lot of stuff is not the point.

Knowing a lot of stuff is there to help you get

to more ignorance.

So knowledge is a big subject, but I would say

ignorance is a bigger one.

So this leads us to maybe think about, a little bit

about, some of the models of science that we tend to use,

and I'd like to disabuse you of some of them.

So one of them, a popular one, is that scientists

are patiently putting the pieces of a puzzle together

to reveal some grand scheme or another.

This is clearly not true. For one, with puzzles,

the manufacturer has guaranteed that there's a solution.

We don't have any such guarantee.

Indeed, there are many of us who aren't so sure about the manufacturer.

(Laughter)

So I think the puzzle model doesn't work.

Another popular model is that science is busy unraveling things

the way you unravel the peels of an onion.

So peel by peel, you take away the layers of the onion

to get at some fundamental kernel of truth.

I don't think that's the way it works either.

Another one, a kind of popular one, is the iceberg idea,

that we only see the tip of the iceberg but underneath

is where most of the iceberg is hidden.

But all of these models are based on the idea of a large body of facts

that we can somehow or another get completed.

We can chip away at this iceberg and figure out what it is,

or we could just wait for it to melt, I suppose, these days,

but one way or another we could get to the whole iceberg. Right?

Or make it manageable. But I don't think that's the case.

I think what really happens in science

is a model more like the magic well,

where no matter how many buckets you take out,

there's always another bucket of water to be had,

or my particularly favorite one,

with the effect and everything, the ripples on a pond.

So if you think of knowledge being this ever-expanding ripple on a pond,

the important thing to realize is that our ignorance,

the circumference of this knowledge, also grows with knowledge.

So the knowledge generates ignorance.

This is really well said, I thought, by George Bernard Shaw.

This is actually part of a toast that he delivered

to celebrate Einstein at a dinner celebrating Einstein's work,

in which he claims that science

just creates more questions than it answers. ["Science is always wrong. It never solves a problem without creating 10 more."]

I find that kind of glorious, and I think he's precisely right,