Light: it's the fastest thing in the universe, but we can still measure its speed if we slow down the animation, we can analyze light's motion using a space-time diagram, which takes a flipbook of animation panels, and turns them on their side.
In this lesson, we'll add the single experimental fact that whenever anyone measures just how fast light moves, they get the same answer: 299,792,458 meters every second, which means that when we draw light on our space-time diagram, it's world line always has to appear at the same angle.
But we saw previously that speed, or equivalently world line angles, change when we look at things from other people's perspective.
To explore this contradiction, let's see what happens if I start moving while I stand still and shine the jfox@example.org.
First, we'll need to construct the space-time diagram.
Yes, that means taking all of the different panels showing the different moments in time and stacking them up.
From the side, we see the world line of the laser light at its correct fixed angle, just as before.
So far, so good.
But that space-time diagram represents Andrew's perspective.
What does it look like to me?
In the last lesson, we showed how to get Tom's perspective moving all the panels along a bit until his world line is completely vertical.
But look carefully at the light world line.
The rearrangement of the panels means it's now tilted over too far.
I'd measure light traveling faster than Andrew would.
But every experiment we've ever done, and we've tried very hard, says that everyone measures light to have a fixed speed.
So let's start again.
In the 1900s, a clever chap named Albert Einstein worked out how to see things properly, from Tom's point of view, while still getting the speed of light right.
First, we need to glue together the separate panels into one solid block.
This gives us our space-time, turning space and time into one smooth, continuous material.
And now, here is the trick.
What you do is stretch your block of space-time along the light world line, then squash it by the same amount, but at right angles to the light world line, and abracadabra!
Tom's world line has gone vertical, so this does represent the world from his point of view, but most importantly, the light world line has never changed its angle, and so light will be measured by Tom going at the correct speed.
This superb trick is known as a Lorentz transformation.
Yeah, more than a trick.
Slice up the space-time into new panels and you have the physically correct animation.
I'm stationary in the car, everything else is coming past me and the speed of light works out to be that same fixed value that we know everyone measures.
On the other hand, something strange has happened.
The fence posts aren't spaced a meter apart anymore, and my mom will be worried that I look a bit thin.
But that's not fair.
Why don't I get to look thin?
I thought physics was supposed to be the same for everyone.
Yes, no, it is, and you do.
All that stretching and squashing of space-time has just muddled together what we used to think of separately as space and time.
This particular squashing effect is known as Lorentz contraction.
Okay, but I still don't look thin.
No, yes, you do.
Now that we know better about space-time, we should redraw what the scene looked like to me.
To you, I appear Lorentz contracted.
Oh but to you, I appear Lorentz contracted.
Yes.
Uh, well, at least it's fair.
And speaking of fairness, just as space gets muddled with time, time also gets muddled with space, in an effect known as time dilation.
No, at everyday speeds, such as Tom's car reaches, actually all the effects are much, much smaller than we've illustrated them.
Oh, yet, careful experiments, for instance watching the behavior of tiny particles whizzing around the Large Hadron Collider confirmed that the effects are real.
And now that space-time is an experimentally confirmed part of reality, we can get a bit more ambitious.
What if we were to start playing with the material of space-time itself?
We'll find out all about that in the next animation.
Right when I was 15 was when I first got interested in solar energy.
My family had moved from Fort Lee, New Jersey to California, from the snow to lots of heat, and gas lines.
There was gas rationing in 1973.
The energy crisis was in full bore.
I started reading "Popular Science" magazine, and I got really excited about the potential of solar energy to try and solve that crisis.
I had just taken trigonometry in high school, I learned about the parabola and how it could concentrate rays of light to a single focus.
That got me very excited.
And I really felt that there would be potential to build some kind of thing that could concentrate light.
So, I started this company called Solar Devices.
And this was a company where I built parabolas, I took metal shop, and I remember walking into metal shop building parabolas and Stirling engines.
And I was building a Stirling engine over on the lathe, and all the motorcycle guys said, "You're building a bong, aren't you?"
And I said, "No, it's a Stirling engine."
But they didn't believe me.
I sold the plans for this engine and for this dish in the back of "Popular Science" magazine, for four dollars each.
And I earned enough money to pay for my first year of Caltech.
It was a really big excitement for me to get into Caltech.
And at my first year at Caltech, I continued the business.
But then, in the second year of Caltech, they started grading.
The whole first year was pass/fail, but the second year was graded.
I wasn't able to keep up with the business, and I ended up with a 25-year detour.
My dream had been to convert solar energy at a very practical cost, but then I had this big detour.
First, the jfox@example.org.
Then, when I graduated from Caltech, the IBM PC came out, and I got addicted to the IBM PC in 1981.
And then in 1983, Lotus 1-2-3 came out, and I was completely blown away by Lotus 1-2-3.
I began operating my business with 1-2-3, began writing add-ins for 1-2-3, wrote a natural language interface to 1-2-3.
I started an educational software company after I joined Lotus, and then I started Idealab so I could have a roof under which I could build multiple companies in succession.
Much later -- in 2000, very recently -- the new California energy crisis -- what was purported to be a big energy crisis -- was coming.
And I was trying to figure out if we could build something that would capitalize on that and get people backup energy, in case the crisis really came.
And I started looking at how we could build battery backup systems that could give people five hours, 10 hours, maybe even a full day, or three days' worth of backup power.
I'm glad you heard earlier today, batteries are unbelievably -- lack density compared to fuel.
So much more energy can be stored with fuel than with batteries.
You'd have to fill your entire parking space of one garage space just to give yourself four hours of battery backup.
And I concluded, after researching every other technology that we could deploy for storing energy -- flywheels, different formulations of batteries -- it just wasn't practical to store energy.
So what about making energy?
Maybe we could make energy.
I tried to figure out -- maybe solar's become attractive.
It's been 25 years since I was doing this, let me go back and look at what's been happening with solar cells.
And the price had gone down from 10 dollars a watt to about four or five dollars a watt, but it stabilized.
And it needed to get much lower to be cost-effective.
I studied all the new things that had happened in solar cells, and was looking for ways we could make solar cells more inexpensively.
A lot of new things are happening to do that, but fundamentally, the process requires a tremendous amount of energy.
Some people say it takes more energy to make a solar cell than it will give out in its entire life.
If we reduce the amount of energy it takes to make the cells, that will become more practical.
But right now, you pretty much have to take silicon, put it in an oven at 1600 F for 17 hours, to make the cells.
A lot of people are working to try and reduce that, but I didn't have anything to contribute.
So I tried to figure out what other way could we try to make cost-effective solar electricity.
What if we collect the sun with a large reflector -- like I had been thinking about in high school, but maybe with modern technology we could make it cheaper -- concentrate it to a small converter, and then the conversion device wouldn't have to be as expensive, because it's much smaller, rather than solar cells, which have to cover the entire surface that you want to gather sun from.
This seemed practical now, because a lot of new technologies had come in the 25 years since I had last jfox@example.org.
There was a lot of new manufacturing techniques, not to mention really cheap miniature motors -- brushless motors, servomotors, stepper motors, that are used in printers and scanners.
So, that's a breakthrough.
Of course, inexpensive microprocessors and a very important breakthrough -- genetic algorithms.
I'll be very short on genetic algorithms.
It's a powerful way of solving intractable problems using natural selection.
You take a problem that you can't solve with a pure mathematical answer, you build an evolutionary system to try multiple tries at guessing, you add sex -- where you take half of one solution and half of another and then make new mutations -- and you use natural selection to kill off not-as-good solutions.
Usually, with a genetic algorithm on a computer today, with a three gigahertz processor, you can solve many formerly intractable problems in just a matter of minutes.
So we tried to come up with a way to use genetic algorithms to create a new type of concentrator.
And I'll show you what we came up with.
Traditionally, concentrators look like this.
Those shapes are parabolas.
They take all the parallel incoming rays and focus it to a single spot.
They have to track the sun, because they have to point directly at the sun.
They usually have a one degree acceptance angle -- once they're more than a degree off, none of the sunlight rays will hit the focus.
So we tried to come up with a non-tracking collector that would gather much more than one degree of light, with no moving parts.
So we created a genetic algorithm to try this out, we made a model in Excel of a multisurface reflector, and an amazing thing evolved, literally, from trying a billion cycles, a billion different attempts, with a fitness function that defined how can you collect the most light, from the most angles, over a day, from the sun.
And this is the shape that evolved.
It's this non-tracking collector with these six tuba-like horns, and each of them collect light in the following way -- if the sunlight strikes right here, it might bounce right to the center, the hot spot, directly, but if the sun is off axis and comes from the side, it might hit two places and take two bounces.
So for direct light, it takes only one bounce, for off-axis light it might take two, and for extreme off-axis, it might take three.
Your efficiency goes down with more bounces, because you lose about 10 percent with each bounce, but this allowed us to collect light from a plus or minus 25-degree angle.
So, about two and a half hours of the day we could collect with a stationary component.
Solar cells collect light for four and a half hours though.
On an average adjusted day, a solar cell -- because the sun's moving across the sky, the solar cell is going down with a sine wave function of performance at the off-axis angles.
It collects about four and a half average hours of sunlight a day.
So even this, although it was great with no moving parts -- we could achieve high temperatures -- wasn't enough.
We needed to beat solar cells.
So we took a look at another idea.
We looked at a way to break up a parabola into individual petals that would track.
So what you see here is 12 separate petals that each could be controlled with individual microprocessors that would only cost a dollar.
You can buy a two-megahertz microprocessor for a dollar now.
And you can buy stepper motors that pretty much never wear out because they have no brushes, for a dollar.
So we can control all 12 of these petals for under 50 dollars and what this would allow us to do is not have to move the focus any more, but only move the petals.
The whole system would have a much lower profile, but also we could gather sunlight for six and a half to seven hours a day.
Now that we have concentrated sunlight, what are we going to put at the center to convert sunlight to electricity?
So we tried to look at all the different heat engines that have been used in history to convert sunlight or heat to electricity, And one of the great ones of all time, James Watt's steam engine of 1788 was a major breakthrough.
James Watt didn't actually invent the steam engine, he just refined it.
But his refinements were incredible.
He added new linear motion guides to the pistons, he added a condenser to cool the steam outside the cylinder, he made the engine double-acting, so it had double the power.
Those were major breakthroughs.
All of the improvements he made -- and it's justifiable that our measure of energy, the watt, today is named after him.
So we looked at this engine, and this had some potential.
Steam engines are dangerous, and they had tremendous impact on the world -- industrial revolution and ships and locomotives.
But they're usually good to be large, so they're not good for distributed power generation.
They're also very high-pressure, so they're dangerous.
Another type of engine is the hot air engine.
And the hot air engine also was not invented by Robert Stirling, but Robert Stirling came along in 1816 and radically improved it.
This engine, because it was so interesting -- it only worked on air, no steam -- has led to hundreds of creative designs over the years that use the Stirling engine principle.
But after the Stirling engine, Otto came along, and also, he didn't invent the internal combustion engine, he just refined it.
He showed it in Paris in 1867, and it was a major achievement because it brought the power density of the engine way up.
You could now get a lot more power in a lot smaller space, and that allowed the engine to be used for mobile applications.
So, once you have mobility, you're making a lot of engines because you've got lots of units, as opposed to steam ships or big factories, so this was the engine that ended up benefiting from mass production where all the other engines didn't.
So, because it went into mass production, costs were reduced, 100 years of refinement, emissions were reduced, tremendous production value.
There have been hundreds of millions of internal combustion engines built, compared to thousands of Stirling engines built.
And not nearly as many small steam engines being built anymore, only large ones for big operations.
So after looking at these three, and 47 others, we concluded that the Stirling engine would be the best one to use.
I want to give you a brief explanation of how we looked at it and how it works.
So we tried to look at the Stirling engine in a new way, because it was practical -- weight no longer mattered for our application.
The internal combustion engine took off because weight mattered, because you were moving around.
But if you're trying to generate solar energy in a static place the weight doesn't matter so much.
We also discovered that efficiency doesn't matter so much if your energy source is free.
Normally, efficiency is crucial because the fuel cost of your engine over its life dwarfs the cost of the engine.
But if your fuel source is free, then the only thing that matters is the up-front capital cost of the engine.
So you don't want to optimize for efficiency, you want to optimize for power per dollar.
So using that new twist, with the new criteria, we thought we could relook at the Stirling engine, and also bring genetic algorithms in.
Basically, Robert Stirling didn't have Gordon Moore before him to get us three gigahertz of processor power.
So we took the same genetic algorithm that we used earlier to make that concentrator, which didn't work out for us, to optimize the Stirling engine, and make its design sizes and all of its dimensions the exact optimum to get the most power per dollar, irrespective of weight, irrespective of size, just to get the most conversion of solar energy, because the sun is free.
And that's the process we took -- let me show you how the engine works.
The simplest heat engine, or hot air engine, of all time would be this -- take a box, a steel canister, with a piston.
Put a flame under it, the piston moves up.
Take it off the flame and pour water on it, or let it cool down, the piston moves down.
That's a heat engine.
That's the most fundamental heat engine you could have.
The problem is the efficiency is one hundredth of one percent, because you're heating all the metal of the chamber and then cooling all the metal of the chamber each time.
And you're only getting power from the air that's heating at the same time, but you're wasting energy heating and cooling the metal.
So someone came up with a very clever idea.
Instead of heating and cooling the whole cylinder, what about if you put a displacer inside -- a little thing that shuttles the air back and forth.
You move that up and down with a little bit of energy but now you're only shifting the air down to the hot end and up to the cold end.
So, now you're not alternately heating and cooling the metal, just the air.
That allows you to get the efficiency up from a hundredth of a percent to about two percent.
And then Robert Stirling came along with this genius idea, which was, well, I'm still not heating the metal now, with this kind of engine, but I'm still reheating all the air.
I'm still heating the air every time and cooling the air every time.
What about if I put a thermal sponge in the middle, in the passageway between where the air has to move between hot and cold?
So he made fine wires, and cracked glass, and all different kinds of materials to be a heat sponge.
So when the air pushes up to go from the hot end to the cold end, it puts some heat into the sponge.
And then when the air comes back after it's been cooled, it picks up that heat again.
So you're reusing your energy five or six times, and that brings the efficiency up to between 30 and 40 percent.
It's a little known, but brilliant, genius invention of Robert Stirling that takes the hot air engine from being somewhat impractical -- like I found out when I made the real simple version in high school -- to very potentially possible, once you get the efficiency up, if you can design this to be low enough cost.
So we really set out on a path to try and make the lowest cost possible.
We built a huge mathematical model of how a Stirling engine works.
We applied the genetic algorithm.
We got the results from that for the optimal engine.
We built engines -- so we built 100 different engines over the last two years.
We measured each one, we readjusted the model to what we measured, and then we led that to the current prototype.
It led to a very compact, inexpensive engine, and this is what the engine looks like.
Let me show you what it looks like in real life.
So this is the engine.
It's just a small cylinder down here, which holds the generator inside and all the linkage, and it's the hot cap -- the hot cylinder on the top -- this part gets hot, this part is cool, and electricity comes out.
The exact converse is also true.
If you put electricity in, this will get hot and this will get cold, you get refrigeration.
So it's a complete reversible cycle, a very efficient cycle, and quite a simple thing to make.
So now you put the two things together.
So you have the engine.
What if you combine the petals and the engine in the center?
The petals track and the engine gets the concentrated sunlight, takes that heat and turns it into electricity.
This is what the first prototype of our system looked like with the petals and the engine in the center.
This is being run out in the sun, and now I want to show you what the actual thing looks like.
(Applause) Thank you.
So this is a unit with the 12 petals.
These petals cost about a dollar each -- they're lightweight, injection-molded plastic, aluminized.
The mechanism to control each petal is below there, with a microprocessor on each one.
There are thermocouples on the engine -- little sensors that detect the heat when the sunlight strikes them.
Each petal adjusts itself separately to keep the highest temperature on it.
When the sun comes out in the morning, the petals will seek the sun, find it by searching for the highest temperature.
About a minute and a half or two minutes after the rays are striking the hot cap the engine will be warm enough to start and then the engine will generate electricity for about six and a half hours a day -- six and a half to seven hours as the sun moves across the sky.
A critical part that we can take advantage of is that we have these inexpensive microprocessors and each of these petals is autonomous, and each of these petals figures out where the sun is with no user setup.
So you don't have to tell what latitude, longitude you're at, what your roof slope angle is, or what orientation.
It doesn't really care.
What it does is it searches to find the hottest spot, it searches again a half an hour later, a day later, a month later.
It basically figures out where on Earth you are by watching the direction the sun moves, so you don't have to actually enter anything about that.
The way the unit works is, when the sun comes out, the engine will start and you get power out here.
We have AC and DC, get 12 volts DC, so that could be used for certain applications.
We have an inverter in there, so you get 117 volts AC.
And you also get hot water.
The hot water's optional.
You don't have to use it, it will cool itself.
But you can use it to optionally heat hot water and that brings the efficiency up even higher because some of the heat that you'd normally be rejecting, you can now use as useful energy, whether it's for a pool or hot water.
Let me show you a quick movie of what this looks like running.
This is the first test where we took it outside and each of the petals were individually seeking.
And what they do is step, very coarsely at first, and very finely afterward.
Once they get a temperature reading on the thermocouple indicating they found the sun, they slow down and do a fine search.
Then the petals will move into position, and the engine will start.
We've been working on this for the last two years.
We're very excited about the progress, we have a long way to go though.
This is how we envision it would be in a residential installation: you'd probably have more than one unit on your roof.
It could be on your roof, your backyard, or somewhere else.
You don't have to have enough units to power your entire house, you just save money with each incremental one you add.
So you're still using the grid potentially, in this type of application, to be your backup supply -- of course, you can't use these at night, and you can't use these on cloudy days.
But by reducing your energy use, pretty much at the peak times -- usually when you have your air conditioning on, or other times like that -- this generates the peak power at the peak usage time, so it's very complementary in that sense.
This is how we would envision a residential application.
We also think there's very big potential for energy farms, especially in remote land where there happens to be a lot of sun.
It's a really good combination of those two factors.
It turns out there's a lot of powerful sun all around the world, obviously, but in special places where it happens to be relatively inexpensive to place these and also in many more places where there is high wind power.
So an example of that is, here's the map of the United States.
Pretty much everywhere that's not green or blue is a really ideal place, but even the green or blue areas are good, just not as good as the places that are red, orange and yellow.
But the hot spot right around Las Vegas and Death Valley is very good.
And is only affects the payback period, it doesn't mean that you couldn't use solar energy; you could use it anywhere on Earth.
It just affects the payback period if you're comparing to grid-supplied electricity.
But if you don't have grid-supplied electricity, then the question of payback is a different one entirely.
It's just how many watts do you get per dollar, and how could you benefit from that to change your life in some way.
This is the map of the whole Earth, and you can see a huge swathe in the middle where a large part of the population is, there's tremendous chances for solar energy.
And of course, jfox@example.org.
The potential to take advantage of solar energy there is unbelievable, and I'm really excited to talk more about finding ways we can help with that.
So, in conclusion, I would say my journey has shown me that you can revisit old ideas in a new light, and sometimes ideas that have been discarded in the past can be practical now if you apply some new technology or new twists.
We believe we're getting very close to something practical and affordable.
Our short-term goal for this is to be half the price of solar cells and our longer-term goal is to be less than a five-year payback.
And at less than a five-year payback, this becomes very economic.
So you don't have to just have a feel-good attitude about energy to want to have one of these.
It just makes economic sense.
Right now, solar paybacks are between 30 and 50 years.
If you get it down below five years, then it's almost a no-brainer because the interest to own it -- someone else will finance it for you and you can just make money from day one.
So that's our real powerful goal that we're really shooting for in the company.
Two other things that I learned that were very surprising to me -- one was how casual we are about energy.
I was walking from the elevator over here, and even just looking at the stage right now -- so there's probably 20,500-watt lights right now.
There's 10,000 watts of light pouring on the stage, one horsepower is 746 watts, at full power.
So there's basically 15 horses running at full speed just to keep the stage lit.
Not to mention the 200 horses that are probably running right now to keep the air-conditioning going.
And it's just amazing, walk in the elevator, and there's lights on in the elevator.
Of course, now I'm very sensitive at home when we leave the lights on by mistake.
But, everywhere around us we have insatiable use for energy because it's so cheap.
And it's cheap because we've been subsidized by energy that's been concentrated by the sun.
Basically, oil is solar-energy concentrate.
It's been pounded for a billion years with a lot of energy to make it have all that energy contained in it.
And we don't have a birthright to just use that up as fast as we are, I think.
And it would be great if we could make our energy usage renewable, where as we're using the energy, we're creating it at the same pace, and I really hope we can get there.
Thank you very much, you've been a great audience.
So here it is.
You can check: I am short, I'm French, I have a pretty strong French accent, so that's going to be clear in a moment.
Maybe a sobering thought and something you all know about.
And I suspect many of you gave something to the people of Haiti this year.
And there is something else I believe in the back of your mind you also know.
That is, every day, 25,000 children die of entirely preventable causes.
That's a Haiti earthquake every eight days.
And I suspect many of you probably gave something towards that problem as well, but somehow it doesn't happen with the same intensity.
So why is that?
Well, here is a thought experiment for you.
Imagine you have a few million dollars that you've raised -- maybe you're a politician in a developing country and you have a budget to spend.
You want to spend it on the poor: How do you go about it?
Do you believe the people who tell you that all we need to do is to spend money?
That we know how to eradicate poverty, we just need to do more?
Or do you believe the people who tell you that aid is not going to help, on the contrary it might hurt, it might exacerbate corruption, dependence, etc.?
Or maybe you turn to the past.
After all, we have spent billions of dollars on aid.
Maybe you look at the past and see.
Has it done any good?
And, sadly, we don't know.
And worst of all, we will never know.
And the reason is that -- take Africa for example.
Africans have already got a lot of aid.
These are the blue bars.
And the GDP in Africa is not making much progress.
Okay, fine.
How do you know what would have happened without the aid?
Maybe it would have been much worse, or maybe it would have been better.
We have no idea.
We don't know what the counterfactual is.
There's only one Africa.
So what do you do?
To give the aid, and hope and pray that something comes out of it?
Or do you focus on your everyday life and let the earthquake every eight days continue to happen?
The thing is, if we don't know whether we are doing any good, we are not any better than the Medieval doctors and their leeches.
Sometimes the patient gets better, sometimes the patient dies.
Is it the leeches?
Is it something else?
We don't know.
So here are some other questions.
They're smaller questions, but they are not that small.
Immunization, that's the cheapest way to save a child's life.
And the world has spent a lot of money on it: The GAVI and the Gates Foundations are each pledging a lot of money towards it, and developing countries themselves have been doing a lot of effort.
And yet, every year at least 25 million children do not get the immunization they should get.
So this is what you call a "last mile problem."
The technology is there, the infrastructure is there, and yet it doesn't happen.
So you have your million.
How do you use your million to solve this last mile problem?
And here's another question: Malaria.
Malaria kills almost 900,000 people every year, most of them in Sub-Saharan Africa, most of them under five.
In fact, that is the leading cause of under-five mortality.
We already know how to kill malaria, but some people come to you and say, "You have your millions.
How about bed nets?"
Bed nets are very cheap.
For 10 dollars, you can manufacture and ship an insecticide treated bed net and you can teach someone to use them.
And, not only do they protect the people who sleep under them, but they have these great contagion benefits.
If half of a community sleeps under a net, the other half also benefits because the contagion of the disease spread.
And yet, only a quarter of kids at risk sleep under a net.
Societies should be willing to go out and subsidize the net, give them for free, or, for that matter, pay people to use them because of those contagion benefits.
"Not so fast," say other people.
"If you give the nets for free, people are not going to value them.
They're not going to use them, or at least they're not going to use them as bed nets, maybe as fishing nets."
So, what do you do?
Do you give the nets for free to maximize coverage, or do you make people pay in order to make sure that they really value them?
How do you know?
And a third question: Education.
Maybe that's the solution, maybe we should send kids to school.
But how do you do that?
Do you hire teachers?
Do you build more schools?
Do you provide school lunch?
How do you know?
So here is the thing.
I cannot answer the big question, whether aid did any good or not.
But these three questions, I can answer them.
It's not the Middle Ages anymore, it's the 21st century.
And in the 20th century, randomized, controlled trials have revolutionized medicine by allowing us to distinguish between drugs that work and drugs that don't work.
And you can do the same randomized, controlled trial for social policy.
You can put social innovation to the same rigorous, scientific tests that we use for drugs.
And in this way, you can take the guesswork out of policy-making by knowing what works, what doesn't work and why.
And I'll give you some examples with those three questions.
So I start with immunization.
Here's Udaipur District, Rajasthan.
Beautiful.
Well, when I started working there, about one percent of children were fully immunized.
That's bad, but there are places like that.
Now, it's not because the vaccines are not there -- they are there and they are free -- and it's not because parents do not care about their kids.
The same child that is not immunized against measles, if they do get measles, parents will spend thousands of rupees to help them.
So you get these empty village subcenters and crowded hospitals.
So what is the problem?
Well, part of the problem, surely, is people do not fully understand.
After all, in this country as well, all sorts of myths and misconceptions go around immunization.
So if that's the case, that's difficult, because persuasion is really difficult.
But maybe there is another problem as well.
It's going from intention to action.
Imagine you are a mother in Udaipur District, Rajasthan.
You have to walk a few kilometers to get your kids immunized.
And maybe when you get there, what you find is this: The subcenter is closed.
Ao you have to come back, and you are so busy and you have so many other things to do, you will always tend to postpone and postpone, and eventually it gets too late.
Well, if that's the problem, then that's much easier.
Because A, we can make it easy, and B, we can maybe give people a reason to act today, rather than wait till tomorrow.
So these are simple ideas, but we didn't know.
So let's try them.
So what we did is we did a randomized, controlled trial in 134 villages in Udaipur Districts.
So the blue dots are selected randomly.
We made it easy -- I'll tell you how in a moment.
In the red dots, we made it easy and gave people a reason to act now.
The white dots are comparisons, nothing changed.
So we make it easy by organizing this monthly camp where people can get their kids immunized.
And then you make it easy and give a reason to act now by adding a kilo of lentils for each immunization.
Now, a kilo of lentils is tiny.
It's never going to convince anybody to do something that they don't want to do.
On the other hand, if your problem is you tend to postpone, then it might give you a reason to act today rather than later.
So what do we find?
Well, beforehand, everything is the same.
That's the beauty of randomization.
Afterwards, the camp -- just having the camp -- increases immunization from six percent to 17 percent.
That's full immunization.
That's not bad, that's a good improvement.
Add the lentils and you reach to 38 percent.
So here you've got your answer.
Make it easy and give a kilo of lentils, you multiply immunization rate by six.
Now, you might say, "Well, but it's not sustainable.
We cannot keep giving lentils to people."
Well, it turns out it's wrong economics, because it is cheaper to give lentils than not to give them.
Since you have to pay for the nurse anyway, the cost per immunization ends up being cheaper if you give incentives than if you don't.
How about bed nets?
Should you give them for free, or should you ask people to pay for them?
So the answer hinges on the answer to three simple questions.
One is: If people must pay for a bed net, are they going to purchase them?
The second one is: If I give bed nets for free, are people going to use them?
And the third one is: Do free bed nets discourage future purchase?
The third one is important because if we think people get used to handouts, it might destroy markets to distribute free bed nets.
Now this is a debate that has generated a lot of emotion and angry rhetoric.
It's more ideological than practical, but it turns out it's an easy question.
We can know the answer to this question.
We can just run an experiment.
And many experiments have been run, and they all have the same results, so I'm just going to talk to you about one.
And this one that was in Kenya, they went around and distributed to people vouchers, discount vouchers.
So people with their voucher could get the bed net in the local pharmacy.
And some people get 100 percent discount, and some people get 20 percent discounts, and some people get 50 percent discount, etc.
And now we can see what happens.
So, how about the purchasing?
Well, what you can see is that when people have to pay for their bed nets, the coverage rate really falls down a lot.
So even with partial subsidy, three dollars is still not the full cost of a bed net, and now you only have 20 percent of the people with the bed nets, you lose the health immunity, that's not great.
Second thing is, how about the use?
Well, the good news is, people, if they have the bed nets, will use the bed nets regardless of how they got it.
If they get it for free, they use it.
If they have to pay for it, they use it.
How about the long term?
In the long term, people who got the free bed nets, one year later, were offered the option to purchase a bed net at two dollars.
And people who got the free one were actually more likely to purchase the second one than people who didn't get a free one.
So people do not get used to handouts; they get used to nets.
Maybe we need to give them a little bit more credit.
So, that's for bed nets.
So you will think, "That's great.
You know how to immunize kids, you know how to give bed nets."
But what politicians need is a range of options.
They need to know: Out of all the things I could do, what is the best way to achieve my goals?
So suppose your goal is to get kids into school.
There are so many things you could do.
You could pay for uniforms, you could eliminate fees, you could build latrines, you could give girls sanitary pads, etc., etc.
So what's the best?
Well, at some level, we think all of these things should work.
So, is that sufficient?
If we think they should work intuitively, should we go for them?
Well, in business, that's certainly not the way we would go about it.
Consider for example transporting goods.
Before the canals were invented in Britain before the Industrial Revolution, goods used to go on horse carts.
And then canals were built, and with the same horseman and the same horse, you could carry ten times as much cargo.
So should they have continued to carry the goods on the horse carts, on the ground, that they would eventually get there?
Well, if that had been the case, there would have been no Industrial Revolution.
So why shouldn't we do the same with social policy?
In technology, we spend so much time experimenting, fine-tuning, getting the absolute cheapest way to do something, so why aren't we doing that with social policy?
Well, with experiments, what you can do is answer a simple question.
Suppose you have 100 dollars to spend on various interventions.
How many extra years of education do you get for your hundred dollars?
Now I'm going to show you what we get with various education interventions.
So the first ones are if you want the usual suspects, hire teachers, school meals, school uniforms, scholarships.
And that's not bad.
For your hundred dollars, you get between one and three extra years of education.
Things that don't work so well is bribing parents, just because so many kids are already going to school that you end up spending a lot of money.
And here are the most surprising results.
Tell people the benefits of education, that's very cheap to do.
So for every hundred dollars you spend doing that, you get 40 extra years of education.
And, in places where there are worms, intestinal worms, cure the kids of their worms.
And for every hundred dollars, you get almost 30 extra years of education.
So this is not your intuition, this is not what people would have gone for, and yet, these are the programs that work.
We need that kind of information, we need more of it, and then we need to guide policy.
So now, I started from the big problem, and I couldn't answer it.
And I cut it into smaller questions, and I have the answer to these smaller questions.
And they are good, scientific, robust answers.
So let's go back to Haiti for a moment.
In Haiti, about 200,000 people died -- actually, a bit more by the latest estimate.
And the response of the world was great: Two billion dollars got pledged just last month, so that's about 10,000 dollars per death.
That doesn't sound like that much when you think about it.
But if we were willing to spend 10,000 dollars for every child under five who dies, that would be 90 billion per year just for that problem.
And yet it doesn't happen.
So, why is that?
Well, I think what part of the problem is that, in Haiti, although the problem is huge, somehow we understand it, it's localized.
You give your money to Doctors Without Borders, you give your money to Partners In Health, and they'll send in the doctors, and they'll send in the lumber, and they'll helicopter things out and in.
And the problem of poverty is not like that.
So, first, it's mostly invisible; second, it's huge; and third, we don't know whether we are doing the right thing.
There's no silver bullet.
You cannot helicopter people out of poverty.
And that's very frustrating.
But look what we just did today.
I gave you three simple answers to three questions: Give lentils to immunize people, provide free bed nets, deworm children.
With immunization or bed nets, you can save a life for 300 dollars per life saved.
With deworming, you can get an extra year of education for three dollars.
So we cannot eradicate poverty just yet, but we can get started.
And maybe we can get started small with things that we know are effective.
Here's an example of how this can be powerful.
Deworming.
Worms have a little bit of a problem grabbing the headlines.
They are not beautiful and don't kill anybody.
And yet, when the young global leader in Davos showed the numbers I gave you, they started Deworm the World.
And thanks to Deworm the World, and the effort of many country governments and foundations, 20 million school-aged children got dewormed in 2009.
So this evidence is powerful.
It can prompt action.
So we should get started now.
It's not going to be easy.
It's a very slow process.
You have to keep experimenting, and sometimes ideology has to be trumped by practicality.
And sometimes what works somewhere doesn't work elsewhere.
So it's a slow process, but there is no other way.
These economics I'm proposing, it's like 20th century medicine.
It's a slow, deliberative process of discovery.
There is no miracle cure, but modern medicine is saving millions of lives every year, and we can do the same thing.
And now, maybe, we can go back to the bigger question that I started with at the beginning.
I cannot tell you whether the aid we have spent in the past has made a difference, but can we come back here in 30 years and say, "What we have done, it really prompted a change for the better."
I believe we can and I hope we will.
Thank you.
(Applause)