The computing revolution that secretly began in 1776

How can you mechanize mathematics? What can you do with it

Those lessons were first approached in largely the 18th century and by people doing work by hand

Very, very quickly, people started asking, what can you do with machines

Hi, I'm David Alan Greer. I am currently a writer and author on issues of technology and industry and things of that sort

I am the author of the book When Computers Were Human, and also the book Crowdsourcing for Dummies, among others

Why is computing part of the Industrial Revolution? The Industrial Revolution is about systematizing production

And it's about producing goods of uniform quality, if not uniform design

at the lowest possible cost for the largest possible market. If you want a date that's easy to remember and just nails things down, you go with 1776

And that's useful for my purpose as a writer, because that's also the year that Adam Smith's The Wealth of Nations is published

And the start of that book is about the description of industrial processes

how we came to them and how we used them to start building uniform products that would have large

markets that would increase the wealth of nations. And those first chapters deal with the division of

labor, the specializations of tasks, and the systematization of work. That book was highly

influential not only in the industrial group, particularly, you know, in London, in the cotton

producing and in the pottery producing fields in northern London, but also amongst the scientific

crowd, because they also had things that were large problems that needed systematic approaches

Astronomy was the first. We had used astronomy for navigation, but there was a question of what

was out there and how did things behave that was being addressed by people purchasing telescopes

or financing telescopes, and then setting up a staff to collect observations

And they would, night after night, go to the observatory and map the heavens

And in the process of mapping the heavens, it doesn't take long to realize the data problem they generated

Suppose it takes a minute or two a night to get one star located

Okay, that means you can get a couple hundred, maybe even low thousands of stars a night

But the figures that you record depend upon the hour of the day

which direction the Earth is facing or your telescope is facing, and the time of year, where the Earth is in its orbit

You'll get different measurements of the stars at different times of year

That means you create a massive pile of data that needs to be reduced to absolute coordinates

to a location somewhere fixed in space. that requires a lot of work and a lot of arithmetic and it required these observatories which could do

the recording with a staff of two or three astronomers to have a large group of people to

help them reduce these data points to something that was absolute so they could start fitting them

into their map of the heavens. That was a repetitive job. There was a lot of it. And the

issue that they all faced was how can you do it for the least amount of money

Part of what we think of as high tech and computing and programming is also the task of

systemization, of regularization, of taking a complex thing that could be done many different

ways and putting it in a form that can be marched through in a fixed series of steps

At base, no one really needs to know the return date of Halley's Comet

There are a certain few scientists for whom it helps explain the universe

But it's mostly just a reminder that this object has been seen

every 75 or so years throughout history and has been recorded as such

But at the end of the 17th century, a group of French astronomers

knowing that it was coming, asked, could we figure it out? It was a test of the science that had been developing before them

of the theories of people like Copernicus and Galileo. And the question was, could they get a date

Could they get the date that was closest to the sun? And could they do it mathematically

And that's actually a tough problem at some level even now, although we have all the programs to do it

because it involves the location of several big objects and needing to move them through space

while you're tracking the comet around the solar system. And what they did was divide the labor

And that becomes a key theme in computing, a theme that was worked out by human beings

and relatively modest mechanical devices before we started putting electronics to it

and rushing off into programs and artificial intelligence and all the rest

We worked out the problems of computing because it was divided labor

And for that first return of Halley's Comet, they had two people working on the location, first of the Earth and second of Jupiter, because Jupiter is a major influence on the motion in the solar system

And then another astronomer tracked the comet, which is pretty small and has little impact in terms of moving other things around in its orbit

and they figured out how to do that and do that repeatedly

repeatedly and in a way that they could double check their work

And that's sort of another one of the themes, that it not just the brilliant insight it not just the algorithms it figuring out how to find mistakes how to find misadditions miscalculations and even misapprehensions misunderstandings of what going on That process which took about a

month, really set the stage for the things that were to come. In particular, it set the stage

for the nautical almanacs. As I said, you and I have lived all of our lives without knowing

the next return date for Hallie's Comet. And our lives will go on

And when it comes, it'll be a big party. And I hope it's better seen than the last time

when it came in the 80s. But it's just a party. It's just watching an odometer flip

The bigger problems, the things that involve production in terms of our living our lives

of feeding ourselves, clothing ourselves, providing shelter, we need to produce goods and services

and the key thing that was involved there was trade and ocean-going vessels

and knowing where they are. Once you're out of sight of land

how do you know where you are? The ancient astronomers pre-17th century

had a lot of various methods that were somewhat ad hoc that sort of involved, this is spring

we know this star is over our destination, we go out, we point the ship at the star

and we pray that we get there. they didn't know where they were on the Earth's globe

And that required an understanding of how to compute longitude and latitude

And latitude is fairly easy to get, at least in the northern hemisphere. Longitude is a lot harder, and it requires knowing where stars are relative to a fixed point on Earth

And that knowledge you have to codify in a book, and you have to do it multiple years in advance

because you give these books to captains and turn them loose across the oceans

far away from wherever that fixed point might be, which in the early days of exploration were one of three points

London, Amsterdam, or Paris. To produce those books accurately, you needed a system

You needed a system that allowed you both to do the calculations and then undo them in a way that was different

because one of the very early pioneers of calculation, Charles Babbage, discovered what he called Babbage's rule

which is two calculations done the same way by different people will tend to make the same errors

There seems to be, in the process of hand calculation, mistakes that trip up everybody

Not all the time, but there's a tendency that if one person makes this mistake, the next person will make it

So you need to approach the problem in a different way, and in particular, in a different way that exposes errors

And that was thrashed out in the late 18th century in the Nautical Almanac in London

and in a comparable publication in Paris. They figured out not only how to divide

because there were multiple objects they wanted to get the locations of

So they divided that amongst a variety of people. And then ways of undoing those calculations in a form that exposed the errors

And that was a key innovation on their part. And that led to these publications, and that leads to the age of exploration and the start

of global trade, global oceanic trade, trade that requires boats to go out of sight

And that, of course, leads very directly to industrialization in the modern world

Same was true with surveying. In the United States, there was, by the early 19th century, there's the problem of figuring

out where the United States actually is, what are its bounds, what are its limits

And that involved surveying first the coasts and then moving in. And that again required, they used nautical almanacs again to figure out the locations of places

But a great deal of calculation because you're basically laying down across the earth a bunch of triangles

And you can figure out where two of the corners of the triangle are. And from those two corners, you can get to the third

And then from that third, that gives you a new triangle. And you can keep marching off across the land

that particularly when they got to california um proved to be a hard thing to do that it was

very difficult to get all the calculations you needed to get that vast space um well surveyed

and in particularly that was needed because you had a bunch of people who thought they owned land

there somewhere. And by thinking that they own land, they had to know where it was. They couldn't

say from this rock to that mountain to that tree. They had to have more exact points. And the

treaties that shaped the West and shaped the United States basically required the new states

to figure out land ownership and the location of land. And so they all faced this same problem

of how do you take large amounts of data and process it

and that required them to think industrially, to think how the two pieces went together

And so there evolves other systems to try to do that quickly

to get first approximations, to be able to get numbers close enough

so that the errors on borders are relatively minor and can be worked out in local negotiations

But it's that process of systematizing, correcting errors, finding approximations, and making them work as civil systems

that was what really drove me to start looking at human calculation

and what was the foundation that it laid for the modern computer age

Those lessons were first approached in largely the 18th century and by people doing work by hand and doing it largely but not exclusively for astronomy or surveying

One of the aspects of building systematic processes around numbers, around calculation

was that very, very quickly people started asking, what can you do with machines

The idea of an adding machine, a machine that could add two numbers

goes back to Descartes. It has a long, long history. And the idea that you can represent

numbers by the turning of a wheel, and then if the wheel turns all around, it turns the next wheel

that was well worked out early. However, it really wasn't part of a process

something that you could rely on. And when you talk about industrializations, you're basically

building processes that can be done by people who at base don't know what they're doing

or more accurately, they are doing something that they gain a skill at, that they understand

their steps and they learn how to do them efficiently, but they don't understand necessarily

the science and the ideas behind them. At the start of the 19th century, there's a great

explosion in the interest of what machines, levers, gears can do. And there is a study of

linkages, for example, of mechanical arms that connect together. And what they could do that

I don't think it's quite lost. I'm sure there are mechanical engineers who will give me a lecture

on this. But it's something that has certainly vanished from our daily contemplation and

contemplation even of non-specialized students. And one of the people who got fascinated with this

was an Englishman named Charles Babbage. He's a start of the 19th century. His father was a banker

Because his father was a banker, his father was also involved in the Caribbean trade

And that meant he was familiar with boats going off to the Caribbean to collect largely sugar

and bring it back to the United Kingdom. And it's at a point where systematized shipping

is starting to really take hold. It really doesn't kick in until the start of the industrial age

where boats run on a schedule. And you know the schedule and you know more or less the date they're coming

Babbage attends Cambridge. He learns astronomy, gets fascinated with it, fascinated with mathematics, and then starts pondering

how can you mechanize mathematics? What can you do with it? He had written a couple of things while he was in college

that in many ways was filling up spaces and filling up shapes

with smaller versions of itself to see how you could approximate them

and what systems would work and what wouldn't. And sometime during that early period

he got involved with the Nautical Almanac. He ends up being on an advisory board for it

And this is when he discovers his rule that two people doing the same calculation the same way tend to make the same mistakes

The second job that's starting to come up and he gets involved and interested is the understanding of insurance, of probability behind it

In particular, insurance is at some level a savings account, nothing more than that

and it's savings that you get to cash in the savings account when you die

or if it's a health insurance, which is later in the century, when you get sick

That means the people running the bank need to know how much money they are likely to pay out

And the understanding of that, the mathematics of that, the mathematics of probability

is just really starting at, again, it's an industrial revolution start, but it's really starting to take hold in industrial life at the start of the 19th century

And it involves the creation of another kind of table called mortality tables

which tell you how long someone is likely to live given that they've lived this long

And they are highly dependent on data and on what people. You don't do them for a huge population because there are differences in the way people live

in their diets, in the work that they do, in the kinds of families that they have

So you tend to do it for smaller groups, and that means you have to do a lot of these tables

and you have to process a lot of data. Babbage pondered it, and he began to realize that for

both astronomy and for these insurance tables, there's a common kind of calculation that could

could be very useful, but was, by the standards of the time, very time-consuming. And it's basically

fitting a curve to data. You have these points, and you want a curve to go nice and smoothly

through them so that you can make estimates between the points, and you can go project out

beyond the end of your curve to figure out where it might be going. And it dawned on him, on Babbage

that that calculation was, in effect, could be reduced to a lot of additions

a very large number of additions and subtractions. And that meant that he could chain together

a bunch of these adding machines and produce a machine that could indeed do that

by just grinding away at a crank, or as he thought of it, being produced by steam

He was working in the very early age of railroads and steam engineering

And he saw his machine as very much in the heritage of locomotive design

And so he produced a machine with very large gears and numbers

and the dials on it were made out of well-machined brass. And the process was probably beyond the engineering ability of his time

His lead engineer pushed British engineering substantially and advanced at both working for Babbage and later And it was also probably the wrong concept to build from Machines are very often done as metaphors

We build a machine to do something like this. And Babbage was building a machine to do calculations like a railroad engine

And railroad engines were not completely safe and secure then. And they were still learning a great deal about how to build them

Babbage never got his working. He built a number of models. He built several that demonstrated the proof of concept

He could fit not the curve he wanted, but a much simpler curve to data

and in a machine that got through the calculations we know at least once

And then he built a lot of rough parts for the machine he wanted to build

and because of that, Babbage and his ideas left a legacy about what they were trying to do more than what they actually did

What he was trying to do was systematize calculations so he could handle large-scale, in both cases, calculations

fitting curves to data and things of that sort. He had contemporaries that were intellectually

in terms of direct connection, far more important. George Boole. George Boole wrote a book called

On the Laws of Thought. We now know those laws of thought as Boolean algebra, which is the

fundamental tool underlying all of the yses that design electronic circuits and computers

That connection has been well known and understood forever. Babbage vanished for a bit

and also the exact intellectual connection is not as clear unless you look at the systemization

the building of an industrial process, the work to lessen the cost of computing

and to move it into a bigger environment. In that sense, he had a tremendous impact

and remains an important figure to this day. Almost 30, 40 years after Babbage did it

A Swedish father and son built one of these machines using Babbage's idea and built it, and it was fully functional, using clock technology

And clocks are much smaller, they're much easier to work with at that scale, they require less energy, and there were lots of standardized parts they could borrow from

In particular, escapement clocks, which were the dominant technology until not that long ago, have an important role in science writ large

and in computing specifically. Clocks were one of the first sophisticated technologies

that had wide distribution in the 18th century. The escapement clock, clocks with a pendulum

with a little gear and a little thing that goes click-clock, click-clock, tick-tock, tick-tock, tick-tock

were a technology that were novel. They were often packaged in ways that made them

in effect, a luxury item, something that the rich would have. but very quickly they became common and they allowed industrialization for example by

setting times when a factory would be open you don't need a clock if you're running a farm

necessarily there might be a few things where knowing an hour or knowing a minute is useful

but for the most part you're following natural rhythms of the day and those natural rhythms have

a very wide margin of error. You can miss them by 15 minutes, 20 minutes

and you will be just fine. If you're setting up a factory

if you're bringing people together to work together, to collaborate together, and if in particular you're dividing a task

up into a linear process, which was one of the very first things that happened

Adam Smith writes about making pins and needles. And in particular, it's a process of cutting the wire

sharpening the wire, putting a head on it for a pin, putting it in the paper that you're going to

sell it with, and moving it on. It's a linear thing. You have to do one step before the other

And if you're dividing it up across different people, it means you have to have people for

all the steps. And that means they all have to be there at the same time. And you really needed

clocks to be able to do that. Scientifically, it made a lot of measurements more interesting

in particularly the measurements of location. You needed that to determine longitude

You needed that to determine location on the Earth. Because of that, it became an important technology

for disseminating ideas, for bringing them to people who became fixated with clocks, with how they worked

of how they could improve them, of what they could do with them, of clockwork mechanisms that became part of other technologies

In computing, the clock, the tick-tock of the escapement ratchet, became part of computing because it became a drumbeat that stepped through the basic mechanisms of calculating devices

As you would go, you just wouldn't let your machine run wild. You would have a device that was going tick-tock, tick-tock, tick-tock, that was controlling the other elements, the other parts

and that allowed them to think about machines that could do calculations in a systematic, orderly way

It gave them a method to control them, but more importantly, it gave them a technology to build off of

to think about, to say, okay, we know this works for doing time. How does it work for collecting data

How does it work for timing additions? What can we do with it

And so these clocks, clockworks and clock mechanisms, are deeply imbued in industrialization, deeply part of calculation, and part of the tools that people used to think about how to build the next generation of devices and how to use them

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