I'm David Alan Grier. I am currently a writer and author on issues of technology and industry and things of that sort. In the past, I have been a computer programmer, a professor, a software engineer, president of the IEEE Computer Society. I am the author of the book "When Computers Were Human" and also the book "Crowdsourcing for Dummies," among others.

Chapter 1 - Computers and the Industrial Revolution 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 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 a 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 to 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 in 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 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 18th 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 oblogics 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.

...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 the 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.

...Chapter two, the power of standardization. Standards are a key part of the industrial world. Building things to standard models, standard parts, goes almost all the way back to 1776. ...In terms of the modern sense of standardization, I really pin it on World War I more than anything, and if you wanted one individual who was more responsible for it than any other, who was a major leader, it's Herbert Hoover. Hoover was an engineer. ...He argued that there were a large number of things that if they were produced to standard forms, would increase the scale of our industrial processes, would allow us to make more products for more people at lower costs, and expand our ability to do things. ...And as the computing age built, they more and more started looking at standard ways of doing calculation, standard ways of expressing algorithms, standard languages for expressing programs. And all of these became a key part of computing that would have been a lot more expensive and a lot slower if it hadn't had the standards there.

Chapter 3, Computing the Human Experience Right now, where we're sitting in Washington is the old patent office. And back in the 1850s, that was the place the first telegraph was connected in the United States. ...The second message was, "What time is it there?" Because at that point, every city had a local time that was measured by when the sun was directly overhead at noon. ...Getting a unified time, which was in place by the late 19th century, helped eliminate a large number of train wrecks and delayed trains and other things that disrupted production.

...The census was done every ten years... by the 1870 census, that takes most of a decade to complete. The 1880 census is never really finished. ...And as 1890 began to approach, the head of the census said, "We've got to do something. We've got to systematize it. We have to industrialize it. We have to reduce the cost." And so he put out a request for someone who could build machines that could count people. And the process that came out that won the contract formed a company that was known then as the Hollerith Tabulating Company, becomes something we all know a little better, IBM. ...It sped the process so greatly that by 1893, the preliminary census was completed. ...There is an assistant director of the census who wrote this stunning document about how he could hold up a card and he could see the person in the card. ...He felt that when he was putting it through the tabulator, he was working out the future of that person. And the bell which indicated that the card had been processed was the bell calling that soul to judgment of heaven or hell. It's sweet and it's endearing, and it also shows how as we start approaching our life through data, through the large processing of data, we start seeing ourselves in new ways.

Chapter 4 - How Computers Change Us... In the 1940s, there was again a lot of computation that was needed for the war, in particular bombing, hitting things, and specifically shooting down aircraft. ...This machine, which would get the name E-NIAC, Electronic Numerical Integrator and Calculator, was a very direct precursor of the modern computer. ...Von Neumann goes to visit the ENIAC... and it dawned on him that the machine that they were really trying to build... had three elements. It had a place where you could store numbers, a scratch pad, if you will, memory that we now know it. It would have a processing unit. ...And that there was a third element in it, and that was a program decoder. These three elements in multiple forms are part of every single computer we have today.

...The key piece of research that laid the foundation for the Internet was the work on ARPANET. ...The first was that there was always going to be a human-to-human element. Email was not the first application. It was probably the third. ...The second part that they grasped and articulated was that it was not only person-to-person, but that there would be repositories... that concept of searching is crucial. ...The PC was that very much in the 70s. People saw this as a personal device... But in working with systems, the fundamental rule is we adjust ourselves. We adjust our thoughts. We adjust the way we work. ...There's an important strain of AI that is building large databases and searching through them. And the search that does it most effectively for that kind of work is called A* search, and that's what we use on our phones to find the fastest way home.

Chapter 5 When Machines Replace Humans... This room in New York City was the main office of a group known as the Math Tables Project. It was the largest collection of human computers, to my knowledge, that has ever been assembled on the face of the earth. ...The substitution of machinery for labor is a huge part of the story of computation. And there are two principal motivations for it. One, reducing activities that we thought required human intelligence to mechanization... The second part is systemization. ...In all of these, you're in effect trying to replace expensive labor with cheaper labor.

...One of the new devices that's coming into manufacturing are automated machine tools... and during the '50s, as they start seeing these tools come up, they protest. And it leads to one of the key fights that we are having today about who owns data. ...The argument that the large manufacturers had is we build the factories... Therefore, your skills are something that we can copy and we can transfer to an automated machine tool. ...That same controversy continues with the collection of data for artificial intelligence. ...The question becomes, who owns the activities that are being captured by data? ...My feeling is with artificial intelligence now... they fail enough that they are not reliable tools for me. ...If I'm going to pay for a mistake, it's going to be mine.