The History of Computing

Voters elect officials in representative democracies who pass laws, interpret laws, enforce laws, or appoint various other representatives to do one of the above. The terms of elected officials, the particulars of their laws, the structure of courts that interpret laws, and the makeup of the bureaucracies that are necessarily created to govern are different in every country. 

In China, the people elect the People’s Congresses who then elect the nearly 3,000 National People’s Congress members, who then elect the Present and State Councils. The United States has a more direct form of democracy and the people elect a House of Represenatives, a Senate, and a president who the founders intentionally locked into a power struggle to keep any part of the government from becoming authoritarian. Russia is setup similar. In fact, the State Duma, like the House in the US are elected by the people and the 85 States, or federal subjects, then send a pair of delegates to a Federal Council, like the Senate in the US, which has 170 members. It works similarly in many countries. Some, like England, still provide for hereditary titles, such as the House of Lords - but even there, the Sovereign - currently Queen Elizabeth the second, nominates a peer to a seat. That peer is these days selected by the Prime Minister. It’s weird but I guess it kinda’ works. 

Across democracies, countries communist, socialist, capitalist, and even the constitutional monarchies practice elections. The voters elect these representatives to supposedly do what’s in the best interest of the constituents. That vote cast is the foundation of any democracy. We think our differences are greater than they are, but it mostly boils down to a few percentages of tax and a slight difference in the level of expectation around privacy, whether that expectation is founded or not. 

2020 poses a turning point for elections around the world. After allegations of attempted election tampering in previous years, the president of the United States will be voted on. And many of those votes are being carried out by mail. But others will be performed in person at polling locations and done on voting machines. 

At this point, I would assume that given how nearly every other aspect of American life has a digital equivalent, that I could just log into a web portal and cast my vote. No. That is not the case. In fact, we can’t even seem to keep the voting machines from being tampered with. And we have physical control over those! So how did we get to such an awkward place, where the most important aspect of a democracy is so backwater. Let’s start 

Maybe it’s ok that voting machines and hacking play less a role than they should. Without being political, there is no doubt that Russia and other foreign powers have meddled in US elections. In fact, there’s probably little doubt we’ve interfered in theirs. Russian troll farms and disinformation campaigns are real. Paul Manafort maintained secret communications with the Kremlin. Former US generals were brought into the administration either during or after the election to make a truce with the Russians. And then there were the allegations about tampering voting machines. Now effectively stealing information about voters from Facebook using insecure API permissions. I get that. Disinformation goes back to posters in the time of Thomas Jefferson. I get that too. 

But hacking voting machines. I mean, these are vetted, right? For $3,000 to $4,500 each and when bought in bulk orders of 16,000 machines like Maryland bought from Diebold in 2005, you really get what you pay for, right? Wait, did you say 2005? Let’s jump forward to 2017. That’s the year DefCon opened the Voting Machine Hacking Village. And in 2019 not a single voting machine was secured. In fact, one report from the conference said “we fear that the 2020 presidential elections will realize the worst fears only hinted at during the 2016 elections: insecure, attacked, and ultimately distrusted.”

I learned to pick locks, use L0phtCrack, run a fuzzer, and so much more at DefCon. Now I guess I’ve learned to hack elections. So again, every democracy in the world has one thing it just has to get right, voting. But we don’t. Why? Before we take a stab at that, let’s go back in time just a little. 

The first voting machine used in US elections was a guy with a bible. This is pretty much how it went up until the 1900s in most districts. People walked in and told an election official their vote, the votes were tallied on the honor of that person, and everyone got good and drunk. People love to get good and drunk. Voter turnout was in the 85 percent range. Votes were logged in poll books. And the person was saying the name of the official they were voting for with a poll worker writing their name and vote into a pollbook. There was no expectation that the vote would be secret. Not yet at least. Additionally, you could campaign at the polling place - a practice now illegal in most places. Now let’s say the person taking the votes fudged something. There’s a log. People knew each other. Towns were small. Someone would find out. 

Now digitizing a process usually goes from vocal or physical to paper to digital to database to networked database to machine learning. It’s pretty much the path of technological determinism. As is failing because we didn't account for adjacent advancements in technology when moving a paper process to a digital process. We didn't refactor around the now-computational advances.

Paper ballots showed up in the 1800s. Parties would print small fliers that looked like train tickets so voters could show up and drop their ballot off. Keep in mind, adult literacy rates still weren’t all that high at this point. One party could print a ticket that looked kinda’ like the others. All kinds of games were being played.  We needed a better way. 

The 1800s were a hotbed of invention. 1838 saw the introduction of a machine where each voter got a brass ball which was then dropped in machine that used mechanical counters to increment a tally. Albert Henderson developed a precursor to a computer that would record votes using a telegraph that printed ink in a column based on which key was held down. This was in 1850 with US Patent 7521. Edison took the idea to US Patent 90,646 and automated the counters in 1869. Henry Spratt developed a push-button machine. Anthony Beranek continued on with that but made one row per office and reset after the last voter, similar to how machines work today. 

Jacob Meyers built on Berenek’s work and added levers in 1889 and Alfred Gillespie made the levered machine programmable. He and others formed the US Standard Voting Machine Company and slowly grew it. But something was missing and we’ll step back a little in time. Remember those tickets and poll books? They weren’t standardized. 

The Australians came up with a wacky idea in 1858 to standardize on ballots printed by the government, which made it to the US in 1888. And like many things in computing, once we had a process on paper, the automation of knowledge work, or tabulating votes would soon be ready to take into computing. Herman Hollerith brought punched card data processing to the US Census in 1890 and punch cards - his company would merge with others at the time to form IBM. 

Towards the end of the 1890s John McTammany had aded the concept that voters could punch holes in paper to cast votes and even went so far as to add a pneumatic tabulation. They were using rolls of paper rather than cards. And so IBM started tabulating votes in 1936 with a dial based machine that could count 400 votes a minute from cards. Frank Carrell at IBM got a patent for recording ballot choices on standardized cards. The stage was set for the technology to meet paper. By 1958 IBM had standardized punch cards to 40 columns and released the Port-A-Punch for so people in the field could punch information into a card to record findings and then bring it back to a computer for processing. Based on that, Joseph Harris developed the Votomatic punched-cards in 1965 and IBM  licensed the technology. In the meantime, a science teacher Reynold Johnson had developed Mark Sense in the 1930s, which over time evolved into optical mark recognition, allowing us to fill in bubbles with a pencil. So rather than punch holes we could vote by filling in a bubble on a ballot.

All the pieces were in place and the technology slowly proliferated across the country, representing over a third of votes when Clinton beat Dole and Ross Perot in 1996. 

And then 2000 came. George W. Bush defeated Al Gore in a bitterly contested and narrow margin. It came down to Florida and issues with the ballots there. By some tallies as few as 300 people decided the outcome of that election. Hanging chads are little pieces of paper that don’t get punched out of a card. Maybe unpunched holes in just a couple of locations caused the entire election to shift between parties. You could get someone drunk or document their vote incorrectly when it was orally provided in the early 1800s or provide often illiterate people with mislabeled tickets prior to the Australian ballots. But this was the first time since the advent of the personal computer, when most people in the US had computers in their homes and when the Internet bubble was growing by the day that there was a problem with voting ballots and suddenly people started wondering why were still using paper. 

The answer isn’t as simple as the fact that the government moves slowly. I mean, the government can’t maintain the rate of technical innovation and progress anyways. But there are other factors as well. One is secrecy. Anywhere that has voting will eventually have some kind of secret ballots. This goes back to the ancient greeks but also the French Revolution. Secret ballots came to the UK in the 1840s with the Chartists and to the US after the 1884 election. As the democracies matured, the concept of voting rights matured and secret ballots were part of that. Making sure a ballot is secret means we can’t just allow any old person to look at a ballot. 

Another issue is decentralization. Each state selects their own machines and system and sets dates and requirements. We see that with the capacity and allocation of mail-in voting today. 

Another issue is cost. Each state also has a different budget. Meaning that there are disparities between how well a given state can reach all voters. When we go to the polls we usually work with volunteers. This doesn’t mean voting isn’t big business. States (and countries) have entire bureaucracies around elections. Bureaucracies necessarily protect themselves. 

So why not have a national voting system? Some countries do. Although most use electronic voting machines in polling places. But maybe something based on the Internet? Security. Estonia tried a purely Internet vote and due to hacking and malware it was determined to have been a terrible idea. That doesn’t mean we should not try again. 

The response to the 2000 election results was the Help America Vote Act of 2002 to define standards managed by the Election Assistance Commission in the US. The result was the proliferation of new voting systems. ATM machine maker Diebold entered the US election market in 2002 and quickly became a large player. 

The CEO ended up claiming he was “committed to helping Ohio deliver its electoral votes to” Bush. They accidentally leaked their source code due to a misconfigured server and they installed software patches that weren’t approved. In short, it was a typical tech empire that grew too fast and hand issues we’ve seen with many companies. Just with way more on the line. After a number of transitions between divisions and issues, the business unit was sold to Election Systems & Software, now with coverage over 42 states. And having sold hundreds of thousands of voting machines, they now have over 60% of the market share in the us. That company goes back to the dissolution of a ballot tabulation division of Westinghouse and the Votronic. They are owned by a private equity firm called the McCarthy Group. 

They are sue-happy though and stifling innovation. The problems are not just with ES&S. Hart InterCivic and Dominion are the next two biggest competitors, with equal issues. And no voting machine company has a great track record with security. They are all private companies. They have all been accused of vote tampering. None of that has been proven. They have all had security issues.

In most of these episodes I try to focus on the history of technology or technocratic philosophy and maybe look to the future. I rarely offer advice or strategy. But there are strategies not being employed. 

The first strategy is transparency. In life, I assume positive intent. But transparency is really the only proof of that. Any company developing these systems should have transparent financials, provide transparency around the humans involved, provide transparency around the source code used, and provide transparency around the transactions, or votes in this case, that are processed. In an era of disinformation and fake news, transparency is the greatest protection of democracy. 

Providing transparency around financials can be a minefield. Yes, a company should make a healthy margin to continue innovating. That margin funds innovators and great technology. Financials around elections are hidden today because the companies are private. Voting doesn’t have to become a public utility but it should be regulated. 

Transparency of code is simpler to think through. Make it open source. Firefox gave us an open source web browser. ToR gave us a transparent anonymity. The mechanisms with which each transaction occurs is transparent and any person with knowledge of open source systems can look for flaws in the system. Those flaws are then corrected as with most common programming languages and protocols by anyone with the technical skills to do so. I’m not the type that thinks everything should be open source. But this should be. 

There is transparency in simplicity.  The more complex a system the more difficult to unravel. The simpler a program, the easier for anyone with a working knowledge of programming to review and if needed, correct. So a voting system should be elegant in simplicity.

Verifiability. We could look at poll books in the 1800s and punch the vote counter in the mouth if they counted our vote wrong. The transparency of the transaction was verifiable. Today, there are claims of votes being left buried in fields and fraudulent voters. Technologies like blockchain can protect against that much as currency transactions can be done in bitcoin. I usually throw up a little when I hear the term blockchain bandied about by people who have never written a line of code. Not this time. 

Let’s take hashing as a fundamental building block. Let’s say you vote for a candidate and the candidate is stored as a text field, or varchar, that is their name (or names) and the position they are running for. We can easily take all of the votes cast by a voter, store them in a json blob, commit them to a database, add a record in a database that contains the vote supplied, and then add a block in chain to provide a second point of verification. The voter would receive a guid randomly assigned and unique to them, thus protecting the anonymity of the vote. The micro-services here are to create a form for them to vote, capture the vote, hash the vote, commit the vote to a database, duplicate the transaction into the voting blockchain, and allow for vote lookups. Each can be exposed from an API gateway that allows systems built by representatives of voters at the federal, state, and local levels to lookup their votes. 

We now have any person voting capable of verifying that their vote was counted. If bad data is injected at the time of the transaction the person can report the voter fraud and a separate table connecting vote GUIDs to IP addresses or any other PII can be accessed only by the appropriate law enforcement and any attempt by law enforcement to access a record should be logged as well. Votes can be captured with web portals, voting machines that have privileged access, by 1800s voice counts, etc.

Here we have a simple and elegant system that allows for transparency, verifiability, and privacy. But we need to gate who can cast a vote. I have a PIN to access by IRS returns using my social security number or tax ID. But federal elections don’t require paying taxes. Nextdoor sent a card to my home and I entered a PIN printed on the card on their website. But that system has many a flaw. Section 303 of the Help America Vote Act of 2002 compels the State Motor Vehicle Office in each state to validate the name, date of birth, Social Security Number, and whether someone is alive. Not every voter drives. Further, not every driver meets voting requirements. And those are different per state. 

And so it becomes challenging to authenticate a voter. We do so in person, en masse, at every election due to the the staff and volunteers of various election precincts. In Minnesota I provided my drivers license number when I submitted my last ballot over the mail. If I moved since the last time I voted I also need a utility bill to validate my physical address. A human will verify that. Theoretically I could vote in multiple precincts if I were able to fabricate a paper trail to do so. If I did I would go to prison. 

Providing a web interface unless browsers support a mechanism to validate the authenticity of the source and destination is incredibly dangerous. Especially when state sponsored actors as destinations have been proven to be able to bypass safeguards such as https. And then there’s the source. It used to be common practice to use Social Security Numbers or cards as a form of verification for a lot of things. That isn’t done any more due to privacy concerns and of course due to identity theft. 

You can’t keep usernames and passwords in a database any more. So the only real answer here is a federated identity provider. This is where OAuth, OpenID Connect, and/or SAML come into play. This is a technology that retains a centralized set of information about people. Other entities then tie into the centralized identity sources and pull information from them. The technology they use to authenticate and authorize users is then one of the protocols mentioned. 

I’ve been involved in a few of these projects and to be honest, they kinda’ all suck. Identities would need to be created and the usernames and passwords distributed. This means we have to come up with a scheme that everyone in the country (or at least the typically ill-informed representatives we put in place to make choices on our behalf) can agree on. And even if a perfect scheme for usernames is found there’s crazy levels of partisanship. The passwords should be complex but when dealing with all of the factors that come into play it’s hard to imagine consensus being found on what the right level is to protect people but also in a way passwords can be remembered. 

The other problem with a federated identity is privacy. Let’s say you forget your password. You need information about a person to reset it. There’s also this new piece of information out there that represents yet another piece of personally identifiable information. Why not just use a social security number? That would require a whole other episode to get into but it’s not an option. Suddenly if date of birth, phone number (for two factor authentication), the status of if a human is alive or not, possibly a drivers license number, maybe a social security number in a table somewhere to communicate with the Social Security databases to update the whole alive status. It gets complicated fast. It’s no less private that voter databases that have already been hacked in previous elections though. 

Some may argue to use biometric markers instead of all the previous whatnot. Take your crazy uncle Larry who thinks the government already collects too much information about him and tells you so when he’s making off-color jokes. Yah, now tell him to scan his eyeball or fingerprint into the database. When he’s done laughing at you, he may show you why he has a conceal and carry permit. 

And then there’s ownership. No department within an organization I’ve seen wants to allow an identity project unless they get budget and permanent head count. And no team wants another team to own it. When bureaucracies fight it takes time to come to the conclusion that a new bureaucracy needs to be formed if we’re going anywhere. Then the other bureaucracies make the life of the new one hard and thus slow down the whole process. Sometimes needfully, sometimes accidentally, and sometimes out of pure spite or bickering over power. The most logical bureaucracy in the federal government to own such a project would be the social security administration or the Internal Revenue Service.  

Some will argue states should each have their own identity provider. We need one for taxes, social security, benefits, and entitlement programs. And by the way, we’re at a point in history when people move between states more than ever. If we’re going to protect federal and state elections, we need a centralized provider of identities. And this is going to sound crazy, but the federal government should probably just buy a company who already sells an IdP (like most companies would do if they wanted to build one) rather than contract with one or build their own. If you have to ask why, you’ve never tried to build one yourself or been involved in any large-scale software deployments or development operations at a governmental agency. I could write a book on each. 

There are newer types of options. You could roll with an IndieAuth Identity Provider, which is a decentralized approach, but that’s for logging into apps using Facebook or Apple or Google - use it to shop and game, not to vote. NIST should make the standards, FedRAMP should provide assessment, and we can loosely follow the model of the European self-sovereign identity framework or ESSIF but build on top of an existing stack so we don’t end up taking 20 years to get there. 

Organizations that can communicate with an identity provider are called Service Providers. Only FedRAMP certified public entities should be able to communicate with a federal federated identity provider. Let’s just call it the FedIdP. 

Enough on the identity thing. Suffice it to say, it’s necessary to successfully go from trusting poll workers to being able to communicate online. And here’s the thing about all of this: confidence intervals. What I mean by this is that we have gone from being able to verify our votes in poll books and being able to see other people in our communities vote to trusting black boxes built by faceless people whose political allegiances are unknown. And as is so often the case when the technology fails us, rather than think through the next innovation we retreat back to the previous step in the technological cycle: if that is getting stuck at localized digitization we retreat back to paper. If it is getting stuck at taking those local repositories online we would have retreated back to the localized digital repository. If we’re stuck at punch cards due to hanging chads then we might have to retreat back to voice voting. Each has a lower confidence interval than a verifiable and transparent online alternative. Although the chances of voter fraud by mail are still .00006%, close to a 5 9s.

We need to move forward. It’s called progress. The laws of technological determinism are such that taking the process online is the next step. And it’s crucial for social justice. I’ve over-simplified what it will take. Anything done on a national scale is hard. And time consuming. So it’s a journey that should be begun now.

In the meantime, there’s a DARPA prize. Given the involvement of a few key DARPA people with DefCon and the findings of voting machine security (whether that computers are online and potentially fallible or physically hackable or just plain bad) DARPA gave a prize to the organization that could develop a tamper proof, open-source voting machine. I actually took a crack at this, not because I believed it to be a way to make money but because after the accusations of interference in the 2016 election I just couldn’t not. Ultimately I decided this could be solved with an app in single app mode, a printer to produce a hash and a guid, and some micro-services but that the voting machine was the wrong place for the effort and that the effort should instead be put into taking voting online. 

Galois theory gives us a connection from field theory and group theory. You simplify field theory problems so they can be solved by group theory. And I’ve oversimplified the solution for this problem. But just as with studying the roots of polynomials, sometimes simplicity is elegance rather than hubris. In my own R&D efforts I struggle to understand when I’m exuding each. 

The 2020 election is forcing many to vote by mail. As with other areas that have not gotten the innovation they needed, we’re having to rethink a lot of things. And voting in person at a polling place should certainly be one. As should the cost of physically delivering those ballots and the human cost to get them entered. 

The election may or may not be challenged by luddites who refuse to see the technological determinism staring them in the face. This is a bipartisan issue. No matter who wins or loses the other party will cry foul. It’s their job as politicians. But it’s my job as a technologist to point out that there’s a better way. The steps I outlined in this episode might be wrong. But if someone can point out a better way, I’d like to volunteer my time and focus to propelling it forward. And dear listener, think about this. When progress is challenged what innovation can you bring or contribute to that helps keep us from retreating to increasingly analog methods. 

Herman Hollerith brought the punch card, which had been floating around since the Jacquard loom in 1801. Those were individuals who moved technology forward in fundamental ways. In case no one ever told you, you have even better ideas locked away in your head. Thank you for letting them out. And thank you for tuning in to this episode of the History of Computing Podcast. We are so, so lucky to have you.

JCR Licklider sent a memo called "Memorandum For Members and Affiliates of the Intergalactic Computer Network" in 1963 that is quite possibly the original spark that lit the bonfire called The ARPANet, that was the nascent beginnings of what we now called the Internet. In the memo, “Lick” as his friends called him, documented early issues in building out a time-sharing network of computers available to research scientists of the early 60s. 

The memo is a bit long so I’ll include quotes followed by explanations or I guess you might call them interpretations. Let’s start with the second paragraph:

The need for the meeting and the purpose of the meeting are things that I feel intuitively, not things that I perceive in clear structure. I am afraid that that fact will be too evident in the following paragraphs. Nevertheless, I shall try to set forth some background material and some thoughts about possible interactions among the various activities in the overall enterprise for which, as you may have detected in the above subject, I am at a loss for a name.

Intuition, to me, is important. Lick had attended conferences on cybernetics and artificial intelligence going back to the 40s. He had been MIT faculty and was working for a new defense research organization. He was a visionary. The thing is, let’s call his vision a hypothesis. During the 1960s, the Soviets would attempt to build multiple networks similar to ARPANet. Thing is, much like a modern product manager, he chunked the work to be done up and had various small teams tackle parts of projects, each building a part but in the whole proving the theory in a decentralized way. As compared to Soviet projects that went all-in.

A couple of paragraphs later, Lick goes on to state:

In pursuing the individual objectives, various members of the group will be preparing executive the monitoring routines, languages amd [sic.] compilers, debugging systems and documentation schemes, and substantive computer programs of more or less general usefulness. One of the purposes of the meeting–perhaps the main purpose–is to explore the possibilities for mutual advantage in these activities–to determine who is dependent upon whom for what and who may achieve a bonus benefit from which activities of what other members of the group. It will be necessary to take into account the costs as well as the values, of course. Nevertheless, it seems to me that it is much more likely to be advantageous than disadvantageous for each to see the others’ tentative plans before the plans are entirely crystalized. I do not mean to argue that everyone should abide by some rigid system of rules and constraints that might maximize, for example, program interchangeability.

Here, he’s acknowledging that stakeholders have different needs, goals and values, but stating that if everyone shared plans the outcome could be greater across the board. He goes on to further state that:

But, I do think that we should see the main parts of the several projected efforts, all on one blackboard, so that it will be more evident than it would otherwise be, where network-wide conventions would be helpful and where individual concessions to group advantage would be most important.

These days we prefer a whiteboard or maybe even a Miro board. But this act of visualization would let research from disparate fields, like Paul Baran at RAND working on packet switching at the time, be pulled in to think about how networks would look and work. While the government was providing money to different institutes the research organizations were autonomous and by having each node able to operate on their own rather than employ a centralized approach, the network could be built such that signals could travel along multiple paths in case one path broke down, thus getting at the heart of the matter - having a network that could survive a nuclear attach provided some link or links survived. 

He then goes on to state:

It is difficult to determine, of course, what constitutes “group advantage.” Even at the risk of confusing my own individual objectives (or ARPA’s) with those of the “group,” however, let me try to set forth some of the things that might be, in some sense, group or system or network desiderata.

This is important. In this paragraph he acknowledges his own motive, but sets up a value proposition for the readers. He then goes on to lay out a future that includes an organization like what we now use the IETF for in:

There will be programming languages, debugging languages, time-sharing system control languages, computer-network languages, data-base (or file-storage-and-retrieval languages), and perhaps other languages as well. It may or may not be a good idea to oppose or to constrain lightly the proliferation of such. However, there seems to me to be little question that it is desireable to foster “transfer of training” among these languages. One way in which transfer can be facilitated is to follow group consensus in the making of the arbitrary and nearly-arbitrary decisions that arise in the design and implementation of languages. There would be little point, for example, in having a diversity of symbols, one for each individual or one for each center, to designate “contents of” or “type the contents of.” 

The IETF and IEEE now manage the specifications that lay out the structure that controls protocols and hardware respectively. The early decisions made were for a small collection of nodes on the ARPANet and as the nodes grew and the industry matured, protocols began to be defined very specifically, such as DNS, covered in the what, second episode of this podcast. It’s important that Lick didn’t yet know what we didn’t know, but he knew that if things worked out that these governing bodies would need to emerge in order to keep splinter nets at a minimum. At the time though, they weren’t thinking much of network protocols. They were speaking of languages, but he then goes on to lay out a network-control language, which would emerge as protocols.

Is the network control language the same thing as the time-sharing control language? (If so, the implication is that there is a common time-sharing control language.) Is the network control language different from the time-sharing control language, and is the network-control language common to the several netted facilities? Is there no such thing as a network-control language? (Does one, for example, simply control his own computer in such a way as to connect it into whatever part of the already-operating net he likes, and then shift over to an appropriate mode?)

In the next few paragraphs he lays out a number of tasks that he’d like to accomplish - or at least that he can imagine others would like to accomplish, such as writing programs to run on computers, access files over the net, or read in teletypes remotely. And he lays out storing photographs on the internet and running applications remotely, much the way we do with microservices today. He referrs to information retrieval, searching for files based on metadata, natural language processing, accessing research from others, and bringing programs into a system from a remote repository, much as we do with cpan, python imports, and github today. 

Later, he looks at how permissions will be important on this new network:

here is the problem of protecting and updating public files. I do not want to use material from a file that is in the process of being changed by someone else. There may be, in our mutual activities, something approximately analogous to military security classification. If so, how will we handle it?

It turns out that the first security issues were because of eased restrictions on resources. Whether that was viruses, spam, or just accessing protected data. Keep in mind, the original network was to facilitate research during the cold war. Can’t just have commies accessing raw military research can we? As we near the end of the memo, he says:

The fact is, as I see it, that the military greatly needs solutions to many or most of the problems that will arise if we tried to make good use of the facilities that are coming into existence.

Again, it was meant to be a military network. It was meant to be resilient and withstand a nuclear attack. That had already been discussed in meetings before this memo. Here, he’s shooting questions to stakeholders. But consider the name of the memo, Memorandum For Members and Affiliates of the Intergalactic Computer Network. Not “A” network but “the” network. And not just any network, but THE Intergalactic Network. Sputnik had been launched in 1957. The next year we got NASA. 

Eisenhower then began the process that resulted in the creation of ARPA to do basic research so the US could leapfrog the Soviets. The Soviets had beaten the US to a satellite by using military rocketry to get to space. The US chose to use civilian rocketry and so set a standard that space (other than the ICBMs) would be outside the cold war. Well, ish. 

But here, we were mixing military and civilian research in the hallowed halls of universities. We were taking the best and brightest and putting them into the employ of the military without putting them under the control of the military. A relationship that worked well until the Mansfield Amendment to the 1970 Military Authorization Act ended the military funding of research that didn’t have a direct or apparent relationship to specific military function. What happened between when Lick started handing out grants to people he trusted and that act would change the course of the world and allow the US to do what the Soviets and other countries had been tinkering with, effectively develop a nationwide link of computers to provided for one of the biggest eras of collaborative research the world has ever seen. What the world wanted was an end to violence in Vietnam. What they got was a transfer of technology from the military industrial complex to corporate research centers like Xerox PARC, Digital Equipment Corporation, and others. 

Lick then goes on to wrap the memo up:

In conclusion, then, let me say again that I have the feeling we should discuss together at some length questions and problems in the set to which I have tried to point in the foregoing discussion. Perhaps I have not pointed to all the problems. Hopefully, the discussion may be a little less rambling than this effort that I am now completing.

The researchers would continue to meet. They would bring the first node of the ARPANET online in 1969. In that time they’d also help fund research such as the NLS, or oN-Line System. That eventually resulted in mainstreaming the graphical user interface and the mouse. Lick would found the Information Processing Techniques office and launch Project MAC, the first big, serious research into personal computing. They’d fund Transit, an important navigation system that ran until 1996 when it was replaced by GPS. They built Shakey the robot. And yes, they did a lot of basic military research as well. 

And today, modern networks are Intergalactic. A bunch of nerds did their time planning and designing and took UCLA online then Stanford, then UCSB and then a PDP10 at the University of Utah. Four nodes, four types of computers. Four operating systems. Leonard Kleinrock and the next generation would then take the torch and bring us into the modern era. But that story is another episode. Or a lot of other episodes. 

We don’t have a true Cold War today. We do have some pretty intense rhetoric. And we have a global pandemic. Kinda’ makes you wonder what basic research is being funded today and how that will shape the world in the next 57 years, the way this memo has shaped the world. Or given that there were programs in the Soviet Union and other countries to do something similar was it really a matter of technological determinism? Not to take anything away from the hard work put in at ARPA and abroad. But for me at least, the jury is still out on that. But I don’t have any doubt that the next wave of changes will be even more impactful. Crazy to think, right?

This prefix “cyber” is pretty common in our vernacular today. Actually it was in the 90s and now seems reserved mostly for governmental references. But that prefix has a rich history. We got cyborg in 1960 from Manfred Clynes and Nathan S. Kline. And X-Men issue 48 in 1968 introduced a race of robots called Cybertrons, likely the inspiration for the name of the planet the Transformers would inhabit as they morphed from the Japanese Microman and Diaclone toys.

We got cyberspace from William Gibson in 1982 and cyberpunk from the underground art scene in the 1980s. We got cybersex in the mid-90s with AOL. The term cybercrime rose to prominence in that same timeframe, being formalized in use by the G8 Lyons Group on High-Tech Crime. And we get cybercafes, cyberstalking, cyberattack, cyberanarchism, cyberporn, and even cyberphobia of all those sound kinda’ ick. 

And so today, the word cyber is used to prefix a meaning around the culture of computers, information technology, and virtual reality and the meaning is pretty instantly identifiable. But where did it come from? The word is actually short for cybernetic, which is greek for skilled in steering or governing. And 

Cybernetics is a multi-disciplinary science, or psuedo-science according to who you talk to, that studies systems. And it’s defined in its most truest form with the original 1948 definition from the author who pushed it into the mainstream, Norbert Wiener: “the scientific study of control and communication in the animal and the machine.” 

Aaaactually, let’s back up a minute. French physicist André-Marie Ampère coined the term cybernétique in 1934, which he called his attempt to classify human knowledge. His work on electricity and magnetism would result in studies that would earn him the honor of having the Amp named after him. But jump forward to World War Two and after huge strides in General Systems Theory and negative feedback loops and the amazing work done at Bell Labs, we started getting MIT’s Jay Forrester (who would invent computer memory) and Gordon Brown, who defined automatic-feedback control systems and solidified servomechanisms, or servos in engineering applying systems thinking all over the place, which also resulted in Forrester applying that thinking to Management, resulting in the MIT Sloan School of Management. And Deming applied these concepts to process, resulting in Total Quality Management which has been a heavy influence on what we call Six Sigma today. And John Boyd would apply systems thinking and feedback loops into military strategy. So a lot of people around the world were taking a deeper look at process and feedback and loops and systems in general. 

During World War II, systems thinking was on the rise. And seeing the rise of the computer, Norbert Wiener worked on anti-aircraft guns and was looking into what we now call information theory at about the same time Claude Shannon was. Whereas Claude Shannon went on to formalize Information Theory, Wiener formalized his work as cybernetics. He had published “A simplification in the logic of relations” in 1914, so he wasn’t new to this philosophy of melding systems and engineering. But things were moving quickly. ENIAC had gone live in 1947. Claud Shannon published a paper in 1948 that would emerge as a book called “A Mathematical Theory of Communication” by 1949. So Wiener published his book called Cybernetics, or the Control and Communication in the Animal and the Machine, in 1948.  And Donald Mackay was releasing his book on Multiplication and division by electronic analogue methods in 1948 in England. Turing’s now infamous work during World War II had helped turn the tides and after the war he was working on the Automatic Computing Engine. John von Neumann had gone from developing game theory to working on the Manhattan Project and nuclear bombs and working with ENIAC to working on computing at Princeton and starting to theorize on cellular automata. J.C.R. Licklider was just discovering the computer while working on psychoacoustics research at Harvard - work that would propel him to become the Johnny Appleseed of computing and the instigator at the center of what we now call the Internet and personal computers.

Why am I mentioning so many of the great early thinkers in computing? Because while Wiener codified, he was not alone responsible for Cybernetics. In fact, the very name Cybernetics had been the name of a set of conferences held from 1946 to 1953 and organized by the Josiah Macy, Jr foundation. These conferences and that foundation are far more influential in Western computing in the 50s and 60s, and the principals that sprang from that and went around the world than credit is usually given.

All of those people mentioned and dozens of others who are responsible for so many massive, massive discoveries were at those conferences and in the clubs around the world that sprang up from their alumni. They were looking for polymaths who could connect dots and deep thinkers in specialized fields to bring science forward through an interdisciplinary lens. In short, we had gone beyond a time when a given polymath could exceed at various aspects of the physical sciences and into a world where we needed brilliant specialists connected with those polymaths to gain quantum leaps in one discipline, effectively from another. 

And so Wiener took his own research and sprinkled in bits from others and formalized Cybernetics in his groundbreaking book. From there, nearly every discipline integrated the concept of feedback loops. Plato, who the concept can be traced back to, would have been proud. And from there, the influence was massive. 

The Cold War Military-Industrial-University complex was coming into focus. Paul Baran from RAND would read McCullough and Pitts’ work from Cybernetcs and neural nets and use that as inspiration for packet switching. That work and the work of many others in the field is now the basis for how computers communicate with one another. The Soviets, beginning with Glushkov, would hide Cybernetics and dig it up from time to time restarting projects to network their cities and automate the command and control economy. Second order cybernetics would emerge to address observing systems and third order cybernetics would emerge as applied cybernetics from the first and second order. We would get system dynamics, behavioral psychology, cognitive psychology, organizational theory, neuropsychology, and the list goes on. 

The book would go into a second edition in 1965. While at MIT, Wiener was also influential in early theories around robotics and automation. Applied cybernetics. But at the Dartmouth workshop in 1956, John McCarthy along with Marvin Minsky and Claude Shannon would effectively split the field into what they called artificial intelligence. The book Emergence is an excellent look at applying the philosophies to ant colonies and analogizing what human enterprises can extract from that work. Robotics is made possible by self-correcting mechanisms in the same way learning organizations and self-organization factor in. Cybernetics led to control theory, dynamic systems, and even chaos theory. We’ve even grown to bring biocybernetics into ecology, and synthetic and systems biology. Engineering and even management. 

The social sciences have been heavily inspired by cybernetics. Attachment theory, the cognitive sciences, and psychovector analysis are areas where psychology took inspiration. Sociology, architecture, law. The list goes on. 

And still, we use the term artificial intelligence a lot today. This is because we are more focused on productivity gains and the truths the hard sciences can tell us with statistical modeling than with the feedback loops and hard study we can apply to correcting systems. I tend to think this is related to what we might call “trusting our guts.” Or just moving so fast that it’s easier to apply a simplistic formula to an array to find a k-nearest neighbor than it is to truly analyze patterns and build feedback loops into our systems. It’s easier to do things because “that’s the way we’ve always done that” than to set our ego to the side and look for more efficient ways. That is, until any engineer on a production line at a Toyota factory can shut the whole thing down due to a defect. But even then it’s easier to apply principles from lean manufacturing than to truly look at our own processes, even if we think we’re doing so by implementing the findings from another. 

I guess no one ever said organizational theory was easy. And so whether it’s the impact to the Internet, the revolutions inspired in applied and sciences, or just that Six Sigma Blackbelt we think we know, we owe Wiener and all of the others involved in the early and later days of Cybernetics a huge thank you. The philosophies they espoused truly changed the world. 

And so think about this. The philosophies of Adam Smith were fundamental to a new world order in economics. At least, until Marx inspired Communism and the Great Depression inspired English economist John Maynard Keynes to give us Keynesian economics. Which is still applied to some degree, although one could argue incorrectly with Stimulus checks when compared to the New Deal. Necessity is the mother of invention. So what are the new philosophies emerging from the hallowed halls of academia? Or from the rest of the world at large? What comes after Cybernetics and Artificial Intelligence? Is a tough economy when we would expect the next round of innovative philosophy that could then be applied to achieve the same kinds of productivity gains we got out of the digitization of the world? Who knows. But I’m an optimist that we can get inspired - or I wouldn’t have asked. 

Thank you for tuning in to this episode of the history of computing podcast. We are so lucky to have you. Have a great day. 

I was giving a talk at DefCon one year and this guy starts grilling me at the end of the talk about the techniques Apple was using to encrypt home directories at the time with new technology called Filevault. It went on a bit, so I did that thing you sometimes have to do when it’s time to get off stage and told him we’d chat after. And of course he came up - and I realized he was really getting at the mechanism used to decrypt and the black box around decryption. He knew way more than I did about encryption so I asked him who he was. When he told me, I was stunned.

Turns out that like me, he enjoyed listening to A Prairie Home Companion. And on that show, Garrison Keillor would occasionally talk about Ralph’s Pretty Good Grocery in a typical Minnesota hometown he’d made up for himself called Lake Wobegon. Zimmerman liked the name and so called his new encryption tool PGP, short for Pretty Good Privacy. It was originally written to encrypt messages being sent to bulletin boards. 

That original tool didn’t require any special license, provided it wasn’t being used commercially. And today, much to the chagrin of the US government at the time, it’s been used all over the world to encrypt emails, text files, text messages, directories, and even disks. But we’ll get to that in a bit. 

Zimmerman had worked for the Nuclear Weapons Freeze Campaign in the 80s after getting a degree in computer science fro Florida Atlantic University in 1978. And after seeing the government infiltrate organizations organizing Vietnam protests, he wanted to protect the increasingly electronic communications of anti-nuclear protests and activities. 

The world was just beginning to wake up to a globally connected Internet. And the ARPAnet had originally been established by the military industrial complex, so it was understandable that he’d want to keep messages private that just happened to be flowing over a communications medium that many in the defense industry knew well. So he started developing his own encryption algorithm called BassOmatic in 1988. That cipher used symmetric keys with control bits and pseudorandom number generation as a seed - resulting in 8 permutation tables. He named BassOmatic after a Saturday Night Live skit. I like him more and more. 

He’d replace BassOmatic with IDEA in version 2 in 1992. And thus began the web of trust, which survives to this day in PGP, OpenPGP, and GnuPG. Here, a message is considered authentic based on it being bound to a public key - one that is issued in a decentralized model where a certificate authority issues a public and private key where messages can only be encrypted or signed with the private key and back then you would show your ID to someone at a key signing event or party in order to get a key. Public keys could then be used to check that the individual you thought was the signer really is. Once verified then a separate key could be used to encrypt messages between the parties. 

But by then, there was a problem. The US government began a criminal investigation against Zimmerman in 1993. You see, the encryption used in PGP was too good. Anything over a 40 bit encryption key was subject to US export regulations as a munition. Remember, the Cold War. Because PGP used 128 bit keys at a minimum. So Zimmerman did something that the government wasn’t expecting. Something that would make him a legend. He went to MIT Press and published the PGP source code in a physical book. Now, you could OCR the software, run it through a compiler. Suddenly, his code was protected as an exportable book by the First Amendment. 

The government dropped the investigation and found something better to do with their time. And from then on, source code for cryptographic software became an enabler of free speech, which has been held up repeatedly in the appellate courts. So 1996 comes along and PGP 3 is finally available. This is when Zimmerman founds PGP as a company so they could focus on PGP full-time. Due to a merger with Viacrypt they jumped to PGP 5 in 1997. 

Towards the end of 1997 Network Associates acquired PGP and they expanded to add things like intrusion detection, full disk encryption, and even firewalls. Under Network Associates they stopped publishing their source code and Zimmerman left in 2001. Network Associates couldn’t really find the right paradigm and so merged some products together and what was PGP commandline ended up becoming McAfee E-Business Server in 2013. 

But by 2002 PGP Corporation was born out of a few employees securing funding from Rob Theis to help start the company and buy the rest of the PGP assets from Network Associates. They managed to grow it enough to sell it for $300 million to Symantec and PGP lives on to this day. 

But I never felt like they were in it just for the money. The money came from a centralized policy server that could do things like escrow keys. But for that core feature of encrypting emails and later disks, I really always felt like they wanted a lot of that free. And you can buy Symantec Encryption Desktop and command it from a server, S/MIME and OpenPGP live on in ways that real humans can encrypt their communications, some of which in areas where their messages might get them thrown in jail.

By the mid-90s, mail wasn’t just about the text in a message. It was more. RFC934 in 1985 had started the idea of encapsulating messages so you could get metadata. RFC 1521 in 1993 formalized MIME and by 1996, MIME was getting really mature in RFC2045. But by 1999 we wanted more and so S/MIME went out as RFC 2633. Here, we could use CMS to “cryptographically enhance” a MIME body. In other words, we could suddenly encrypt more than the text of an email and it since it was an accepted internet standard, it could be encrypted and decrypted with standard mail clients rather than just with a PGP client that didn’t have all the bells and whistles of pretty email clients. 

That included signing information, which by 2004 would evolve to include attributes for things like singingTime, SMIMECapabilities, algorithms and more. 

Today, iOS can use S/MIME and keys can be stored in Exchange or Office 365 and that’s compatible with any other mail client that has S/MIME support, making it easier than ever to get certificates, sign messages, and encrypt messages. Much of what PGP was meant for is also available in OpenPGP. OpenPGP is defined by the OpenPGP Working Group and you can see the names of some of these guardians of privacy in RFC 4880 from 2007. Names like J. Callas, L. Donnerhacke, H. Finney, D. Shaw, and R. Thayer. Despite the corporate acquisitions, the money, the reprioritization of projects, these people saw fit to put powerful encryption into the hands of real humans and once that pandoras box had been opened and the first amendment was protecting that encryption as free speech, to keep it that way. Use Apple Mail, GPGTools puts all of this in your hands. Use Android, get FairEmail. Use Windows, grab EverDesk. 

This specific entry felt a little timely. Occasionally I hear senators tell companies they need to leave backdoors in products so the government can decrypt messages. And a terrorist forces us to rethink that basic idea of whether software that enables encryption is protected by freedom of speech. Or we choose to attempt to ban a company like WeChat, testing whether foreign entities who publish encryption software are also protected. Especially when you consider whether Tencent is harvesting user data or if the idea they are doing that is propaganda. For now, US courts have halted a ban on WeChat. Whether it lasts is one of the more intriguing things I’m personally watching these days, despite whatever partisan rhetoric gets spewed from either side of the isle, simply for the refinement to the legal interpretation that to me began back in 1993. After over 25 years we still continue to evolve our understanding of what truly open and peer reviewed cryptography being in the hands of all of us actually means to society. 

The inspiration for this episode was a debate I got into about whether the framers of the US Constitution would have considered encryption, especially in the form of open source public and private key encryption, to be free speech. And it’s worth mentioning that Washington, Franklin, Hamilton, Adams, and Madison all used  ciphers to keep their communications private. And for good reason as they knew what could happen should their communications be leaked, given that Franklin had actually leaked private communications when he was the postmaster general. Jefferson even developed his own wheel cipher, which was similar to the one the US army used in 1922. It comes down to privacy. The Constitution does not specifically call out privacy; however, the first Amendment guarantees the privacy of belief, the third, the privacy of home, the fourth, privacy against unreasonable search and the fifth, privacy of of personal information in the form of the privilege against self-incrimination. And giving away a private key is potentially self-incrimination. Further, the ninth Amendment has broadly been defined as the protection of privacy. 

So yes, it is safe to assume they would have supported the transmission of encrypted information and therefore the cipher used to encrypt to be a freedom. Arguably the contents of our phones are synonymous with the contents of our homes though - and if you can have a warrant for one, you could have a warrant for both. Difference is you have to physically come to my home to search it - whereas a foreign government with the same keys might be able to decrypt other data. Potentially without someone knowing what happened. The Electronic Communications Privacy Act of 1986 helped with protections but with more and more data residing in the cloud - or as with our mobile devices synchronized with the cloud, and with the intermingling of potentially harmful data about people around the globe potentially residing (or potentially being analyzed) by people in countries that might not share the same ethics, it’s becoming increasingly difficult to know what is the difference between keeping our information private, which the framers would likely have supported and keeping people safe. Jurisprudence has never kept up with the speed of technological progress, but I’m pretty sure that Jefferson would have liked to have shared a glass of his favorite drink, wine, with Zimmerman. Just as I’m pretty sure I’d like to share a glass of wine with either of them. At Defcon or elsewhere!

Welcome to the History of Computing Podcast, where we explore the history of information technology. Because understanding the past prepares us to innovate (and sometimes cope with) the future! Today we’re going to cover a paper by one of the more colorful characters in the history of computing. 

John Perry Barlow wrote songs for the Grateful Dead, ran a cattle ranch, was a founder of the Electronic Frontier Foundation, was a founder of the Freedom of the Press Foundation, was a fellow emeritus at Harvard, and early Internet pioneer. 

A bit more of the old-school libertarian, he believed the Internet should be free. And to this end, he published an incredibly influential paper in Davos, Switzerland in 1996. That paper did as much during the foundational years of the still-nascent Internet as anything else. And so here it is. 

—————

A Declaration of the Independence of Cyberspace

Governments of the Industrial World, you weary giants of flesh and steel, I come from Cyberspace, the new home of Mind. On behalf of the future, I ask you of the past to leave us alone. You are not welcome among us. You have no sovereignty where we gather.

We have no elected government, nor are we likely to have one, so I address you with no greater authority than that with which liberty itself always speaks. I declare the global social space we are building to be naturally independent of the tyrannies you seek to impose on us. You have no moral right to rule us nor do you possess any methods of enforcement we have true reason to fear.

Governments derive their just powers from the consent of the governed. You have neither solicited nor received ours. We did not invite you. You do not know us, nor do you know our world. Cyberspace does not lie within your borders. Do not think that you can build it, as though it were a public construction project. You cannot. It is an act of nature and it grows itself through our collective actions.

You have not engaged in our great and gathering conversation, nor did you create the wealth of our marketplaces. You do not know our culture, our ethics, or the unwritten codes that already provide our society more order than could be obtained by any of your impositions.

You claim there are problems among us that you need to solve. You use this claim as an excuse to invade our precincts. Many of these problems don't exist. Where there are real conflicts, where there are wrongs, we will identify them and address them by our means. We are forming our own Social Contract. This governance will arise according to the conditions of our world, not yours. Our world is different.

Cyberspace consists of transactions, relationships, and thought itself, arrayed like a standing wave in the web of our communications. Ours is a world that is both everywhere and nowhere, but it is not where bodies live.

We are creating a world that all may enter without privilege or prejudice accorded by race, economic power, military force, or station of birth.

We are creating a world where anyone, anywhere may express his or her beliefs, no matter how singular, without fear of being coerced into silence or conformity.

Your legal concepts of property, expression, identity, movement, and context do not apply to us. They are all based on matter, and there is no matter here.

Our identities have no bodies, so, unlike you, we cannot obtain order by physical coercion. We believe that from ethics, enlightened self-interest, and the commonweal, our governance will emerge. Our identities may be distributed across many of your jurisdictions. The only law that all our constituent cultures would generally recognize is the Golden Rule. We hope we will be able to build our particular solutions on that basis. But we cannot accept the solutions you are attempting to impose.

In the United States, you have today created a law, the Telecommunications Reform Act, which repudiates your own Constitution and insults the dreams of Jefferson, Washington, Mill, Madison, DeToqueville, and Brandeis. These dreams must now be born anew in us.

You are terrified of your own children, since they are natives in a world where you will always be immigrants. Because you fear them, you entrust your bureaucracies with the parental responsibilities you are too cowardly to confront yourselves. In our world, all the sentiments and expressions of humanity, from the debasing to the angelic, are parts of a seamless whole, the global conversation of bits. We cannot separate the air that chokes from the air upon which wings beat.

In China, Germany, France, Russia, Singapore, Italy and the United States, you are trying to ward off the virus of liberty by erecting guard posts at the frontiers of Cyberspace. These may keep out the contagion for a small time, but they will not work in a world that will soon be blanketed in bit-bearing media.

Your increasingly obsolete information industries would perpetuate themselves by proposing laws, in America and elsewhere, that claim to own speech itself throughout the world. These laws would declare ideas to be another industrial product, no more noble than pig iron. In our world, whatever the human mind may create can be reproduced and distributed infinitely at no cost. The global conveyance of thought no longer requires your factories to accomplish.

These increasingly hostile and colonial measures place us in the same position as those previous lovers of freedom and self-determination who had to reject the authorities of distant, uninformed powers. We must declare our virtual selves immune to your sovereignty, even as we continue to consent to your rule over our bodies. We will spread ourselves across the Planet so that no one can arrest our thoughts.

We will create a civilization of the Mind in Cyberspace. May it be more humane and fair than the world your governments have made before.

———

Thank you to John Perry Barlow for helping keep the Internet as de-regulated as it can be. Today, as we are overwhelmed by incorrect tweets (no matter what side of the politically isle you fall on), disinformation, and political manipulation, we have to rethink this foundational concept. And I hope we keep coming back to the same realization - the government has no sovereignty where we gather. 

Thank you for tuning in to this episode of the history of computing podcast. We are so, so lucky to have you. Have a great day. 

The name Claude Shannon has come up 8 times so far in this podcast. More than any single person. We covered George Boole and the concept that Boolean is a 0 and a 1 and that using Boolean algebra, you can abstract simple circuits into practically any higher level concept. And Boolean algebra had been used by a number of mathematicians, to perform some complex tasks. Including by Lewis Carroll in Through The Looking Glass to make words into math. 

And binary had effectively been used in morse code to enable communications over the telegraph. 

But it was Claude Shannon who laid the foundation for making a theory that took both the concept of communicating over the telegraph and applying Boolean algebra to get to a higher level of communication possible. And it all starts with bits, which we can thank Shannon for. 

Shannon grew up in Gaylord, Michigan. His mother was a high school principal and his grandfather had been an inventor. He built a telegraph as a child, using a barbed wire fence. But barbed wire isn’t the greatest conducer of electricity and so… noise. And thus information theory began to ruminate in his mind. He went off to the University of Michigan and got a Bachelors in electrical engineering and another in math. A perfect combination for laying the foundation of the future. 

And he got a job as a research assistant to Vannevar Bash, who wrote the seminal paper, As We May Think. At that time, Bush was working at MIT on The Thinking Machine, or Differential Analyzer. This was before World War II and they had no idea, but their work was about to reshape everything.  At the time, what we think of as computers today, were electro-mechanical. They had gears that were used for the more complicated tasks, and switches, used for simpler tasks. 

Shannon devoted his masters thesis to applying Boolean algebra, thus getting rid of the wheels, which moved slowly, and allowing the computer to go much faster. He broke down Boole’s Laws of Thought into a manner it could be applied to parallel circuitry. That paper was called A Symbolic Analysis of Relay and Switching Circuits in 1937 and helped set the stage for the Hackers revolution that came shortly thereafter at MIT. 

At the urging of Vannevar Bush, he got his PhD in Biology, pushing genetics forward by theorizing that you could break the genetic code down into a matrix. The structure of DNA would be discovered by George Gamow in 1953 and Watson and Crick would discover the helix and Rosalind Franklin would use X-ray crystallography to capture the first photo of the structure. 

He headed off to Princeton in 1940 to work at the Institute for Advanced Study, where Einstein and von Neumann were. He quickly moved over to the National Defense Research Committee, as the world was moving towards World War II. A lot of computing was going into making projectiles, or bombs, more accurate. He co-wrote a paper called Data Smoothing and Prediction in Fire-Control Systems during the war. 

He’d gotten a primer in early cryptography, reading The Gold-Bug by Edgar Allan Poe as a kid. And it struck his fancy. So he started working on theories around cryptography, everything he’d learned forming into a single theory. He would have lunch with Alan Turning during the war. He would And it was around this work that he first coined the term “information theory” in 1945.

A universal theory of communication gnawed at him and formed during this time, from the Institute, to the National Defense Research Committee, to Bell Labs, where he helped encrypt communications between world leaders. He hid it from everyone, including failed relationships. He broke information down into the smallest possible unit, a bit, short for a binary digit. He worked out how to compress information that was most repetitive. Similar to how morse code compressed the number of taps on the electrical wire by making the most common letters the shortest to send. Eliminating redundant communications established what we now call compression. 

Today we use the term lossless compression frequently in computing. He worked out that the minimum amount of information to send would be H = - Sigma Pi log2 Pi - or entropy. 

His paper, put out while he was at Bell, was called “A mathematical theory or communication” and came out in 1948. You could now change any data to a zero or a one and then compress it. Further, he had to find a way to calculate the maximum amount of information that could be sent over a communication channel before it became garbled, due to loss. We now call this the Shannon Limit. And so once we have that, he derived how to analyze information with math to correct for noise. That barbed wire fence could finally be useful. This would be used in all modern information connectivity. For example, when I took my Network+ we spent an inordinate amount of time learning about Carrier-sense multiple access with collision detection (CSMA/CD) - a media access control (MAC) method that used carrier-sensing to defer transmissions until no other stations are transmitting.

And as his employer, Bell Labs helped shape the future of computing. Along with Unix, C, C++, the transistor, the laser, information theory is a less tangible yet given what we all have in our pockets on on our wrists these days, more tangible discovery. Having mapped the limits, Bell started looking to reach the limit. And so the digital communication age was born when the first modem would come out of his former employer, Bell Labs, in 1958. And just across the way in Boston, ARPA would begin working on the first Interface Message Processor in 1967, the humble beginnings of the Internet.

His work done, he went back to MIT. His theories were applied to all sorts of disciplines. But he comes in less and less. Over time we started placing bits on devices. We started retrieving those bits. We started compressing data. Digital images, audio, and more. It would take 35 or so years 

He consulted with the NSA on cryptography. In 1949 he published Communication Theory of Secrecy Systems,  pushed cryptography to the next level. His paper Prediction and Entropy of Printed English in 1951 practically created the field of natural language processing, which evolved into various branches of machine learning. He helped give us the Nyquist–Shannon sampling theorem, used in aliasing, deriving maximum throughput, RGB, and of course signal to noise. 

He loved games. In 1941 he theorized the Shannon Number, or the game-tree complexity of chess. In case you’re curious, the reason deep blue can win at chess is that it can brute force 10 to the 120th power. His love of games continued and in 1949 he presented Programming a Computer for Playing Chess. That was the first time we thought about computers playing chess. And he’d have a standing bet that a computer would beat a human grand master at chess by 2001. Garry Kasparov lost to Deep Blue in 1997.

That curiosity extended far beyond chess. He would make Theseus in 1950 - a maze with a mouse that learned how to escape, using relays from phone switches. One of the earliest forms of machine learning. In 1961 he would co-invent the first wearable computer to help win a game of roulette. That same year he designed the Minivan 601 to help teach how computers worked. 

So we’ll leave you with one last bit of information. Shannon’s maxim is that “the enemy knows the system.” I used to think it was just a shortened version of Kerckhoffs's principle, which is that it should be possible to understand a cryptographic system, for example, modern public key ciphers, but not be able to break the encryption without a private key. Thing is, the more I know about Shannon the more I suspect that what he was really doing was giving the principle a broader meaning. So think about that as you try and decipher what is and what is not disinformation in such a noisy world. 

Lots and lots of people would cary on the great work in information theory. Like Kullback–Leibler divergence, or relative entropy. And we owe them all our thanks. But here’s the thing about Shannon: math. He took things that could have easily been theorized - and he proved them. Because science can refute disinformation. If you let it. 

We are in strange and uncertain times. The technology industry has always managed to respond to strange and uncertain times with incredible innovations that lead to the next round of growth. Growth that often comes with much higher rewards and leaves the world in a state almost unimaginable in previous iterations. The last major inflection point for the Internet, and computing in general, was when the dot come bubble burst. 

The companies that survived that time in the history of computing and stayed true to their course sparked the Web 2.0 revolution. And their shareholders were rewarded by going from exits and valuations in the millions in the dot com era, they went into the billions in the Web 2.0 era. None as iconic as Google. They finally solved how to make money at scale on the Internet and in the process validated that search was a place to do so.

Today we can think of Google, or the resulting parent Alphabet, as a multi-headed hydra. The biggest of those heads includes Search, which includes AdWords and AdSense. But Google has long since stopped being a one-trick pony. They also include Google Apps, Google Cloud, Gmail, YouTube, Google Nest, Verily, self-driving cars, mobile operating systems, and one of the more ambitious, Google Fiber. But how did two kids going to Stanford manage to become the third US company to be valued at a trillion dollars?

Let’s go back to 1998. The Big Lebowski, Fear and Loathing in Las Vegas, There’s Something About Mary, The Truman Show, and Saving Private Ryan were in the theaters. Puff Daddy hadn’t transmogrified into P Diddy. And Usher had three songs in the Top 40. Boyz II Men, Backstreet Boys, Shania Twain, and Third Eye Blind couldn’t be avoided on the airwaves. They’re now pretty much relegated to 90s disco nights. But technology offered a bright spot. We got the first MP3 player, the Apple Newton, the Intel Celeron and Xeon, the Apple iMac, MySQL, v.90 Modems, StarCraft, and two Stanford students named Larry Page and Sergey Brin took a research project they started in 1996 with Scott Hassan, and started a company called Google (although Hassan would leave Google before it became a company). 

There were search engines before Page and Brin. But most produced search results that just weren’t that great. In fact, most were focused on becoming portals. They took their queue from AOL and other ISPs who had springboarded people onto the web from services that had been walled gardens. As they became interconnected into a truly open Internet, the amount of diverse content began to explode and people just getting online found it hard to actually find things they were interested in. Going from ISPs who had portals to getting on the Internet, many began using a starting page like Archie, LYCOS, Jughead, Veronica, Infoseek, and of course Yahoo!

Yahoo! Had grown fast out of Stanford, having been founded by Jerry Yang and David Filo. By 1998, the Yahoo! Page was full of text. Stock tickers, links to shopping, and even horoscopes. It took a lot of the features from the community builders at AOL. The model to take money was banner ads and that meant keeping people on their pages. Because it wasn’t yet monetized and in fact acted against the banner loading business model, searching for what you really wanted to find on the Internet didn’t get a lot of love. The search engines or portals of the day had pretty crappy search engines compared to what Page and Brin were building. 

They initially called the search engine BackRub back in 1996. As academics (and the children of academics) they knew that the more papers that sited another paper, the more valuable the paper was. Applying that same logic allowed them to rank websites based on how many other sites linked into it. This became the foundation of the original PageRank algorithm, which continues to evolve today. The name BackRub came from the concept of weighting based on back links. That concept had come from a tool called RankDex, which was developed by Robin Li who went on to found Baidu. 

Keep in mind, it started as a research project. The transition from research project meant finding a good name. Being math nerds they landed on "Google" a play on "googol", or a 1 followed by a hundred zeros.

And within a year they were still running off University of Stanford computers. As their crawlers searched the web they needed more and more computing time. So they went out looking for funding and in 1998 got $100,000 from Sun Microsystems cofounder Andy Bechtolsheim. Jeff Bezos from Amazon, David Cheriton, Ram Shriram and others kicked in some money as well and they got a million dollar round of angel investment. And their algorithm kept getting more and more mature as they were able to catalog more and more sites. By 1999 they went out and raised $25 million from Kleiner Perkins and Sequoia Capital, insisting the two invest equally, which hadn’t been done. 

They were frugal with their money, which allowed them to weather the coming storm when the dot com bubble burst. They build computers to process data using off the shelf hardware they got at Fry’s and other computer stores, they brought in some of the best talent in the area as other companies were going bankrupt. 

They also used that money to move into offices in Palo Alto and in 2000 started selling ads through a service they called AdWords. It was a simple site and ads were text instead of the banners popular at the time. It was an instant success and I remember being drawn to it after years of looking at that increasingly complicated Yahoo! Landing page. And they successfully inked a deal with Yahoo! to provide organic and paid search, betting the company that they could make lots of money. And they were right. The world was ready for simple interfaces that provided relevant results. And the results were relevant for advertisers who could move to a pay-per-click model and bid on how much they wanted to pay for each click. They could serve ads for nearly any company and with little human interaction because they spent the time and money to build great AI to power the system. You put in a credit card number and they got accurate projections on how successful an ad would be. In fact, ads that were relevant often charged less for clicks than those that weren’t. And it quickly became apparent that they were just printing money on the back of the new ad system.

They brought in Eric Schmidt to run the company, per the agreement they made when they raised the $25 million and by 2002 they were booking $400M in revenue. And they operated at a 60% margin. These are crazy numbers and enabled them to continue aggressively making investments. The dot com bubble may have burst, but Google was a clear beacon of light that the Internet wasn’t done for.

In 2003 Google moved into a space now referred to as the Googleplex, in Mountain View California. In a sign of the times, that was land formerly owned by Silicon Graphics. They saw how the ad model could improved beyond paid placement and banners and acquired  is when they launched AdSense. They could afford to with $1.5 billion in revenue. 

Google went public in 2004, with revenues of $3.2 billion. Underwritten by Morgan Stanley and Credit Suisse, who took half the standard fees for leading the IPO, Google sold nearly 20 million shares. By then they were basically printing money. By then the company had a market cap of $23 billion, just below that of Yahoo. That’s the year they acquired Where 2 Technologies to convert their mapping technology into Google Maps, which was launched in 2005. They also bought Keyhole in 2004, which the CIA had invested in, and that was released as Google Earth in 2005. That technology then became critical for turn by turn directions and the directions were enriched using another 2004 acquisition, ZipDash, to get real-time traffic information. At this point, Google wasn’t just responding to queries about content on the web, but were able to respond to queries about the world at large. They also released Gmail and Google Books in 2004.

By the end of 2005 they were up to $6.1 billion in revenue and they continued to invest money back into the company aggressively, looking not only to point users to pages but get into content. That’s when they bought Android in 2005, allowing them to answer queries using their own mobile operating system rather than just on the web. On the back of $10.6 billion in revenue they bought YouTube in 2006 for $1.65 billion in Google stock. This is also when they brought Gmail into Google Apps for Your Domain, now simply known as G Suite - and when they acquired Upstartle to get what we now call Google Docs. 

At $16.6 billion in revenues, they bought DoubleClick in 2007 for $3.1 billion to get the relationships DoubleClick had with the ad agencies. 

They also acquired Tonic Systems in 2007, which would become Google Slides. Thus completing a suite of apps that could compete with Microsoft Office. By then they were at $16.6 billion in revenues.

The first Android release came in 2008 on the back of $21.8 billion revenue. They also released Chrome that year, a project that came out of hiring a number of Mozilla Firefox developers, even after Eric Schmidt had stonewalled doing so for six years. The project had been managed by up and coming Sundar Pichai. That year they also released Google App Engine, to compete with Amazon’s EC2. 

They bought On2, reCAPTCHA, AdMob, VOIP company Gizmo5, Teracent, and AppJet in 2009 on $23.7 Billion in revenue and Aardvark, reMail, Picnic, DocVerse, Episodic, Plink, Agnilux, LabPixies, BumpTop, Global IP Solutions, Simplify Media, Ruba.com, Invite Media, Metaweb, Zetawire, Instantiations, Slide.com, Jambool, Like.com, Angstro, SocialDeck, QuickSee, Plannr, BlindType, Phonetic Arts, and Widevine Technologies in 2010 on 29.3 billion in revenue.

In 2011, Google bought Motorola Mobility for $12.5 billion to get access to patents for mobile phones, along with another almost two dozen companies. This was on the back of nearly $38 billion in revenue. 

The battle with Apple intensified when Apple removed Google Maps from iOS 6 in 2012. But on $50 billion in revenue, Google wasn’t worried. They released the Chromebook in 2012 as well as announcing Google Fiber to be rolled out in Kansas City. 

They launched Google Drive They bought Waze for just shy of a billion dollars in 2013 to get crowdsourced data that could help bolster what Google Maps was doing. That was on 55 and a half billion in revenue. 

In 2014, at $65 billion in revenue, they bought Nest, getting thermostats and cameras in the portfolio. 

Pichai, who had worked in product on Drive, Gmail, Maps, and Chromebook took over Android and by 2015 was named the next CEO of Google when Google restructured with Alphabet being created as the parent of the various companies that made up the portfolio. By then they were up to 74 and a half billion in revenue. And they needed a new structure, given the size and scale of what they were doing. 

In 2016 they launched Google Home, which has now brought AI into 52 million homes. They also bought nearly 20 other companies that year, including Apigee, to get an API management platform. By then they were up to nearly $90 billion in revenue.

2017 saw revenues rise to $110 billion and 2018 saw them reach $136 billion. 

In 2019, Pichai became the CEO of Alphabet, now presiding over a company with over $160 billion in revenues. One that has bought over 200 companies and employs over 123,000 humans. Google’s mission is “to organize the world's information and make it universally accessible and useful” and it’s easy to connect most of the acquisitions with that goal.

I have a lot of friends in and out of IT that think Google is evil. Despite their desire not to do evil, any organization that grows at such a mind-boggling pace is bound to rub people wrong here and there. I’ve always gladly using their free services even knowing that when you aren’t paying for a product, you are the product. We have a lot to be thankful of Google for on this birthday. As Netscape was the symbol of the dot com era, they were the symbol of Web 2.0. They took the mantle for free mail from Hotmail after Microsoft screwed the pooch with that. 

They applied math to everything, revolutionizing marketing and helping people connect with information they were most interested in. They cobbled together a mapping solution and changed the way we navigate through cities. They made Google Apps and evolved the way we use documents, making us more collaborative and forcing the competition, namely Microsoft Office to adapt as well. They dominated the mobility market, capturing over 90% of devices. They innovated cloud stacks. And here’s the crazy thing, from the beginning, they didn’t make up a lot. They borrowed the foundational principals of that original algorithm from RankDex, Gmail was a new and innovative approach to Hotmail, Google Maps was a better Encarta, their cloud offerings were structured similar to those of Amazon. And the list of acquisitions that helped them get patents or talent or ideas to launch innovative services is just astounding. 

Chances are that today you do something that touches on Google. Whether it’s the original search, controlling the lights in your house with Nest, using a web service hosted in their cloud, sending or receiving email through Gmail or one of the other hundreds of services. The team at Google has left an impact on each of the types of services they enable. They have innovated business and reaped the rewards. And on their 22nd birthday, we all owe them a certain level of thanks for everything they’ve given us.

So until next time, think about all the services you interact with. And think about how you can improve on them. And thank you, for tuning in to this episode of the history of computing podcast. 

The Oregon Trail is a 2100 plus mile wagon route that stretched from the Missouri River to settleable lands in Oregon. Along the way it cuts through Kansas, Nebraska, Wyoming, and Idaho as well. After parts were charted by Lewis and Clark from 1804 to 1806, it was begun by fur traders in 1811 but fin the 1830s Americans began to journey across the trail to settle the wild lands of the Pacific Northwest. And today, Interstates 80 and 84 follow parts of it. But the game is about the grueling journey that people made from 1824 and on, which saw streams of wagons flow over the route in the 1840s. And over the next hundred years it became a thing talked about in textbooks but difficult to relate to in a land of increasing abundance. 

So flash forward to 1971. America is a very different place than those wagonloads of humans would have encountered in Fort Boise or on the Boeman Trail, both of which now have large cities named after them. Instead, in 1971, NPR produced their first broadcast. Amtrak was created in the US. Greenpeace was founded. Fred Smith created Federal Express. A Clockwork Orange was released. And Don Rawitch wrote The Oregon Trail while he was a senior at Carleton College to help teach an 8th grade history class in Northfield, Minnesota. 

It’s hard to imagine these days, but this game was cutting edge at the time. Another event in 1971: the Intel 4004 microprocessor comes along, which will change everything in computing in just 10 short years. In 1971, when Apollo 14 landed on the moon, the computer was made of hand-crafted coils and chips and a 10 key pad was used to punch in code. When Ray Tomlinson invented email that year, computers weren’t interactive. When IBM invented the floppy disk that year, no one would have guessed they would some day be used to give school children dissentary all across the world.

When he first wrote OREGON, as the game was originally known, Don was using a time shared HP 2100 minicomputer at Pillsbury (yes, the Pillsbury of doughboy fame who makes those lovely, flaky biscuits). THE HP WAS running Time-Share BASIC and Don roped in his roommates, Paul Dillenberger and Bill Heinemann to help out. Back then, the computer wrote output to teletype and took data in using tape terminals. But the kids loved it. They would take a wagon from Independence, Missouri to Willamette Valley, Oregon - making a grueling journey in a covered wagon in 1848. And they might die of dissentary, starvation, mountain fever or any other ailment Rawitch could think of. 

Gaming on paper tape was awkward, but the kids were inspired. They learned about computers and the history of how the West was settled at the same time. When the class was over, Don printed the code for the game, probably not thinking much would happen with it after that.

But then he got hired by the Minnesota Educational Computing Consortium, or MECC, in 1974. Back in the 60s and 70s, Minnesota was a huge hub of computing. Snow White and the Seven Dwarves had offices in the state, and early pioneers of mainframes like Honeywell, Unisys, ERA (and so Control Data Corporation and Cray from there), and IBM, all did a lot of work in the state. The state had funded MECC to build educational software for classrooms following the successes at TIES, or the Total Information for Educational Systems which had brought a time-sharing service on a HP 2000 along with training, and software (which they still do) to Minnesota schools. From there, the state created MECC to create software for schools. 

Don dug that code from 1971 back up and typed it back into the time sharing computers at MECC. He tweaked it a little and made it available on the CDC Cyber 70 at MECC and before you knew it, thousands of people were playing his game. By 1978 he’d publish the source code in Creative Computing magazine as the Oregon Trail. And then JP O’Malley would modify the basic programming to run on an Apple II and the Apple Pugetsound Program Library Exchange would post the game on their user group. 

The Oregon Trail 2 would come along that year as well and by 1980, MECC would release it along with better graphics as a part of an Elementary Series of educational titles - but the graphics got better with a full release as a standalone game in 1985. Along the way it had gotten ported for the Atari in 1983 and the Commodore 64 in 1984. But the 1985 version is the one we played in my school.

We loved getting to play on the computers in school. The teachers seemed to mostly love getting a break as we were all silent while playing, until we lost one of our party - and then we’d laugh and squeal at the same time! We’d buy oxen, an extra yoke for our wagon, food, bullets, and then we’d set off on our journey to places many of us had never heard of. We’d get diseases, break limbs, get robbed, and watch early versions of cut scenes in 8-bit graphics. And along the way, we learned.  

We learned about a city called Independence, Missouri. And that life was very different in 1848. We learned about history. We learned about game mechanics. We started with $800. 

We learned about bartering and how carpenters were better at fixing wagon wheels than bankers were. We tried to keep our party alive and we learned that it’s a good idea to save a little money to ferry across rivers. We learned the rudimentariness of shooting in games, as we tried to kill a bear here and there. We learned that rabbits didn’t give us much meat. We learned to type BANG and WHAM fast so we could shoot animals and later we learned to aim with arrow keys and fire with a space bar. The bison moved slow and gave more meat than the 100 pounds you could carry back to your wagon. So we shot them. We learned carpenters could fix wheels and to conserve enough money to ferry your wagon so you didn’t sink or have one of your party drown. 

We learned that you got double the points for playing the carpenter and triple for playing the farmer. We wanted to keep our family alive not only because we got to name them (often making fun of our friends in class) but also because they gave us more points. As did the possessions we were able to keep. 

By 1990 with a changing tide, the game came to DOS and by 1991 it was ported to the Mac. Mouse support was added in 1992 and it came to Windows 3 in 1993. Softkey released The Oregon Trail: Classic Edition. And 

by 1995 The Oregon Trail made up a third of the MECC budget, raking in $30 million per year, and helped fund other titles. Oregon Trail II came in 95, 3 in 97, 4 in 99, and 5 made it into the new millennia in 2001. All being released for Windows and Mac. And 10 years later it would come to the modern era of console gaming, making it to the Wii and 3DS. 

And you can learn all of what we learned by playing the game on Archive.org ( https://archive.org/details/msdos_Oregon_Trail_The_1990 ). The Internet Archive page shows the 1990 version that was ported and made available for the Apple II, Macintosh, Windows, and DOS. The Internet Archive page alone has had nearly 7.2 million views. But the game has sold over 65 million copies as well. 

The Oregon Trail is beloved by many. I see shirts with You Have Died of DIssentary and card versions of the game in stores. I’ve played in Facebook games and mobile versions. It’s even been turned into plays and parodied in TV shows. That wagon is one of the better known symbols of all time in gaming lore. And we still use many of the game mechanics introduced then, in games from Dragon Warrior to the trading and inventory system inspiring the World of Warcraft. 

We can thank The Oregon Trail for giving our teachers a beak from teaching us in school and giving us a break from learning. Although I suspect we learned plenty. And we can thank MECC for continuing the fine tradition of computer science in Minnesota. And we can thank Don for inspiring millions, many of which went on to create their own games.

And thank you, listener, for tuning in to this episode of The History of Computing Podcast. We are so so so lucky to have you. Have a great day! And keep in mind, a steady pace will get you to the end of the trail before the snows come in, with plenty of time to take ferries across the rivers. Rest when you need it. And no, you probably aren’t likely to beat my high score. 

SimCity is one those games that helped expand the collective public consciousness of humans. 

I have a buddy who works on traffic flows in Minneapolis. When I asked how he decided to go into urban planning, he quickly responded with “playing SimCity.” Imagine that, a computer game inspiring a generation of people that wanted to make cities better. How did that come to be?

Will Wright was born in 1960. He went to Louisiana State University then Louisiana Tech and then to The New School in New York. By then, he was able to get an AppleII+ and start playing computer games, including Life, a game initially conceived by mathematician John Conway in 1970. A game that expanded the minds of every person that came in contact with it. That game had begun on the PDP, then in BBC BASIC before spreading around. It allowed players to set an initial configuration for cells and watch them mutate over time. 

After reading about LIFE, Wright wanted to port it to his Apple, so he learned Applesoft BASIC and PASCAL. He tinkered and By 1984 was able to produce a game called Raid on Bungeling Bay. And as many a Minecrafter can tell you, part of the fun was really building the islands in a map editor he built for the game. He happened to also be reading about urban planning and system dynamics. He just knew there was something there. Something that could take part of the fun from Life and editing maps in games and this newfound love of urban planning and give it to regular humans. Something that just might expand our own mental models about where we live and about games. 

This led him to build software that gamified editing maps. Where every choice we made impacted the map over time. Where it was on us to build the perfect map. That game was called Micropolis and would become SimCity. One problem, none of the game publishers wanted to produce it when it was ready for the Commodore 64 in 1985. After Brøderbund turned him down, he had to go back to the drawing board. 

So Wright would team up with his friend Jeff Braun who had founded Maxis Software in 1987. They would release SimCity in 1989 for Mac and Amiga and once it had been ported, for the Atari ST, DOS-based PCs, and the ZX Spectrum. Brøderbund did eventually agree to distribute it as it matured. 

And people started to get this software, staring at a blank slab of land where we zone areas as commercial and residential. We tax areas and can increment those rates, giving us money to zone other areas, provide electricity, water, and other services, and then build parks, schools, hospitals, police stations, etc. The more dense and populous the city becomes, the more difficult the game gets. The population fluctuates and we can tweak settings to grow and shrink the city. I was always playing to grow, until I realized sometimes it’s nice to stabilize and look for harmony instead.

And we see the evolution over time. The initial choices we made could impact the ability to grow forever. But unlike Life we got to keep making better and better (or worse and worse) choices over time. We delighted in watching the population explode. In watching the city grow and flourish. And we had to watch parts of our beloved city decay. We raised taxes when we were running out of money and lowered them when population growth was negatively impacted. We built parks and paid for them. We tried to make people love our city. 

We are only limited in how great a city we can build by our own creativity. And our own ability to place parts of the city alongside the features that let the people live in harmony with the economic and ecological impacts of other buildings and zones. For example, build a power plant as far from residential buildings as you can because people don’t want to live right by a power plant. But running power lines is expensive, so it can’t be too far away in the beginning. 

The game mechanics motivate us to push the city into progress. To build. To develop. People choose to move to our cities based on how well we build them. It was unlike anything else out there. And it was a huge success. 

SimCity 2000 came along in 1993. Graphics had come a long way and you could now see the decay in the icons of buildings. It expanded the types of power plants we could build, added churches, museums, prisons and zoos. - each with an impact to the way the city grows. As the understanding of both programming and urban planning grew for the development team, they added city ordinances. The game got more and more popular. 

SimCity 3000 was the third installment in the series, which came out in 1999. By then, the game had sold over 5 million copies. That’s when they added slums and median incomes to create a classification. And large malls, which negatively impact smaller commercial zones. And toxic waste conversion plants. And prisons, which hits residential areas. And casinos, which increase crime. But each has huge upside as well. As graphics cards continued to get better, the simulation also increased, giving us waterfalls, different types of trees, more realistic grass, and even snow. 

Maxis even dabbled with using their software to improve businesses. Maxis Business Simulations built software for refineries and health as well.  

And then came The Sims, which Wright though of after losing his house to a fire in 1991. Here, instead of simulating a whole city of people at once, we simulated a single person, or a Sim. And we attempted to lead a fulfilling life by satisfying the needs and desires of our sim, buying furniture, building larger homes, having a family, and just… well, living life. But the board at Maxis didn’t like the idea. Maxis was acquired by Electronic Arts in 1997. And they were far more into the Sims idea, so The Sims was released in 2000. And it has sold nearly 200 million copies and raked in over $5 billion dollars in sales, making it one of the best-selling games of all times. Even though now it’s free on mobile devices with tons of in app purchases… 

And after the acquisition of Maxis, SimCity is now distributed by EA. Sim 4 would come along in 2003, continuing to improve the complexity and game play. And with processors getting faster, cities could get way bigger and more complex. SimCity 6 came in 2013, from lead designer Stone Librande and team. They added a Google Earth type of zoom effect to see cities and some pretty awesome road creation tools. And the sounds of cars honking on streets, birds chirping, airplanes flying over, and fans cheering in stadiums were amazing. They added layers so you could look at a colorless model of the city highlighting crime or pollution, to make tracking each of the main aspects of the game easier. Like layers in Photoshop. It was pretty CPU and memory intensive but came with some pretty amazing gameplay. In fact, some of the neighborhood planning has been used to simulate neighborhood development efforts in cities. 

And the game spread to consoles as well, coming to iPhone and web browsers in 2008. I personally choose not to play any more because I’m not into in-app purchasing. 

A lot of science fiction films center around two major themes: either societies enter into a phase of utopia or dystopia. The spread of computing into first our living rooms in the form of PCs and then into our pockets via mobile devices has helped push us into the utopian direction. 

SimCity inspired a generation of city planners and was inspired by more and more mature research done on urban planning. A great step on the route to a utopia and eye opening as to the impact our city planning has on advances towards a dystopian future. We were all suddenly able to envision better city planning and design, making cities friendlier for walking, biking, and being outdoors. Living better. Which is important in a time of continued mass urbanization. 

Computer games could now be about more than moving a dot with a paddle or controlling a character to shoot other characters. Other games with an eye opening and mind expanding game play were feasible. Like Sid Myers’ Civilization, which came along in 1991. But SimCity, like Life, was another major step on the way to where we are today. And it’s so relatable now that I’ve owned multiple homes and seen the impact of tax rates and services the governments in those areas provide. 

So thank you to Will Wright. For inspiring better cities. And thank you to the countless developers, designers, and product managers, for continuing the great work at Maxis then EA. 

Today, we think of Pixar as the company that gave us such lovable characters as Woody and Buzz Lightyear, Monsters Mike Wazowski and James P Sullivan, Nemo, Elastagirl, and Lightnight McQueen. But all that came pretty late in the history of the company.

Let’s go back to the 70s. Star Wars made George Lucas a legend. His company Lucasfilm produced American Graffiti, the Star Wars Francise, the Indiana Jones Francis, The Labrynth, Willow, and many others. Many of those movies were pioneering in the use of visual effects in storytelling. At a time when the use of computer-aided visual effects was just emerging. So Lucas needed world-class computer engineers.

Lucas found Ed Catmull and Alvy Ray Smith at the New York Institute of Technology Computer Graphics Lab. They had been hired by the founder, Alexander Schure, to help create the first computer-animated film in the mid-70s. But Lucas hired Catmull (who had been a student of the creator of the first computer graphics software, Sketchpad) and Smith (who had worked on SuperPaint at Xerox PARC) away to run the computer division of Lucasfilm, which by 1979 was simply called the Graphics Group. 

They created REYES and developed a number of the underlying techniques used in computer graphics today. They worked on movies like Star Trek II where the graphics still mostly stand up nearly 40 years later. And as the group grew, the technology got more mature and more useful. REYES would develop into RenderMan and become one of the best computer graphics products on the market. Pioneering, they won prizes in science and film. RenderMan is still one of the best tools available for computer-generated lighting, shading, and shadowing.

John Lasseter joined in 1983. And while everything was moving in the right direction, in the midst of a nasty divorce when he needed the cash, Lucas sold the group as a spin-off to Steve Jobs in 1986. Jobs had just been ousted from Apple and was starting NeXT. He had the vision to bring the computer graphics to homes. They developed The Pixar Image Computer for commercial sales, which would ship just after Jobs took over the company. It went for $135,000 and still required an SGI or Sun computer to work. They’d sell just over 100 in the first two years - most to Disney. 

The name came from Alvy Ray Smith’s original name he suggested for the computer, Picture Maker. That would get shortened to Pixer, and then Pixar. The technology they developed along the way to the dream of a computer animated film was unparalleled in special effects. But CPUs weren’t going fast enough to keep up. 

The P-II model came with a 3 gig RAID (when most file systems couldn’t even access that much space), 4 processors, multiple video cards, 2 video processors, a channel for red, blue green, and alpha. It was a beast. 

But that’s not what we think of when we think of Pixar today. You see, they had always had the desire to make a computer animated movie. And they were getting closer and closer. Sure, selling computers to aid in the computer animation is the heart of why Steve Jobs bought the company - but he, like the Pixar team, is an artist. They started making shorts to showcase what the equipment and software they were making could do. 

Lasseter made a film called Luxo Jr in 1986 and showed it at SIGGRAPH, which was becoming the convention for computer graphics. They made a movie every year, but they were selling into a niche market and sales never really took off. Jobs pumped more money into the company. He’d initially paid $5 million dollars and capitalized the company with another $5 million. By 1989 he’d pumped $50 million into the company. But when sales were slow and they were bleeding money, Jobs realized the computer could never go down market into homes and that part of the business was sold to Vicom in 1990 for $2 million, who then went bankrupt.

But the work Lasseter was doing blending characters that were purely made using computer graphics with delicious storytelling. Their animated short Tin Toy won an Academy Award in 1988. And being an artist, during repeated layoffs, that group just continued to grow. They would release more and more software - and while they weren’t building computers, the software could be run on other computers like Macs and Windows. 

The one bright spot was that Pixar and the Walt Disney Animation Studio were inseparable. By 1991 though, computers had finally gotten fast enough, and the technology mature enough, to make a computer-animated feature. And this is when Steve Jobs and Lasster sold the idea of a movie to Disney. In fact, they got $24 million to make three features. They got to work on the first of their movie. Smith would leave in 1994, supposedly over a screaming match he had with Jobs over the use of a whiteboard. But if Pixar was turning into a full-on film studio, it was about to realize the original dream they all had of creating a computer-animated motion picture and it’s too bad Smith missed it.

That movie was called Toy Story. It would bring in $362 million dollars globally becoming the highest-grossing movie of 1995 and allow Steve Jobs to renegotiate the Pixar deal with Disney and take the company public in 1995. His $60 million investment would convert into over a billion dollars in Pixar stock that became over a hundred thousand shares of Disney stock worth over $4 billion, the largest single shareholder. Those shares were worth $7.4 billion dollars when he passed away in 2011. His wife would sell half in 2017 as she diversified the holdings. 225x on the investment. 

After Toy Story, Pixar would create Cars, Finding Nemo, Wall-E, Up, Onward, Mosters Inc, Ratatouille, Brave, The Incredibles, and many other films. Movies that have made close to $15 billion dollars. But more importantly, they mainstreamed computer animated films. And another huge impact on the history of computing was that they made Steve Jobs a billionaire and proved to Wall Street that he could run a company. After a time I think of as “the dark ages” at Apple, Jobs came back in 1996, bringing along an operating system and reinventing Apple - giving the world the iMac, the iPod, and the iPhone. And streamlining the concept of multi-media enough that music and later film and then software, would be sold through Apple’s online services, setting the groundwork for Apple to become the most valuable company in the world. 

So thank you to everyone from Pixar for the lovable characters, but also for inventing so much of the technology used in modern computer graphics - both for film and the tech used in all of our computers. And thank you for the impact on the film industry and keeping characters we can all relate to at the forefront of our minds. And thank you dear listener for tuning in to yet another episode of the History of Computing Podcast. We are so lucky to have you. And lucky to have all those Pixar movies. I think I’ll go watch one now. But I won’t be watching them on the Apple streaming service. It’ll be on Disney service. Funny how that worked out, aint it.