Speaker 1: Welcome to tech Stuff, a production from I Heart Radio.
Speaker 1: Hey there, and welcome to tech Stuff. I'm your host,
Speaker 1: Jonathan Strickland. I'm an executive producer with I Heart Radio
Speaker 1: and I love all things tech. And you know what,
Speaker 1: um twenty one years ago? Man, that blows my mind.
Speaker 1: But twenty one years ago, the world was very concerned
Speaker 1: that a clock, a a a digit changing from to
Speaker 1: zero zero was going to completely turn our technological world
Speaker 1: upside down. I'm talking about the Y two K problem.
Speaker 1: And some of you out there might be too young
Speaker 1: to even know what that is, or maybe you were
Speaker 1: born after two thousand, you have no clue. But for
Speaker 1: those of us who were working in the nineties, this
Speaker 1: was a big deal. It was something that a lot
Speaker 1: of people were worried about, and it all had to
Speaker 1: do with those two little digits at the end of
Speaker 1: the year. And we're gonna learn about why why two
Speaker 1: K didn't in the world, because, I mean, spoiler alert,
Speaker 1: it didn't. So let's listen back to this episode, which
Speaker 1: originally published on January two thousand and fourteen. Like someone
Speaker 1: cut and now things aren't working, also building up to
Speaker 1: something terrifying. Yeah, it's gonna build up to a NonStop
Speaker 1: replay of Prince over and over again, which it starts
Speaker 1: out awesome, but as it goes on, let me tell
Speaker 1: you that gets old. Okay, we're talking about the Y
Speaker 1: two K Bug obviously, people, Yes, yes, that is what
Speaker 1: our episode is about today. All of our fans who
Speaker 1: hate it. Whenever I do cheesy humor, I apologize, don't
Speaker 1: really apologize. It is who I am. So the reason
Speaker 1: why we're talking about why two K Bug years after
Speaker 1: the whole issue happened, is because, you know, we ask you,
Speaker 1: guys what you want to hear, and in this case,
Speaker 1: a listener named James sent us a message on Twitter
Speaker 1: and said, hey, guys, you should do an episode on
Speaker 1: the Y two K Bug. Heart heart James. Well, James,
Speaker 1: we heart heart you two. Now we're going to do
Speaker 1: our episode on the Y two K Bug. It's a
Speaker 1: pretty interesting story because it's one of those things where,
Speaker 1: you know, it really illustrates a few basic things about
Speaker 1: computing and human nature in general. One of those things
Speaker 1: is that when something new is created, no one who
Speaker 1: is around has any idea of how long it's gonna last,
Speaker 1: and they don't have any any appreciation of things that
Speaker 1: they do then lasting into well into the future, right, well,
Speaker 1: especially things like computer programming. I mean, no one in
Speaker 1: say the nineteen sixties or seventies was expecting any of
Speaker 1: the programs they were writing to last for forty years. Yeah,
Speaker 1: computers were developing very quickly, and the general thought was that,
Speaker 1: you know, this is changing so fast that programming is
Speaker 1: going to change in at a crazy speed too. But
Speaker 1: as it turns out, while the hardware changed, the practices
Speaker 1: that were established early on remained pretty much standard. And
Speaker 1: also a lot of this old programming would find its
Speaker 1: way into subsequent generations of software. So even if it
Speaker 1: wasn't something that people were continuing to do later on, uh,
Speaker 1: there'd still be these old fragments of code incorporated into
Speaker 1: stuff that did have it. Now we're kind of dancing
Speaker 1: around what that old thing was. Oh, oh, the the
Speaker 1: old thing, of course being I just got really excited
Speaker 1: that I knew the answer to this um being the
Speaker 1: digits in the year. Yeah. So here was the issue
Speaker 1: back in the fifties and sixties when programmers were having
Speaker 1: to put a code in for the year, which is
Speaker 1: important for certain types of calculations, right, anything that's time
Speaker 1: based Obviously you need to have a way of recording
Speaker 1: the time so that you can compare times from different
Speaker 1: points and draw your calculations based on that different you know,
Speaker 1: for for for example, when people have been depositing paychecks
Speaker 1: or right. So if you if you have a bank
Speaker 1: account that has interest, for example, time is obviously a
Speaker 1: factor there. It's not just the amount of money that
Speaker 1: you've been continuously putting into or taking out of that
Speaker 1: bank account. It's also the amount of times since you
Speaker 1: established that bank account. And there's some complicated calculations that
Speaker 1: are very time sensitive, so you have to have that
Speaker 1: kind of stuff built into your algorithm, right right, or
Speaker 1: in other cases, you know, records of dates of birth
Speaker 1: or dates of medical surgery or all kinds of things. Yeah,
Speaker 1: so many different applications, to the point where there were
Speaker 1: even technologies that you wouldn't imagine would ever need to
Speaker 1: know what year it is that had the stuff built
Speaker 1: into it. And here's the problem when you have two
Speaker 1: digits for your year. See the computer programming getting started
Speaker 1: in the nineteen fifties and nineteen sixties, they figured, hey,
Speaker 1: we've got practically half a century before we have to
Speaker 1: worry about two digits, it's turning into zero zero. Clearly,
Speaker 1: we're gonna totally fix this later. And computer memory right
Speaker 1: now is incredibly expensive, so let's let's let's be really
Speaker 1: conservative and just use two digits for the year, and
Speaker 1: we'll be fine until these other problems work themselves out.
Speaker 1: Oh and and I mean computer memory was so precious
Speaker 1: and saving, especially across the course of for example, an
Speaker 1: entire spreadsheet full of interest calculations. Saving two digits per
Speaker 1: year was big. So so just by doing a month, month, day, day, year, year,
Speaker 1: you know, just just the two digits each, you could
Speaker 1: save a huge time and hassle for yourself at the
Speaker 1: at that current moment, right right, because I mean, you know,
Speaker 1: think about just a few years ago how expensive it
Speaker 1: was to buy, say a terrabyte for a hard drive,
Speaker 1: compared to today, now it's much more affordable. Well, you know,
Speaker 1: as opposed to when I was a kid, when a
Speaker 1: terabyte was a completely unimaginable amount of information. Yeah, when
Speaker 1: I was a kid, I couldn't imagine ever filling up
Speaker 1: a megabyte of space. So you know, as time has
Speaker 1: gone on, memory has become less and less of a
Speaker 1: problem in the sense that we were able to make
Speaker 1: more of it more affordably. Back then very expensive and
Speaker 1: precious stuff that you only had so much to work with,
Speaker 1: and it was expensive to use. So cutting it down
Speaker 1: to two digits made sense at the time. But the
Speaker 1: problem was that when you roll over from nine to
Speaker 1: two thousand in the computer terms, that goes from ninety
Speaker 1: nine to zero zero, which meant that people weren't really
Speaker 1: sure what was going to happen. Right, would the computer
Speaker 1: think that it was all of a sudden Would that
Speaker 1: completely bark all of your calculations for for example, interest rates, yeah,
Speaker 1: or the the age of a person. So your example,
Speaker 1: if it's figuring out the age by subtracting the current
Speaker 1: date from your date of birth or the date of
Speaker 1: birth from the current data, should say, so, let's say
Speaker 1: it's ninety nine and you were born in ninety, then
Speaker 1: that's pretty easy. It's years old. Okay, got it. But
Speaker 1: then let's say it goes zero zero and you were
Speaker 1: born in ninety. So at zero zero minus ninety suddenly
Speaker 1: like oh um am I getting negative numbers because now
Speaker 1: a negative age that doesn't make sense. And so you
Speaker 1: can have all sorts of computer problems ranging from the
Speaker 1: financial industry to health to all pretty much everything that
Speaker 1: had any sort of code in it that included the year,
Speaker 1: which extends to things like like elevators that had microchips. Yes, yeah, elevators.
Speaker 1: I mean that's pretty that that was a real concern.
Speaker 1: People are like, I do not want to be in
Speaker 1: an elevator on New Year's Eve because you don't know
Speaker 1: if that thing is going to make it to the floor.
Speaker 1: You want by right, And I mean, and of course,
Speaker 1: you know, they weren't afraid that the elevator was going
Speaker 1: to slow down to a rate, to a negative motion
Speaker 1: rate or anything like that, but they were afraid that
Speaker 1: the code and the microchip crashing would I don't know,
Speaker 1: cause a fire and make the elevator drop or just
Speaker 1: or just stop or just stop entirely and refused to open.
Speaker 1: People had a lot of just uncertainty about exactly what
Speaker 1: was going to happen to code and whether or not
Speaker 1: it was going to cry as an entire system when
Speaker 1: this this year changed, over right, And so this this
Speaker 1: fear started to kind of rear its head in the
Speaker 1: ninety nineties. Uh, it really reached a fever pitch in nine.
Speaker 1: That was when I think the general public became really
Speaker 1: aware of it before that due to media complete over saturation.
Speaker 1: Yeah yeah, I got a little, a little crazy, be
Speaker 1: a lot crazy, depending about where you lived. In the
Speaker 1: United States, it's certainly became crazy. So you had you
Speaker 1: had computer scientists who were and programmers who were saying
Speaker 1: earlier than this, like, hey, guys, maybe we should fix
Speaker 1: this is you know, this is a problem and instead
Speaker 1: of perpetuating it across multiple industries at infinitum, maybe we
Speaker 1: should address it and that way, just establish a new
Speaker 1: rule going forward. Now, computer memory not such a big deal. Now,
Speaker 1: why don't we Why don't we fix it before we
Speaker 1: get Hello? So any what is this thing on? Hello?
Speaker 1: And the problem was that a lot of people didn't
Speaker 1: listen until it started getting closer to two thousand and
Speaker 1: people began to really worry about the possibility that this
Speaker 1: could bring about, if not some sort of technological armageddon,
Speaker 1: at least a lot of glitches and problems that could
Speaker 1: have been avoided. So then they had to say, well,
Speaker 1: what are we going to do about it? The obvious
Speaker 1: solution was also the most time consuming and expensive one,
Speaker 1: which was the manually go through and start updating code
Speaker 1: and changing it so that it's a four digit year
Speaker 1: instead of a two digit year and uh and then
Speaker 1: thus increasing the usefulness till at least nine thou right, Yeah,
Speaker 1: I mean, I mean, you know, the alternate there's to
Speaker 1: recode just so that programs would recognize that zero zero
Speaker 1: probably meant two thousands instead of nineteen hundred. But that's
Speaker 1: a less effective solution. And b I mean, you just
Speaker 1: need to change it over at the next turn of
Speaker 1: the century, not that probably those same programs were going
Speaker 1: to be in use, but you never know, right. The
Speaker 1: thing is that, you know, you have these legacy systems
Speaker 1: that certain companies rely on that were originally programmed, you know,
Speaker 1: thirty forty years ago, and you know they continue to
Speaker 1: rely on them because they do exactly what the company
Speaker 1: needs them to do, right And Okay, so so either way,
Speaker 1: these changes might have to be entered by hand thousands
Speaker 1: of times or hundreds of thousands of times in a
Speaker 1: single program um and each change then has to be
Speaker 1: tested against errors. Of course, eventually code was developed to
Speaker 1: help automate the process, but you know, I mean it
Speaker 1: was just a big undertaking. Yeah. You might remember if
Speaker 1: you watch the documentary Office Space that the characters at
Speaker 1: in a tech the company and office space were they
Speaker 1: that was their job. They went into other companies and
Speaker 1: helped update their code to meet the Y two K issue,
Speaker 1: which kind of raises another question, which is what was
Speaker 1: this company going to do after the year two thousand?
Speaker 1: But at any rate, that was actually a very real concern.
Speaker 1: I mean, spaces is a great parody of all of that,
Speaker 1: kind of sure, but but there was a concern that,
Speaker 1: you know, with with all of these extra per gramming
Speaker 1: jobs that were going to be created, that that businesses
Speaker 1: would crash and burn. And some of them did. I mean,
Speaker 1: most of them just moved on to other things and
Speaker 1: found freedom and not having to do this incredibly tedious
Speaker 1: work anymore. Right, And then there was a lot of
Speaker 1: other crashing and burning in the tech industry for unrelated reasons.
Speaker 1: That was the whole dot com bubble burst. But it
Speaker 1: didn't have anything to do with Y two K directly. So, uh,
Speaker 1: here's the other problem is that a lot of these
Speaker 1: programs didn't recognize even if even if two thousand was
Speaker 1: going to be fine, even if they could recognize the
Speaker 1: five that was two thousand was a four digit year,
Speaker 1: they didn't necessarily recognize that two thousand was going to
Speaker 1: be a leap year. And here's the reason why. So
Speaker 1: leap years actually follow an algorithm, a set of rules, obviously,
Speaker 1: So the the basic rule is that for every four years,
Speaker 1: you added an extra day, a leap day, at the
Speaker 1: end of February to balance out the calendar year with
Speaker 1: the solar year. Because the solar year is close to
Speaker 1: three sixty five point to five days, not quite point
Speaker 1: to five, almost point to five, which is important. Yeah,
Speaker 1: So if you stretch out over an incredibly long time
Speaker 1: for us humans, let's say a few centuries, your calendars
Speaker 1: will start to become misaligned because it's not quite three
Speaker 1: sixty five point to five days in the solar year.
Speaker 1: So that means that occasionally you have to ignore the
Speaker 1: leap year. And the way the rule goes is that
Speaker 1: if the let's see if I can get this right,
Speaker 1: if the century is divisible by one hundred but not
Speaker 1: by four hundred, it would not be a leap year.
Speaker 1: So if it's divisible by both one hundred and four hundred,
Speaker 1: it's a leap here. So in other words, seventeen hundred,
Speaker 1: eighteen hundred, and nineteen hundred were not leap years. Was
Speaker 1: because sixteen hundred is divisible by four hundred. Two thousand
Speaker 1: also divisible by four hundred, so it should be a
Speaker 1: leap here. However, because you got just have zero zero
Speaker 1: as the digits. If the computer thinks it's nineteen hundred,
Speaker 1: the computers also knows the rule that nineteen hundred is
Speaker 1: not a leap year, so it says, hey, this, this
Speaker 1: big zero kind of number is totally not a leap year, right,
Speaker 1: So it's only three d sixty five days, not three
Speaker 1: hundred three, And we we don't have a f every
Speaker 1: twenty nine this year, is what I would say. But
Speaker 1: there was totally a fevery twenty nine here, which meant
Speaker 1: that other calculations would get thrown off because it wouldn't
Speaker 1: take that leap day into account. So all these calendar
Speaker 1: applications weren't also had to be corrected. So suddenly people
Speaker 1: were like, oh boy, this is a big old mess here.
Speaker 1: We've got to fix this and uh and so so
Speaker 1: a lot of time and effort and attention was directed
Speaker 1: to this. And there was a third problem as well.
Speaker 1: Wasn't there having to do with all of the nines.
Speaker 1: Oh yeah, Oh, I totally forgot about that. I'm glad
Speaker 1: you brought that up. Yes, So, okay, in the old days,
Speaker 1: children gather around this, gather around the digital fireplace. You know,
Speaker 1: if Netflix still has that digital fireplace. Stared started up
Speaker 1: back in the old days. Children. Sometimes programmers, in order
Speaker 1: to designate the end of a program, would just type
Speaker 1: out a string of nines. It was essentially just the
Speaker 1: code to say, this is where stuff ends, y'all. Uh
Speaker 1: so had a date in Exeptember nine that if you
Speaker 1: were to write it, I would be like nine. You know,
Speaker 1: a lot of nines. And the worry was that certain
Speaker 1: programs which would see that as meaning this is where
Speaker 1: stuff stops and would stop working. So you had a
Speaker 1: lot of digit problems here. So some of this you
Speaker 1: could count on, you know, just a a kind of
Speaker 1: a jerry rigged system of this is how I'm going
Speaker 1: to designate this is the end of a program, And
Speaker 1: it was just kind of arbitrarily chosen that would be stuff.
Speaker 1: Some of it was more of a practical consideration, the
Speaker 1: idea of we need to save time and money, so
Speaker 1: therefore we're shortening this year to two digits. In either case,
Speaker 1: it ended up meaning lots and lots of work for
Speaker 1: people in the late nineteen nineties, and you got a
Speaker 1: lot of attention. I mean, there were there were things
Speaker 1: like industries that were already taking advantage of the time
Speaker 1: in the nineties to address this. The software industry was
Speaker 1: way ahead of the game. Oh yeah, yeah, I mean
Speaker 1: back by you know, I think few people were on
Speaker 1: top of it. Certainly by a lot of people had
Speaker 1: already kind of corrected the problem, right, So the software
Speaker 1: that was being produced from that point going forward had
Speaker 1: already addressed it. Now, granted, there was still software that
Speaker 1: was out previously that had this old code in it,
Speaker 1: but the new code coming out of the software industry
Speaker 1: had had adjusted for this kind of problem. But there
Speaker 1: were other industries that were lagging behind. And in fact,
Speaker 1: according to one study, uh the cap Gemini America consulting
Speaker 1: firm did a study. They found that the state and
Speaker 1: federal government systems were the furthest behind. And when you
Speaker 1: think of all the information that state governments and federal
Speaker 1: government here in the United States requires to operate, things
Speaker 1: like taxes that are dependent upon or infrastructure. Infrastructure, yeah,
Speaker 1: your water systems, all sorts of stuff that rely on
Speaker 1: can puter systems that are run by spy satellites, all
Speaker 1: of the stuff, communications, everything. I mean, there's entire industries
Speaker 1: that are dependent either completely or in part on state
Speaker 1: and federal systems. All of those were at risk because
Speaker 1: they were the first behind. They had the least amount
Speaker 1: of progress on addressing the Y two K problem. Uh,
Speaker 1: such a huge deal that the president at the time
Speaker 1: it was Bill Clinton, assigned the two thousand Information and
Speaker 1: Readiness Disclosure Act into law, and that was designed to
Speaker 1: create a collaborative environment among multiple industries. So that is
Speaker 1: one industry developed the best practices and tools to address
Speaker 1: the Y two K problem, it would be there was
Speaker 1: an incentive to share the information across other industries so
Speaker 1: that we didn't. It's not a competition, it's it's hey,
Speaker 1: let's all get this done together. Kind of like I
Speaker 1: would like my stuff to continue not being on fire.
Speaker 1: How about I give this information to you guys, and
Speaker 1: maybe that will decrease the chance that my stuff will
Speaker 1: be on fire. In two thousand and that was that
Speaker 1: was a big motivator. As it turns out, helped a lot.
Speaker 1: There were other areas of the world that we're also
Speaker 1: being very responsive to this European Commission issued a report
Speaker 1: about Y two K to the European Union member countries
Speaker 1: that all kind of got them. On the same page,
Speaker 1: the British government announced that the British military would be
Speaker 1: on hand to assist local police forces in the event
Speaker 1: of emergency services breaking down as a result of the
Speaker 1: Y two K problem. And there there was so much hype.
Speaker 1: I mean, I mean, yeah, well, we'll talk more about
Speaker 1: hype in a second. The United Nations held a conference
Speaker 1: on it. They were trying to facilitate more sharing of information,
Speaker 1: particularly but you know, that's that's cool, that's that's not hype,
Speaker 1: that's preparedness, right. Well, they were particularly worried about a
Speaker 1: lot of regions in Asia that were there were at
Speaker 1: least thought of to be behind the curve on this
Speaker 1: on addressing the HIT two K problem. So they wanted
Speaker 1: to make sure that everyone in the world had an
Speaker 1: equal chance of catching up, so that they could minimize
Speaker 1: any effects that the Y two K problem. They have
Speaker 1: not keep in mind, this is still at a time
Speaker 1: where no one was really sure what was going to happen,
Speaker 1: at least not on a global scale. There were some
Speaker 1: people were saying like, well, you know, this system over
Speaker 1: here is probably gonna be okay, because it's not really critical,
Speaker 1: and even even if it were, you know, it would
Speaker 1: just be something that we could adjust by writing a
Speaker 1: couple of extra lines of code to correct that problem
Speaker 1: other systems. People were like, I don't know if that
Speaker 1: airplane will stay in the air. I mean, that wasn't
Speaker 1: legitimate fear some people. I don't know, Okay, maybe fear
Speaker 1: that people absolutely and and you know, on a on
Speaker 1: a person to person basis, the amount of panic varied
Speaker 1: um and problem they were depending on how much media
Speaker 1: they had consumed about it, and excitable they were to
Speaker 1: begin with. I want to say, towards the end of
Speaker 1: a lot of the media coverage lent leaned more towards
Speaker 1: the satirical and the the kind of jokey world's gonna
Speaker 1: end next month kind of stuff, less less of the
Speaker 1: actual fearmonger ring style, and more of the no one's
Speaker 1: really sure, but you know, the worst case scenario could
Speaker 1: be that kind of thing. So it wasn't at least
Speaker 1: as as bad as you know, next month, everything you
Speaker 1: know will be different because nothing's going to work, and
Speaker 1: you know, start building your bomb shelter now, Um, you know,
Speaker 1: there weren't a whole lot of serious reports that were
Speaker 1: coming out like that, and I'm sure the Onion had
Speaker 1: a lot of fun with it. We'll hear more about
Speaker 1: the Y two K problem and why it wasn't as
Speaker 1: big a calamity as we were originally expecting, but first,
Speaker 1: let's take a quick break. All right, So we're back now.
Speaker 1: The clock is ticking down. I know you've been waiting,
Speaker 1: waiting all episode to learn what would happen about to
Speaker 1: turn to two thousand? What half? Okay, so technically we're
Speaker 1: all still here, so I guess we can draw some
Speaker 1: conclusions right off the bat. And and and I mean,
Speaker 1: this event is in our relatively recent path, and it
Speaker 1: was really only years ago. And most of you guys
Speaker 1: are probably remembering this, some of you, and some of
Speaker 1: some of you folks who are in maybe middle school
Speaker 1: or whatever. Maybe this is all new to you, in
Speaker 1: which case, hey, welcome to the ridiculous panics that the
Speaker 1: rest of the world went through before you were born.
Speaker 1: Your parents were silly. Yeah, So, as it turns out,
Speaker 1: a lot of the work that was being done leading
Speaker 1: up to two thousand was successful, I mean, and there
Speaker 1: was a lot of work. It was uh. One estimate
Speaker 1: said that globally the world spent about three hundred billion
Speaker 1: dollars that's billion with a B to address the Y
Speaker 1: two K problem, and about just a little less than
Speaker 1: half of that was spent in the United States alone
Speaker 1: to address this issue. And that ranged from everything from
Speaker 1: wide computer networks to like we were saying, microprocessors that
Speaker 1: control things like microwaves, and you know, really in that case,
Speaker 1: it was more of testing it to see, you know,
Speaker 1: if you were to digitally alter the clock of the sheen,
Speaker 1: would it continue to operate properly that kind of stuff, right,
Speaker 1: And and in the most most cases things things were
Speaker 1: absolutely fine. And and people people kind of knew that,
Speaker 1: I mean that there was a little bit of this
Speaker 1: media frenzy, but um but a p Poles indicated that
Speaker 1: Americans expected minor problems at worst, um but that some
Speaker 1: thirty percent had planned stockpiles just in case. Yeah, yeah,
Speaker 1: that the food money, that kind of that was. Yeah,
Speaker 1: they weren't necessarily creating an armed militia, although there was
Speaker 1: some of that going on too at the time. But
Speaker 1: you know, it's it's one of those things where I
Speaker 1: think a lot of people were jokingly saying like, yeah,
Speaker 1: I mean, everything's gonna be fine, nothing's gonna be a problem.
Speaker 1: But then like, you know, but just in case, I
Speaker 1: think I'm gonna take it easy this year, uh or
Speaker 1: just that day specifically, we have New Year's Eve to
Speaker 1: two thousand to make sure that, you know, let's let's
Speaker 1: not let's not put ourselves in danger unnecessarily. But nothing's
Speaker 1: going to happen, you know. Cautious optimism is probably how
Speaker 1: I would describe it. Yeah, and basically, none of those
Speaker 1: big doomsayer kind of things, the worldwide power failures, the
Speaker 1: total breakdown of transportation infrastructure, that planes falling out of
Speaker 1: the sky, none, none of that. None of that happened. Now,
Speaker 1: to be fair, one reason a lot of that may
Speaker 1: not have happened is because so much work was done
Speaker 1: addressing the problem. Right. I still don't think that every
Speaker 1: computer in the world would have simultaneously caught on fire
Speaker 1: and started eating your face. No, that's the likelihood of
Speaker 1: that was very low, pretty low. I mean, some other
Speaker 1: spooky stuff would have had to have been going, but
Speaker 1: they we're talking some paranormal activity stuff at that point.
Speaker 1: But no, I think, you know, here's here's The problem
Speaker 1: with assessing how Y two K worked out because a
Speaker 1: lot of people said, oh, it was a lot of
Speaker 1: worry over nothing, nothing really big happened. But part of
Speaker 1: that was because so much work had been done to
Speaker 1: address the issue on a on a code level, to
Speaker 1: make sure that the code in some very critical systems
Speaker 1: was updated to not have this problem. So you could
Speaker 1: argue that the reason why there wasn't a problem was
Speaker 1: because we caused such a fuss in the first place. Sure,
Speaker 1: it's also possible that if we had never done anything
Speaker 1: and someone in two thousand said, hey, guys, I just
Speaker 1: thought of something that we probably should have thought about before.
Speaker 1: That everything's fine now, but you know what could have
Speaker 1: happened was blah blah blah. Sure that might have happened
Speaker 1: to the clue ending Yeah, yeah, like this is that's
Speaker 1: what really happened. But here's what could have happened. That's
Speaker 1: kind of the opposite of the clue endings. But yes, um, yeah,
Speaker 1: so the the you know, it's hard, it's impossible to
Speaker 1: say in hindsight, right, how I would have turned out
Speaker 1: differently had nothing happened. I imagine that we would have
Speaker 1: seen a lot of other glitches and systems that would
Speaker 1: have been time consuming to fix. And we did see
Speaker 1: some glitches, right, It wasn't like everything went off without
Speaker 1: a hitch. Right. Well, okay, most of the glitches were
Speaker 1: kind of preemptive. Some some large chemical plants and oil
Speaker 1: pipelines were shut down preemptively during the transition and and rebooted.
Speaker 1: UM Service was suspended on like major freight railroads and
Speaker 1: Amtrak on New Year's Eve for for a final round
Speaker 1: of equipment and signal checks. Um. Yeah, uh, you know,
Speaker 1: the workload on programmers over the past couple of years
Speaker 1: had had been increased like twenty six in order to
Speaker 1: solve the problems. So that was an effect anyway. Uh, yeah,
Speaker 1: I mean there there were you know, some of the
Speaker 1: some of the problems that came up were very comical
Speaker 1: in nature. Yeah, there were, I mean, okay, there were legitimate,
Speaker 1: like a few hundred reports of errors amongst small businesses,
Speaker 1: but needs most most of them were resolved in a
Speaker 1: matter of hours after they had been reported. Um. There
Speaker 1: was the temporary shutdown of a Defense Department ground station
Speaker 1: that that processed info from a from a satellite from
Speaker 1: a spy satellite. UM. But it didn't have any major consequences. Yeah,
Speaker 1: I mean there were there were a couple of really
Speaker 1: good ones. Um for okay. So, so this was when
Speaker 1: uh al Gore was the vice president. This is my
Speaker 1: favorite of the White UK problems. By the way, um
Speaker 1: for for a minute, his town hall web page informed
Speaker 1: visitors that it was January three, uh ninete if they
Speaker 1: arrived via netscape and January three, nineteen thousand, I'm sorry.
Speaker 1: If they were coming in via Futurama. We know that
Speaker 1: by that time al Gore's head is in a jar.
Speaker 1: So maybe it was accurate. It could be. It could
Speaker 1: have been like this was a glimpse into the Futurama future.
Speaker 1: Um um, there was a there was a glitch in
Speaker 1: the New York Times. Oh I love this one, dude, No,
Speaker 1: this one's my favorite. I retract by earlier statement. This
Speaker 1: one's my favorite. They can both be your favorite. Um okay. So,
Speaker 1: so there's a telephone service that would read an automated
Speaker 1: selection of the New York Times and other newspapers to
Speaker 1: um New Yorkers with with vision problems, and um it
Speaker 1: informed clients that they would be hearing the January three
Speaker 1: hundred issues. So before we start recording. I said, I
Speaker 1: could just mention the top headline dirigible races reach inevitable
Speaker 1: draw for you're running. I think, I I want, I
Speaker 1: kind of want that alternate history, right were you? What
Speaker 1: would have been amazing as if it had actually read
Speaker 1: the headlines from January three d at that point. Now
Speaker 1: that's not exactly that's not what happened. It just had
Speaker 1: the date wrong. On the date part. The actual content
Speaker 1: was the same, was the one for January third, two thousand.
Speaker 1: It's not like the computer glitched and went and looked
Speaker 1: up some microfiche brought it back and read it out.
Speaker 1: I wish that had happened though. That would have been
Speaker 1: so awesome. That would have been delightful. UM, I mean,
Speaker 1: like other stuff. Uh, there was some some legal battles
Speaker 1: that arose over all of this. Xerox, Nike, Unitis, and
Speaker 1: a whole bunch of other companies were a few major
Speaker 1: other companies. Um UH sued their insurers for reimbursement for
Speaker 1: having to have spent hundreds of millions of dollars on
Speaker 1: these repairs. Um citing language from nineteenth century business contracts
Speaker 1: wherein insurers had to repay ship owners for money spent
Speaker 1: trying to prevent a ship from sinking. Yeah, interesting sighting
Speaker 1: of a precedent. Yeah, that didn't work out so well. Um,
Speaker 1: suits generally generally settled on the side of the insurance
Speaker 1: come benize because I think arguing that because nothing bad happened,
Speaker 1: then we shouldn't have been forced to prevent something bad
Speaker 1: from happening is a weird argument, because if nothing bad happened,
Speaker 1: that's possibly proof that the thing you had to do
Speaker 1: worked oh well. And even I mean even if you
Speaker 1: if you spend that money preventing a ship from sinking
Speaker 1: or preventing a computer from crashing. Um. You know, in
Speaker 1: this particular case, the companies had seen the ship sinking
Speaker 1: several years before they actually informed the insurance company that
Speaker 1: it was an issue, and so in that case, the
Speaker 1: courts were like, you knew about this beforehand. This interesting,
Speaker 1: this is stuff that you had to take care of.
Speaker 1: And um, I see there were some other like practical
Speaker 1: outcomes that were, you know, just the way people had
Speaker 1: reacted to Y two K and started stockpiling stuff. That
Speaker 1: meant that once the new year happened and society did
Speaker 1: not crumble, a lot a lot of people returned to
Speaker 1: space heaters, um like so many that that SEARS started
Speaker 1: incurring a titter not in but um but charging stocking
Speaker 1: fee because people so many people were worried that the
Speaker 1: infrastructure would be gone, that they wouldn't have gas or electricity,
Speaker 1: you know. And then they once once that those problems
Speaker 1: went away, like once two thousand came around and everything
Speaker 1: was fine, then they're a, well, I don't really need
Speaker 1: this anymore. Charity groups collected a lot of extra cand
Speaker 1: goods that year. Uh not so many people traveled by
Speaker 1: airplane on New Year's Day that year, right, I mean
Speaker 1: not that many people travel on New Year's Day to
Speaker 1: begin with, but even spetistically fewer. Yeah, there were some
Speaker 1: of those people who were worried about that whole airplane
Speaker 1: dropping out of the sky thing. And here's the thing
Speaker 1: is that while this YE two K problem sounds like
Speaker 1: it's like, well, yeah, sure it happened once, they'll never
Speaker 1: happen again. We've got more to say about Y two K,
Speaker 1: but that's gonna have to wait till after this break alright. Alright,
Speaker 1: So there there are a bunch there. There are like
Speaker 1: many much multiple other problems, like like the Y t
Speaker 1: K problem, they're all time dependent, and they're all code dependent. However,
Speaker 1: the the year in which each one would hit its
Speaker 1: big old problem is different from one example to another,
Speaker 1: mostly because engineers have a wicked sense of humor. Well
Speaker 1: I'm not sure, okay, So so I don't I don't code.
Speaker 1: I'm not a programmer. I I've never used any kind
Speaker 1: of back end sort of thing. I know how to
Speaker 1: make things bold and h ham l on my own.
Speaker 1: But that's that's about it. Um. But so so apparently
Speaker 1: in various programs, UM, the beginning of time starts on
Speaker 1: various dates. Yeah, the beginning of time tends to be
Speaker 1: the date that whatever was created was put into action,
Speaker 1: although not all of all the time. So, and it
Speaker 1: can depend on the numeracle system that the coding is using. UM.
Speaker 1: I know, for for IBM PCs, the beginning of time
Speaker 1: is January on up. And uh, the time itself goes
Speaker 1: up in seconds. So the second is the base integer
Speaker 1: for this whole thing, um, And it's a thirty two
Speaker 1: bit integer. So that means that if you if you
Speaker 1: do the math, and you're thinking, okay, it's a thirty
Speaker 1: two bit integer. Each second is another increment. So every
Speaker 1: second that passes goes up another one. If you're limited
Speaker 1: to thirty two bits and you're starting days January one,
Speaker 1: nineteen eighty, you can extend that out and you see
Speaker 1: that in two thousand one sixteen you have hit the
Speaker 1: limit of of the integers you have. You are no
Speaker 1: longer able to go up without rolling over. It's kind
Speaker 1: of like those old alright, gather around that digital fireplace,
Speaker 1: children and the old days we had digital uh like
Speaker 1: pinball machines, and once you hit a high score at
Speaker 1: a certain level, it would turn over, meaning it would
Speaker 1: go back to I actually did that on the Star
Speaker 1: Trek one. I'll tell you about some time. Anyway. I was, Yeah,
Speaker 1: I had seventeen free replays by the end of that.
Speaker 1: I ended up leaving because I couldn't keep playing all day.
Speaker 1: I was in college at the time. Money will spend
Speaker 1: Mom and Dad. Anyway, two thousand, one h and sixteen
Speaker 1: is when those integers will reach the limit, meaning that,
Speaker 1: UH don't know what's going to happen after that. It's
Speaker 1: not gonna be able to make these these time dependent
Speaker 1: calculations accurately anymore, because it won't be able to track
Speaker 1: time in a in a way that makes sense to
Speaker 1: the computer anymore. So you would think, oh, well, clearly,
Speaker 1: all right, so we've got the y two k problem
Speaker 1: and the two thousand, one hundred sixteen problem with IBM PCs.
Speaker 1: But after that we're okay, right, well uh well, so
Speaker 1: so Windows NT sets the beginning of time as January one,
Speaker 1: six one, So apparently they were thinking, like, okay, Shakespeare
Speaker 1: would totally use Windows INT just before, you know, shortly
Speaker 1: before he dies, so clearly he would have written, you know,
Speaker 1: some of his greatest plays using a machine using Windows NT.
Speaker 1: So let's start the I have no idea why they
Speaker 1: chose January. Yeah, and okay, so it uses a sixty
Speaker 1: four bit integer to track time, so way more integers
Speaker 1: than you know, twice as much as the thirty two
Speaker 1: bit intager that IBMPC did, and furthermore uses a hundred
Speaker 1: nanoseconds as its increment. So so it's problem is a
Speaker 1: yeour right, So it's here's the thing. It covers a
Speaker 1: much greater span of time, right because it starts in
Speaker 1: sixt one and it won't end until four, so that's later.
Speaker 1: But because of that hundred dano second problem that eats
Speaker 1: up those managers pretty quickly. If it had done it
Speaker 1: as a second intager, it would extend much further out.
Speaker 1: But hey, good good news for Apple users. According to Apple,
Speaker 1: um mac is okay out to the year. Uh yeah,
Speaker 1: um so, I mean not that it matters, because you're
Speaker 1: gonna update all your stuff every year. Anyway, you have
Speaker 1: Apple fanboys. I'm saying that I'll love I'm not entirely
Speaker 1: positive that you are. Really. My wife has a iPhone.
Speaker 1: I I love her. I've got a Mac. I mean,
Speaker 1: I'm granted my Mac. It's like eight years old. At
Speaker 1: this point. It might actually be an Apple computer, not
Speaker 1: a Mac. They might have devolved. But anyway, yes, at
Speaker 1: any rate, all of these problems are going to be
Speaker 1: a little bit easier to fix than the Y two
Speaker 1: K problem, right, And and it's one of those things
Speaker 1: where the Y two K problem that was something that
Speaker 1: was so uh grounded in the very basic code that
Speaker 1: so many different UH systems were using. That's probably the
Speaker 1: scope of it was enormous, right, And we didn't have
Speaker 1: the tools available than that we do today for for
Speaker 1: going in and addressing propagating things. Only that, but we've
Speaker 1: got a greater time scale for all of these problems.
Speaker 1: It's not something that's you know, five years away. Although
Speaker 1: we can't just have the attitude of oh well that's
Speaker 1: you know, that's like twenty more years. We don't need
Speaker 1: to worry about that. No, we should definitely take the
Speaker 1: steps to address these issues. So, yes, it is one
Speaker 1: of those things where we see it over and over again.
Speaker 1: Does it mean that we are done that? No one
Speaker 1: is ever going to make this kind of mistake just
Speaker 1: for the sake of convenience or or efficiency or economics. Uh,
Speaker 1: We're never gonna make a plain old mistake. No, we're human.
Speaker 1: We make mistakes. That's kind of kind of thing. They're
Speaker 1: they're warm and fuzzy. It's us. Yeah, well you know
Speaker 1: we're good at that and making mistakes. I am great.
Speaker 1: I'm like I learned from my mistakes. I can repeat
Speaker 1: them almost exactly. So, um, yeah, it's something that will
Speaker 1: price see also pop up. And of course those people
Speaker 1: will eventually be ridiculed like do don't you remember why
Speaker 1: I do? K? And uh, you know, we'll just we'll
Speaker 1: relive this drama multiple times. But hey, some of these
Speaker 1: are problems that are so far in the future that
Speaker 1: it's our descendants that they are gonna be worried about
Speaker 1: them unless we find some digital immortality or something. Yeah.
Speaker 1: See there you go say, I think that what all
Speaker 1: of this is not taking into consideration is that we
Speaker 1: are clearly going to hit the singularity in years. Yes,
Speaker 1: you know, we're getting We're rapidly approaching what Hurtswil said
Speaker 1: would be the singularity. And I'm a little skeptical right now,
Speaker 1: but hey, it could be proven wrong. But you know,
Speaker 1: when we see problems like this rise up, it does
Speaker 1: make you wonder about that singularity and think maybe that
Speaker 1: maybe that would only be really super awesome for a
Speaker 1: very relatively short time until our code ran out. I
Speaker 1: hope you guys enjoyed that classic episode of tech Stuff
Speaker 1: and you learned a little bit about Y two K,
Speaker 1: and you wonder, you know, are we going to see
Speaker 1: this happen again, because that's a fear and uh, it
Speaker 1: really does show that sometimes a short cut is not
Speaker 1: the best way to go about things. Sometimes it pays
Speaker 1: off to, you know, take the long route. If you
Speaker 1: have any suggestions for future episodes of tech Stuff, get
Speaker 1: in touch with me and let me know what those
Speaker 1: might be. It can be a technology, it could be
Speaker 1: a company, it could be a trend in tech. The
Speaker 1: way to do that is to go over to Twitter
Speaker 1: and send me a message. The handle that you should
Speaker 1: use to to contact me is text stuff hs W
Speaker 1: and I'll talk to you again really soon. Yeah. Text
Speaker 1: Stuff is an I heart Radio production. For more podcasts
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