What's going on? I am Greg Salsby enjoyed today by Jim Sonnes of FanDuel. We're going to talk about the players whose stock is rising after an impressive week number seven. What's going on Jim? I'm all good Greg. It was a pretty fun week seven slated games. The problem is that a couple of these guys on this list are a result of injuries. That's never fun. Talk about guys whose stock is up as a result of that. So a little bit of a bummer, but overall still some fun football on Sunday for sure. It was a really fun Sunday in week seven capped off by a phenomenal game between the Seattle Seahawks and the Arizona Cardinals. It's kind of sad in that fantasy owners and experts were calling for Chase Edmonds since before week one, back during draft season, he was everybody's favorite stash because as much as people like Kenny and Drake, they love the idea of Chase Edmonds more. Chase Edmonds time has come unfortunately due to an injury to Kenny and Drake and the Cardinals are on a buy. So maybe he'll get healthy, but Chase Edmonds looked the part last night. It's what we've been waiting for all season long. You have 14 and a half fangal points and if this injury to Drake is as serious as it looked, Chase Edmonds is going to be the top add on waiver wires and season long leagues and certainly someone in just a couple of weeks in DFS were going to be targeted. Yeah, because if we get Chase Edmonds with no Kenny and Drake, he's kind of the prototype of what I want out of a running back specifically because he gets targets. Like it's not hard to figure my prototype. That's my kind of running back. I like a DFS. I want guys who will get targets and there is no concern about that with Chase Edmonds. He actually has 14% of the Cardinals targets this year, despite playing limited snaps. So if we get him out there for 70% of the snaps, that's going to be a really hefty number, which will give him a great floor and access to a tremendous ceiling. So Chase Edmonds, he's been great so far, could get more early down work. And I think that's more important in Arizona than a lot of places because Cliff Kingsbury has done a great job of scheming up their ground game. We doesn't get a lot of credit for that. It's mostly focused on Kyler Murray, but their ground game is creative and fun to watch. And I think that Edmonds can take advantage of that as he has shown on his limited attempts so far this year. So you give me efficient running plus targets in a good offense. I'm going to take that every time. So Chase Edmonds, the kind of running back I want, I would love for Kenny and Drake to be healthy because we want to see guys like that be on the field, be healthy, work through these injuries. But if he's not able to go, Chase Edmonds will be a guy we talk about on the hurry up in a positive sense from a DFS perspective in the not-so-distant future. The talent's always been there for Chase Edmonds. It's been the opportunity and the injuries now. He's going to step into a major role. Whenever he's out on the field, he makes something happen. Last night, he did just that. And hopefully the injury to Kenny and Drake isn't too serious that both of these guys can excel. Right now, Chase Edmonds looks like a major ad and someone's who stock is clearly rising. Talking about backup running backs in the Sunday night football game, that brings us to the other side of the field where Chris Carson has been having a fantastic season for the Seahawks. And Carlos Hyde was kind of just there. Well, Hyde steps up to the plate now as the primary ball carrier for the Seattle Seahawks. The team that until this year just ran the ball too much. But we're letting Russ cook now. And that's also good for the running game. And let's target as you've always pointed out for the running back behind them. And right now, with Chris Carson potentially out, that means more Carlos Hyde. Yeah, you hit all the points there, Greg. We're all good. We can just move on to the next point because you hit it. We got a running back in an offense led by Russell Wilson, who will get targets like side me up, baby. Again, I'd rather have Chris Carson be healthy. But if we're not going to get Chris Carson healthy, at least we know that Carlos Hyde is going to be the kind of running back we like to target. And the second half when Carson was out, we saw Hyde get 10 of 13 running back carries. He had three out of five targets for running backs. He had four total targets for the game. So what we have here again is a running back in a good offense who will get targets and get a lot of early down work. That's a lot of boxes to check. So again, I'd love for Chris Carson to be healthy because like you said, he's a very usable guy in daily fantasy. He's someone that we have talked about plenty on this show in the past. But if he can't go, I think we have a pretty good idea of the kind of workload Carlos Hyde is going to get. It's going to be good work. And it's not like Carlos Hyde has been dust. Like he played well last year for Houston when he's gotten chances for Seattle this year. He's played pretty well. Looks good on that touchdown run last night. So I do think that Carlos Hyde is someone deserving of our attention. He'd be the kind of running back we want to target. So hopefully Carson's okay. But if he's not, I think we should have a good level of confidence plugging Carlos Hyde into our lineups. Although maybe not nearly as young as Chase Edmonds and not as clearly the guy as Chase Edmonds would be because DJ Dallas and Travis Homer are there in Seattle. Carlos Hyde was the one that took the reins in the second half last night and both catching the ball out of the backfield and running it. He's going to be the man in Seattle. No buy week either this week for the Seahawks. So they're in position to have success. And that means Carlos Hyde, if Chris Carson is out, should be in your lineups this weekend.  And I wasn't sure which direction you were going to go, which rookie quarterback you were going to choose here between Justin Herbert and Joe Burrow, who both had fantastic games this past Sunday. It was Herbert that had over 38 fangirl points for the Chargers in their victory against the Jacksonville Jaguars. Herbert has burst onto the scene. And the crazy thing was, I saw this on Twitter today, would Tyrod Taylor still be the starter if he doesn't have that lung injury? Would they, Anthony Lynn, have put in Justin Herbert because I don't know that he would and Herbert just looks so, so good. And so did Joe Burrow for that matter. The rookie quarterback's having a fantastic season here thus far in 2020. And we finally get to watch two of this Sunday too. So this is going to be a fun little week of games for sure. But Justin Herbert, we know he's been good. I don't need to tell you he's been good. He's been awesome. You can see that with your eyes. I want to talk about how much confidence they have in him in letting him throw. And I think that's the key thing for me because the Chargers have a tendency to be a little bit too run heavy at times. Maybe this is because Austin Neckler's out. They don't want to lean on Joshua Kelly and Justin Jackson's being banged up. Maybe that's the reason. But in Sunday's game, Herbert threw 43 times. That is despite the fact, they were leading by at least one score. They're leading by seven or more points for the entire fourth quarter. So that's really good volume for Justin Herbert. That's great for him because he's been tremendous in that volume. He doesn't need a lot of volume to go off, but it also means that we can have trust in his past catches and stack up Justin Herbert. We can pair him with Keenan Allen, who has a 32% target share of the games he's played with Mike Williams and Justin Herbert. We can go to Hunter Henry if he's healthy because he's had 20% of the targets in those games. That makes me feel really good. I was worried that Herbert would be efficient, but he might not get the volume that we want. The volume has been there. And I think that's a really encouraging thing, especially when you pair it with the efficiency and the fact that Herbert is a good runner as well. So Herbert right now at least is checking every box from a fantasy quarterback perspective. And he might be getting his right guard and his right tackle back pretty soon. Those are two really good players that he's been playing without and it hasn't really mattered. So Herbert has been good, but he might get even a little bit better once those guys get back. I was not as high as everyone on Justin Herbert coming out of the draft because he ran a really weird horizontal offense in Oregon, but he showed that was a product of the offense, not a product of him, but the way he has played so far. So I am okay buying fully into Justin Herbert. He has been tremendous and the chargers know it. I think that's a big thing for us knowing we can expect them to throw the ball a good amount each week. Justin Herbert doesn't look like a rookie out there and that's the best thing you can say for a young quarterback. When you're making the players around you better, well, it's just impressive and the fantasy numbers are going to go up. When players like Jaylen Geithen and Virgil Green are scoring touchdowns on a regular basis, there's something to say about the quarterback and Justin Herbert has proven without Austin Eckler, he could be a dominant force and that's what Herbert is right now, Justin Herbert, somebody we are banking on in the coming weeks in fantasy football. That's it for us here on the Fandal Hurry Up Gym. We appreciate the time. Good luck this week. Same to you, Greg. Looking forward to talking to you once again on Friday to talk about what looks like a pretty fun week eighths late as well. Absolutely. We'll get to week eight tomorrow as Tom Becky will join the program as we'll go over his top stars in it DFS for this upcoming weekend. For Jim Sonnis, I'm Greg Sosman. Thank you so much for watching. Enjoy Monday Night Football tonight and we'll see you back here tomorrow for another edition of the Fandal Hurry Up.


Good afternoon, everyone, and welcome. This is Melissa Armo with a stock solution. I'm here today to review the FI. The FI had a magnificent move today and yesterday and for the last week. Today is only the second day of June, and look how bullish we have started off this month. And it's a summer month. Yesterday I saw the way that we gassed out and held and rallied, and I felt very confident we would proceed with the rally today. I thought we might do it in a gap up. This morning we did it, and instead we had a slight gap down. And even with the slight gap down today, we didn't fall. The market is so bullish. We are almost over the previous level from April 20th, which was 2010-92. And if we don't get over today, it's only because the market closes in 15 minutes, actually, or less than that. But we very well might. We might actually get over before the close. And this is an incredibly bullish move for the market. The market is going to make a brand new all-time high this year soon. And I can't wait till it happens. I've been predicting this for some time. The previous level was last year, actually about a year ago. When we hit up at 213.78, that was the previous high in the spot. It's taken us one solid calendar year now or a little bit more, and we're going to get over this level. I predicted this extremely well. And the way that I did it was based on reading the gap. I read the bearish gaps in the market. I read the bullish gaps in the market. I have a rating system. It's a 26-point rating system that allows me to predict what stock or an ETF is going to do. It can predict anything, that gas, by reading the price movement of the gap in the daily chart. And that's how sales are predicted. And reading all of the bearish gaps that happened in the drop-off at the beginning of the year, I mean, I've got to tell you, everyone thought we were going to fall and break and that we were bearish. A lot of people shorted this market. However, I predicted we would hold. I said we weren't always holding the uptrend. We had never broken the uptrend. You do not reach trends based on moving averages. You don't reach trends based on higher highs and higher lows or lower lows and lower highs. You read the gap. That's how you determine pretty much everything that anything does. So you could be long the market overnight. I'm actually in a call, an option, and I made this call actually several months ago for everyone that was on my list. I called it the market call of the lifetime, call of the lifetime because it was an incredible prediction that I made. And I did it back in February. I forget the exact date that I sent out the email, but it was way down in here. So if anyone did that call, everyone is up, and we're going to hit up over the high this month. I don't know the date, but it's going to happen in June because this activity today and yesterday just confirms to me how bullish we are because we could have pulled all the way back. We could have pulled back to 208. We could have pulled back in here. I didn't want to see us pull back in here. We're not going to do it. Bottom line is, market's going to hit up over the high. I predicted this would happen when many people said we were bearish or we're drop or break or fall, and even the people that didn't say we'd go over the high. This is one of the reasons I trained successfully and have a successful business where I'm teaching people how to train. And it's one of the reasons why people come to me and want to learn how I can see this and how I can make the predictions ahead of time. You can learn how to do this. All you have to do is take my Golden Gap class that teaches you how to predict price movement in stocks and ETFs like this buy. So, great call by me, Melissa Armo with a stock swash. If you'd like more information on the Golden Gap class, email me. It's June 11th and 12th. I am running a Memorial Day special through tomorrow. Tomorrow is the last day. If you want to sign up for the class next weekend and learn how to do everything that I know how to do about making money in the market in Gap, the special runs through tomorrow. That's it. Three months free in the trading room and three free mentoring sessions with me, which is a great deal. Email me at MelissaTheStockSwish.com if you'd like more information and congratulations to everyone that is in this Market Call of the Lifetime. Hennies people paid for the spider option and everyone is up. So congratulations to all of you and thank you for following me. And have a great day.


So the next talk is on the impossibility of tight cryptographic reductions by Christoph Bader Tibor Jagger Young Lee and Sven Sheik and Tibor is going to give the talk. Thanks for staying so long to the last talk. So yeah, I'd like to start this talk with explaining or maybe recapitulating what we mean by tight reductions and cryptographic security proof. So what we usually do when we approve security of a cryptosystem, like for example a digital signature scheme, is that we first describe a security model. For this example here, we have an adversary which receives as input a public key is then allowed to output messages, receives back signatures for these messages and it wins this experiment or breaks the security of the scheme if it is able to output a valid message signature pair. And what we then do in order to prove that a given signature scheme is secure in the sense is that we describe a reduction. And this reduction is an algorithm which takes this adversary, uses it as a subroutine to solve some computational problem which is assumed to be hard. Now we say that the reduction is tight if essentially the running time and the success probability of the reduction are about equal to the success probability and the running time of the adversary. And about equal means here that they should be identical up to a small constant factor. Why is it interesting to consider tight security? So first of all, it's an interesting theoretical question. We want to develop techniques which allow us to and get tight security proofs for given constructions and there are many examples of constructions for which you do not know any tight security proof and then it's interesting to understand the reason. So maybe there are inherent reasons that we cannot overcome. Maybe it's sometimes impossible to get tight security. And the second motivation is more practical. So if you want to instantiate a crypto system in practice, then at some point we have to decide on cryptographic parameters like the size of modularize, size of algebraic groups and so on. And if you want to do this in a theoretically sound way, so in a way which kind of respects the security guarantees that we get from our security reductions, then we have to take the tightness of the reduction into account. And this means basically that if we have a non tight reductions, then we have to choose relatively large parameters. Well, if you have a tight security reductions, then we can choose small or essentially optimal parameters. So there are many examples of tightly secure crypto systems from all different domains of cryptography. So we have digital signatures, IBE, pseudo random functions, key exchange and so on. And in particular, the best paper award of this conference goes to a paper which constructs probability key encryption which is tightly secure. So I guess one can say that tight security is an important research topic in cryptography. And there are also many examples of crypto systems for which we are not able to prove tight security. And then it's of course interesting to understand the reasons why or what is the difference between tightly secure constructions and non tight security constructions and which properties must the crypto system have or not have in order to allow for tight security proof. A similar result in the domain of tightly secure crypto is due to Cora and Cora considered digital signatures in a single user setting. Single user setting means that the attacker receives this input a single public key. And he considered so-called unique signatures where unique signatures means essentially that for each message, there's only one unique signature which is accepted by the verification algorithm. And in the context of Cora's paper, one should always mention the follow up paper by Cacvi and Kils from EuroCrypt 12, which corrects a subtle issue in this work. So what Cora does is he considers this a security experiment for signatures and he essentially shows that if a signature scheme satisfies this property that it has unique signatures, then it is impossible to get a tight security proof for the scheme. More precisely, any security reduction which turns an adversary in the sense into an algorithm which solves a computationally hard problem has to lose a factor of at least one over Q where Q is the number of signatures requested by the adversary. This result is proven as follows. So Cora assumes the existence of a tight reduction and he shows that the existence of such a reduction implies an algorithm called the meter reduction. So what we are doing here is we kind of apply a reduction against a reduction and this meter reduction is able to solve the computational problem on its own, resulting to an adversary. The difficult task for the meter reduction is that it has to simulate all oracles expected from the reduction. So in particular, it has to simulate the adversary. So the key ideas behind Cora's technique is to develop a technique which allows an efficient simulation of the adversary without breaking any cryptographic hardness assumption. And more precisely, what Cora shows is that if a signature scheme has unique signatures, then any reduction, regardless whether it's tight or not, so any reduction implies an algorithm M which solves a computational problem P in about the same running time as the reduction. And with a success probability epsilon M, which is at least the success probability of the reduction minus one over Q, and this basically implies that the success probability of the reduction epsilon R cannot be significantly larger than one over Q. So the reduction loses a factor of Q and this is only part of the story. So what actually shows is that this inequality here holds.  Okay, for Cora's result, this term is actually not very annoying, because if you consider signatures in a single user setting, then we have Q, the number of signature queries polynomial bounded, so it's very small. We have the message space exponentially large. So everything inside this red box here is very close to one. Okay, so basically we get more or less this result here up to a small difference, which is incurred by this last annoying term here. There are some limitations of Cora's technique. The first one is that it's not able to consider any reduction, but it has to consider a restricted class of reductions. So basically he looks at reductions which treat the adversary as a black box by just executing it. And there are only few advanced capabilities of the reduction. So the reduction is allowed to run the adversary several times sequentially. But for instance, it is not allowed to run two copies of the adversary in parallel also. So this is a restriction, but it's not a very bad restriction or a very, very strong limitation, because most reductions that we know in cryptography satisfy these conditions. And the second minor limitation, of course, technique is that the analysis is relatively complex. The most important limitations of Cora's technique is this annoying term here, because as I have explained on the previous slide, this term makes the techniques of Cora only applicable in settings where we have that queue, or whatever replaces queue in a different setting here, is much smaller than the size of the message space or an equivalent of this. This is acceptable if you consider digital signatures in a single user setting as done by Cora, Capricills and other papers, but it makes it very difficult to apply these techniques to different settings. One particular setting that we would like to consider is the more realistic notion of multi-user security for signatures, which is more close to the real world. And in this case, we have an adversary which receives as input not a single public key, but a list of public keys, PK1 to PKN. And still, the goal of the attacker is to output a message signature pair. And as in the standard similar user experiment, the attacker is allowed to issue a signature queries. So in this case, he would output a message along with an index J, which points to one of the public keys, and he receives back a signature on the, which is computed using the secret key that belongs to public key J. And second, we want to allow the attacker to adaptively corrupt users, which means that the attacker may output an index J and receives back the secret key SKJ, which belongs to this public key. And if you want to have meaningful tightness results for practice, for real-world applications, then we actually want tightness in a security notion of this type here. So we want tightness in both the number of signatures Q and also in the number of public keys N that the adversary sees. Now, usually, it is sufficient to consider the single-user setting, which is much simpler and it's much easier to write proofs in the setting, because a single-user setting is known to imply multi-user security, but the reduction is not tight, it loses a factor of 1 over N. Essentially, because the reduction has to guess the public key for which the adversary outputs a valid signature at the end. So what happens if you try to prove that this 1 over N security loss is inherent and cannot be avoided? So our natural approach would be to apply Cohen's technique, and what we want to show using this technique is that we have this inequality here, epsilon M is lower bounded by epsilon R minus 1 over N. So that's what we would like to show. What we get using Cohen's result is this here. Now, we have this additional annoying term, and this time it is particularly annoying, because if you look at it for a second, then you can see that everything inside this red box here is equal to N. So we get 1 over N times N is equal to 1, so the lower bound that we get is epsilon M is larger than epsilon R minus 1, which is trivial. It's completely pointless to have this result. And we want to overcome this limitation. So our goal is to prove that the security loss of 1 over N is impossible to avoid, and to achieve this, we proceed as follows. First of all, we define a weaker security notion than the multi-user security setting that I've just shown you, which is somewhat counterintuitive, because we want to prove an impossibility result, and the weaker the security notion is, the harder should it become to prove that this security notion is impossible to achieve as a tight security reduction. But it turns out that this weaker security notion is extremely helpful to develop a new meta reduction technique, which gets rid of this annoying term. So in a sense, we've made our life harder, but still we're able to get a useful result. And the reason is that this weakness of the security definition provides exactly the leverage that we need to prove our results. And finally, given that we have this new meta reduction techniques, which is much simpler than previous techniques, we can generalize it to consider many other settings. So first of all, the weaker security definition looks like this. As before, we have an adversary which receives this input and public keys, and the adversary is still allowed to corrupt users, but not adaptively. So after seeing the list of public keys, the adversary has to pick one index J, outputs his index J, and receives back all secret keys for public keys PKI, where I is not equal to J. And second, the adversary does not have to compute a signature, or to forge a signature, but it has to the computer secret key which belongs to public key PKIJ. This is an extremely weak security experiment for signatures, which should be very easy to achieve in practice. But as I've already explained very briefly, so if we can show that there is no tight security proof for this very weak security model, then it's immediately in price that we cannot achieve security in any stronger notion, in particular in the strong multi-user security sense that I've showed you a couple of slides before. And a second thing that you may have noticed here is that the security experiment is not specific to digital signatures anymore, but it makes sense to any public key scheme, like public key encryption, identity-based encryption, and so on and so on. So in a sense, we have already generalized our results a bit. Second, we developed this new meter reduction technique, and the idea, now first of all the result of this technique, okay, we get rid of this annoying term, we consider exactly the same class of reductions as core, so we have reductions that treat the adversary as a black box and have the same few capabilities as core technique, but a big advantage of this technique is that it's very much more simple to analyze. The intuition behind this bound is as follows. So intuitively, we want to prove that in the moment when the reduction outputs this list of public keys, it has committed to a single public key for which it is able to both... So it has committed to a single index J, such that it is able to output all secret keys that belong to the public keys except for public key J, and at the same time it is able to output... It is able to take the secret key J from the adversary and leverage this value to somehow compute a solution to this computational problem. And now if you look at this moment here, right after the reduction has output the public keys, then we can have two different cases here. The first case is maybe at this point here the adversary has committed to a single index J, such that it is able to proceed the experiment. In this case, the reduction cannot be tied because if you have an adversary which simply picks J at random, then the reduction can just hope that it will pick the right value to which it has committed, and otherwise it will not be able to continue. And the second case is, so if the reduction is tied, we must have that there is more than one value of J, and in this case the problem P cannot be hard. And what we have to prove in this case is the second here. So in the rest of the talk I want to focus on the second claim here. So what we do is following Kuro's approach, we construct a meter reduction. When this meter reduction works as follows, it receives this input and instance of the computational problem P, forwards this instance to the reduction, starts the reduction and lets it run until it outputs the list of public keys. And when the reduction has output all these public keys, the meter reduction stores the internal state of the reduction. And in this instance it takes a snapshot of the current state of the reduction. That's the first step. And then the meter reduction iterates through all possible possible values of J. So it executes reduction R starting with J equal to one, and sees if it outputs on the list of secret key which are not equal to SK one. And then it repeats this process with J equal to two and so on and so on for all possible values. And it builds a meter reduction to learn all secret keys because there are at least two indices for which the reduction kind of outputs all secret keys. So what we get from this computation is we get a list of all secret keys. And now we can use this list of secret keys simply in a very simple way to simulate an efficient adversary. So we execute the reduction once more starting from the snapshot state that we have stored and we simulate an adversary which simply picks an index J uniformly random and we receive back from the reduction list of secret keys. And finally we are able to output SK J. Because we have received it from the reduction. And because we assume that the reduction works it will output a solution to the problem P and we can output it as well. So this provides a perfect simulation of a successful adversary and therefore the reduction will produce the solution to problem P for us. Of course this doesn't work as generic as I have just explained. And so we have to make or put up some restrictions or some requirements on the public key scheme that we are considering. So what we essentially need is that for each public key there is at least there is either one unique secret key. This holds for many examples of crypto systems like like Elgar Maier, Schnorr, signatures, DSA signatures and so on and so on. And second, we need that one can efficiently verify that a given secret key belongs to a given public key which also holds for many examples of constructions. And one can generalize this to a notion that we call re-randomizable secret keys. I do not want to explain this into too much detail but it basically means that given a public key which can have many corresponding secret keys and so if we have this public key and the matching secret key we can sample uniformly random from the set of all secret keys that match this public key. And the result that we get from this technique is that we can show that a public key scheme, so any scheme not only signatures but also public key encryption and so on that satisfies the both conditions cannot have a tight security proof in a multi-user setting. So it's impossible to avoid this security loss. Okay, finally we generalize this approach and this is from my point of view the most interesting part of this result. So our goal is to make this impossibility result easily applicable to two different scenarios beyond public key crypto and the multi-user setting. So what we do is we first describe a generalized experiment which kind of condenses the required properties that we need and then we can derive many impossibility results for instance for multi-user security with corruptions but also for other applications for example digital signatures in a single user setting as considered by a corral, coffee kills and so on and also for more applications. So in the paper we also have non-detected key exchange but everything generalizes also to say authenticated key exchange also. And this generalization essentially works as follows. So we consider an abstracted security experiment which looks pretty much like the experiment that I've just showed you. So we have a relation S. S contains tuples X, W where X is a statement and W is a witness that this statement is in this reduction in this relation. And we have an experiment, kind of security experiment for this relation. So the adversary receives his input and statements. Outputs an index J receives back witnesses for all statements which are not equal to XJ. And finally the attacker has to output a witness W and J. And if we make a similar requirement in this relation here so we need that it is efficient to verify that the given tuple X, W lies in this relation and that witnesses are either unique or re-randomizable and then we can easily use this technique for example to get the result that I've just showed you so if you want to consider a public key curve to a multi-user setting, we just define the relation such that it contains the... it contains tuples consisting of public keys and corresponding secret keys. But we can also consider signatures in a single user setting. In this case we would define the relation such that it contains N different messages and we can take arbitrary N messages from the message space like the first N messages according to some order and the witnesses would be signatures over these messages. Yeah, to summarize, so we have developed new techniques to prove, formally prove that in certain cases type reductions are impossible to achieve. The results are stronger because we consider this weaker security model than previous works but the proof is also extremely simple. We have additional applications which work in cases where we do not have something like an exponential size message space because we do not need this annoying term and we can also use this technique to derive criterions which allows to check very easily whether a given scheme can have a tight security proof or not. So for example if a scheme has unique secret keys or some unique signatures, then one cannot hope to get tight security in a multi-user setting with corruptions. And finally, using this master theorem it's very easy to adapt this technique to other settings by just describing a suitable relation and showing that this relation satisfies the properties that we need. And that's the end of my talk. Thank you very much for your attention. Yes, of course. So can you use the master theorem to get an impossibility result for tight reduction in the multi-user setting but a weaker multi-user setting where you don't get the secret key you just attack one of whatever out of N public keys like a signature scheme. So first of all this would probably be a weaker impossibility result because the security that you're describing gets stronger. It would be possible if we are able to define a suitable relation and then I guess we would have to look more closely at a particular security experiment that you have in mind. But if you can describe a suitable relation which satisfies the property then it's fine. Any other questions? So just to follow on that that is why your result is not in conflict with the results tomorrow because that results in the static corruption model as far as I understand. Which result are you referring to? The best paper award tomorrow. Ah, okay. I think this construction doesn't satisfy our conditions because there is no such thing like a unique secret key. So you have this now a wrangled pair F embedded in secret keys and then this is... But also it's in the static model for corruption. Static model for corruption. For static corruption. Ah, okay, wait. We have two dimensions. So one dimension is the number of ciphertexts that the adversary sees and the second dimension is the number of public keys that the adversary sees. So in the number of public keys I think, correct me if I'm wrong, I think that this construction does not have unique secret keys, right? Because you have this re-endomization there's now a wrangled pair F which is somehow embedded in the secret key. We have one more question. Yeah. Since the mirror reduction runs the reduction n times, isn't then the running time of the mirror reduction n times the reduction? It is. Aren't they supposed to be close? So, exactly. The running time is n times the running time of the reduction. The only thing to show is that if there exists a tight reduction then we get a polynomial time algorithm for solving a problem for which no polynomial time algorithm should exist. And therefore it's okay to run the reduction n times. Any other questions? Okay, let's thank T Boroghe.


All right, I'm Dylan Mulvin. I'm a postdoctoral researcher at Microsoft Research where I work with Tarleton, and I also collaborate with Merrill. Thank you so much for being here. Thanks for spending your lunchtime with me, and thanks to Kerry and Dan, especially for helping get this set up. I'm gonna just start by taking you back to 1999 when there was excitement in the air, and people were wondering, would airplanes fall out of the sky? Would bank accounts suddenly dissolve into dust? Would nuclear missiles self-launch? Would Wired Magazine run an image of the Angel of History totally naked on its December cover? The answers, of course, were no, no, no, and yes. So I'm gonna spend about the next 20 minutes or so talking about the Y2K crisis and why I think it's a potentially rich episode in the history of computing and technology, and really gives us possibly some important lessons for thinking about the management of crisis and how we talk to people in the face of vulnerability, and especially in the face of vulnerability that's a result of technological precarity. So I'm gonna introduce you to some of the ingredients that are a part of this project, but it is a work in progress, and I've tried to make this slide presentation out of only objects and text that were available prior to the very first 2000. I didn't use a slide software from that period, but you'll have to forgive that. So today I wanna argue that the Y2K bug is a crucial chapter in the history of the public pedagogy surrounding computing. Key moment in other words of how we kind of calibrated a way for talking to the public about how computers work. It was also a moment for teaching people how their lives were already captured in data, whether or not they recognized it, and that things like infrastructure and computing could put them and their data at risk. And something as simple or seemingly simple as the representation of the calendar in computer code could bring everything to a crashing halt. So the agenda for today is pretty brief. I'm gonna start with some background on Y2K for those of you who weren't actively working on this remediation, and for any teenagers who are here who have no idea what happened. And here I'll detail some of the technical origins, and it's a pretty broad gloss given the short time period we have, and some of the concerns about computer literacy in the 1990s. This will introduce my Y2K archive, such as it is, and some of the documents and sources that I'm drawing on to try to compile this history. And finally, in the last section, I'm gonna talk briefly about the labor of repair and how people were talking about the labor of repair in this period and kind of contesting narratives about who was doing the work and what that work looked like. So let's start with some background. As you remember, the main problem that people imagined was driving the Y2K crisis was something called the century digits problem, or representing a date in six digits instead of 10. And this was an especially dangerous problem because the two-digit year format was used in a bunch of different computer languages, mostly from the 1950s and 1960s, but one language in particular called COBOL, and we'll come to it later, gets kind of singled out as a problematic language, especially because it was used in financial and banking systems and things like waste treatment facilities. So why would you choose to code digits in six years instead of, six digits instead of eight? Sorry, I think I said 10 earlier. So anybody who remembers that period, why was that choice made? Yeah? To save space. So the main reason was compression. There was limited computer memory in the late 1950s and early 1960s, so you had to make hard decisions about what kind of information was crucial to include. And actually excluding one and nine is a pretty easy choice because most of the information that you were coding would eventually be printed out. If you had to use it, you could print it out and you could pre-print a template form that had one and nine on it. If you had a checkbook in the 1990s, you'll remember it always said one nine so that you wouldn't have to go through the laborious act of writing out those two digits. And there was some thinking, right? Maybe these programs and these applications will last 10, 15, 20, 25 years, really optimistically. Maybe they'll last until the 1980s. But very few people, though there were exceptions, but very few people were imagining that they would last 40 years. And if we think today about the kinds of temporalities that are imagined for the applications that are being written, still hardly anyone is thinking in a 40-year timeline if they're even thinking one or five years ahead. So those two digits that you erased from the year were pretty minor memory savings if you were just creating an Excel spreadsheet of your friend's birthdays, let's say, or if not Excel, but a spreadsheet. But if you were trying to manage a database for a financial firm or an insurance corporation or government agencies, the Social Security Administration, those memory savings were significant because of hardware costs and the labor costs of keeping up that hardware. So what was COBOL, which I'm gonna kind of focus on as a problematic language? Well, COBOL stands for the Common Business Oriented Language and it emerged from something that's referred to as the software turmoil of the 1950s and early 1960s. And here I'm really indebted to Paul Ceruzzi and Nathan Enzmanger's histories of this period. And this is from Nathan's book. This is the cover of the communications of the ACM from 1961. And you'll notice, oh, it's not that clear, so I'll describe it to you. This is from January 1961. These are all of the available languages and there are dozens and dozens and dozens of different programming languages spiraling upwards in the shape of the Tower of Babel. And this represents the kind of question at that period is like what language should we use and different hardware manufacturers had different proprietary languages and different applications had different languages. And there wasn't a shared lingua franca for getting things done. So the government and the military stepped in, this is all in the United States, to say we need a compromise, right? We need a shared language that can work across hardware and across applications. And COBOL was one attempt to create that compromise. So there were a few criteria, right? It had to be readable by novices, in particular a managerial class that wouldn't necessarily be coding literate, had to be able to read or roughly grok what it said and what the purpose of a line of code would be. It had to be free of proprietary control and it had to be used for a wide range of applications. All of that meant that it was inelegant, right? It was super ugly, it was super easy to read which made it like less specialized and less interesting as a language to learn. But in 1960, the US government announced that they would not purchase or lease any equipment that couldn't run COBOL, which basically sealed it as a lingua franca for the short period going forward. So despite all of that, a tiny number of people learned COBOL. And this is gonna come up again as we talk about the labor of repair. If you can see this picture, this is the quote unquote 25th anniversary celebration for COBOL and you can see Grace Hopper in the front there who had, and what you can't see is that that's a cake in the shape of a tombstone that says COBOL on it because this is some of the people responsible for creating it and imagining that it's kind of heyday was fading and this was of course still 15 years prior to the Y2K crisis. So we have a kind of contradiction here. By the late 1990s, COBOL was by most measures the most widely used programming language in existence. It was used in 80% of all business operations, but had some of the fewest practitioners.  So it was, COBOL was de classe, it was designed to be readable again by managers, not necessarily people doing the programming. And it was referred to as a trade school language. So those are the first ingredients of this project. A problem that was created out of compromise, out of a desire to save on hardware and to make an easily readable language. And already you can kind of see the foreshadowing considerations of literacy and pedagogy and teaching new kinds of people to read code. Sometimes this slide just makes my computer shut down. So I might have to get through it kind of quickly. But there are other aspects of the Y2K crisis and how it was sort of constructed in the late 1990s that are really important. But first I have to say there's still, of course, mystery and widespread disagreement over whether or not the Y2K crisis was real or whether or not it was a false alarm. But I wanna say that whether or not Y2K was a true threat, it instigated massive programs of remediation and public education. In the lead up to the year 2000, estimates of reaching compliancy and the cost of reaching compliancy range from 300 billion U.S. dollars to 600 billion U.S. dollars. And that's a pretty big range, but no matter what a massive amount of money in the United States, compliancy is estimated at having cost $100 billion. In terms of disasters, would be one of the most expensive disasters of all time. And it didn't actually cause a disaster. So in other words, the legitimacy of this threat, historically speaking, is pretty secondary to the effects that the perceived threat had since the changes that it engendered were real. And this, I call it kind of crisis pragmatics. A crisis that is felt to be real is real in its effects to tweak the sort of Thomas theorem of sociology. And I think that the pragmatics of this crisis were tied entirely to the structure of the problem, that there was a precise moment at which you could point to and say, that's when everything's gonna go haywire. That's when planes are gonna fall out of the sky. And there were, of course, there were these lags and these kind of strange temporalities to the crisis. Some credit cards stopped working in 1998 if their expiration date was for the year 2000, but there was this sort of imagined moment that when we flipped from 1999 to 2000, everything's just going to explode. So unlike a hurricane or an earthquake or even climate change which have these hazy timelines for unfolding, you know something's going to happen, but you don't know exactly when. Y2K was sort of perfect for creating fear and compelling action. The next thing that's important is competing notions of literacy and numeracy. So first was a concern with how computers would read or count numbers, right? And fear about ambiguous numbers that 99 would be confused with 19, or the year 2000 would be confused with the year 1900 or some other unknown date. We might call this a kind of machinic numeracy or innumeracy. I'm more concerned with a second kind of literacy that we more often think of when we say computer literacy, which is efforts to train non-specialists in understanding how computers work. And specifically what the risks of something like old code or a legacy system would be or what a calendrical error would mean for something like infrastructure. And there were enormous hurdles to getting people to understand these risks and to appreciate these risks and to balance that out with just straight up fear mongering. All right, and it wasn't just like normal folks who had to be confused, convinced in late 1998, the New York Times was still writing about the Y2K crisis as a problem for quote-unquote computer users, right? Unable to imagine that in 1998, everyone was a computer user, whether or not they sat at a keyboard or used a gray box, right? If they weren't actively using computers, their lives were being used by computers and structuring the mundane and everyday aspects of their existence. Another aspect of getting over this sort of barrier to understanding is a strong potent sense of betrayal, right? Ellen Ullman writing in Wired in April 1999 said, I think puts it really well. She said, after being told for years that technology is the path to a highly evolved future, it's come as something of a shock to discover that a computer system is not a shining city on a hill, perfect and ever new, but something more akin to an old farmhouse built bit by bit over decades by non-union carpenters. So in other words, the chances of successful literacy campaigning depended on teaching people that they were already entwined in digital technologies and all that, then the technology always involves constant upkeep and repair, right? That it's not just a finished perfect product that works or doesn't work, that it requires attention, right? And people to work on it and to keep it going and it might not go the ways that you expect. And you can sort of see in this quote some of the issues again of repair that are gonna come up and labor. All of this brings me to my archive. So as a historian, the Y2K crisis offers a really challenging problem. How do you write a history of something that may or may not have happened? And one way to do that would be to go out and interview people and weigh their opinions against other people's opinions and then compare the evidence and decide whether or not it would have happened. That's not what I'm doing. Instead, I'm trying to focus on what did happen, right? That pragmatic response to the fear that something was going to happen. This creates another problem, which is because it didn't happen, because Y2K appears as a kind of punchline to the joke that was the 1990s, its archive is really spotty. And Y2K played out in newspapers and network news, but it also played out in pamphlets and paraphernalia and memorabilia. If you were alive then, you'll remember just the amount of stuff that was branded with Y2K. And it played out on the web, on websites that nobody pays the server costs for now in 2017. So some of it's captured by the internet archive, but actually very little of it is captured. There is an archive, however, in the classical sense and the Charles Babbage Institute has some of the papers related to a couple of organizations. And I've been there and I've looked at them and I'm gonna tell you a little bit more about them. The two organizations that the CBI has are the Center for Y2K and Society. Does anybody know or remember this organization? Is that it for you? No, so the Center for Y2K and Society, it was an independent organization run by concerned citizens who believed that the government was downplaying the risks of Y2K. So they were on the far end of the chicken little spectrum. And I'll tell you a little bit more about their collections in a minute. But the other organization that CBI has is the papers of the International Y2K Cooperation Center, which was paid for by the World Bank and backed by the UN and headed up by a guy named Bruce McConnell, who was a high ranking bureaucrat within the White House. So looking at their two approaches, we can kind of see differing styles in teaching people and approaching vulnerable populations in the face of technological precarity. So the Center for Y2K and Society or CYS is fascinating. And one of the most fascinating things is their record keeping. So as far as I can tell, everything the CYS ever read or looked at is printed out. And it's printed out and kind of thrown into a box in Minnesota. And it makes sense, right? If you're an organization devoted to the idea that society is about to collapse, and in particular computer technologies are about to collapse, you can't house your records or your documentation online or on computer hardware. You have to print it out. So the documentary evidence that they leave behind shows this build-up of the kind of ballast of paranoia, right? And everything that they have is an email, four words, press, clippings are all organized and annotated to support the theory that some sort of systemic collapse is imminent. I have, you know, there are just millions of examples, but here's one where somebody else has produced a pretty mild risk assessment and they've printed it out and the person has just written nothing new here, right? Unremarkable because a mild risk assessment. And other things that are less mild, right? They'll have more exclamatory annotations and then that's been filed away. The most significant thing they did though was circulate supposedly 20,000 copies of this thing, which is called the Y2K community report card and they sent it across the country trying to get different organizations to respond and speak to their preparedness for Y2K and then they compiled the results and here's an image of the questionnaire which you can't really make out, but the results of their survey confirmed their worst fears. They, it seemed to show that things like waste treatment facilities weren't ready, that vulnerable institutions like nursing homes were totally woefully uninformed and that America was doomed. Their holdings also really captured the long tail of the Y2K crisis and as I mentioned a minute ago, the many commercial opportunities that it seemed to present to kind of shill survivalist materials. So here's instructions for ordering something called the Y2K kitchen, which was a set of resources for cooking with canned and dried foods. This is a role-playing game called Countdown to Y2K. This is a book called Y2K for Women, How to Protect Your Home and Family in the Coming Crisis and I think what, and there's just many, many, many more that show that no opportunity was lost to process stereotypes and cultural affinities and cultural norms through a kind of paranoid template that Y2K provided. The second organization, so if the Center for Y2K in society was devoted to this kind of grassroots fear mongering, then the International Y2K Cooperation Center was devoted to sort of top-down fear assuaging. Everything will be okay. And the materials from their archive include professionally organized news clippings, by day and subject, a script for a 1-800 number that anyone could call and it would sort of tell you everything was gonna be okay with an automated voice. And if you could make it through the phone tree, you might actually talk to a human who would tell you everything was going to be okay, especially if you were responsible for an institution that had a computer system that you thought needed to be remediated. And it also includes details of something that was called the Y2K Expert Service Core, which was a quote, international network of Y2K experts who have volunteered their time and expertise to make available advice, intellectual capital and information. It also includes this very extensive project called the Y2K Community Conversations Campaign. And these conversations were promoted as opportunities for business leaders and institutions to share their Y2K preparations with locals. So come and hear how your local business or your state business is actually totally ready for Y2K. So in this case, it wasn't about explaining how things are gonna be okay or helping people prepare for disaster, but just saying like, don't worry, we're ready. It was also an opportunity to kind of demystify computer technologies. So whereas some government agencies in this period were focused on risk assessment and remediation, the Cooperation Center was also trying its hand at community organizing with developing a kind of pedagogy of preparedness. And I think what the collections of both of these organizations show was an attempt in this period, right, in the late 1990s to educate diverse populations in the realities of technological precarity, right? In the realities of what it means to use old code and old systems and legacy systems. It was an attempt to kind of collapse any division between computing and everyday life, right? By educating people about the many daily activities that were dependent on computers. And they lodged their explanations at multiple registers at the local, right? What your pharmacy is doing, what your school is doing, and at the mundane, right? How your credit card may or may not be at risk, how your social security checks may or may not be at risks. And then also the catastrophic, right? So one organization devoted more emphatically to the catastrophic and the other one to downplaying those risks. The last part of the archive is press coverage. And specifically I'm looking here at how labor was talked about in this period and who was being described as responsible for repairing Y2K errors. So you'll remember from the beginning of this talk that cobalt's widespread popularity was in total contradiction to the number of people who were fluent in cobalt. And out of this you get these stories about old programmers being taken off of golf courses and brought back to work on programs that they had worked on their entire careers, that they hadn't been paid very well for, that no one had appreciated them for, and being paid lots and lots of money to come back and fix them. This is one story from the Washington Post, but there's an LA Times story that I think really captures these dynamics. Here's an excerpt. Once considered the dinosaurs of the technological revolution in mind the metaphors. Cobal programmers have become a hot commodity precisely because they stayed in the high tech Jurassic era. Like priests who dutifully maintain dusty heaps of scrolls, they're being recalled from seclusion to recover the ancient knowledge of cobalt. Okay, so if cobalt is the ancient knowledge kept by priests who weren't appreciated in their time, then Y2K was the sort of secret code that lay dormant in the text, right? And this is funny except I think it's entirely typical of the actual active mystification that was happening about technology at this time. So on the one hand you had very active efforts to demystify technology, to explain how things are actually fit together and how you're at risk and not at risk. And at the same time, very strange ways of talking about the labor of fixing computer code. And we know this because the Y2K crisis also led to one of the first massive hiring Indian IT workers and the first wave of body shopping where hundreds of thousands of workers in Hyderabad and Sydney were employed to fix Y2K errors. And nowhere in the coverage of the remediation effort as this talked about. And of course this wave of body shopping was a part of ongoing changes as a result of globalization and shifts in labor markets that Mary Gray can tell you a whole lot more about. But instead you get these stories of underappreciated coders who were ignored in their time being called back for one last job, right? So this is where I'm at. Maybe the threat of Y2K was real, right? Or maybe it was a $600 billion pragmatic response to an imagined disaster. But in either case, it was one of the world's largest attempts at basic technological remediation. There are kind of two stories that can be told here. One is what looks like a punchline, what Louis Menand recently called a nutty cocktail of Luddite millennialism and digital overthink, right? But from another perspective, this is a hugely significant episode in crisis planning and management and a population-wide attempt at basic computer literacy campaigning. I think that the reality is probably somewhere between these two. And that the kind of interest and focus on technological vulnerability, on relationships of interdependency and that Y2K surfaced in this period make it a really rich site for talking about literacy building and the acts of care that we undertake at particular moments and just how we talk to people about how computers work. So thank you for your time and I'm really looking forward to our discussion. Merrill. I'm wondering how US-centric this was considering you are from Canada and if there was a sort of US isolationist or some kind of response that, and that position of the US in a particular way in relation to the rest of the world when it came to managing this, but also if there were like Canadian, if there are like Canadian archives of this too, yeah, I guess, two kinds of things. I mean, I can answer a little bit of that from the Canadian perspective, but does anybody else want to comment on what they perceive as the US-centric nature of the crisis? I mean, Sheriff, you were talking yesterday about the UK. So it was crazy to bug, that was one thing I wanted to ask you. Yeah. The terminology. In the UK, definitely, the Y2K bug was something anyway. To be honest, some of what you were saying would absolutely map over. I don't remember the survivalist instinct. I think the North America, perhaps has their monopoly on narrative, but it was very much about finance because of the city of London. So the city of London being seen as this kind of great, we had the Big Bang and the way in which the stock exchange was kind of electrified and stuff. So it was very much around that. So we didn't have as much of the community effort from what I remember. So it was there, but it came out differently. Yeah. This is related to that question. US is also different in that you do a month a year instead of a month a year. And so how did that fit in? Was this code used in other countries where that format already had to be re-arranged? That's a really good question. Again, because Merrill gave me off as a Canadian, of course, that ruins my life, especially because my wife's birthday is March 10th and my daughter's birthday is October 3rd, and so it's just like, it's impossible. Was it also about the ages of the infrastructure, so what different countries have dealt with? Like with COBOL or certain kinds of instantiations, would this problem not have shut up in countries where the financial infrastructure was newer, so a newer language was set up with different choices or maybe there was more storage, so certain kinds of, I don't know. That's an interesting question. So I can give you a few responses. One is that there's always a center in periphery problem, which is so the way it played out in Canada was as an American problem that we also have to deal with, because our computer software comes from the United States, our banking software comes from the United States, and we're interdependent with the United States, so anything that affects you will affect us. So there was no idea that we could somehow throw up a border and be isolated from the Y2K crisis. In the United States, and in some of the ways that it was talked about, there was also a totally xenophobic discussion, which was an idea that, okay, we're gonna spend $100 billion to reach compliancy. We're gonna introduce new regulations that are going to limit our exposure to this problem. What we can't predict is what all of the countries who stole our software are going to do, right? And I'm not gonna name the countries that they named, but they named very particular countries that had stolen our software and used it in their infrastructural projects. And we can't guarantee compliancy in that case. Some of the largest, most populated countries in the world, right? China? I was gonna say, yeah, right? So, but again, that's a question about empire and its stretch and the ways in which it gets taken up either intentionally or unintentionally. There's another element to this, and were you the one who worked with insurance companies? It was you. So we can talk a lot about that, which is the efforts to limit liability within the United States and exposure to lawsuits if there were disasters. So that's a big part of this question, too. And other countries just don't have that structure of litigation. So in Canada, there was no fear that lawsuits as a result of Y2K would bring down the economy, as there was in the United States, that fear, because you can't sue people that easily in Canada, in part because you have to pay their legal fees if you try to. So there are, yeah, all sorts of different ways that they play out, but certainly it's a U.S. focused problem because that's where the hardware and the software came from. Yeah. I definitely agree that the litigation risk of avoidance was something that certainly drove a lot of the headlines. I think it's also interesting to map this crisis with the growth of the beginning of PCs being sold because for the first time, I can't remember when IBM sold its first PC, but at what, 95? Oh, much earlier. Oh, much earlier. Okay. What? Was it that much? Okay. But in any event, the boom in PC sales taking off meant that there was a lot more mind-share penetration in the general population, which goes to that wire, quote, sense of betrayal. Yeah. That could be experienced by a lot more people as opposed to it just being an expensive business problem. Right. And for the most part, PCs weren't at risk. No. But if you had one, you'd probably worry about unknown known. And sure enough, if you bought a computer in 97 through 99, you'd most likely bought it with a sticker on it that said Y2K compliant. Yeah. Since you were out as a Canadian, I'll myself as somebody who once run a cobalt program. A high priest. That was disgusting dirty work of dealing with money. By the late 90s, if you're doing stuff on the web, I mean, there were no web servers running cobalt. Right. But I mean, this is a really rich talk and there's so many threads to pursue. I want to ask about a different kind of labor because one of my recollections of this is sort of call it the formative aspects of the Y2K crisis. At the time, I worked for Tufts University and it was very important to the university that we hire a famous consultant. It wasn't phrased like that, but that was the signal that we were taking it seriously, that we had a guy who had written columns about Y2K coming and talking to us every week.  I mean, have you followed those threads in sort of the rise of this sort of high-priced consultant fear mongering? Yeah, I haven't followed that thread. I don't know how I would follow that thread except in the largest version of this project I would do something that I think is partly happening in this room which is ask people where they were for Y2K and how they prepared for it or if they were responsible for an organization or a part of an organization, what was imagined. Talking to somebody who was a professor in 1999 and happened to be the chair of a department, his university asked him to sit in the sort of server room with all the other departmental chairs on New Year's Eve 1999 to just stare at the computers and he said no. But those sorts of, I think oral history is really the only real way of recovering that aspect of it and it would be really difficult to parse how much of that was theatrical and how much of that was necessary and what we really actually think of as unnecessary. It might actually be important to bring in high-priced consultants if it assuages fears and allows people to just do their job that might actually be a kind of minor cost or it's just a total boondoggle. It's really difficult to draw those lines but it's an interesting historical question, yeah. Are you going to go through all this again in 2038? Well, I think it depends on if the world exists in 2038 but it seems like, do you want to explain to everyone why? There is a counter for, I think it's a number of seconds or is it a number of microseconds? I can't remember microseconds. In UNIX, the traditional 32-bit UNIX or you'll gradually be replaced by 64 but 32-bit UNIX, the last date that can be represented in that format is somewhere in 2038 unless you change it to an unsigned in which case you get it longer but then you cut off earlier dates. So some version of this problem might exist again in 2038 to the extent that people are still using 32-bit UNIX systems especially embedded systems that might not be replaced for 30 or 40 years. So it's entirely possible and it would be a question if it plays out the same or if it plays out differently because we went through this in 1999 and it seemed like a false alarm, right? And what the social costs are to apparent false alarms for... I could also look forward to try 100 about how the... Maybe the moment's going to be around then, so... Yeah. So Bruce Lewinstein at Cornell had an NSF grant to document the Y2K, public perceptions about the Y2K problem. And I'm curious as if you worked with it and if the idea of trying to document as you go along is successful or not. Right. And I've looked a little bit at his research and it's actually in the archive as well. I think possibly both organizations noted it. And what for me has been important about that research so far is kind of arc of fear that seemed to peak around... Now I can't remember if it was April 1998 or April 1999 and then by December 1999 fear had really sort of dropped off and cynicism had peaked, right? Which is again funny except that when we're talking about the management of crisis really important to balance those things out that you can't... If you have too much cynicism you can't prompt collective action and if you have too much fear you can't prompt responsible action. What are the innovative features of that collection? They figured out a way to capture television references from the major broadcast networks relating to Y2K including J-Leno and anything else and you'd be able to track that that way I think really strongly. Yeah. Yeah, it's such a rich project and I appreciate the archival dimension of it in particular but I'm wondering a little bit about what the post-mortem of all of this was. I mean, I'm thinking in particular about a lot of SDS scholarship that's looked at the breakdown of large technical systems the Challenger disaster, Breitner one that comes most immediately to mind the way that these large bureaucracies sort of knit the world back together after this happens and this seems like it would be an interesting comparison with some of those. I think also of the Hook and Mouth Outbreaks of the UK and we're going to file a breakdown protocol breakdowns. So I'm just curious about what, you know, did the James Glikes and public intellectuals and journalists undertake any post-hoc analysis or did we just kind of move on? So it comes up a little bit in SDS scholarship. There's this pretty important piece about repair by Thriften Graham that talks about Y2K but mostly in the valence of perceived disasters that didn't happen, right? And so it gets totally rewritten as this punchline, as the Louis Monon line, as a kind of joke. And as like a person committed to self-sabotage I often seek out these jokes and then try to make them serious and see, like, oh, what really happened there? And if we did a different kind of post-mortem on that that wasn't just, like, oh, okay, we blew it, right? We didn't understand computers well enough to reasonably assess what kind of danger they presented. That being said, I'm working on a kind of long-term project with a colleague who does histories of the AIDS movement in the 1990s and its relationship to technology and community internet provision. And so the project, compared to this one, which we just kind of call bugs, looks at these two things as kind of mirror images, right? A crisis in which everyone was paying attention but nothing happened and a crisis in which a lot of people died and no one was paying attention. And when we started on the project we were thinking of them as these sort of mirror images and they would offer an opportunity to kind of provoke and understand the others from a different angle. But what we also started to find was just tons of references in the Y2K literature about HIV and AIDS, right? About the spread of harm through networks, through vulnerable systems and vulnerable people. And even in Manuel Castel's work in the Network Society he often returns to HIV and AIDS as a way of mapping networks and especially networks of sort of compounded harm. And there's an online resource for people living with HIV and AIDS called The Body that some people might be aware of. And on The Body you get columns in 97, 98, 99 about the other millennial crisis, right? And Tony Kushner's Angels in America subtitled Millennium Approaches, right? And so you actually have these kind of twin crises of the 90s that play out in different ways but are then refracted in each other. And so part of looking at this project is looking at the understanding of crisis, not just now and doing a postmortem but in the 1990s and the ways that these sort of relationships were being thought through. Yeah. Other than the 2038 problem, have you looked into possibilities for other such disasters looming like internet addresses, et cetera, et cetera, which I think are pretty well under control but I don't know. There might be a number of other things. In the next 50 years it could happen. I mean, I haven't actively sought to compare this to the internet addresses problem or to the 2038 problem because there's no shortage of impending disasters and it's a kind of question of, this goes back to the thing I just said, right? There is no shortage of disasters and crises and people in harm's way and people who need help and who are vulnerable and what's interesting about this crisis, and this is what I pointed to, the actual structure, that it was a switch from 9s to 0s and all of the sorts of millennial fear-building that come with the turnover of any century and I know it's not the century but whatever, that it's a question of which crisis actually emerges as the one that needs attention paid to it, right? So it would be remiss of me to look forward and say, well, that crisis is going to play out this way or that way but we have to look backwards sometimes and see, oh, it's strange that that one is the one that got the attention. Yeah, Tarleton. I think the point about the shape of the crisis is really interesting, this idea of like, it hasn't happened yet but we all kind of know the date, right? It's a very unusual one. It was making me think about this as an exact comparison but I was thinking about part of your story is how do people have to learn that infrastructure that they count on is vulnerable in ways that they have otherwise not wanted to think about?  It's perfect, it's seamless, it works great and then suddenly to have to discover and then have to act upon. I was thinking about things like, you know, when there were major commitments to retrofit bridges because the science, you know, sometimes it's because, you know, the Tacoma Narrows collapses or there's some striking disaster but other times it's moments where the science develops an argument that says what we thought was sturdy could be vulnerable in certain circumstances and when you said that this was one of the most expensive kind of remediations I was wondering if we could, if we counted those things like if the sort of like bridge retrofit has a like widespread, that's a network that, you know, has certain kinds of invisible vulnerabilities. I don't know what the numerical, I don't know how you amass that number but it's another one where you sort of like, you want to count on the idea that roads, roads are put and bridges carry cars and that those things, you know, if the wind blows the wrong way they don't twist themselves. There was one region Minnesota that triggered a lot of this. Right, right. So there's one shape of like there's an incident that then makes other things vulnerable not just that bridge but every bridge but there's also things like discoveries about infrastructure that then have to raise questions. Yeah, so I brought this up rudely. This is a, you know, Google Ngrams aren't perfect things but this is a Google Ngram of the term infrastructure crisis. And infrastructure crisis is really interesting to me because it seems to be one of the only problems that we currently have that has sort of trans-partisan agreement that infrastructure is a virtuous thing that need in need of repair and treating, you know, in Trump's acceptance speech on the night of the election, you know, he talked about the infrastructure crisis. So you can see from this that it kind of took off in the mid to late 1980s that's where the term really started being used and I have another one that goes to 2007 but it really peaks around the year 2000 and it's extremely, it is the highest popularity in the 1990s which is interesting to remember because it seems to also be very current presently. So one answer to that question is there are these moments in which certain things seem to be in crisis and now we're talking about infrastructure being in a 30-year period of crisis and how that actually works as a kind of engine for promoting whether it's like scientific investigation or social scientific investigation and the kinds of questions that we have to ask is like, okay, so are we concerned about bridges or roads or computer infrastructure or internet security or nuclear safety or but the infrastructure crisis just becomes a kind of pen for holding those things in, right? We can kind of lump those things in there. That being said in the late 1990s few people were talking about computers as infrastructure, right? Even within science and technology studies, Paul Edwards writes computers as infrastructure in 1997, I think. So convincing the very field that I think would most embrace that concept contemporaneously with this crisis and I'm not sure that if you ask politicians when they think of an infrastructure crisis, if they're thinking about old computer codes and the risks that it poses I don't know that partly answers your question. Yeah. Two provocations I'd like you to respond to. I mean if you view this as a sort of calendaring software promote crisis then you'd think one of the responses is okay, time is important we need to get this right in our systems. Yet it seems like every leap year every leap second etc there's a news story about some major system that could not cope and did something wrong. The other way to look at this crisis is that it wasn't the Y2K was the trigger, but this was really about misunderstanding understanding the longevity of software. I mean those of us who wrote some of these programs knew we were doing a terrible job and simply assumed that they would be thrown away. Right. That would have been the responsible thing to do and oh my god they're running 20 years later of course they're not Y2K compliant we were lucky that they were 1990 compliant and there were actually 1990 problems as well. But then you see something like the Amazon S3 problem last week if you're familiar you know a typo in some command line takes out systems then it turns out they've never rebooted this stuff you know and that's sort of like one of the maintenance lessons out of Y2K. Yes of course you're going to have to there will come a point where you will have to restart these things and you really want to know how that stuff works. So we haven't actually learned the longevity reasons longevity lessons either. I guess if I turn that into a question it's like are we doomed? No I mean I think your provocation captures I think was kind of the tension of this of this history and the way that the problem is described is it an easy problem to fix like okay we just need to do a better job of X in this case representing the calendar right and yeah those problems come up all time there was that thing last year that 4chan somebody on 4chan made an image that said like oh set your iPhone to the date January 1st 1970 and reboot it and we've introduced a cool thing that will make it seem like Apple in the 1970s right it'll be a blast from the past of course a brick to your phone because if you're a west of GMT that's not it doesn't exist in UNIX time right and so that like the Y2K crisis exposes the fact that calendars are infrastructural and they're actually pretty easy to tweak and the ways that they're integrated with other forms of technology are easy to tweak so yes that is certainly an aspect of it and you have to be careful about the representation of time and technology but also it was a trigger right it was a way of saying yes we need to be more responsible about the longevity of our software and if anything we're less responsible about the longevity of our software as we were in 1999 so if there was one lesson that came out of it it was that very few people will be held responsible or accountable for technical for decisions and design choices that were made at one point and how they played out in the future and if there's another lesson it's that you have to be really careful with the public's trust right so either you're saying I'm sorry we made a decision in 1960 and now it's having this impact right I'm sorry but here's what you need to do to prepare yourself but then you have the after effect which is I'm sorry we told you that that was maybe going to be a disaster it probably was but we fixed it right either that's an opportunity to build trust and say okay we're telling you we're telling you that we screwed up or it's an opportunity to lose trust but it was also at that point imagine as a chance to make computer engineers more responsible right and so I just there's another article from the 1990s about well this is an opportunity to start certifying all computer engineers right this is this is finally the call like we need to have a professional organization so everybody can be a software engineer unless they're a certified software engineer and there's this quote in 1998 John R. Speed who is the Executive Director of the Texas Board of Professional Engineers right he says many have called themselves software engineers wrong they're the local music dropout who chooses to use that title right and so this is actually a kind of incredible moment in which this division of kinds of engineer was still sort of animating the ways people viewed this problem it's like this is a result of people who aren't engineers who made engineering choices and now we're having to pay for the consequences if engineers built buildings the way programmers wrote programs the first woodpecker would end civilization yeah I remember that it's a great name thanks everyone what was the 1990 problem and I don't remember hearing about that I mean it was a widespread but the same sort of thing where people didn't expect it


So, 6 says, if a balloon filled with di-nitrogen tetroxide gas at 500 degrees Celsius and 0.87 atm is cooled to 128 degrees Celsius, what is the new pressure of the N2O5 gas? Okay? So, we know some things about it already, right? We know the initial temperature, right, so that's T1 is 500 Celsius and we know P1, too, right? It says it's 0.87 atm. What else do we know? So, T2, right, the temperature that it changed to, 128 degrees Celsius, and P2, it asks, well, it asks, what's the new pressure of the gas, right? So, that's what it's looking for. Now, remember to get this, you don't have to remember all of those laws, you know? You just have to remember the ideal gas law, and that's PV equals nRT, right? And you just do 1111 and then divide it by PV equals nRT, but 2222, okay? And then you ask yourself, did P change? Yes. Yes, so you can't cancel that out, right? Because P1 does not equal P2, right? Did V change? No. So what does that mean? If V did not change, then that means V1 equals V2, right? So essentially V1, or V1 is V2, right? So if that's the case, we can cancel both of those out. That makes sense, right? Did the number of moles of gas change? No, so it's the same argument, right? n1 equals n2. Does R ever change? No. So that can cancel out. So we've got this new equation, right? So what's our new equation here? P1 divided by P2, very good. This T1 divided by T2. T1 over T2, very good. And what are we looking for, P2? So we want to isolate that variable. We could do it a number of ways. The way I like to do it is just flip it over, right? And then just multiply by P, both sides by P1. But let's flip it first, okay? So now we've got P2 on the top. So what we do to one side, we've got to do to the other side. And then, of course, we want to isolate the variable P2. So we're going to multiply by P1, right? Because P1 is being divided by P2. So what's our new equation? P2 equals, yeah? Very good. And you want to think about it this way. So the temperature decreased, right? Would you expect the pressure to increase or decrease? You'd expect it to decrease. So you would think that it would be less than 0.87 ATM, okay? The other thing that you want to do is get this in kelvin, okay? So do you remember how to do that? Yeah, add 273. So that's going to be 773. And then, so now we're in kelvin. So that's absolute temperature. So now we can plug that in there. So we always want to remember, we've got to change that to kelvin.  So anyways, I'm just going to put it over here so we'll have more room to plug and check. So P2 equals, well, T2, which is 401k, P1, 0.87 ATM. It's very similar to what we were doing today, remember? Yeah. And in fact, you'll see that it's very, very similar to the things that you just keep repeating the same thing. And then T1, of course, is going to be 773 kelvin. And of course, kelvin cancels leaving you with ATM. Right? Would you expect ATM to be your unit? Yes. Because you're looking for pressure. Okay, so you want to always keep all that stuff in mind. So you have 401 times 0.87, and then divide that by 773. Now remember, we thought it should be less, right? Yeah. And in fact, it is, which is cool, and it should be the two sick foods, right? Because this one is two sick foods. Okay. So when I get it, I get 0.4518. Does it make sense? Yeah. Oh, we did? So you just want to do it stepwise. All of these are stepwise things.  And the other thing you want to ask yourself is does my answer make sense? It went down, you know? You would expect it to go down. From hot to cold, you know? Here, if you put a balloon, it's going to, you know, decrease in pressure and put it in the cold. Okay, cool.