But this is the high school math addition. It's mostly going to focus on actually what happens with ZKPs and how they work. So we have lots of identity. Identity is contextual. You want to use different things at different times, depending on what you are trying to accomplish. If you're driving badly and you need to show it, it's a driver's license talking to a police officer. If you're going across the border, you're using a passport, all sorts of things. Lots of these are government, but a lot of them are other things, universities, degrees, bank accounts, membership in a club, all sorts of things. All of those are elements of identity. And so we've lived for 2,500 years with paper credentials. Paper credentials have a model that you should recognize, but I want to call it out so you realize what we're talking about, which is an issuer gives you a piece of paper because of some reason, some relationship you have with that. The issuer is some sort of authority, and they give you a piece of paper for some reason. You tuck it away in your wallet, perhaps. If it's useful in a mobile environment when you're running around in the world, you might put it in your filing cabinet for whatever reason. Sometime later, in an entirely separate transaction, a verifier says, show me those pieces of paper you have.  Proves, when you do that, and I put quotes around the word prove, who issued the credentials. It's going to have some sort of name or icon logo on the piece of paper. Who holds the credential? It's going to have some sort of binding to you, that it's your credential and it's you that is presenting it. And that the claims are unchanged. They haven't been modified. You haven't forged the document. The trust that they're trying to figure out is mainly with you and mainly they're concerned about, are you forging these documents? Have you faked these for whatever reason? That's a lot of what you're doing, but as well, there's other sorts of trust. There's the technology around it. Does the item you're presenting look legitimate? Does it look forged? Is it look like you would forge it? Often they'll ask for three pieces of information or four because there's no way you could forge four documents. That's going to be all with the same name on them. Never. But they over collect information to try to correlate them, and then they go off on their own systems and try to figure out, OK, did you present something valid, real? And then the other side of it is the governance. What is the authority that issued the credential? Are they trustworthy? What processes do they have before they issued that credential to you? And so if it says government of British Columbia on it, that might carry some weight. If it carries, we actually had a lot of experience with when we worked with the Law Society of British Columbia to, for their issuance, because people wanted to know, well, how does the government or the law society verify that the right person is getting the right credential, that they're actually a lawyer? What's their login process? Can you get an account and fake an account and so on? So do they have trusted processes? Paper credentials are what we're using in the digital world right now. We scan them and we send them off. This is a screenshot that somebody sent me the other day of Google's identity process for some sort of program they have, where they ask you to take a selfie while you're holding your driver's license, your government ID. And good enough, it must be you, because that looks like you in the picture. There's no way you could have faked that. So what we're trying to do is introduce a world where there's verifiable credentials. So credentials that contain the same information, the same thing that paper ones are, but have some cryptography and some processes built in so that you can verify it. So you've got the same model. You've got your issuer. You've got your verifier. You've got your holder. We added an element that I'll talk about a bit later called a verifiable data registry. So that's adding one more component. And I'll talk about it. The ceremonies, the transactions that occur are the same. An issuer gives to the holder. That's one transaction. The holder presents to verifiers. That is a separate transaction. And that's really important, that there's an issuance process. You get something. You get a digital document that's cryptographically signed. And then you share it with the verifier. I've removed the quotes around proves here. Who issued the credential? Who it was issued to? That it was issued to you and that you're the one presenting it. That there's a binding to you. Claims are unchanged. We've got cryptography for that. That's helpful. And the claims have not been revoked. That can be added if the issuer wants a mechanism to be able to revoke. I put asterisks on the who holds the credential because verifiable credentials come in different flavors. The one I'm talking about today in on creds includes that binding between who the credential was issued to and is holding onto it and then presenting it. That's inherent in the credentials. Not all verifiable credential models have that built-in mechanism for binding. Still required is, does the verifier trust the issuer? The holder, they don't have to worry so much about. It's virtually impossible to force these. We'll get into the math to show why it's virtually impossible to do that. But the verifier still has to decide, oh, this was issued by some school that I've never heard of. Do I trust that school? I may have to do research to figure that out. I can figure out who issued it, but I don't. But I have to figure out if I trust them. I wanted to highlight that this is different from the OpenID Connect model that you're familiar with, the login with Facebook. This is different in that the triangle is the same. It looks the same there. We've got a holder, it's labeled user, and we've got a verifier labeled relying party. And it looks the same, but it's different in that when the user is using their phone and sharing their credentials, they're actually telling the issuer, hey, somebody wants to see my credentials, send them over. And the line, physical line at the bottom there is the actual flow of data. So in a single transaction, all three of the parties participate and the issuer knows every time you do it. So the big thing we're trying to do, and certainly from a government perspective of what government of British Columbia is trying to do, is separate out those so that when you use your credentials, the issuer doesn't know you're doing it. And this is an important privacy and tracking feature that we're trying to eliminate. We want the verifier to be able to do, operate in a digital economy without the tracking of the issuer along to figure out what they're doing and how they're doing it. That makes sense. Okay. A non-creds is, as I said, a flavor of verifiable credentials. It contains a couple of features beyond generic W3C standard that go beyond So those things are selective disclosure.  When you present it, you can only show some of it. You can selectively disclose which attributes of the credential you want to show. A thing called predicate proofs. This is what we're going to talk about even more. All of this is based on zero knowledge proofs, but this is the most obvious that it's a zero knowledge proof, which is I prove that I am older than a certain age. I'm older than 19. Based on the date of birth that's in the credential without exposing the date of birth. So again, I get the check mark. Derived presentations. So I'm not sharing the credential actually when I use the non-creds. I'm not actually getting a credential and then showing it to the verifier. I'm actually deriving a new credential that I'm generating on the fly and then sharing it with the verifier. With that, I'm getting unlinkable identifiers. A credential, a cryptographic credential with signatures has a whole bunch of uniquely unique data correlatable to your credential.  You may share something that's unique about you. You may share your driver's license number, but you don't expose correlatable identifiers just by the act of presenting something. And then the last is multi-credential presentations. This is a big deal, which is. You can share, for example, our example in the Law Society that I am a lawyer and this is my government identity, my name from the government perspective and I can share those two things in a single transaction and prove that they were both delivered to me to the same wallet, to the same identity, same individual. Last thing I wanna touch on before I get into the math is verifiable data registry. So this is how the verifier doesn't call home to the issuer every time they verify and that is that before issuing a credential, the issuer publishes to some public place the key necessary or keys necessary to verify the presentation. So instead of the verifier getting the data and then calling the issuer to say, hey, can you tell me the public key so I can verify this data? It goes to some neutral place, often a blockchain. It can be a ledger, it can be a blockchain, but can be anything, can be a database, can be via an API, can be to DNS, can be to a web server. Wherever, as long as it's public such that the verifier can get to it. Make sense? All right, hyperledger non-creds, just a quick pitch is a project of the Hyperledger Foundation. There's a complete open source implementation plus the specification. It's been used for seven plus years. We've been using it and working on it for over seven years and then before that was a project called IDMix from IBM. The big change in moving it to a project and outside of where it's been is that it's ledger agnostic, meaning that part about where you store the key that can be anywhere. And that's what's expanded about this. We've removed a dependency on a particular implementation, Hyperledger Indy and made it generic. And by the way, with a single key stored on a ledger, you can issue a billion credentials. I do wanna make it clear that when a credential is shared, it's peer to peer. Nothing goes on the ledger or wherever at the time you issue it and nothing about the credential goes on the ledger. The one other thing is the issuer may revoke the credential again by publishing to a ledger, but that is not about the individual. So there's nothing that is put on a public place about individual data for a particular credential. Cool? Okay, why is it important? I put this in, hopefully, if you wanna take a look at the slides, I did wanna get these key points in. The big thing is we spend a ton, governments, I mean, spend a ton on physical identity cards and programs related to that. And sending out paper credentials, passports and driver's license and have fancy technologies to make sure you can't forge them and so on. That same idea is needed for digital credentials and so we wanna build out that capability and we think verified digital trust is extremely important and verifiable credentials is a great model to do it. We think it will be the model. Okay, now we switch. Now we're into the math. Okay, this is the fun part. High school edition though. We're not getting into college here. What is a zero-knowledge proof? I've already talked about this, a method by which a prover can prove to another party that they know a value of X, but without sharing X. So they know the value, but they don't wanna share it. So the value is in the credential and they wanna prove something about it, but without sharing the value itself. Core of a non-creds, the classic examples, but actually a non-creds uses it in a whole bunch of places. So the holder knows some piece of information, wants to prove it to the verifier, but without exposing any other information. The verifier doesn't know X, wants to know that the prover knows it, but doesn't wanna know the actual value. So let's start with Waldo. How do I prove that I know where Waldo is without telling you where Waldo is? You know how to do this? Take a big piece of paper that's at least four times the size of the Waldo picture. You move the Waldo picture around such that in a little hole, you can see Waldo and now I can prove I know where Waldo is, but you have gained no knowledge of where Waldo actually is. I then remove it, show you the picture again, you don't know anything, you haven't gained any knowledge. That's a zero-knowledge proof. We haven't even got to high school. This is the nursery school edition. Okay, so I start with this picture. Do you know who, well first, do we know who Waldo is? Are you familiar? Okay, we're familiar with who Waldo is. So somewhere in that picture Waldo exists. I wanna prove to you I know where Waldo is, but I don't want you to know because you'll just show off and show other people. So what I do is I take a big piece of paper and then I don't move the paper over Waldo, I move the picture of Waldo around so that he's in the little box. And then I've proven to you, because you can see, oh, yep, that's Waldo, but when I move it around and take it back, you still have no idea where he is. You didn't gain any knowledge. You know that I know, but you didn't gain any knowledge. Cool, nursery school edition of, so attributes, the proof is actually probabilistic. It's not deterministic. So you're actually proving it's very likely and where likely is, you'll see what I mean by likely. There's a level of randomness in it so that I'm essentially as the prover stuffing some other information, random information that is what prevents you from figuring out what the actual value is, but it used enough to prove that I know it. And there's two different forms, basically interactive and non-interactive. And so we're gonna talk about interactive and non-interactive proofs. Three requirements we're trying to get to, completeness, soundness, and zero knowledge. Completeness means if the statement is true, the prover can be confident it is true. If the statement is false, soundness, if the statement is false, nothing the prover can do can make it true. So if you have a date of birth and you're under 19 and you're trying to prove you're over 19, you will not be able to do it. So soundness and then the last is zero knowledge that no additional knowledge is shared in the zero knowledge proof, okay? So we're gonna call four things. We're gonna cover functions and inverse functions. We're gonna cover exponents, modulo operator and prime numbers. So this is your warm-up course for the part where we get to the zero knowledge proof. So a function, given a value X, I transform it in some mechanical way. And so it's basically a machine where I put an input in and I get a transformed output out. First one there, X plus two. So if I put 25 in, I get 27 out. Easy enough, functions. We remember that, right? Inverse functions. This is where you did the manipulations to reverse it.  You remember that? So an inverse function is where you are reversing the function you started with so that when you take the result of the function, you got back the original value, okay? That's what we don't want. For ZKPs, we want exactly none of those. We want a function which has no useful, is impossible to invert. You can't take the output and come back to what the original value was, okay? Function, inverse function, good? Okay, exponents, remember these? Two to the third, two times two times two, easy. You remember those? X to the five, five Xs. There's a couple of laws of exponents and this is actually where you're gonna see the magic happen is in these. X to the zero equals one, right? Remember that one? X to the one equals X. You just knock it off, X to the one. X A times X B is X to the A plus B. And then the last one, X A to the B is X A times B. So we're gonna use these in a bit. So you might come back to this when you're looking at the slides after and seeing it. Modulo, do you remember modulo? That's pretty easy, right? Modulo is simply the remainder when you do a division. So if I, in this case, divide, take 321 and modulo 17, I divide 321 by 17 and I ignore what the result is and I take the leftover, which is in this case, 15. Modulo, good. For some reason that I don't quite get but it's common to use a clock for this analogy for modulo, so I don't know. I left it in the slides just cause it was okay. Exactly, and then you knock the 12 off and it's modulo. There you go, modulo 12. All right, good. I think this was the last one, prime numbers. We all know those, divisible by one and itself and nothing else. And so there's a long stream of them, a very long stream of them, infinite number of them in fact. Okay, so no math. We're gonna talk about Alibaba's Cave. How many, I don't care how many of you have heard of Alibaba's Cave, we're still gonna go into it. This is an interactive zero-knowledge proof based on probability. So, Bob, we gotta have Bob and Alice, right? Cause it's a credentials thing, you always have Bob and Alice. So Bob's a verifier, Alice is a prover, we've got Alibaba's Cave and it's got a magic door in it and the magic door has a code on it. Alice knows the code or she claims to know the code. And what the code allows her to do is go through the door. So what Bob is gonna do is gonna ask Alice to go into the cave without telling him which path A or B that Alice is gonna take. And then Bob will say, Alice goes in, she went in the A side, Bob will say, come out the A side. And Alice goes, oh thank goodness, I went in the A side so I can come out and I can prove I know it. I know the code. Well, that's not gonna convince me. You do it once, you're not gonna convince. You got a 50-50 chance, right? So now you do it again. Alice goes back in again, she picks the same one but Bob says, come out B. Now, if Alice doesn't know the code, she's sunk, done. After two iterations, she's done. But if she knows the code and she went in A, she can still come out B cause she can go through the wall and come out B. So now two iterations have been done and Bob's gone, wow, seems like she might know that. Let's do this a hundred, well, 20 times. Let's do it 20 times. And if Alice is every time able to do this where she randomly goes in and picks one side or the other and Bob tells her to come out one side or the other, Bob can be pretty sure that Alice knows the code, that she couldn't have guessed every time which is the right one. So there's the rounds. Obviously any time this talks about what Alice chooses, what Bob chooses, if you do this N times, you're gonna be pretty confident. And the first time Bob picks one and Alice went the other way, it's immediately obvious to Bob that Alice doesn't know the code. So it turns out, I thought it was on that slide, but anyway, completeness, if Alice honestly knows the secret code, Bob will eventually be convinced. They'll have done it enough times that he's convinced. If Alice doesn't know the code, it's gonna be very obvious pretty soon.  And Bob doesn't learn the secret code. He doesn't know it, Alice still knows it, but that's it. So let's do it without the math. We need a one-way function. This is where we get into how to do this with functions. So the function we're using is G to the X mod P. And that's actually a common function I think used in lots of other things, but this is the thing. G and P are public and known values. So both Bob and Alice in this case, no G and P. X is the thing that Alice knows that Bob doesn't know, okay? So that's our function that we're gonna use. Hopefully we all remember the math we just went through. It is virtually impossible to go backwards to find X with that formula, with that function. So the summary of the steps, Bob and Alice agree on G and P. They share that, eh, good enough. Alice knows X, and she tells Bob F of X. She does the math to come up with F of X. As we said, can't be a reverse, so that doesn't help Bob. Bob doesn't know X from that. Alice generates a random number R that she keeps to herself, whoops. Calculates F of R and tells that to Bob. Okay, so now Alice knows F of X and F of R. Then Bob randomly sends Alice a number C that is either a zero or a one. Now this is where we come into those exponential things that work. Alice defines a new variable, V, which is R plus X times C. So she takes the R that she knows, she takes the X that she knows, and she takes the C that Bob gave her, and then she does the, again, runs the function, runs V through that function. Shares it with Bob. Bob is able to check knows F of R, Alice told her, told him, knows F of X, knows C, because he made it up, and then also knows F of V, and so he does the math to figure out, do those all line up. And if that is, then Alice passes. Woo-hoo, Alice knows it for one iteration. So here is the math, that if we go back to our, you know, exponents piece. So that's the formula checked by Bob. So if we expand out F of R and F of X, we get our original GR mod P, GX mod P to the C, which by going back to our exponents G, which is G to the R plus X times C. We've just altered the way we've calculated it. And by doing that, we see that G to the R plus X times C is the same as what Alice calculated. And so without knowing X, without knowing R, Bob is able to determine, yep, she knew it. So this is a list of the variables involved. X is say four, nice small number. G is five, P our modulo is gonna be a prime number. G can be any constant, P has to be a prime number, so we wanna use that, so we're gonna use 17. Then we just do the F of X calculations. So G to the X, which is five to the fourth. Modulo P is 13. R is the random number that Alice collected, chose. Same thing again, we do the same calculation. And then Bob sends either a zero or a one over, random choice, there's our randomness coming into this. So we've got our randomness and our probabilistic is coming into it. And then the result of V depends on what C is. The case one, if C is zero, you'll see that Alice sends Bob V of F, which is 10 and the calculation is done. Bob's able to do the calculation and it matches. If the case two, C equals one, is done, the math also matches. So again, homework, you can take this back and verify for yourself that this all works. So that is the core of it right there. That's how you do it. Cool? It's kind of fun. Alice knows X, she can always give, oh, and by the way, oh yeah, Alex knows X, he can always give the right response. Alice doesn't know X, she has a probability one half of giving the correct value. So correct only if Bob sends a C equals zero, for example. So doing it once doesn't really get us there. That probability part isn't there. We do it 20 times and Alice has a one in a million shot. So we start again, X stays the same, but R becomes different, C becomes different. And so we do the calculation over and over. And so back and forth, Alice and Bob are going 20 times. And after 20 times, the probability is one in a million that Alice has been guessing what Bob would do every time and sending the right value. Okay? Now imagine we're trying to do a zero knowledge proof in daily life and Bob and Alice have to go back 20 times. Think of the API you would use back and forth 20 times to figure it out. So interactive, yeah, it's not gonna cut it. So this gets a little more complicated of generalizing it. So first of all, instead of choosing C between zero and one, just doing it every time, C is between zero and P minus one. Remember, P minus one is our prime number for our modulo. So in our case, we chose 17. So C is now gonna be between zero and 16 in those. And every professor, Saka is a Japanese professor who actually I stole lots of this from and enjoyed listening to while she presented it. She did a really good job. That represents each bit in C is an instance of a zero and one iteration. So this, and think back to this when I show you what P looks like of how many bits of information are in P when you see it. I'll be showing that in a bit. But it reduces the number of iterations necessary. If I've got 20 bits in there, I only need to do one iteration and I can be pretty confident that that's gonna be known. But even one interaction is too many. We wanna get it down to Bob sends a request, Alice sends a response and that's it. We wanna get down to just one back and forth. So this is what makes it non-interactive. It's a little bit tricky. Bob specifies a hash function H and a random number I. So the random number is the new thing that gets introduced that Bob asked. So instead of asking for C halfway through the process, upfront he asks for this function H of F, H and I. I is used to prevent replay attacks. So a familiar thing in doing cryptography is you put some variation into every interaction you do so that nobody can listen in, hear a response and then reply with the same one, replay what worked before. So I makes it every presentation unique. So that's how we get there. In real life, X doesn't have to be a number to start out. So one of the things is ultimately in a zero-knowledge proof, always X is a number. But X could be a string that you hash into a number and now you use that number as part of the zero-knowledge proof. It constrains what you can do with it. So for example, you can't prove your date of birth if it's in a string as a predicate, but as long as it starts out as a number, you can do predicates on it and things like that. But you can always do things like selective disclosure, not revealing some of the value, some of the attributes, while still proving the entire credential, proving all of the attributes that you have them all, but without revealing some of them. So you can use that. Then numbers GP and C are really, really big. So that's what P looks like in an Anancred's presentation. It's a very large number. And remember I said C represents the number of bits. That's a lot more than 20 bits. So you get the probability is a lot less than one in a million that you've got it, which is of course the whole point. So the proof is, even though it's probabilistic, the chance of fooling it is pretty low. That's what G looks like. So P is the random number. C is arranged from zero to one less than that. And then G. So ZKPs in Anancred's binding and identifier of the holder. So this is where you can put an identifier for the holder. The holder can share and prove that they know how that credential was bound to them. They know the secret that's in there, but they do it without sharing that binding identifier. So there's not an identifier uniquely identifying the person. Normally in non-zero knowledge proof credentials, you would put an identifier that the owner of it can prove they have control over. Some, you know, you might put a public key in there and then get the verifier to prove they know the public or the private version of that. That's a unique identifier. We don't want that, so we use blinding for doing that. We can blind all of the data values for selective disclosure in a similar way. Predicates and revocation, I didn't go into the details of how that gets done, but you can take a look at that and go into that. Bunch of references here, in case you wanna look it up. Glad to have, you know, people can read these. These tend to be more accessible than the academic papers. CL signatures, academic paper, that is the non-high school math edition. It's ugly, oh. But it's there, you've got a link there, but you've got other ones here that are more accessible. CKPs in real life, why do they matter? No shared new identifier. This is big for government. If you think about a national identity number, SSN in the United States, an SIN in Canada, that's legislation. There's big, you know, it requires rules to be established by elected bodies to put these things into place. If we have to introduce new ones to put all sorts of new identifiers in for all sorts of individuals and organizations, that's a bit of a problem. And so we don't wanna do that if we can avoid it, so it allows that. Also gets us to that non-correlation, that unlinkability. A verifier receives proof of a credential, a second verifier receives another, and they can't correlate the identity across them. Crucial. So you've got unlinkability from the issuer, but you also have to cross all the verifiers. That's really important. The techniques you've seen of selective disclosure and predicates for minimizing the amount of data you're sharing. So you can prove something with whatever is necessary. So walking into a bar, you do not need to disclose the color of your eyes to get a drink in a bar. It's just not needed. Yet we do it every time. Well, I don't, but that's what we're doing, is showing all, and more importantly, showing the address we live and all that stuff. That is totally unnecessary, and so we wanna minimize that. Often it's done not because it's needed for the transaction, but it's needed for the verification that the person has to go to offline to figure out who you are and whether you really are, who you say you are, and all sorts of other checking that you're gonna do to figure it out. By getting the data from a trusted source, from a verifiable source, we're able to collect less data. We only need to collect what's necessary for the actual transaction. And then a lot of it is fighting back against online tracking. We really would like to take a dent in that, which is, again, coming back to this unlinkability. We don't wanna have, in the case of the government, tracking every bar you go into, and every time you buy cannabis, and so on and so forth. There are all sorts of reasons for not doing it, but that's a super good one, is we don't have it when we use a paper credential. We wanna be able to operate online digitally, but we want the same privacy and protections we have when we're using a piece of paper. Talked about these things. Duplicate slide, nice. Mentioned predicates used as bullet proofs, and revocation used as accumulators, so for those who know some cryptography, that's the techniques that are being used. Wanted to highlight this one. This is one of our participants in the Hyperledger community. They are doing decentralized finance, DeFi application, where they are actually putting a verifier into a smart contract. So the verifier that I talked about would use that. Basically, when doing an on-chain transaction, the user who is trying to execute the transaction might provide KYC information via a zero-knowledge proof based on a credential they were issued. So who issued it and so on, and whatever minimum data is necessary to be collected could be collected as part of the smart contract, which could be just enough to say, oh, I'm a citizen of Canada. That might be enough. And then they can proceed with an on-chain transaction. So super interesting, got links in there to the company, their product, and then a video. And they just had a hackathon this past week that was evidently super interesting and leading to that. Everywhere paper credentials are used, this is a possibility for replacing them. And I think this is why I think it's inevitable that this will happen, this will be the way we'll be doing it in the future. It's the question of how we get there, how soon and how accessible it is to everyone and we make it work for the vast majority. But there's lots and lots of use cases. So call out, join Hyperledger and on creds. You can deploy your own agents using Aries, Hyperledger Aries. You can get a wallet like John mentioned in the keynote from the government of British Columbia. You can download from two of the app stores, but there's a bunch of other ones as well. So you can give it a try. And then see how it fits into your own project. I forgot to, and I'm bad at this social media stuff. I'm doing a workshop on May 31st. So if you wanna get into details of how actually Hyperledger can be used and actually play around with credentials and use them, I am doing a workshop with Hyperledger that's remote on the 31st of May. So coming up soon. There we go. Thank you. Thanks for attending. Any questions? I didn't leave a whole lot of time, but I got through all my slides. So yes. Thanks.  And Mike, I'm very excited about the proposition of not selecting a disclosure. It's the biggest advantage of this I find. And, but I'm also very of, like really a government institution being able to truly allow for a decentralized, you know, like I'm surprised and I'm amazed and perhaps happy that you guys are leading the charge as part of the government. But I wonder, so my concerns around this thing that I wanna, but I feel like you're already addressing but I wanna confirm it, is things that are unlinkability and tracking. So I'm very personally like, my concerns are surveillance, of course tracking all the movements. Like you can't do that with your IP ID, but you can certainly do that with digital ID, your phones, whether it's on device stuff, in the mobile app that the government designs if it's not on the ledger itself. And also the idea of like a revocation so you can just sort of immediately like, you know, like with the truckers, bank accounts gone, ID is gone. Now you're just like stranded on like the middle of the road. So I'm wondering with unlinkability, is that part of this solution as part of the government plan? So yeah, so a couple of things there. Nothing personal or anything else goes on a ledger. Nothing. So the only thing that goes on a ledger is something an issuer wants to broadcast the world so that you don't have to go to the issuer to get it. So that's one. The wallet is a concern and that's why BC is open by default. The way we can do that is have the wallet be open source code, auditable, verified by others. They can see what's in there and how it gets deployed, how it gets used, what happens within it. The correlatability of the surveillance, 100% it is that breaking up of the transaction of the issuance to the holder and the holder using it with a verifier. We want that separation. So we're really passionate about that need to separate those things out so that there isn't that ability to do that surveillance. Really reduce it. As you say, like cell phones, you know, location tracking, we're not addressing that. What we're trying to do is if you use a credential and in our case, we're worried about a government-issued one, we wanna have that separation, that non-tracability. And so we try to do it both. The issuer doesn't know where you've used it and then verifiers can't correlate you across others. With the caveat that if the information you share makes you correlatable, so we just make sure that just by presenting data, there's nothing correlatable in there, that every presentation is completely unique and useless to try to consolidate across. So I have a follow-up with that. Those are awesome pieces of information to get. On the side of the app, so for example, one way around the surveillance thing, assuming that for some reason, you can't trust the open source code of the wallet, is being able to access that information throughout, like without downloading the app, without the view, through some kind of interface that you can just, like the metaverse, that the blockchain that's out there, you will be able to access in your own personalizing. Let's say I create like my Xcode app and that's my wallet or everyone else, like it does through an app in WebAssembly or something, is that possible? And the other thing is that on the host issuer, say the issuer verifier, host verifier side, is what about the host? Like what, like I know you said like, no personally identified information is there, but like, do they track, yeah, I call us to them or whatever, it's like, you know, there's easy ways to say, hey, and this bar, these IDs are being queried, so someone could be like, just like, like, traffic monitoring traffic of a, like, wire network, gather and all that. So the answers to that is basically, open source can be done anything. So yes, you can build your own wallet, you could host it. Now the intro, or you could then use it. The interesting thing there is, as a government, do we wanna trust a wallet that is randomly showing up? So we expect that the way that will be done is for now, we're only issuing to the VC wallet, not because we track with it, but because we know what's in it. We've done the analysis of what's in the code. If you bring a random wallet in that somebody gave you, it could be tracking you. Hey, you just made a phone call from a police station. Would you like me to get a lawyer for you? You just used your, you know, we don't want that kind of use of it. So what we expect is there will be other wallets that others will be able to do it, but they will have to be compliant with and prove that they can be in the same trusted way. So that's more or less that one. The host issuer verifier, I mean, the whole point of the verifier can always monitor what they're doing, we're trying to make it so that they can't correlate across presentations. What other things they can collect, what other things they collect today? Less control over that. I don't mean the verifier, I mean the other side. Yeah, the host can't, the host can't. Sorry, the issue. What is the host? Like I'm curious actually, because I feel like I, again, I'm not a math person, I'm more of an application engineer, so I use all these things and I never understand them. Sorry, what host do you mean? So the host basically, where the information is stored for the verifier to connect to instead of the issuer, but that's the host, the device is the host. Right now in what we're doing, it's all right there. It's all offline. Yeah, it's all peer-to-peer with your device and that. This is our way of, say, allowing you to have a server that holds your own data. Okay, so the host, so when the verifier in front of you is talking to the host. They're talking to your machine. Got it, got it. Yes, yes. You've got a peer-to-peer conversation going on. Another part, you know, I mentioned Aries, another part of it is it actually uses other cryptographic techniques to establish a secure end-to-end encrypted session between you and the verifier. So there's the ability to establish a relationship between you and, say, the government, or you and your bank. One of the interesting uses of that, I'll just throw out another little tidbit that might interest you, but having that trusted peer-to-peer relationship kind of like signal between you and your bank is, you know those SMS you get and email you get from your bank that say, hey, you need to log in and do something or, you know, nobody. Trust those anymore, right? Throw them away. Email's not trusted. SMS is not trusted. You really need to know and think and you get trained not to respond. Well, if you actually could use the BC wallet to send messages, the verifier, after they've established a relationship with you could send you messages via that secure encrypted channel. You might be able to trust them again. Organizations have huge value in being able to say, hey, we can actually have a channel that we can use that our customers could trust. It's a big deal. And I'll pass this back on to the last thing, which is the authority, like establishing authority for issuers. Yes. Do you imagine that to be, imagine the government? No, so that will be sort of domain oriented.  Their authority is the organizations of colleges and universities within that. Mining community has the London Metals Exchange, as a, so all sorts of places. Like the public key, like the public key. Oh, those are where people choose to do them. Some of the, you know, right now, Microsoft offers a service that allows you to put, route them in Bitcoin. They can be Ethereum. There's Ethereum based. We're using a ledger that is operated by a set of known parties. So it's a, what's called a permissioned ledger. Everyone can read from it, but only certain people can write to it. And so it's permissioned in that way. But a Bitcoin based one, anyone could, could write to that time. Okay, let's get out of here.


So a quick update for console players of Pow World, the latest patch has just dropped, if you missed this it actually released late last night on PC, but today guys for Xbox players mainly I'll give you another rundown on the patch notes and hopefully the fixes many of you may be having. How's it going guys, my name's DPJ and if you do enjoy the video leaving a like really helps out and if you like what you see and want to see more, be sure to subscribe. Okay so this patch dropped last night, well the patch notes dropped last night, but the steam patch dropped with the patch notes, Xbox had to wait. So yes and many of you may have missed this so let's just go through it quickly again. Okay so both patches are now out but if you missed them these are the patch notes. Major fixes, fixed an issue where the game would always crash and save data would be corrupted when a total number of powers captured by the guild reached approximately 7,000. Okay so in the previous patch saved data that had already been in this state for servers to servers world data remained in a broken state that made it impossible to load, but after applying this patch it will be resolved and will load properly. Fixed an issue where some weapons equipped by other players would disappear when a player used a grenade in multiplayer. Fixed an issue where although the displayed capture probability increased when the capture power was strengthened with Lithmuc effigies, the capture probability did not actually increase at all due to an internal processing bug. I'm so glad that one means thick people, I suffered with that. Base related, fixed an issue where if a power was manually assigned to a breeding farm that went to sleep it would not wake up forever. I mean I don't know why that makes me laugh inside but it just does. Okay so yeah that's fixed now. Fixed an issue where no wood would drop when a pallet base found a tree. Okay so on to others. Implemented countermeasures against some cheats and exploits. Good to see. Hopefully they keep working on this and then they say we will continue development placing top priority on fixing major problems and issues. Thank you for your continued support for power world. So there we have it guys that patch has now been dropped on Xbox. It was already released on PC but if you're a console player I expect an update. I think on PC I'm not sure it was like a couple of gig if that. Probably won't be that much on Xbox though but yes the patch is now live guys hopefully it resolve any issues you may be having especially with all save files because I'm seeing I've actually got friends that I suffered with this too. So there we have it guys if you enjoyed the video leave a like really helps out if you like what you see and want to see more. Be sure to subscribe and hopefully guys I will see you on that next one.


Now, let us get some intuition on the behavior of the stocks. As I told, now we have kind of learning how to define stocks and flows. Now, let us try to see what will be the behavior over time, the entire thing is called system dynamics. Dynamics mean evaluation over time. So, let us see when this values are the input stock if it or the flows when it changes then what kind of behavior we can expect in the stocks. And we can do that graphically we do not really need any match to it so that we can build a intuition. So, this given the what we want to say compute the behavior of the stock given the flow rates we know how the flows are happening what is happening in the stock that is called as you know we are just integrating it. So, we can do it graphically. So, before that we will try to understand what is it that we want to do. Let us consider simple example like this I have a stock and I have a net flow into the stock ok. So, what we see is x axis always time unless otherwise stated. Suppose the flow rate is changing like this over time we want to see how the stock changes. Flow rate suppose changed from say time t 1 to t 2 the same time t 1 to t 2 we want to figure out how the stock changes. Flow rate is positive let us assume it is positive let us take this as 0. So, we expect the stock is going to increase correct. How much will be the quantum of increase let us not worry about the shape let us just take it like suppose it change like this. So, what should be the quantum of increase the change should be the area under this curve that we have taken let me draw a more simpler example. Let us take flow time t 0 10 20 time minus 30 y axis says 0 10 and 20 let us assume the flow is 0 then there is a rectangular pulse from time 10 to time 20 and then again it falls back to 0. So, there is a rectangular pulse is given as a net flow into the stock. So, let us assume this is the behavior of the flow over time. Now, you want to plot the behavior of my stock over time let us assume my initial value of stock is 100. Let us assume the initial value of stock is 100. So, until time 10 what will be the value of stock it is going to remain the same 100 there is no change in flows. So, for this refer this diagram the net flow is 0. So, that means, the value of stock remains at 100. So, here we are going to assume initial stock is 100 units ok. Until time 10 it is 100 then what happens from time 10 to 20? It will increase how will it increase?  It is going to increase it is a ramp function it is going to increase linearly right until value of what? What will be the maximum value of the stock? So, it is going to go up to 300 and after that what happens at time 20 onwards 20 to 30 again this falls to 0, but the stock remains unchanged. Stock does not fall to 0 stock continues at 300. You can assume time step of say 1 1 minute say assume time is in minutes. So, it is quite easy. So, every minute I am adding 20 units into the system right from here time 10, 11, 12, 13, 14. Time 11 I have added 20 units at time 12 I have added another 20 units. So, from here from time 10 to time 11 it goes from 100 to 120 then go to 140, 160, 180 to 200, 220 to 40, 260, 280, 300 right. So, every time step I am getting a the equal amount which is being put here is added here. So, this now coming back to the figure here. So, what happens is as the flow changes over time from say time t 1 to t 2 this area will be equal to this change. The change in the stock value will be equal to the area under the curve for the flow rates ok. This is kind of the change in stock is equal to area of the under the flow rate between the same time interval say t 1 to t 2. So, this is why we actually say that this stock has memory. The stock stay remains at the value of 300. So, that means it has a memory of all the past events that has occurred. It has accumulated it and now stores it at the value of 300. So, that is what we refer to as memory. And there is inertia unless the flow changes nothing influences stock, stock continues to remain the same. It does not leave it any time or it does not increase automatically it continues to remain there. So, that is what we indicate by the word inertia. Yesterday's lecture I talked about stocks are influenced by inertia and memory. So, this is what I meant. So, let us look at a more interesting example. Let us just quickly escalate it for the graphical integration. Let us look at a more example. So, same example earlier. Assume this is your net flow now. You have all rectangular pulse the net flow is now a ramp function it increases and it decreases linearly to time 30 at to 0 and then it goes to minus 2 then again comes back to 0 and then it remains 0 from time 50 to time 60. So, y axis goes from 0 1 and 2 0 minus 1 minus 2 that is the y axis and this is the input function given. So, how will the output stock look like? I am just going to mark the time units 10, 20, 30, 40, 50, 60. Assume the initial value of stock is 0. If it is not specified assume it is 0 ok. We will assume the initial value of stock is 0. Then what will happen to stock from time 0 to 10? So, the area under this is 20. So, it has to go to 20. So, since I already had 20 let me since I am not sure how the dynamics are going to go later let me just make intervals of 10, 20, 30, 40, 50. Let us see what happens. So, we expected to linearly increase to 20 that is the value of stock very same as the previous example right ok. Now, what happens? From time 10 to 20 what will happen to the value of stock? What will be the value of stock at time 20? 30. 30. What you do is you calculate the area under this curve half into base into height that is 10 units. So, you are already at time at not time. At time 10 you are already at value 20. So, 20 plus 10 you are at 30. So, you are going to reach 30, but how are you going to reach it? Which side is it going to be like this or is it going to be like this first one? So, simple reason the rate is increasing from time 10 to 11 from time 10 to 11 only small unit is added to your stock, but from time say 19 to 20 large quantity is added to the stock right. So, the amount added here the growth should be higher than the amount here. So, that can intuitively ask us to draw a curve like this. Anyway this is 30. So, it is not that accurate with this figure, but it is 30. So, what happens from 20 to 30? Increase or decrease? Stock will increase. The flow shows a decreasing rate, but still every time unit some positive quantity is added to the flow. So, as long as there is a positive quantity look at it it says net flow. Net flow means inflowment is outflow. So, if it is positive means it is being added to the stock. So, large quantity is added first and then at every time unit smaller and smaller units are added until it hits a total of 40 because area under the curve continues to remain the same at 10. So, now the curve goes like this. So, this is 30, this is 40, the y axis value is 30 and 40 sorry. Then what happens from 30 to 40? Now, net flow is negative that means, I am removing from the stock. Again what is happening here? I am removing less quantities and then I am removing large quantities. So, the shape will be I have two only options either this or this one. Yep comes like this and then again though the flow net flow is actually increasing, but it is still all negative values. Again I remove large quantities initially and then bring it back to these quantities. So, this values will be again back to 20 and then since there is no change in flows it continues to remain straight at 20. Calculate net flow. Given a net flow we can integrate it nicely, but when we have both inflows and outflows given separately like this figure, here the inflow starts at 10, it is constant to 10 until time 15 and then time 15 to 25 linearly decreases and 25 hits 0 and remains constant at 0 till time 30. Outflow starts at 20 then drops to 10 at time 10. Then from time 15 onwards it decreases at a constant rate until it hits minus 20 at time 30. Once you have the net flow we can always calculate the this one stock. So, we will learn how to calculate the net rate. Again x axis is time let us do 5, 10, 15, 20, 30, 35. What we want is net flow. So, from until time 10 anyway both inflow and outflow are constant. So, what should be value of net flow? What is the value of net flow? At every time instant you are taking the difference right. So, it will work out the same thing. So, inflow is 10, but outflow is 20. So, net flow becomes minus 10. Net flow is minus 10. So, this is your net flow to minus 10. It is just inflow minus outflow 10 minus 20 is 10. I am just taking subtraction. At this point both inflow and outflow are the same. So, that means net flow is 0. I am not neither adding nor subtracting. So, this has to jump back to 0, up to time 15 is 0. Now, it becomes tricky. I am having a linear decrease in both outflows as well as inflows. So, what should be the value? How does it increase? Now, you start worrying about areas. I have here because the same thing. So, you just go say one time step norm or rather up to time 20. At time 20 outflow is reduced by so much and inflow what is the area under inflow and the area under outflow we do the subtraction. Area under outflow from here to here is 25, half into 5 into 10 is 25. Area under inflow, inflow graph if you see you have a rectangle here and then a triangle here. So, from time 15 to 20 area under outflow is half into 5 into 10, 25 units area under inflow is half into 5 into 5 plus 5 into 5. So, you get 12.5 plus 25. So, inflow minus outflow adds about 12.5 units into a system because inflow is higher than outflow. You are following how we got it? So, this is the area under the curve of inflow and this area under the curve for outflow. So, time at this time point in time I am having it. So, another 12.5 units are added. So, the net flow then becomes 12.5 here and we are doing the math correct and the same slope comes here. So, I am going to get a line something like this here. And here there is no inflow, but outflow is negative. So, negative outflow means you are adding to the system. You know there is a negative outflow means you are just adding to the system further then you are removing from system. Here you are adding and here outflow is also positive. So, you are adding here and removing here. But when outflow become negative that means you are adding at two places you are adding here plus adding here. So, actually this slope becomes higher and here I am not adding anymore I am adding only here. So, I will get a flow like that. So, it kind of has a crazy pattern right there. But if you got the concept. So, what you are trying to do here is calculate the net flow first and then using the net flow computed because if net flow is constant then I know it is a linear increase in stock. If net flow is increasing then I know it is some sort of parabolic function whether it is and I get different shapes in the stock. So, once I get this I can get the other one. So, that is one more math involved that is area covered under this curve. So, that equals this. So, then what you essentially have is it increases up to 0.5. So, pretty much your net flow will go up to 0.5. So, this has to be at 0.5. You hear it? It is inflow and outflow net area is 12.5 correct. So, 12.5 means the time unit is fixed half into base and time unit is fixed. So, I have to multiply it by the height which will be then equal to 5 right, height equal to 5. So, that means, the time 5 is when it goes in area. So, then you calculate the other one. So, here the only thing is the slope will increase because this is also getting added and this also gets added because then and here then slope will be lesser than the previous level. It will linear function. So, this point is at 5. So, this also has to come at 5. 5 it is fine it is a linear function it will work out the same thing. So, it will change at 25. Let me get rid of this part. So, let us do our line here. So, let us keep it 5. So, it goes up to 5 here and then so, the slope should not change then it should go to 10 and then it will change to 20. Is it what we are getting? See this it was a linear example. So, it was easy. Suppose this net flow itself had an hyperbolic things then we need to kind of double check it, but for this case it will just work if we just take the differences and start plotting it. It should work yeah it should work. Now, let us do one more example. So, this example is kind of trivial given given your stock compute flow. So, this is called as graphical differentiation. Given a stock we cannot compute inflows and outflows separately. We can only compute net flows only net flow computable. We already know it for this trivial case. What will be the values here? How will it change? Time units goes from 0, 4, 8, 12, 16, 20 etcetera. So, 0 to 4 eventually increase has been 40 linearly. If it is a linear increase in stock then it must be a rectangular constant value for this. It has been increasing. So, it must be 4. So, it must be 10, up to time 4, 8, 12, 16, 20. So, up to 4 then it must be constant at 10. From time 4 to time 8 it reduces until it hits 0. That means this flow has to be negative. Let us take minus 10 then flow has to be constant at minus 10 then again there is an increase. So, it must be constant here up to 12 then again there is a decrease it is this 12 then again there is an increase and so on. All what we have is a kind of just a linear input to changes constant, but you can see the dynamics that is happening just by the input. Input is constant like the net flow is constant is always at 10 and then again it comes to false to minus 10 and again increases to less 10. And even with that simple inputs we can find that our stock keeps fluctuating in this fashion or the other way the stock fluctuates in linear fashion that all it tells us is the net flow is actually constant. So, this is an important the idea here is not this graphical integration difference common you guys can easily do it it is you are not here without trying to figure out what how to do differentiation integration and visualize it. The idea here is when we start looking at actual pictures and graphs many times you will be finding many such you know graph such keeps increasing and decreasing over time. The main thing to understand is it need not be because even the entire thing is changing even if things are constant and even if fluctuating at only two different end points still it can give a kind of a sawtooth kind of a behavior or a kind of hill kind of a casino sort of behavior can be seen just by keeping the values constant. So, those kind of intuition is what we need to tell you.


i gyfaint iawn i'n ddal yma, i ddwy gyd mewn gwag cyfaint eich Maehera. OK, felly ydych chi gyd yn ymdweud, mae'r ffordd iりw'r disgthiwn i'r dim'r ffordd hyn. Gwyn i bobl ydych chi'n gweithio, wrth gwrs, o'ch bydd gweithio gwybodaeth ar gyfer hwn neu яlyw'ch ac mae'n gweithio'r newid hwm, ac mae'r newid hwmionau, yng Nghym Rhaid, Edward Craig, Galen Strawson, rhaid i'r gweithio'r newid hwm yn y gweithio'r gweithio'n gweithio'n gweithio'n gweithio'n gweithio'n gweithio'n gweithio'n gweithio. As I've been explaining Hwm, I take it that his two definitions are intended to capture all that we can legitimately mean by causation. But according to the new Hwmians, there's something more, and Hwm believes that there's something more in objects. Incidentally, Peter Cale is also somewhat in the new Hwmian camp, though he takes a rather more agnostic line on whether Hwm actually is a believer. That's why I haven't mentioned him here. But there are quite a few others as well, Donald Livingstone, Janet Broughton. It's been quite a trend in recent years towards interpreting Hwm in such a way that his two definitions are not really intended to specify what causation is, but rather something like all that we can know of it. Now the main argument I think that has pushed people in this direction to suggest that Hwm thinks there is something more to causation than is in his two definitions, is to do, I think, with the extent to which Hwm is committed to causal science. So the assumption has been that if Hwm is a real believer in causation, then he must be a believer in real causes, and real causes, we all know, are more than his two definitions. I think that's wrong. I think Hwm does think that a real cause is just what his two definitions say, but I'll argue for that shortly. If you come across the term skeptical realism, that's often used for this point of view. Realism, because the claim is that there is something to causation going beyond the two definitions, typically described in terms of a priori inference. The thought is this. When a causes b, a has some property, we have no grasp of it at all. We have no impression of this property, but we suppose that there is some property in a, which is such that if we knew of it, we would be able to infer that b would follow a priori. That's what a real cause is, a real necessity. That's a kind of logical necessity in there, but it's beyond our grasp. So it's skeptical realism because it's realist about that kind of necessity, but skeptical in the sense that it denies that we have any real grasp of what that kind of thing would be. So what I want to do now is first of all make clear that there is something to the case that the new humians have put, in that one ought to recognise that Hwm is very much committed to causation. In other words, the impetus behind that view I think is absolutely correct and has provided a useful corrective to those who are inclined to say, well, Hwm isn't really a believer in causation. He clearly is a believer in causation and he's a believer in causal science. So four particular points I'm going to go through here. First of all, Hwm says that causation is the basis of all empirical inference. He proposes rules by which to judge of causes and effects. He talks of secret powers and he advocates a search for hidden causes. So let's go through those quickly. Okay, so first of all, in the argument concerning induction, absolutely clear, the only connection or relation of objects which can lead us beyond the immediate impressions of our memory and senses is that of cause and effect. Perhaps even more clearly in the inquiry, so his considered view, all reasonings concerning matter of fact seem to be founded on the relation of cause and effect. So if Hwm thinks we ever can infer anything beyond what we immediately perceive, it's got to be on the basis of causation. Immediately after the section on the idea of necessary connection in 1315, it's called rules by which to judge of causes and effects, we get this. Since therefore it is possible for all objects to become causes or effects to each other, it may be proper to fix some general rules by which we may know when they really are so. Now that seems strange if you think Hwm isn't a believer in causation. He's just given these two definitions of cause, in terms of constant conjunction and inference. And now he's saying, well, let's sort out some rules by which we can judge when things really are causes and effects. The problem is that what we experience in nature often involves compounded causes and compounded effects. Separating out exactly what's the cause of what can be quite difficult. So Hwm gives some rules in this section designed to facilitate that. Again, it's hardly the sort of thing you do if you don't believe that causal reasoning makes any sense. In the inquiry particularly, Hwm talks about secret powers. And I think these quotations are the sorts of things that make people most inclined to go towards new Hwmianism. He talks about the secret powers of bodies, those powers and principles on which the influence of objects entirely depends. That kind of thing. He seems to talk as though he thinks that powers and forces are genuine things in objects. How does that square with his analysis of causation? Now he clearly thinks that necessity or power is an essential component of the idea of a cause. And he says this repeatedly, according to my definitions, necessity makes an essential part of causation. And I mentioned two other passages from the treatise there which say the same kind of thing. Again in the inquiry, necessity may be defined two ways conformably to the two definitions of cause of which it makes an essential part. So there's no way that you can say that Hwm is a believer in causation but not say that he's a believer in necessity. Here he is saying necessity is an absolutely essential part of causation. So if causal reasoning is the foundation of all our reasoning concerning matter of fact and necessity is an essential part of our notion of cause it looks like Hwm must in some sense take necessity seriously. He also advocates a search for hidden causes. So here's a passage which is in the treatise but it's actually copied more or less exactly in the inquiry in section 8. And here he's saying that the layman may find that things act erratically and just says oh sometimes the causes work sometimes they don't but philosophers who know better, in other words natural scientists try to find underlying hidden causes which will explain why things work on some occasions and not on others. And lo and behold they're successful. Normally when they do that they do actually find the hidden explanation that they're looking for in terms of other causes. Okay so those are the sorts of points that can be made and I think they're very strong points to show that Hwm is a serious believer in causation. Somebody who wants to say he's just rejecting the notion of cause or indeed rejecting the notion of causal necessity I think is simply wrong. What I want to challenge is the presumption that this implies causal realism in any sense that goes beyond his two definitions. I don't think it does. So here are three points that can be made to substantiate that. First of all I'm going to say a little bit about Barkley. Then I'm going to talk a bit about the argument. I'm just going to review the argument that we've already seen in detail and then I'm going to show you a footnote which I think is also rather significant. So first of all Barkley. Barkley famously is an instrumentalist. Remember he thinks that objects in the world have no causal power whatever. When we see one billiard ball hitting another and the other one moving actually what's happening, what's really happening there is that God is creating impressions in our mind as of billiard balls.  Barkley says it's absolutely fine in those circumstances to do science, to talk about physical object as causes, to assign powers, things like the gravitational force proportional to the mass and inversely proportional to the square of the distance. There's really no such thing as gravitational force. There's really just God pulling all the strings making sure things work in a certain way. But doing all the mechanics is absolutely fine. We can do science even though what we're identifying as forces in objects are not really forces in objects. Now if Barkley can do it, Hume can do it. And the passage here which is taken from the first inquiry, there are some words in the introduction to the treatise as I've noted there, that passage is very reminiscent of the Barkleyan passage. He's saying that science is a matter of resolving the particular effects that we observe into a few general causes. It's all about systematisation. And that notion of science can go perfectly well for an instrumentalist. We've looked at the argument of 1314, and I just want to draw attention to some points concerning that argument. First of all it's structured entirely around the copy principle. Hume sets out to find the impression from which the idea is derived. That's why 1314 is set up as it is. It's entirely a quest for an impression which will generate the idea. Moreover he's absolutely clear that the copy principle is a tool for deciding questions of meaning. And I've given one passage there, just an example, one from the treatise, one from the abstract, one from the inquiry. Moreover he says that that's what he's doing, that he's trying to find out what causal terms mean. And again, quotations from the treatise, the abstract and the inquiry. When he identifies the impression of necessary connection and he observes that it's a subjective impression, it's in the mind as it were, rather than objects, he explicitly draws the apparently anti-realist implication. When he says necessity is something that's in the mind, not in objects. That's entirely consistent with what he's been doing. He's looking for the impression that's going to explain the meaning of the idea of necessary connection. He finds it, it's in minds, not in objects, and he draws the conclusion that necessity means something that's in minds, not in objects. And then he gives two definitions, of course, which incorporate precisely that anti-realist perspective. Notice anti-realist in terms of denying the existence of anything beyond the two definitions. So the whole structure of Hume's argument seems precisely designed to deny that there is anything beyond the two definitions when we talk about necessity or power. What about those passages in the inquiry where Hume talks about powers in objects? That may seem a little bit puzzling. Well, Cames, Lord Cames, Henry Hume, who was a distant cousin of Hume's actually, and something of a mentor of his when he started off at Edinburgh University, in 1751 Cames published essays on the principles of morality and natural religion, and he quoted Hume's references to powers in the inquiry against him. So Cames said against Hume, look, here you are talking about powers in objects, and yet you are drawing the conclusion that there is no such thing as power in objects. So you're inconsistent. Now, Cames particularly cited the first three sentences of the 16th paragraph of section four of the inquiry. That had been published in 1748. In the 1750 edition, Hume added a footnote to the following sentence. The word power is here used in a loose and popular sense. The more accurate explication of it would give additional evidence to this argument C section seven. So what I think is going on here is this. Cames and Hume knew each other well. They swapped manuscripts prior to publication. But Cames advised Hume not to publish the inquiry because he thought it was too dangerous. It had anti-religious stuff in it. I think Cames put this objection to Hume. He said, look, you're inconsistent. Look at this paragraph, paragraph 16. You are referring to hidden powers in objects. That's inconsistent with your own conclusion about necessary connection in section seven. So Hume puts a footnote in and says, when I refer to powers in objects, bear in mind, this has to be interpreted in the light of my discussion of the idea of necessary connection that's coming later in section seven. So actually I think that footnote gives tremendously strong evidence given the circumstantial connection between the point at which Cames was criticising Hume and the point at which the footnote was inserted. Besides which, I think there's another much simpler explanation why Hume puts all this stuff about powers in the inquiry. In the treatise, Hume's idea of causation is actually a pretty crude one. He puts it nearly all in terms of one object being followed by another, A followed by B. Or if you look at the rules by which the judge of causes and effects, it gets a little bit more complicated. A is followed by B but only when C is present and not when D is present. It's that kind of thing. Now in the inquiry, Hume has realised that that's not the way scientific causation works. When you calculate the motion of billiard balls or the motion of planets, you don't simply do it in terms of one kind of event followed by another kind of event. Rather what you do, you attribute forces to the objects. For example, gravitational forces between planets between planets and the sun, between the moon and the earth. You calculate the overall force and then you predict the motion on the basis of that using the laws of motion. So he's realised that science works in terms of forces, not in terms of just one event followed by another. In the inquiry, that kind of talk is quite prominent. But it's very striking that Hume talks about such things twice in footnotes to section 7 of the inquiry. That's of the idea of necessary connection. I think he's precisely making the point there that this sort of talk of forces is entirely consistent with his account of necessary connection. When he talks about powers and forces, all he means to talk about is uniformities in the object, uniformities in the events, how they happen, systematisation. Nothing metaphysically deeper than his two definitions can encompass. Okay, let's come back to those two definitions. Why two definitions? One of them is based on regular succession. One of them is based on the mind's tendency to infer. A common objection against Hume is that the two don't seem to coincide. You could have A followed by B repeatedly and reliably without anyone ever knowing of it. And if nobody knew about it, then nobody would infer B from A. So the second definition wouldn't apply. On the other hand, A might be followed by B quite a lot of the time and somebody observes that. But it might be that A often isn't followed by B as well. But maybe that isn't observed. So somebody mistakenly infers B from A. In which case it looks like the second definition applies but not the first. So there's a problem. We've got two definitions, but they don't seem to be co-extensive. They don't apply to the same things. Now I think the way to make sense of the definitions, again, this is controversial, okay? There are a lot of different discussions of the two definitions. Different scholars have different views as to how they should be interpreted. I've got some references on the website to things to read about this. My own view about it is this, roughly. I don't think we should think of the definitions as intended to specify necessary and sufficient conditions. Remember, Hume has a genetic understanding of meaning. In order to understand what necessary connection means, what the idea means, we have to understand where it comes from, the impression. Now that's a very different notion of meaning from one that's couched in terms of necessary and sufficient conditions. So I suggest that what's going on is that the second definition is specifying sort of something like paradigm conditions in which that impression arises. When A is followed by B again and again, you C and A, you find yourself inferring a B, don't you? There you are. Having found yourself making that inference, you now know what the essence of necessity is. It's to do with inferring B from A, something following from another, consequentiality. But nothing in Hume's theory requires that having got that idea, you should only apply it to the cases in which it naturally arises. I think the point of the first definition and the rules by which to judge of causes and effects is to say this is how you should systematise the application of that idea. So you get the idea from the paradigm case where you find yourself drawing that inference, but then if you're systematic, you apply it elsewhere whenever you find a constant conjunction. Now that makes the two definitions complementary. They're not conflicting, they're doing different jobs. And I think it makes pretty good sense. The second definition identifies the idea, the first gives you a criterion for applying it. Now interestingly, in the moral inquiry, this is something to which Don Garrett drew attention, and I think it's very insightful. In the moral inquiry, you get two definitions of virtue or personal merit. And they seem to be very similar. That is, the relation between them is very similar to the relation between the two definitions of cause. So personal merit consists altogether in the possession of mental qualities useful or agreeable to the person himself or to others. And then he refers back to that as a definition. My hypothesis defines virtue to be whatever mental action or quality gives to a spectator the pleasing sentiment of approbation. Now how do we square that? Well what Hume is doing here, and it's very clear from his discussion, he's saying that moral ideas arise from a particular kind of impression, the impression of a generalized moral approval. Now unless you've actually felt that, unless you've experienced moral approval, you won't even know what people are talking about when they express it. I'm sorry, this thing is, can I stop it? Shall I restart that? So unless you've experienced that impression of moral approval, you won't even know what people mean when they talk about it. But once you've got that impression and hence got the idea, you can then examine the occasions that prompt it. And if you do that in a systematic way, if you look at how people apply the notion of moral approval, you'll find that there is a system to it that we standardly apply it in cases where people have qualities that are useful or agreeable either to themselves or to others. So that is the analysis of personal merit or virtue that Hulme gives. And then he actually applies it critically. He says, look at the monkish virtues, celibacy, mortification, self-denial, humility, fasting, solitude, all these sorts of things. And he says, actually these aren't virtues. They've been described as virtues, but they're not. Because they're not useful or agreeable to oneself or others. So it's a similar kind of thing as with the discussion of causation. You get an idea, either the idea of personal merit or the idea of one thing following from another, but then you systematise the application of it so that you draw up general rules about when is the right time to apply it. And that corresponds to the first definition in each case. Now, notice that that understanding does tell strongly in the direction of a fairly traditional understanding of Hulme. Anti-realist in the sense of denying anything beyond the two definitions. We're reading, in a sense, reading necessity into the world rather than reading it off the world. Just as, in a sense, we read moral virtue into things rather than reading it off them. That doesn't mean that we're irrational in doing that. That doesn't mean we're making a mistake. But the crucial point is it's our systematisation of the application of the idea that's doing the work here. It's not that we're getting better at observing moral virtue in the world. We're getting better at applying that concept to the world. So the difference in which by applying the concept in this way, we raise a new creation by gilding or staining natural objects with the colours borrowed from internal sentiment. Hulme there is talking about morality, but something not far from that seems to be going on in the case of causation.


How far can I kick a field goal? Let's find out. Starting off at the 20 yard line for a 30 yard field goal. My biggest concern was from 40 yards. I thought it might be rusty, but we pinned it. Quick gritty break. Is that Justin Jefferson? Gaining some confidence, 45 was not easy, but it cleared and 50 just cleared as well. If I hit from 60, you have to subscribe. And finally, I wanted to try from 60.


Today I'm Dom from Coast XP. We run adventure tours by boat along the Newcastle and Lake Macquarie coastline. Throughout the year we're able to see things like common and bottlenose dolphins, longnose first seals, we've of course got Magnificent Humpback whales. I grew up on the Mid-North Coast in Coffs Harbour and I became a scuba diving instructor before moving to Newcastle. Of course I fell in love with the city and thought how can I add to this destination. So one of the best days that come to mind from being out on the water sharing in those experiences with our guests is we had a customer on board with his three-year-old daughter and a GoPro in one hand and his daughter in the other and over the side of the boat a humpback whale swam directly underneath the boat and he has this fascinating picture of his daughter in one hand, the whale behind in the water, all in the one shot which I think is just a fantastic way of sharing in what we do and of course that's why we do what we do.