J2 SAY 09 Jared Pereira blockchain for education innovation

hi thanks cool so I think this talk was titled like blockchain in or education innovation with the blockchain which is like kind of what it is but not exactly more so I'm talking about the math etic Opportunity and distributed computing pathetic is the science of learning and so the topic is how does the presence of distributed computing systems and crypto systems in society change how people learn and I'm so basically you can frame this in two ways one like fast forward into the future right where everything worked block chains are everywhere people are using this to run society schools governments banks whatever this technology is omnipresent in our days right so kids children are actually interacting with decentralized systems in their day to day lives and so the question this raises is how does this change their minds how does the structure of the way they approach life learning and knowledge change as a result of interacting with these systems and this may seem like potentially putting a little too much on to like blockchain systems right like is this changing people but I think it does it's a I think a lot of us would agree that it's sort of a very fundamental perspective shift kind of in the lineage of computing as an innovate innovation and so I think this is a really valid question and I think we need to care about how the things we build changes people's minds we need to care about how it transforms the way you think about the world and so what this comes down to is learning is the creation of knowledge and learning at multiple levels learning within an individual how do I learn in relation to society how do I create knowledge in myself learning in relation to a community how do we learn what it means do sharding or do you know how do we learn any of this how do we create knowledge and so I would like to tie a lot of this back to a specific theory of knowledge from a psychologist called Jean Piaget called constructivism and basically what this boils down to is this idea that knowledge is constructed within individuals based on the interaction between what you experience and your ideas so for a little--just frame i'm gonna jump into constructivism sort of theory of knowledge then I'm gonna jump into learning and then I'm gonna pull it back to like how does this actually influence what we're doing so constructivism this is how people construct knowledge how I decide what it means to know something I have an experience I have an idea and those two might have a difference and I attempt to reconcile them this is coming from a genetic epistemology perspective which is essentially tracing back the genesis of knowledge and how does that if we study that how can we what does that teach us about knowledge so it's the two major concepts in it are this idea of assimilation and accommodation assimilation is when I take experiences I have in the world and I fit them to my ideas so you could kind of frame it as you know when you I'm sure this was happening all of you where you go out in the world and you're faced with a problem and you're like oh yeah probably a blockchain could fix that right we're assimilating the world into our mental models an accommodation is when you change your mental model to fit the the world where it's like oh I entirely thought that this would work this would be easy and it turns out the world doesn't work that way and I have to change the way I approach things and so this theory I think was around sort of propagated in 40s 50s somewhere around there and it focuses specifically on just like what is knowledge it doesn't really focus on a process by which we can propagate knowledge or create knowledge and so sometime after Jean Piaget there was this proposal for constructionism which is a learning theory and weekly it's this idea of learning by doing you do things and then you build things or you write things and that creates knowledge in yourself more strongly it's this idea of learning by creating meaningful artifacts meaningful meaning that they have a impact on your experience so your ideas will only change or change most effectively when the artifacts you're creating have an impact on your experience right it's that relationship between ideas in the world again and so this was put forward by say more popper who is this really incredible mind he was a pediatric psychologist AI researcher and computer scientist so this really neat intersection and it's sort of recasts Jean Piaget as an epistemology instead of like him just studying how children learn what we're really studying when we study learning is the not genesis of knowledge itself or what it means to define knowledge so popper kind of proposed this idea that like okay if we understand that knowledge occurs in these ways we can and and we understand that knowledge when you're constructing knowledge when you're actually having experiences you're using models information and resources that come from your environment using like things your parents told you things you see the idea of basically culture in permeating mental models and so we can actually construct environments popper calls these micro worlds in order to intentionally give people learning powerful ideas and so the most important piece here and this is sort of like the core of the exciting ideas that popper produced which was computers the generalized computational environment can be a constructed environment for metamath etic ideas soma thetic the science of learning mehta would be like the basically thinking about learning about thinking about it loops back on itself and i'm being messy but the idea is that we can impart ideas about the construction of knowledge to self through computers and this kind of stems on the idea that everything in a computer is knowledge that's constructed by people right when you're coding when you're interacting with it you constructing systems you're kind of teaching the computer and through teaching the computer perhaps we can learn to teach ourselves and so this is also kind of this is a very long quote the important part is first the separation between the learning process and what is learned is a mistake essentially in order to the separation between teaching and the idea like so basically in order to teach something to someone else you have to understand what that is and these processes are not things that happen first you understand and then you teach they're actually intrinsically tied together and this is something that I think a lot of people resonate with but it's not reflected in the models that we actually engage with in the world so this popper kind of was very prolific in learning cycle learning theory in the 70s wrote a book called Mindstorms which I highly recommend and the question is like what happened with that and so they had this environment called logo and it was really really cool and worked did yeah it was kind of like fairly well distributed and it was I don't know if any of you interacted with turtle it's essentially like a tiny little turtle that you tell to go up right left and it draws pictures on the screen and it was a way to teach children computer science and it kind of worked it was a I think starting point for a lot of people and then we also had ideas like small talk from Alan Kay which was a academic programming and it is still prominent in computer science curriculums today and these are all stemming from the same ideas of like can we create learning environments that are computational environments that teach people how to learn and we have like things like boot camps propagating something quite kind of like computer science today but really there hasn't really been a broad change in education nor a widespread computational literacy there's still a large gap between the potential for these ideas and how they've actually manifested in society and so here's the question of like how can we use these things in order to change that in order to what is the opportunity that is presented in this new paradigm and so generally the paradigm I'm talking about is like cryptosystems or social computation which is kind of ill-defined but generally I mean things like aetherium get so just like distributed Merkle trees other cryptographic social networks like secure saddle but and they change things in two ways number one is an unprecedented pervasiveness computers were previously our computation was previously largely a individual thing right you exist on your computer your computer talks to other computers as individual servers but now we're taking this idea and sort of making it fundamentally social where the interactions between different computational environments is constructing sort of a shared reality and this provides the opportunity for a computational mindset to infiltrate society at a much much higher level than just like computers as workstations and then the second thing is because it's social it gives us new social metaphors for talking about computation it gives the ideas of forking consensus merge conflicts web of trust it's all of these things that help us and help people think about both computers and reality and so it also gives us potentially the opportunity to try and do this better we're rebroadcasting a lot of these core ideas of computational learning or we have the opportunity to rebroadcast them in the systems we build in the systems that change the world so what if we do that we build new foundations with this idea of learning learning at all levels has sort of a core piece of it and so there's there's lots of little ways we can do this and I recognize that this is sort of extremely vague or fuzzy which is because learning as an idea is sort of extremely big and fuzzy it's specifically related on the creation of knowledge and so I think what I'm gonna try to do here is just lots of little pieces where I think we can exemplify these traits and perhaps through the little pieces we can construct a meaningful whole so the three areas is we can build tools for learning right we can actually use the systems to build specifically learning tools also all tools we build regardless of whether they're for academics are learning or not can have learning oriented or learning first features right like if even if we're building governance systems learning can be a first-class citizen there and learning can be a way to build tools the way we research the way we develop that learning can be a first-class citizen there too and so tools for learning I work on a project called fathom and this is kind of what we're thinking about like how do we put together assessment systems in order to incent allow people to learn freely and there are also other sort of apps or systems we can build to do that like prediction market systems for sourcing and incentivizing new knowledge there's a lot more there potentially but I this is kind of the most obvious point and the more subtle ones I think are things we should have in tools for example this idea of view source which is something that's really taken for granted and web browsers but like we don't really think about it in terms of smart contract systems this idea of making available again this the the computational ideas to our to the people who are interacting with these systems simulations allowing people to play with the crypto systems we built I don't know if any of you guys there's this really good simulation of game theory as a way it I forget what it's called but that's the URL where essentially you pick strategies and simulate a bunch of runs of game theory agents doing it and it's a really playful interactive way to learn the ideas of game theory or do we need security like signals so the way web browser signals security to the users do we need to signal learning do we need to signal that the website is open source or the smart contracts are open source do we need to make that as primary a goal as security which is you know a little radical but ideas or there are also systems we can take that are making our development research systems fundamentally respect learning right so the way moving away from this kind of like production or product driven work cycle where it's like I build a thing release it to the world iterate on that and more so to the idea that people through their learning can or through just constructing knowledge in themselves and others can arise meaningful artifacts this is kind of the fuzziest but I think it's also the most interesting how do we create essentially things like research institutions but research institutions more fundamentally in line with the work that we do as opposed to a distinct entity like they exist in modern education so just some closing thoughts I started this talk with like jumping to the future and being like what happens when we change children but I do think that like the benefits of thinking deeply about learning are important today they're not only things we build today for the future but things that influence and help us build better and most importantly I think to me the this idea that hiding the novelty of what we're doing is not a good idea we need to embrace the fact that the thing systems ideas we're talking about are they're not fundamentally new right they have a lineage but they are new they're new systems and we shouldn't disguise that to people we shouldn't try and like swindle people into thinking that this is the same as what they've always known we should create bridges to allow them to come into this new paradigm and change their minds this is kind of like a question going into UX and UI and kind of research like that and I think it's a very loaded question but it's important to think deeply on the ideas we're propagating and don't we want to propagate the ideas that let us do what we're doing and kind of like on a more optimistic note there there's a lot of talking and education about the school of the future and I think really the school of the future looks like the things we're doing right the things as an industry we're learning and going on with and everything happening there and so we're doing pretty good the Industries is open and collaborative and stemming directly from the lineage of the open-source movement and so we're on the right path but we still need to foster a culture that respects learning as a fundamental part of the progress of work and of the things we all do briefly if you want to get in touch that's by email I don't have like business cards or anything and that's the project I work on Fadem Network cool thank you [Applause] yeah thanks so I have like 10 minutes if there are questions cool if not cool Hey I thank you for your talk first of all super important subject matter something that I think a lot of people need to think about especially as we want to grow the industry with the think about how we educate people and how we onboard people into the industry one of the things that you mentioned was that hiding the novelty of our work isn't a good idea I don't want to use this time to promote my ideas but I think one of the things that I think about and I would love to hear your thoughts on is how we as an industry sometimes reject a lot of complexity outwards so that we kind of have this allure and we build up our own kind of egos but that also pushes people away and that's not conducive to bringing people on in educating them so just what are your thoughts on that and how do we as an industry help or change that thank ya I think I'm pretty agreed on that being a bad thing right we don't want this aura of mysticism of like this is special knowledge that only we can have and projecting that and even things like you know developing our own language for talking about it can be conform a real wall to people coming in I think the solution is not right at like it's we shouldn't be hiding complexity we should be creating higher-level ideas that make them easy to propagate so we should be recasting the knowledge we have in ways that is easy to transmit and while still not losing what makes it fundamentally what it is right we shouldn't make it disappear we should make it present in a way that people can understand and I think what's cool about that is if we do it correctly it recasts our understanding as well it's not like we are the like giving knowledge it's this continuous process of translating knowledge and engaging with it in new ways that makes the industry better makes individuals better and propagates a culture of information yeah cool awesome talk the have you thought about how we might be able to target you know get involvement from different communities and just kind of bring bring this understanding like we're both spreading knowledge but we're also kind of engaging knowledge that is dormant in communities and so like have you thought about how we might do that and you know get more people involved from different backgrounds I think it's a two part thing one is we need to be have not necessarily extremely rigorous but good definitions of like what it all fundamentally is right so it's not all fundamentally about like coding or like cryptography or anything like that and saying it is alienates other communities but if we can come up with like a shared common basis that is like okay if you're interacting in this thought space this is what we're talking about then that can be an onboarding point for any kind of community you can kind of drop into an existing knowledge base and be like join us here this is the pathway and then the second is sort of I think tied to that one which is just like expanding our definitions of what is valuable work in this space and kind of opening the doors to let people engage how they they can I think it's a hard problem but I think the easiest Lucien is just like create opportunities for it like if we give people money for weird things and and new things and different spaces and all sorts of stuff like that you said that what we're doing is new but it comes from a lineage of thought and so particularly as it relates to constructivism can you talk a little bit about the lineage that what we're doing comes out of because I don't know anything about the background like how has constructivism been applied since its creation so constructivism being the theory of knowledge or construction is a really messy language action is yeah so constructionism was like largely propagated in the 70s kind of by I think a group at the MIT Media Lab and I think the number one lineage of that was logo and turtle and sort of small talk and this general idea of I think they really kind of propagated object-oriented programming is like one of the first things like small talk really put that idea out there as sort of a novel metaphor to think about programs and so that's kind of where that came from in terms of the lineage constructionism kind of at least in in the since mm I think it has not seen as much of a vitalization in society I think it is present in the open-source movement though and how people engage with software in general right the idea that like forking runnin experimenting with software is a way to learn is kind of still becoming a thing that wasn't a very robust answer and I don't have a very robust timeline for it but I would love to get into that more cool so I guess I have a question about what you see in the community now do you believe that there is that a large percentage of the community is actually learning or do you think that memorization no so this is interesting I think there was like a tweet from Vlad awhile ago that was like maybe the most important thing that came out of this is all the learning it inspired right like I think there is a genuine shift in mindsets and a genuine progress being made in how people create knowledge I think there is new knowledge being created in in one in cells right and that's present just in how eagerly people are attacking the world it's like we got this thing that we think is exciting we're gonna apply it to everything and through applying it to everything we're going to change ourselves and change the world and I think that's sort of evidence of there being something new here and something new in people's minds and I think there is a large element of potentially cargo cult ISM and not totally engaging with the fundamental pieces of knowledge but there there is a movement towards it and I would broadly think that most people in working in this space do learn and are learning and creating new things yeah thanks a lot yeah thanks for the talk I got a question I wanted to relate to a talk that we heard this morning with rain and she was talking about again onboarding people into the industry and and how we can do that anything as you say that we have shared interest with other communities I think about the artificial intelligence community for example they need win on board people and to make them you know not be afraid of that my question is do you think that as an industry we have kind of a disadvantage I mean in the blockchain industry twin board people because of either the much trolling that who you get when you when you try to enter the community and of me--sometimes bad image that you get through the many scams in the project is it is that some kind of disadvantage for in the industry I mean probably right the way people engage with this if the way people in with his ideas is by the noise that we project then that's sort of seating the wrong thoughts its setting us off from the start and I think potentially you could tie the image problems or the trolling to a problem with our understanding ourselves I think we're still where we don't totally have robust ideas of the knowledge we're working with we're still building the framework and because we exist in this in-between space social experiences like trolling like you know extreme signaling are a way of survival a way of people to work with this stuff and I think changing that will be fundamentally the idea of learning and us learning about ourselves in order to come to a strong shared understanding and culture before we can or through a process of taking that outwards yeah Thanks [Applause]