 Thank you very much. Oh super loud So I Maybe before I started presentation Two things so one is that I've been here before Charing the two sessions, but this is only because I was chairing the sessions right because this is all Zunke organizing this But importantly tomorrow and the day after we have this workshop steps that don't ask me to co-organize with him and You can check it out on this website and if you're still interested in joining we are at Coat University and Yeah, you can you are happy to come to us and or send me a message and join either one day or two days and just talk to me about this Then the idea of this talk was to talk about decentralized autonomous organizations what I thought is to take a step back and we had already very nice presentations today about How such a DAO could work on the legal side and how it can have to finance research I try to go and and give you kind of a journey through the history of of science and And the theoretical background there and how this could inform us how we can actually build blockchain applications and systems in a for science Word to the Akasha project so so I've just recently started to to work with this Akasha of the Akasha foundation was founded by Mihai Alicia who is a co-founder of Ethereum and the project that's currently well known as a Crypto economic experiment if you want to say that's this Akasha depth decentralized application and you can go to the website Akasha dot world and look at it downloaded. There's also a web version of a browser version available now But this is this is one aspect of it what what we are now currently working on is growing a team That is exploring how we can use basically blockchain applications to build Collective collective intelligence as well as we are kind of describing the border of blockchain and collective intelligence Which is a new term maybe for some of you and but just fundamentally to to have a paradigm shift in how organizations are working and that's a That definitely has also an application in research and science and this is how I came to the whole field Because I had an idea that I thought there is something about this whole way how it's self-organizing that could be very well applied to research And then I read Zunka's paper and that's how for one year now. I'm in this rabbit hole so Actually so to start with I want to make a claim and that is that the research discovery process actually already is decentralized and The poor problem that we are facing is that our organizations are currently not or not yet So that's the way that we are as human beings currently organized we have very hierarchical structures Scientific laboratory resembles very much the organization structure of the German military in the first world war and of companies and the Universities are structured in the same way and there's some social biologists That that have studied this and compared it to other systems of organization in biology And they describe the human system basically as we are creating partitioned hierarchies Because we believe this is how we have to control people and organize them and the instructions flow down and parallel streams and Actually creating a lot of bottlenecks We have multiple levels of command and a lot of information is lost in the centralized system also Also, also be as the risk of information loss or you have a single note of failure so decentralization now as actually The process to move back from a centralized entity through a decentralized network of hubs and nodes and Spokes to a distributed mesh basically, so the The word decentralization at least according to the interpretation of my colleague Philip Sheldrake also is actually describing the process of moving through this three phases here and The internet in itself it initially was a plant as a distributed mesh network where you have no single point of failure It's a military research project or initiative Ultimately, so if one node is destroyed you will still find ways to wire around and find information and flow happening So in this system We basically try to eliminate single notes of failure in another way speaking scientifically the PI in a way is a single note of failure in that sense that that that he has a lot of burden to carry you have to write the grants you have to Review papers you have to write papers you have to take care of all the students and things are at least getting stuck there And much worse things can happen In terms of also abuse of power and these kind of things that we have seen recently some in institutions in Europe So now science actually is a decentralized self-organizing system and here I refer to Michael Poulani who Wrote this article the Republic of Science and actually I'm grateful to Stefan Krauss was a professor in Oslo And he was at the last meeting and he introduced that at his essay to us and and so I it's an analysis of how Scientific structure actually is organized and he did it because he was concerned about the policy changes in the UK and how they are changing to a more quantified research policy system that tried to Direct the choice of the research as what to do and to evaluate them which in the 60s wasn't really implemented yet which is implemented today and So he describes that assigned activities of scientists are coordinated and rely on constant communication And the adjustment of independent initiatives occurs in response of the results obtained by others It is kind of obvious we're building on the shoulder of giants or and we heard us in the previous talk as well Then he goes on that he wants that if we are changing this we may basically Bring science and the scientific progress to a virtual standstill that this is just the second part and I'm not Complaining about I'm just trying to analyze what we are seeing and now when you think about a decentralized autonomous organizations and the Concepts behind it. There's a there's an important term that we hear many times and that is Stigmarie, okay, and this is a social biological term that was introduced by a biologist I guess he was in the in the 60s also and that suggests that you can define it as Important determinants of an individual's behavior are stimuli from work previously accomplished So I found it really cool because it really mirrors the analysis that we had from Pugliani on how how he thinks research is working and Actually, Stigmarie was used to describe how termites are building their their complex structures without an apparent building plan and there's another Study and there's a book called the ants by by her dobler in the 80s And he says individuals in a dense heterarchy Respond not only to the Stigmarie stimuli from work in progress, but also to stimuli received from their neighbors Okay, and and and this process is actually something we can illustrate and funny enough It was illustrated not in the 80s, but again in the 60s in the essay by Pugliani and that is He gives the example of a group of people that have the task to build a puzzle on the floor And this is this long text is better put text, but you can read it later That's why I put it here. Just tell you so so you're building a puzzle and you have one you have one organizing center like the boss And and you're blindfolded and now you're presenting the pieces of puzzle to this guy And he's the one that tells you where to put the puzzle. So that's a very leggy process Not working well, but what works very well is if Instead of doing this you have all the people Maybe some have specialized tasks like looking a bit cleaning up and doing other things But in all that they are looking at what my neighbors are doing where I am at and and maybe that helps me to instruct To find the slot for my own piece because I see the progress of the others as well. And again, this is actually How we could describe a scientific process and and we are looking into scientific literature We know what others have discovered. We are building up on these hypotheses. We are not gonna reinvent the wheel so From this basically, how do we now and approach an approach decentralized science and What we need according to my understanding is Three boundary conditions. So we require a free flow of information Apparently if we are Restricting the access to information we are locking out not people in very elite institutions But potentially those that are not able to for instance access the scientific literature as the equally as as we can do here then We need to establish some rules for governance So I guess what is very important is to to be open and inclusive and to to somehow have a System of reputation established as well that allows us to to filter the good and the bad things and the crazy things although there are examples that this works actually quite well and an open project and We need to remove obsolete intermediaries because they are Currently not doing is a good deal. So first one Free flow of information is actually established as of today because as some of you have probably also installed on their Google Chrome browser Sci-hub plug-in allows us to in real time when you read a paper and science on nature That's behind the paywall you download the PDF. It goes directly to sci-hub I just did it with my last paper in blood Like the pre-print that was behind a paywall is already there you can read it and I Asked the journal is it okay to have a pre-print and they told me no you cannot have a pre-print this we are not doing this And we are not going to accept it. So 2018 for a biologist that's the reality and The theoretical concept behind this is that data and knowledge are actually something that's defined by a economist and Berkeley called so-called anti rival goods There's also work But primavera the Philippi on this approach and that is that actually value that we can gain as a society from freely disseminating knowledge It's larger and it's exceeding the value that's the profit that a single entity can gain by putting the information and knowledge Behind a paywall and this is I think important to inform us of how we should design system Design decentralized systems that are there to to create value for us Unfortunately, we cannot necessarily measure all the externalities that that occur But in principle that would be the case and a good example for this is the distribution of language So imagine and you you would you would define you you are gonna speak your own language now And you try to buy a bread as impossible. It will not work, right? But the more people speak your language that the higher the value would be for this new language that you have developed and An example for this would be not only in that knowledge like medical information or publications But also computer code would also fall into this category of an anti rival good The more people are using a software the more valuable it becomes and Linux is a prominent example of that Then open as an inclusion. There is a nice example and Laurie was speaking yesterday. And so it's a very famous mathematician He was basically autodidactically training himself in India to to work He lived most of his life in severe poverty and he tried several times to to send his documents to to to Britain to Mathematicians I guess an Oxford and their comment was well He has a taste for mathematics and some ability, but he lacks the educational background and foundation needed to be accepted by mathematicians So that's a very sad thing because we have a dot org email address or an affiliation with an institution we are somehow thinking that we are chosen to be the smart guys and the voices of others are just not heard or you cannot actually even make the The way to be heard and that's a really silly thing Now there are already ways of successful collaboration And this is a super long text But I find it cool because I'm from a biomedical field So just want to give you one extra excerpt out of this and that is so Vaneva Bush was running the War Department of Research in the US. They built an at MIT the radar lab to try to shoot down the German planes even at night it's really awesome stuff and To to get there they had to put the people in it in a team together and and and and had a physicist to work on this But there also was interest in medical research and then he said after the war for biologists in particular for medical Scientists, which might be this biomedical is why I enjoyed a lot There can be a little indecision for their war work hardly has hardly required them to leave the old path They will basically carry on war research and they did carry this on in their familiar peacetime laboratories And their objectives are remaining much the same. So they are fighting like this Yeah, we have no systematic approaches of curing cancer, but the physicist They have left the epidemic epidemic purses. They were kind of put in these camps Where now they had to work in a combined effort, of course They were now triggered to determine you have to build this but at the same time they had quite a lot of resources and the freedom of choice and In a combined effort, they felt the steer of achievement of doing something as a team They have been part of a great team now as peace approaches when asked where they will find objectives worthy their best and actually we see Physicist or physical funding has remained relatively flat over history and Interestingly, we see quite cool projects coming out of it It's also that physics to defend of the biologists and other fields is a more mature field So we are like 200 years behind physics and biology and medicine I'd say but Nevertheless, so the CERN would be an example for a large massive and actually quite hierarchically structured Collaborative experiments put together by humans. There are other examples and Like linux the internet Wikipedia Polymath project and even the ethereum foundation They they all start with something that Peter Glor from MIT as a center for collective intelligence Describes as a collaborative innovation network, which usually starts in a small group of people that have a crazy idea They are intrinsically motivated and that's actually actually a nucleus initially and surprisingly by the way because we always think This field is scientific field and this is so big and all these thousands of scientists and no Actually, there's really very few that are really super experts in one field and then the rest are just running after them like the lemmings I mean if you think about CRISPR and Cas9 this is micro RNAs if you're familiar with that It's like one like two three amazing papers and then everyone else is just doing it You have like a peak thousand papers the next year and honestly most of it. You can just burn, right? So it's this nuclear group that started field and and that's actually can then have a very big impact on society and create something radically new So we we don't have to close our eyes and say it's impossible to start as 10 or 15 people are for the theorem something That's gonna be very big So how to scale this that the importance is that in order to remove the single point of failures Nothing works if you imagine you would now entrust Facebook or any other company currently exists to manage Globally such innovation networks. This is not likely to happen, right? so and this is where I think the The idea of a decentralized autonomous organization and the decentralized infrastructure that we are currently building fits very nicely in and To just paraphrase it it would require Or enable us to have transparent Stakeholder controls and decide control and decentralize the organized entities and we have heard a lot of struggle here already these days Actually struggle of understanding how this can be implemented and we are not sure really what is gonna work from that So at Akasha, we have now started to think about something that we call the conversational now And I'm not gonna show these diagrams now, but I just want to say this is informed by work from Paul Pangaro who He phrases he put this term out that wealth creation has shifted from prior knowledge to the ability to gain new knowledge in action And it's a bit complicated can sink it in but what it actually means is if we have free access to all the information We have to wonder how do we create now? Some value to at least feed the people that are working on doing this right and and and creating then the new information and And I think that's where the key struggle and the problem right now is how can we find new mechanisms that enable us to? Yeah, to get paid for the for the conversation that we are doing because this is the time that we spent Talking with other people or thinking by ourselves. So having an internal conversation And and this is a resource that is limited. This is our attention Yeah, and someone that got it very wrong is actually all these social media of today that are just sucking our attention for stupid stuff But the networks are there in these platforms But but the paradigm that they have used and this is what Paul Pangaro also says they have been wrong And there was a discussion in Berlin in 2011 If you look at this his talk where people in the audience were exactly debating the same and said well, you know We can tweet we can co-work on the internet with all the things But do I trust Twitter with all the data that I would put in them? And and so this was before Ethereum before the blockchain Movement basically and I think with this new technology there's a new way to open this discussion and that's what we are currently doing and now in the end I give you an crazy idea So the end of institutions some some radical thoughts of how could we change a research institute or build a research in the future So basically I would say there would be no publications Results results are annotated by librarians that are experts in data annotation They are publishing the results and very clear description Basically instantaneously on the institute server. So the institute maintaining the database and the integrity for the for the For the academic workers and maybe you have a librarian in every lab That could be actually cool and then scientists work within this system at the heterographic network level and In order to create this heterarchy and you get rid of the hierarchies You would have a pool of definitely qualified people and usually they are always more than they would be fitting in the institution So instead of having impact factors and p-values Fighting about about this kind of stuff. You would basically run a lottery. Okay. So we had a pool of People that could be included in the next round of research in the institute and we give them five-year appointments like Universal basic income for five years to do research. That's kind of a fellowship You have to be qualified for this and definitely you will earn less than you would earn in the industry So it's something that you have to really wonder whether you want to do it But what we want are people that are intrinsically motivated. Yeah, and not people that that are kind of Doing it necessarily just for the fame and not contributing much to our advancement and basically anyone could be contributing we could even say that those that are not going in the first tier track of like going through a good university and getting the education qualifications to enter the lottery could still enter the lottery by Proposing good ideas and maybe helping from the outside on the on the platform to work on the kind of crowd-sourced projects And that could earn you something not much reputation But just the token to take part in the next lottery and maybe you make it in And actually this is something cut funny I told Zunke so I thought when you read this book the glass bleed a beat game from Hermann Hesse he describes this world of the scientists and the world of the new normal mortal people and And he describes science as a game Or basically any any kind of intellectual thing and this is so important and like they don't they don't even want to think about real-world problems They're just getting an expert in in one field and that's the scientific world and and they take also some normal people in and and And and educate them But then normally they go back and do companies and stuff But those that are really intrinsically motivated sacrifice their life and live kind of like monks in the scientific field and I thought okay, this is cool actually this Is actually how maybe scientific? Work used to be as well and anyways, I just recommend to read this if you are with the background of academia and So I want to thank you. This is the end of my talk and currently I'm working with with Mihai Philip Sheldrake and Andre Samba who are forming our nuclear research team at Akasha and We are doing other things and this was now really on my reflections on research and Blockchain, but yeah, I Just want to thank them too because there's a lot of influence I get from them right now. Cool. Thanks Have you figured out how this actually interfaces with Akasha network yet or is it still under research? Okay again, so what I told you here is kind of both ideas and everything and With the within the Akasha system the reason why I got kind of sucked into this and like a year ago I I uploaded some of my genotyping data to to to Akasha in December and And I ran a description below about what I did and all the primers are used and melting temperatures everything And so I said hey, here's my lab book I'm gonna have a new thread column on the Akasha depth that is now here my lab book for all the genotyping And so now everyone could go in and look at this and actually vote on it Even could even maybe fork it and have a new thread and add other comments And so it basically this is already there right so and it's very simple and what I didn't say is like products like the polymath They are just a block. Okay, that is just an open block where mathematicians put challenges and then Piece by piece try to direct the people to the answer. So It's simple, but I'm not sure if I answer your question, but yeah Thanks, thanks for the nice talk and it was really inspiring to to see all the literature what you read and get inspiration from and That's what I want to give a kind of link to Steven Johnson writes about technology and innovation And he wrote a book about Wonderland And he writes in that book that all the new innovations and new technologies are rising from a playful way so he says that play and Yeah, doing silly things without any reason talking on Twitter with other Scientists can lead to really crucial and and super innovation. So if you're looking for your next book, please read that cool right cool, then we have a Skype