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Where Science Meets Web3 - A DeSci Panel
Recorded: May 5, 2025 Duration: 1:02:51Space Recording
Short Summary
In a groundbreaking Twitter space, experts discussed the transformative potential of decentralized science (DeSci), highlighting trends in community-driven funding, innovative partnerships, and the integration of blockchain technology in research methodologies. The conversation underscored the importance of privacy and collaboration in reshaping how scientific inquiry is conducted and funded.
Full Transcription
Thank you. Good morning, everyone.
Good afternoon.
Good evening.
This is Tor Constantino for today's Twitter space brought to you by the fine folks over at Oasis Protocol. We're going to let some people join us. So we'll get things rolling here in just a couple of minutes.
Hello, we hear you loud and clear. This is your moderator, Tor Constantino from Forbes.
We're going to get rolling here in just a second
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We're going to get started in just about 60 seconds. Thank you. All righty, let's get things going.
Good morning, good afternoon, good evening to everyone who might be joining different time zones around the world.
Welcome to today's Twitter space discussion on de-sci or decentralized science.
I'm Tor Constantino. I am your moderator for this session.
I am an AI contributor at Forbes as well as an AI contributor over at Inc.com.
contributor over at Inc.com. We're thrilled to have you here today. Whether you're a seasoned
We're thrilled to have you here today.
researcher, a Web3 enthusiast, or simply curious about the future of science and innovation,
we've assembled a fantastic panel of thought leaders and practitioners to help us explore
this fast-moving field. Now, before we dive in, a few quick ground rules to set the tone.
This is a recorded public conversation, so please be mindful of your contributions.
When we open the floor for audience questions a bit later on, we ask that you keep your
comments concise and respectful.
Harassment, trolling, or disruptive behavior will not be tolerated and may result in your
removal from this forum.
With that said, let's begin by having each of our panelists briefly
introduce themselves. So let's start first with Robert from Oasis. Robert, would you care to
introduce yourself? Yeah, absolutely. So welcome everybody to our DSI panel. This is something
that we kind of just wanted to organize with some projects that we've been talking to. And I think
it's really valuable to talk about these things openly
instead of just in closed conversations.
So I'm Robert.
I'm a BD specialist with Oasis.
I have a background in physics.
I got my PhD in 2023,
which is just a year and a half ago.
Since then, I've been working
kind of in a different sector,
going for Web3, of course,
which is another one of my great passions.
But I love science, I love research, and I would love to see a future where I could possibly combine the two.
So I'd love to talk about those things here today.
Fantastic, Robert. I can spell PhD, so I've got that going for me.
Let's kick it over to Robin from ReflexDAO.
Hey, everyone. Thank you for having me. Let's kick it over to Robin from ReflexDAO. Hey, everyone. Thank you for having me. So my name is Robin. My background is in machine learning and computer science. I've been joining the Web3 space 2017. And I'm an early contributor to Ocean Protocol and SingularityNet and so on. And yeah, I've been following them and working in the community.
AngularityNet, and so on.
And yeah, I've been following them and working in the community.
Then I had my own project around decentralized data collaborations called Data Union.
And now I'm using my knowledge and the technology that we've been building to build DSAI DAOs,
so like Reflex DAO.
I'm happy to talk about DSAI and the impact of user data and how we can use it for the
good of the patients and the impact of user data and how we can use it for the good of the patients
and the users.
Excellent.
We look forward to your contribution today.
And last but certainly not least, the team over at WellShare.
Please, Stefan, if you would introduce yourself and your background.
Hello, everybody.
Thanks, Stefan.
My name is Stefan.
I'm working for a company called WellShare.
I've been one of the lead developers at Molecure once, actually once actually if you know those guys this is quite a large name in space
uh building the ipnft protocol and everything but now i'm moving on to welshare and we're mostly
dealing with uh previously preserving data collection of users and the utilization for
this data for ai agents which is quite some awesome thing to do,
particularly if you look at it from a Web3 perspective.
We're not too sure if Web3 is actually
the major benefit of this all.
It's mostly about utilizing data and privacy,
but it somehow all comes together
and Walsh tries to contribute to that space
by building reusable protocols, actually.
Excellent, excellent.
Thank you, panel.
So glad that you're all here.
Look forward to a very dynamic and engaging discussion.
Our topic for today's discussion is DeSci,
if you might be into the wrong form, that's okay, stick with us,
or Decentralized Science.
It's an emerging movement that applies the principles of Web3,
such as blockchain, tokenized incentives, and decentralized government to reimagine how scientific research is funded, shared, and validated.
Traditional science is often hampered by closed access, limited transparency, and reliance on centralized gatekeepers, such as publishing houses and grant agencies, DSI seeks to make research more open, equitable, and collaborative
by establishing permissions, participation, open data sharing,
and direct funding through mechanisms such as DAOs and crypto-based rewards.
And while the term DSI gained traction around 2021 or thereabouts,
the foundational ideas of open science, reproducibility, and decentralization
have been around for decades.
And with that, as set, now the table is set with a definition, a working definition for
the listeners.
Let's dig into the first question to our panel, and this is open to everybody on the
panel.
What was the aha moment that made you realize science needs decentralization as well as decentralized finance and all the other areas where we typically find it?
Thoughts?
That's open to Robert, Stefan, and Robert.
Go for it. So yeah, for me, it was kind of,
when I was doing my research,
I realized that a lot of the work that I was doing,
at least, was funded directly through the federal government.
And this was fine because for the most part,
things ran steady and there was no major shakeups
and we were just able to do the work that we wanted to do.
And, you know, as fundamental research, it wasn't anything really applied.
But, you know, it made me realize like, OK, well, if you're getting a grant through the Air Force, then, you know, obviously this is they have to have some incentive to give you this grant. They have some end goal here. And also you're subject to political whims and all these things.
And I was fortunate not to have to worry about that.
You know, I was not the one applying for these grants.
My advisor was.
But, you know, this is a reality of any form of research is often you are trying to, you
know, make your case to this higher body and a centralized body control of these funds.
And you may not align with them on all
the specifics. So I think one way that the centralized science kind of comes into the fold
is if you have enough people just out in the open that support what you're doing, you could
possibly make that a reality without having to go through these much larger organizations. And that
by itself, just the funding aspect, I think is very powerful.
And I'm sure there's other ways that, you know, you can decentralize different aspects
of your research, but I think funding is definitely a very low-hanging fruit.
Excellent insight.
Robin, how about you?
What was the aha moment that made you realize science needs and can benefit from decentralization?
Yes, I mean, I come very much from the decentralized data collaboration space so for me the idea that basically now users
for example have fit have fitness devices or other devices where they collect their data
and then later a company like apple or ura they the data, but the user does not have full write over the data.
And then seeing the disconnect,
like other scientists want to have data
to use it for their research,
but as it's now in the silo,
the way out of that is not really easy.
And so the science cannot use the data.
And so even if we then take one step further,
if not a scientist finally is able to create a paper
with some data, then somebody
else finds it and creates a product.
And then there's a disconnect between the profit then being made from the user and the
scientists.
And I think this is just like something that the decentralized science can revolutionize,
removing all the middlemen and basically being able to connect all of these parties together.
And that's what we're aiming for, ReflexDao, to connect somebody. I give my data.
I know what science has been created with it. And I even get then my feedback and my personal
help out of this. So, yeah, connecting, removing all the middlemen. I think that's a really big
step forward that science can achieve. Interesting. Stefan, how about you? What
was the aha moment that you realized that science and
exploration can benefit from decentralization yeah i would like to take this literally uh because
i i always thought that i had an aha moment right back in 2020 when i was also dealing with
the question how can we put user data to work without uh putting them into silos and then when
i when i started working for my last
employer i said this was molecule today bioxpressive maybe this time um i started there with a with a
totally wrong picture in my head about what those guys want to build and then i figured out oh this
is mostly about fundraising and i wasn't aware how how bad the situation is in science actually
it's more like it's really hard to do,
as I think Robert said there,
it's really hard to acquire the right amount of money
for some kind of revolutionary ideas
because many people in that space,
particularly the large players,
aren't aware or maybe they are to risk averse
putting money into things that are highly explorative or highly experimental.
And with Molecule, it was mostly VitaDAO that actually was my eye open.
I mean, I was never really deep into longevity or anything, but I noticed how many people wanted to research in this space and they simply couldn't get any money.
And VitaDAO, I think, made up the case where the race, I don't know how much was
that? And I don't know the net value anymore, but it was around two or three million dollars in
value back in 2021. And then I noticed that this is really an enabling aspect and that people
really wanted to participate in governance. And governance. So at that point, I noticed this was
actually our moment where I noticed that people really wanted to be responsible driving forward
the research aspects and this is what would really fascinated me about the space on the screen.
Interesting. For the second question, let's stay with you Stefan and we'll circle back
around with the team so you're not always stuck last to answer the questions and grab dregs
for responses. Stefan, how can DSI help younger scientists
who are often left out of mainstream funding,
which you raised, but also publishing as well?
It can be very challenging for younger scientists
to get their work published.
Yeah, I think there are like three questions
or three elements of this, right?
You already mentioned the term publishing, which is like maybe related to the term peer reviews.
And I think Robin already came up with the term, how can you prove something about data that you haven't put in there in the first place?
So all this kind of stuff is somewhat related.
But what I've seen, let's make an example of Vallindol maybe, right?
So I know those guys very
well, and they want to do synthetic biology. And I know
that many of the researchers that they are talking to are
those are like PhDs. They're pretty young. They're very,
very early in their career. And they particularly choose
Valley doll and everything that those people do to build up
the the the the the initial funding for the labs that they
need to create synthetic molecules for example and I think it's this this whole
space resonates so much more with their daily experience because they're quite
young people right it's so simple to just go on a on a project like biorex
was you say okay well I okay, what do I need?
I need $250,000 or something to set up.
This is a kind of sequencing device or something.
And raise money instantly from a large crowd of people.
This works pretty well if we're in a bull market.
So if the bear is going on, this is maybe not that simple.
But it's very simple to set it up.
And so every time I talk to those kind of guys i was quite amazed how how quickly everybody understood how this works
even everybody tells me that but three is like a very close ecosystem because nobody understands
what's going on but this is not exactly true for for young people right they can just jump on it
and start raising money that is what's what i would would say is the big benefit for younger scientists.
Interesting. Great insights. Robin, what are your thoughts as far as how DSi can help younger
scientists and how they can benefit from access to this decentralized approach to research?
Yeah. So first of all, all communication, for example, happens a lot in Discord or in Telegram.
And so you're not necessarily have to, you know, like identify your age or your background.
It's more about the quality of your contributions than about, you know, like everything else.
And you don't have to necessarily put your age first.
So like in a way, if you're a young scientist and you can contribute and you do the work and you help other people and you push things forward and then you're there and you can do things.
So like, I think that's the open nature of this decentralized world is basically removing these barriers that you normally have. Like first you need a CV, you have to get into the good university. Then you have to get into the, you know, like you need all of these steps to reach somewhere in the normal science world. You need all of the stepping stones.
In the decentralized world, the barrier of entry are much lower. So I think that's why
it's a much more open field. And so everybody is kind of welcome. And that's, I think, a big
advantage. And why it's just, yeah, it makes a lot of sense for young people to go into space.
It's just, yeah, it makes a lot of sense for young people to go into space.
Robert, do you have additional thoughts as to how younger scientists can benefit through this new trend and emergent application of decentralized science?
Yeah, I'll just add, I think the other two responses pretty much hit the nail on the head.
But I just want to add that, you know, in my personal memory, I remember watching a YouTuber, I can't remember the name of, but essentially, he had his own
biology lab, he was synthesizing, like new bacteria, proteins, and things like that, and
demonstrating like real effects that he can create. And it was really cool to me. And at the
time, I was like, I have no idea how much this costs or what sort of experience you would need.
But it made me realize, like, yes, I guess the meme is true. You can just do things. You don't need
a team of 100 people and, you know, a billion dollars to do some interesting research. It may
not be the most, you know, commercially successful research, but if there's a demand for it, then
people will fund it. And so, you know so when I saw this, I was watching this,
I was like, well, this would be actually a great use for DSI, right?
You have these younger scientists who might have,
they might not have all the credentials or connections,
but they have the right knowledge
and they might just need the right equipment.
And that's where you can kind of bring everybody together.
So yeah, that's basically it.
Interesting concept.
I guess the days of science for the sake of science or knowledge for the sake of knowledge with the government used to fund. I know that that has dissipated to your point that
there has to be a lot of end return and a return on that investment, so to speak.
Staying with you, Robert, for a second, what are some sensitive, what about areas of sensitive research data and where that fits into this DSI protocol, issues like electronic medical records or unpublished findings?
How does OASIS enable scientists and other communities to share responsibly while protecting data, especially patient health information, as well as ownership
of research?
Right.
So we at Oasis, of course, we're very focused on privacy and blockchains.
That's really our intersection points.
Lately, we've been talking about AI as well.
I think that maybe plays a part, but our original roots, one of the first applications discussed even five years ago or more
was in healthcare and medical records. And basically, our technology uses trusted execution
environments, these TEEs, which let you compute on private data. And we've built two systems out
of this. One is on-chain called Sapphire, which is a confidential EVM.
And I think that's very valuable because you can have this publicly available information
with access controls.
And you can permission out who can see what data under what levels, under what circumstances.
On the flip side of things, we also have Raffle, which is off-chain.
This allows for much greater scalability in analyzing data and even in sharing it as well.
But it lacks as much decentralization as Sapphire has.
It's not a persistent blockchain.
So there's these two points on the spectrum here.
And I think when you combine the two, you can get basically, you know, you can build any application that you want. As far as the specifics of sense of data
and things like that, I think it's super powerful to be able to leverage all these medical records
and, you know, actually produce outcomes that will benefit people. You know, we talk a lot about just
keeping our data private because we want it to be private,
but I think there's also the flip side of a lot of it is private just due to legal reasons
where it cannot be shared.
If you want to maintain HIPAA compliance
as an organization of some kinds
and you have collected data,
you can't just go sharing it willy-nilly
to the world for research.
There's very strict controls on that.
And so, for example, this is maybe not the Oasis Foundation's direct role,
but the Oasis Labs has built private SQL,
which you could run on Google Cloud today.
And that is HIPAA compliant.
So that is something that, you know,
if you want to be able to do computation on private data,
that's in a database, for example, you can do that.
So there's all these different ways of accomplishing the same goal.
And I think we have yet to see this entire industry be revolutionized.
But I think all the pieces are there to do that.
Excellent insights and response.
I was unaware that Oasis had a HIPcompliant solution already available. That's fascinating.
Pivoting over to decentralized autonomous organizations, Robin, how are DAOs changing how research gets funded and managed?
And can you walk us through how Reflex DAO works in action?
And can you walk us through how ReflexDAO works in action?
Sure. Yeah. So, I mean, we are using what Stefan has been building.
So IP NFTs and also the tokens that come with it as a funding mechanism.
And so basically the difference between traditional organizations is that our DAO and in general also the bio DAOs have the opportunity to be more of a general organization
that cares about the people.
So like we don't necessarily have the maximum profit goal.
So like if you compare this
with traditional healthcare systems,
they have shareholders,
they want to maximize the profit of the shareholders.
The DA dow instead is
aiming to to please its its participants of course we want to make money and and we do that now by
by raising money for different initiatives so for for example we we are in reflex tower building
different sensors so different centers for different purposes for example rings with
specific sensors to to monitor for certain chronic diseases or other devices. That's one thing. We create the IP NFTs out of it.
The DAO owns a share of those, but also investors and the community owns shares in it.
And later when we sell the devices, we make some revenue and give back to the people who invested.
The same happens for something that we call IP subscriptions.
That's basically detection algorithms or mechanisms for chronic diseases.
Again, these getting funded by the community.
A share gets owned by the DAO.
So like the DAO members have an upside, but also investors.
And so like later when then somebody wants to detect a chronic disease that
they have, they subscribe to it
and yeah then the revenue gets shared again so that's something that uh traditional companies
don't do so like it's just impossible for me to invest into into the research part of of like a
large healthcare corporation um and it can be that there are billions of dollars being made
but like yeah it ends up in the in the shareholders' pockets and not goes back to the people.
So that's a major, major change that basically happens through DAOs.
We concretely have our own device already so that we are selling.
We're building a showcase, so we have our own device.
We have an end-to-end case where we have a mobile app.
The user doesn't need a wallet, so the wallet is included.
My parents, who are 70 years old, are using it and monitoring their own health without having to deal with MetaMask first or something.
And then we have a DSiLAB where the data gets collected and can then be used for decentralized science.
So that's concretely how we are approaching it.
And in the long run, we are then going to make more sales, more subscriptions, and so on.
Fascinating. Fascinating. Stefan, pivoting over to the data side, I worked at a company,
IQVIA, for nine years. They were a large player within the health informatics and data analytics
space. Very, very sensitized to a couple of things as far as pseudonymized patient level information.
And one of the things that I used to speak to somebody on our scientific team, and he would
say that a single patient record is not all that useful. To the patient it is, of course.
But when you're trying to come up with large trends and make large discoveries,
you need a lot of information and you need
a large sample to get there.
So the question for you is, how can WellShare give people ownership of their health data,
which to them means a lot, but in a larger research scale, a single record really, it's
not statistically significant or clinically significant
but yet still make big discoveries how do you strike that balance that's exactly
the right question actually it's maybe the first question should be why would
any anybody care most mostly right right so just one electronic health record may
not bear like the solution on how to cure cancer, but it's the connection of them all.
The problem is that just leaking one, just leaking your EHR data might have a major impact on your life, right?
And the example that I usually give here is particularly interesting for women, because if you're pregnant and this misinformation leaks involuntarily and
you want to get a good job, I'm sorry to say that because I'm male, there's a good chance
that you are not getting the job because you are a high risk from the perspective of a
certain employer.
This is something that, of course, shouldn't be there.
But of course, if you just know it, you don't have to tell the woman why you don't want
to get a job.
Right.
And this is interesting right so if you leak data about yourself that's
else related people can can make a lot of stuff all of that and you don't want
that so the the question that we were asking it was mostly doesn't really
matter to a user if they own their own data in a certain sense and very
honestly I think nobody really cares about the ownership so much.
I think Robin made the case that that's also very valid.
Maybe ownership means that you get some kind of reward if your data, for some reason, contributed to a research findings in the long run, right?
So maybe somebody finds a new kind of pharmaceutical molecule or something, and that helps some people getting rid of COVID.
Very nice. Maybe you get $10, maybe a hundred out of that in in crypto value you could build this like that that would that would give the term ownership a real meaning right but honestly
with welshare we think it's it's much more than that maybe it's not a monetary incentive you have
there maybe it's really the incentive that if you have a certain
condition or you maybe will or you think that you could get that condition good example is diabetes
many people suffer from diabetes these days or they live with it actually um if you if you think
you could be affected with that you might be interested in contributing your data sets even
though you're still healthy to us to a kind of research system
that can later on help you staying healthy right so there are so many companies like aura who
actually collect data in private and who who build um artificial intelligence driven machines that
help individuals to profit from individualized medicine or not not actually medication but from
individuals to profit from individualized medicine or not not
actually medication but from let's call it behavior hints right so you the
machine can tell a person how to behave better so they are not running to the
into the risk of getting a certain condition but I think so this is the
main reason why people would like to contribute their data because they in
the long run will see some certain benefit and to your point
There's lots of data available and I think for 20 years people care about that problem
How can we say how can we keep the data private the way we are approaching it is
We don't want to have the data and we don't want to see it. We actually never want to see it
We only want to know other people and our case is actually agents to compute over the data and even that is only likely the tip of the iceberg the question
is if you if you think about a researcher today or a clinical trial what those people are doing or
what those processes are doing they want to find ideal candidates that help them conducting their
research and this is exactly what versure
tries to build right it's a matching protocol that tries to find patients that have a certain kind of
profile maybe they're totally healthy but the profile already hints towards the situation that
could get they could get into this protocol helps the agent to identify the users or the patients
that actually would help the research and then getting in touch with them.
This is why we don't like to talk so much
about ownership of data.
It's more like it's the default
that a patient owns their data.
It's more like how can we allow other parties
to get in touch with those patients or users
so they can just close the data in secrecy
or however they are.
That's what we address.
Interesting.
So fascinating insights from all three panelists here.
Very, very good information being delivered here.
Now this next series of questions are going to be open to everybody.
Stefan, we'll start with you first. What kind of real-world impact have you seen so far in your organization's work, whether
through community engagement, discoveries, or even potentially policy influence?
If there's something tangible that you could share with the listeners.
So one thing I noticed is exactly what I just said before, but let me phrase it slightly differently. So it's a better response to that to the question. Every time
we want to build some, I don't know, call it data collection tool for bioexperty or
something, mostly like the requirement is, OK, here's some kind of survey, you put data
into it, maybe daily. And then there's a huge, I don't know, lake of data that we can now,
I don't know, run our bots on. So there's a gigantic database full of data, just give
me everything, put a constant Boolean flag at the right and say it's saying users fine
with that. And we already we actually noticed that people started rethinking this aspect when we said,
you know, if you put privacy and TPA compliance first, you cannot just put everything on a large
public or less public pile of data and just say, yeah, let's compute over it, right? It's more like
they understood that data privacy really plays a role here. And we got the feedback several times.
They said, okay, if you know how to solve that,
we happily use your solution
because just putting data on the pilot
is a simple thing that we can come up with.
And this is how we're negotiating right now
what kind of requirements
actually are coming up for us.
But this is the feedback that I got
from the community that I know.
And I think we already have some little impact
on how people think about data in general.
Interesting.
Robin, over at ReflexDAO, do you have a real-world example or real-world impact that you can share from your organization's work?
Again, whether via community engagement, any sort of novel discovery or policy discussion or influence?
I mean, it's maybe a small thing, but it's a real-world impact.
So I've been using our app now for several months,
and I'm doing the breathing exercise that we offer.
And I mean, yeah, so basically my resting heart rate has decreased by a lot.
So it's actually helpful.
So I started with the idea to collect my data.
In the end, now collecting my data and actively
doing controlled breathing made me healthier.
So I'm really happy about it.
And several of our community members are now also
reporting this.
And yeah, we have really cool effects.
So in the end, it's something I didn't expect.
But yeah,
that's a real impact for me from my point of view.
Wow. That's a great example. And sometimes those are the most powerful examples,
being able to show the macro through the micro and an example like that. Robert, how about
over at Oasis? Is there a real world impact that you can share with the audience that has come about through the existence of the various protocols that your organization has put in place, whether it's policy influence, a discovery, a community engagement, or an actual benefit to users such as the one that Robin described?
described? Yeah, I would say at a very high level, I think I've seen a transformation in
how much privacy and in particular TEs are talked about within the last year or so.
I started as an Oasis community member in late 2021. And at the time, there was basically nobody
talking about privacy outside of just money, Zcash and Monero, basically.
Nobody was really turned on to the idea of confidential compute yet
outside of key players that are working in the industry, including Oasis, of course.
But I've seen in the last year, very mainstream people really emphasizing,
even I think Vitalik now, really emphasizing the importance of implementing
privacy at the base level of protocols. Really something that, in my opinion, should have really
been focused on many years ago, but I'm glad to see that that's changing now. And I think Oasis
has been definitely a thought leader in that space. As far as the specifics, like Desai is something that we really have not had a hand in so far.
That's kind of one of my goals working for Oasis right now.
I would love to, you know, foster these relationships and see, you know, an ecosystem grow out of this.
I would like to see Oasis become a thought leader in Desai itself, not just privacy.
So that's kind of maybe where we're starting here, right? This could be
the start of something very nice. For anyone who's listening in, please get in contact with me. I'd
love to hear more about what you're doing with DSi. But yeah, that's basically where I'll leave it.
I think there's still a lot of room to grow in that sort of industry.
Interesting. Robert, I think you're exactly right when you talk about that even now this idea of TEs and confidential computing are just coming to the fore, especially when you're looking at this merger between AI and decentralization or DAI or whatever you call it, crypto AI, that computational, confidential computating is being even more and more important.
So staying with you, Robert, for this particular question, what's the most exciting way your project is using smart contracts,
tokens or DAOs to reshape the research process?
I mean, you kind of said that you want to chart this
course. What's your vision for it? Right. So I would like to see a situation where
multiple different protocols can have smart contracts that interact in the same way that we
have DeFi money Legos right now, right? So that, you know, you can have a DEX and then
a lending protocol builds on top of that,
and stable swaps and liquid staking and all these different parts. So that's the DeFi world.
I would like to see something similar be built with confidential smart contracts for
decentralized science. So you might have a DAO system for funding, and then the funding itself
is, I suppose, DeFi. But then you can also have things like data sharing
that goes on top of that.
And who gets permission for the data,
that has to be in a smart contract,
I think ideally at least.
And so the more complicated that the systems get,
I think the more contracts you'll need to see
kind of built on the same network
and interacting with one another.
So yeah, especially with, I would say data sharing,
that's the biggest thing because, you know,
the level of complexity and who has permission
to see what data, that needs to be, you know,
pretty rigidly defined.
Otherwise, you're just recreating the same system
that you have already.
Certainly. Great points.
Robin, what's the most exciting way that your project is using either smart contracts, tokens, or DAOs, in your opinion?
I mean, you are a DAO, but talk us through that from your perspective as an insider.
Yeah, so I mean, to be be honest we didn't write too too
many smart contacts in our in our history so far we're using the the protocols and the things that
that we like and that we think are are good and so the one that that we really are using actively
and every user of us uses it is basically we're creating a data nft for them from ocean protocol and so like that's
a way of how you can manage your data sharing and so then the data the user basically allows our our
our server our back end to to use the data by sending them a data access token and so that's
like a real world use case every every every user does it with our app um they do they do it by
flipping flipping a small little button inside the app.
I want to share my data.
If they de-flip it, they delete the data.
But that's basically now in practice,
like a way that they are on-chain registering their consent to use the data.
And I think that that's really cool.
So, like, they don't have to even think about it as it's a mobile app
and the wallet is included.
They don't even have to see and
that it's now using blockchain technology but for us from a digital point of view it's actually
doing it and if somebody asks why are you allowed to use the data we can show it and so that that's
i think a really cool aspect but for our users yeah we try to to keep it simple for them and and
um focus focus on their personal health journey instead of on the blockchain as the first principle.
But yeah, that's something that we use already.
Every one of our users uses it.
Pardon my ignorance.
You said health NFT.
Can you expand on that a little bit?
I mean, many people, myself included,
a lot of exposure to NFTs were just JPEGs
that cost $200,000 with bored apes on them.
But can you unpack that a little bit as far as this use case of a non-fungible token within the health space?
So this is basically a data NFT.
And the idea is that it allows you to manage access to your data.
So users share their data if they want to.
And when they opt in for that,
they basically get this data NFT
into their wallet,
into their personal self-custodial wallet.
And so they can then choose
to share the data with us.
Basically, this happens
over their mobile app.
And so that sends us token to us
and we can see this transaction
on a blockchain.
We're even sponsoring the gas so they don't have to pay for it but yeah that's basically
practical practical way of having like your your own own own data for yourself and you can manage
it um we also have a use case where you can share them access to the data with a bot for example
with an ai agent or with the doctor so then somebody else can also use the data.
But it's basically an act that the user does,
and it's happened on-chain.
So that's a real-world use case.
So basically, forever it is stated, this happened.
And nobody can basically delete this flag
or the information from a private database or something
like this.
And they don't have to fill a lengthy document
and send it somewhere or something.
Interesting.
Fascinating.
Stefan, an exciting way that your project is either using DAOs or tokens or smart contracts
to help reshape the research project or process.
Yeah, that would be the perfect question for the job I got before WellShare.
But at WellShare, we also...
Everybody can look that up on BioExpress.
But at WellShare, there are actually two things,
and I think Robin also got it pretty much right.
I just wanted to actually say one thing.
The way on how you token gate things
or how you access gate things
comes with a little problem in the middle,
and this is really hard to solve.
And that's usually,
if you have access to a certain kind of data, how i make you forget that again i mean spoiler alert you cannot forget
what you already have said right it's it's a major problem this whole space once an ai whatever it
is has access to a certain kind of data you cannot make it unseen this is how it works
the only way around that is never disclose the data itself, always compute over the data.
Right. And then you run into a thousand different problems.
I just wanted to make the very clear.
This is a main problem. We had lots of discussions with other developers.
If you if you put something in the wild, it's all that it's it's gone.
But I don't want to to to to move too far outside of our current pitch deck, but there is a good reason why we're at the moment not talking about it so much.
What we want to achieve is that agents get access to user data or get access to data that they can compute upon or get more information out.
or get access to data that they can compute upon or get more information out, right?
What we are envisioning is that those AI agents,
I think many people will know what's coming next,
that those AI agents pay for it.
The question is who's getting the money?
What kind of currency do you use?
Do you know how much they have to pay?
Is there some kind of bidding model in between?
But this is, I guess, the problem space uh that we're moving into and that's
going to be solved definitely by a kind of tokenization which of course is built on top of
smart contracts so dows i guess won't play a major role besides being the ones who are requiring
certain data accessibility at wall share but the tokenization aspect at one point certainly will be
that ai agents are going to pay with a certain currency or maybe with liquidity to access the data as a whole or getting access to users individually.
And then maybe exchanging a certain kind of new token with the users.
Interesting. Interesting.
Stefan, we're going to stay with you and ask uh i'm sorry you dropped out of there for a minute i didn't mean to speak over you
no i think it was done already i don't know when when it stopped but just saying build a token
economy so people might get rewarded with uh certain tokens that they can exchange for tokens
that uh bio agents i'm sorry agents put on the protocol to bid for data access might get rewarded with certain tokens that they can exchange for tokens that
bio agents, sorry, agents put on the protocol to bid for data access. This is what we have in mind.
Please don't cite me yet. Don't quote me on this one.
This is not even part of our official pitch deck yet, but now it's out of the box.
Understood. Understood.
So making a pivot here, Stefan, what do you think AI and DSi, how they can work together to accelerate discovery while maintaining the trust and transparency that we've already talked about in several of the question and answer so far?
I think one of the interesting building blocks here is identity, right? So how can you prove that you are allowed to do something? And how can I maybe incentivize or put money where my mouth is saying, okay, if you give me $1,000, I don't know, I share data with you, which is not exactly what you should build. But that's what's certainly possible there. And this is where, so maybe make make it more abstract so we are currently living in a
world where ai agents are being developed at an insane pace right so everybody and their mother
now the question is how do those ai agents communicate with data sources and do they pay
for it right everybody already built some kind of ai agents knows how expensive it is to just use anthropic law 3.7.
This is insanely expensive.
And it's not so much about the LLM itself.
It's about the data that's going to be utilized by those agents in the long term.
For example, accessing origin strategies, DKGs, knowledge graphs, everything.
All that kind of stuff will cost some money in the long run.
And the way that I would like to think about it is mostly it's so much it's really
frictionless if you pay for all the data all the access using crypto primitives
and don't don't call your crypto just use tokens that that I that are made for
this particular use case like data tokens that Robin already mentioned.
We would call it like IPNFT fractions or whatever.
IPTs.
There are others, right?
And I guess this makes it so frictionless
to interact between machines
that this might be the ideal way of doing
or conducting economic transactions in the future.
Robin, what are your thoughts as to how artificial intelligence
and D-Cy can work together to accelerate discovery?
Yeah, so for us with our customers and our app and then collecting data,
we offer a lot of metrics already in our app.
But still, for insiders,
it's easy to see, okay, what does it mean? But the one aspect that really is interesting for them
is like now with an LM, and especially here is of course, privacy preservation is important.
You can talk to your data. I can ask questions like, hey, what's going on? What are the trends
of my data that I've been collecting? And so that's something where you normally go
and visit the doctor, you know?
So it could also be done in the future,
an AI agent that basically helps you with that.
But from my point of view,
that's like a very, very important aspect of AI
and DCI coming together.
It's like my data, I connected to an LM,
I connected to AI, and now I can get insights to this.
And the next step then is, of course,
now we have the data of multiple users.
Now everybody can become a scientist.
So I can ask questions about the data of many people
because the AI can convert my question
into an analytic script.
It can then run it in a decentralized data cloud,
basically enabling these things
that normally would need complex computer scientists to do or doctors to
do now being taken over by the AI and so just accelerating my personal and everybody's access
to the data and in science in general so that's why I think like AI and DCI are match made in
heaven you know so normally you would have to spend a long time to find the right people to do
things and a lot of money to find the right doctor.
Now this just happens much more quickly.
And I think this is really an important factor.
Interesting.
Robert, how about you?
Thoughts on the merging or the combination
or the one-two punch of designed AI going forward?
Yeah, I think the answer is given already
or probably more insightful than I can give. One thing I wanted to kind of touch on, which I don't know if this
makes any sense, but I figured I'll just say it. Yeah, if you've seen data, of course, you can't
forget what you've seen. But I suppose in principle, there must be a way that if you have an AI agents
that you configure to not have memories of what it's seen and it never leaks that information
again the implementation is maybe harder than the theory but if it never leaks information and it
doesn't have memories but it simply makes decisions based on data I suppose in principle that you
could have such a system again I think that's much harder to build than to just think about. But that was just where my mind was going.
I just wanted to touch on that.
You know, maybe that's not exactly focused on the D side part of things, but yeah.
No, but it's a fair point on the AI side.
And I think you're right.
And I think even when they do try to program those types of systems, people still try to
jailbreak those programs and find
end arounds. But to your point, if it's not able to keep that data or it's washed every 24 hours
or whatever, there may be a way around it. Robert, starting with you, do you think DSI
is ready to collaborate with traditional academia? And how high of an ivy climb does D-Sci have to get over that cloistered wall?
I doubt that D-Sci is going to be the limiting factor here in terms of wanting to collaborate.
I think the difficulty will be the other direction, getting more highly reputable academic institutions
to want to collaborate. Not to say that they don't,
but they tend to be slower moving. Their funding is through all these organizations and governments
that we've mentioned. So they generally have their procedures in place and they don't want
to mess with that. Coming from my perspective in academia, I, of course, was happy to get any input from anybody
about what we were doing if it was relevant. But input may be different from more structured
collaboration where there's funding on the line and deadlines and things like that.
So I think DCI is ready. I don't have as much insight into if academia is ready though
interesting robin what are your thoughts uh how long or how how hard of a slog is it going to be
for dsai to to get buy-in amongst traditional academia so the traction that we are seeing is
basically because of the uniqueness of the data.
So the thing is, we can now produce data sets that like traditional academia can only produce with a lot of money.
So we're doing a lot of sleep recordings.
So like very special continuous sleep recordings of heart rate data.
And so this would mean like the patients who have a certain chronic disease will have to go to the lab every day, you know, every day, and then just to continuously have the data. And so with our device, you just get the get high grade data automatically by just wearing it while you sleep. And so now we are already
finding traction in researchers who are saying, okay, this is something that I really want to
want to get into. And I want to learn more about it. And so we have first groups of trials that
are ongoing with our device because the people
say, I would just, it's not affordable.
We cannot do this otherwise, you know?
And so this is a unique factor.
So I think D-Sci has just had like certain advantages over traditional science that,
yeah, I think we'll make some experiments at first, you know, like possible.
And then we will see how, what, what comes out of it. You know, like it's, it's an untested field, you know, new data, new insights. Let's
see, maybe they, the, the scientists can derive certain really cool insights. And then, yeah,
this might open the door to really, to a broader, broader experimental space for that, for data.
Fascinating. Great response though, as far as the uniqueness of the data that can be
derived and generated. Stefan, anything that you'd care to add as far as how long or how soon we
might see a collaboration between traditional academia and DSi? Unfortunately, I must say
that I have far more information that I may not share. Okay, very good.
Because, yeah, no, no, I cannot share that.
But I was sitting in that office and I can tell you
there are lots of people dealing exactly with that problem.
I want to generalize it and say,
many of the players in academia,
and most of the universities,
they, you can be happy if they know what Bitcoin is.
Right. So if you raise money on, let's say, I know I can still sit before the audience,
maybe if you raise money on the base blockchain, that's an L2 on some Ethereum,
exactly. So I mean, in Europe, they want to have euros. In America, they want to have dollars. Even with European universities, they have a problem getting fundraising in dollars, right? So this is already a big friction point. They have to educate them.
like creating a wallet or something.
But very honestly, all the users who want to put funds on it,
they usually cannot expect them to install a MetaMask private, not gasoline.
This is usually never working.
And I guess there's still quite a lot of friction in the system
that doesn't really allow to onboard the people you really need to onboard.
But I think it's a technical thing.
So the more you put effort into the usability of things, the more people will start onboarding.
But I think onboarding the masses will still take around one or two years.
Excellent insight as well that there's still a lot of friction in the system.
So this is our last prepared question. And Stefan, we'll give you a first crack at it.
What should the ideal DeSci landscape look like in a few years from now?
Where would it be ideally in your mindset if you had a magic wand that could make it such?
Ideally, I think it's the vision that many people in that current ecosystem also have, and that is we want to have communities who care about certain conditions.
And I mean, now we're reducing D-Sci to medical research again.
Of course, D-Sci could be so much more.
I know people working in space exploration and stuff.
since my roots are always in medical science,
that's basically, I would always say,
ideally, patients or users who are interested
in a certain condition, dementia is a good example,
they become active members of those DAOs,
and they contribute knowledge, questions, money,
whatever it is, right?
But they contribute to a DAO that means something to them.
Everybody gets a feeling that they contribute
something meaningful.
And in the long run, and this is maybe the best answer
to the question that I could give,
it should be a totally liquid ecosystem of DAOs
that where people can actually exchange the governance tokens
and say, I believe in this project,
but tomorrow I don't believe it anymore I will believe in that project and this
whole ecosystem is hyper liquid so you can actually move the money where it's
gonna be needed next right so and then the money flows back to the ecosystem
that's I guess the essential vision that we are that I've been working towards
before and that now adventure we're contributing data to it, but it's, I guess, this is like
the ultimate vision, getting people and getting real users into the Discord servers and enabling
them to help themselves by adding money or knowledge.
Interesting.
Robin, how about you?
What's your vision of the DSI landscape look like within the next three to five years?
And what would you ideally like it to look like within that time?
So my idea vision for now also focusing a bit more on the medical use case would be that the protocol starts caring about the user.
So like the data of a user is interesting if the user is sick, you know, like if we just collect the data of healthy people, okay, maybe some of them are really, really good, good pushing themselves.
So that's interesting.
But on the other hand, a protocol, a DCI protocol, which would allow that like somebody who is not healthy becomes interesting to it.
So like it starts supporting it.
Like it sends its sensors because it wants to know more about this person and wants to crack the case how to make them healthy again
that would be like my ideal landscape so that's something that we also want to enable with reflex
now like if we find out not doing so well we give you a massive discount so we can know more about
you because you're interesting to us and that's i think i think the future of this i should go in
this direction you know so finding basically paying people who are not healthy to join you know that that will be my
idea case so that's that's how it should be in the future and and the tokenomics and everything
could could be modeled like this we have a free hand you know so like we can we can set the
systems up and in the end like the healthy people they would still be happy you know
one day they could be in the same situation and if if we don't have the data of the not so healthy
people, then we are going to miss out. We need it. This is what we're going after. So
that's my vision.
Interesting. Robert, how about your vision and that of OASIS for DSi within the next
few years?
Yeah, I'd like to see, again, an ecosystem that is interconnected,
that is composable, and something that I think the barrier to entry is a lot lower.
Right now, if you want to get into DSi and private compute,
then you're basically building from scratch.
And this is an important thing for people to be doing,
but maybe in the future, I don't know about a couple of years, but somewhere down the road, making it so that if you're, let's say, you know, an academic institution or something like that, and you want to do some sort of crowdfunding or some sort of crowd decision making, that it's not this whole project of, you know, building a DAO yourself and,
and dealing with tokens and different blockchains and things like that.
Everything needs to be abstracted away is what I'm kind of trying to do.
I think it's definitely possible, but I think we do have a road to get there.
And yeah, I'm looking forward to seeing how that evolves over time.
Excellent. Excellent.
So that concludes the prepared questions and the prepared discussion that we
had again, huge thanks to each of each of your panelists for your insights. We have a couple of
minutes here, maybe enough time for one or two questions from the audience. And so we'll open
it to them. If you want to speak, please request the mic and we'll do our best to bring you up in
that order when it's your turn. Please briefly introduce yourself, keep your question very short, and above all else, let's keep things respectful and constructive. We're
here to learn from each other, and civility is the key. So the floor is open. If you would like
to speak or ask a question of the panel, now is your opportunity.
All right.
It doesn't look like anybody's jumping into chomp at the bit, so that is fine.
With that, since there are no audience questions, I'd like to give each of our panelists a chance to give their final thoughts.
So, Robert, we'll start with you and then Robin and then Stefan.
Anything we missed that's important to note on this topic of DSI in closing?
I don't really have anything too specific to add.
I think just, you know, we need to keep our eye on the prize of we're trying to create real changes in the world, you know, real research results and things like that.
research results and things like that.
I think in other areas of crypto,
there tends to be this kind of lost in the weeds attitude
where we're worried about infrastructure
and all these systems.
And how do we build infrastructure for our infrastructure?
And then we kind of lose sight of things.
So I'm not saying this is already happening with DCI,
but I think that's very important to not do again,
not to repeat the same mistake.
Indeed. Robin, final thoughts?
Yeah, so I'm also very much looking forward
to building more products and building more subscription
and helping people.
That's what we want to achieve.
And I think that's the important part,
to not lose the product and the real use case
for people out of sight in design.
Excellent. Stefan, you get the final word.
Very nice.
I don't know how many people here, developers,
already know because of XKCD, which is a stick man cartoon.
And there's one that I always have to think about.
It's like two people saying, oh, no, look at that.
There are 13 competing protocols.
Let's just build one that actually combines them all.
And the final picture is, OK, now we have 14 competing protocols.
Right.
And this is actually something that Web3 came into life.
So this is why we build on Web3.
Everything is just open.
But still, it feels like how many blockchains do we have?
How many tools do we have?
How many ideas of identity do we have?
And I think it's always good to take a step back, was what already has been built what worked and what didn't and I think these are should be
built on stuff that all people maybe already tried but failed because they
couldn't put the money on I guess particularly in open science there are
so many primitives that I found it look very promising but for some kind of
reason never made it so I think it's a good time to to see what others are
built to look of to look after what others are building and get more inspiration instead of just thinking that everybody can build everything on their own a better way.
Outstanding. Outstanding.
Well, that's going to wrap it for this particular Twitter space.
I would like to thank our incredible panelists for sharing their time and expertise.
Thank you to the audience for tuning in. A special thank you goes out to the sponsor,
Oasis Foundation, for making this important conversation possible.
Today we covered the fundamentals of DSI,
what it is, why it's needed,
and how it can transform the way science is conducted
and funded globally going forward.
We heard various perspectives on research incentives,
reproducibility, open access,
as well as exciting tools and real
world applications that are being
built in the ecosystem now.
We hope you'll join us again for our next Twitter space.
Details will be posted soon. Until
then, be well, stay curious,
and you're welcome to disconnect. Thank you.
Thank you. Great hosting.
Thank you, guys.
