[Music]
hello everyone and uh can you all hear
me awesome um I'm vaugh McKenzie landel
I'm one of the co-founders of butter
we've uh been working in the governance
space for a very long time and um
obviously very excited about fut talk in
prediction markets and that's why we're
all here we have this incredible panel
full of lots of people who my love and
admire um and I'm going to just hand
over to each of them to give a very
short introduction and and then we'll
kick
off yeah um I'm Martin um so in a
previous live Ann nois we started with
prediction markets and uh wanted to
implement F fi and other things um so in
in general yeah I I'm absolutely a super
big fan of that uh but I think on this
panel I will a little bit play the the
skeptic here um because yeah I think as
as Robin
mentioned well you have the idea and
then you have the all all the details
that need to be uh figured out so I I
think I can a little bit bring in that
perspective I just talked so I'm Robin
Hansen so uh I'm Calvin also ctif uh I'm
the co-founder
ofari um we are uh we just announced our
project a few days ago uh our plan is to
help um thousand and other organizations
make great impactful uh uh positive DEC
decisions um y hi everyone uh I'm CJ
from from Limitless we're building uh
like uh basically we're processing
around million dollars in a day in bets
right now for like zero day contracts on
financial markets uh I believe that like
with crypto we can build the the world's
largest economy uh on chain uh outside
the jurisdiction of any one particular
nation state and I think that uh as well
as that we need to build really
efficient Global marketplaces on on top
of the infrastructure and so that's what
we are doing at Limitless
Labs thanks guys really appreciate that
so we're here at diak today and um so
the first question is how do prediction
markets tie to diak how do prediction
markets and epistemic tech make the
biggest impact in the vein of diak on
differential progress defense and
democracy over to any one of the
panelists one ring to rule the
mall if you could have reliable
prediction markets on whatever policy
question you have then you can just do
better on all of your other areas of
life you could have better know how to
pursue longevity better know how to
pursue decentralization whatever it is
you're trying to do having better
information on that can make you do that
better so that could we do much better
and how does that map directly to say
for example
defense yeah no I I can just replicate
that so um so yeah I think the the the
promise is is is very clear so the
promise is whether we we talk about um
yeah even simple things like this
community node or uh so from from micro
from micro decisions whether to show
that Community node or not to show that
to extremely large micro macro decisions
should we raise the interest rate or
should we make this huge uh um um well
defense spending here or there uh in
general the promises that um this is it
tool for more more robust decision-
making to bring in yeah to to have a
better quality of of of of bringing
information that actually um show shows
the true true impact of a decision yeah
so I'm going to make a comment here like
so over the last uh few weeks uh
everybody has seen uh aot um lots of
people are talking about uh prediction
markets of course predicting uh who's
going to win the election and and uh
this made a lot of uh generate a lot of
excitement uh but uh actually the most
interesting thing is not like predicting
only predicting probabilities that
normal prediction markets they do but uh
predicting the consequences of of things
so if you could have for instance uh
conditional markets on uh inflation on
uh GDP growth on um um spending on
unemployment conditional on uh
candidates right this would be even much
more interesting for for for democracy
you could actually see like a scorecard
for the candidates right like a game you
can pick one this one's better on this
one this one's better on this other
thing right so this is the promise of
using conditional markets for decision
making yeah sorry man go ahead maybe let
me let me throw in one kind of uh uh
concept to challenge this this idea so
to say I mean I'm just pulling up here
uh coin Gecko and and and look at prices
of of of crypto and well they change by
6 7% a day um so I think prediction
markets rely on the assumption that
markets are so efficient um that out of
those prices we can uh get reliable
information um or better information but
I would argue well there is also a lot
of noise uh in in in markets and I would
say that uh markets here um prices
change by 6% is largely not related to
any meaningful signal but is is or well
I need to be careful the statement but
but there's still a lot of noise so that
that's I guess my question how how can
is there enough signal in the
noise so when you compare head-to-head
this mechanism to other ones
consistently this wins so that means all
those other mechanisms have more than 6%
mistake think about any committee you've
ever been on think about the gossip
Network do you really think that's
within 6% of the truth come on like
being 6% close is great compared to what
we usually have
yeah I would I guess I would comment the
like the whole question from from a
little bit of like a different angle I
think that definitely prediction markets
have a lot of power in terms of like
fusting and decision- making uh but I
think like in a in a crypto context
what's really interesting and Powerful
uh is the fact that essentially we can
build these like Global efficient
marketplaces and so I I really believe
that markets in general accelerate human
progress like if it wasn't for markets
we wouldn't be where we were today in
almost every field uh and even like they
have positive trickle down effects like
science funding for example Brian
Armstrong sells his coinbase stock to
fund like moonshots and and science
funding that's a trival example in in in
a global context but still kind of
proves the point and I think that like
building prediction markets on chin can
be defensive in the sense that uh we
actually have a capital formation and
wealth generation outside of the the
nation state in this kind of global
onchain economy uh and I think why
that's defensive is because we can build
this kind of resilient independent
decentralized systems that manag to kind
of form their own Capital like without
for example being taxed on it also
without the very heavy regulation which
is a big issue there are only 16
designated contract makers in the United
States There are 16 licensed derivatives
exchanges but money cannot move globally
at the speed of info in the traditional
system here it can and we can build
these really powerful marketplaces that
are Global and accelerate human progress
I completely agree I think markets are
very important important piece of
technology I actually do believe that
one of the reasons that we are able to
accelerate defense particularly with
prediction markets is because we're
basically getting rid of any Authority's
ability to lie to us right because we
can delegate information and Truth to
markets I think this is great and um
actually speaking about this if you
think about futaki so far as you said
we've had lots of messy details I'd love
to know what you think the key
challenges in implementing futak will be
for re World organizational decision-
making
right uh so um some some some challenges
of course uh Robin mentioned uh the
matter of the alst and the in the
boardroom uh so there's always this uh
this risk that uh uh prediction markets
and also decision markets are um some
sense threatening to uh the power of uh
uh insiders of some organizations that
maybe are not making most uh uh
efficient uh uh decisions so this is uh
for sure a big challenge uh so another
challenge uh that is uh marching uh uh
I'm going to try to connect uh the
previous question from marching to uh
the combinatorial market idea from Robin
which is part of our basically Grand
Vision on fitar which is uh um so matter
of noise um when we evaluating a
potentially a small or medium siiz uh
prop proposal or decision in a company
um many of those if you're relatively
small or medium you're not going to have
a clear impact uh visible impact on on
the share price uh so that makes it
really hard to um to use this directly
to estimate uh but if you've had a a
full Network or full tree uh where you
can see like you can you could have uh
markets for a share price or token price
but connected to these you also see the
kpis market for different kpi number of
uses Revenue uh uh other kinds of
metrics important for the company so uh
you could actually see okay maybe I
don't there's a lot of noise I don't see
the impact of this decision on uh the sh
token price but I see the impact of this
decision on this minor kpi that has but
this minor kpi is associated with this
major kpi which is in then related to
the share price so I think that's a this
is BR vision for many decisions is
actually have the markets all the
information connected to each other
maybe the to kind of reorient the
question what problems are you running
into building and operating these things
prediction markets fakis what are the
hard problems what are the
solutions yeah I I I can say one one
hard problem or well relatively hard
problem is to just uh find traders that
are comfortable kind of going into those
um into those positions and just to give
you give you an example of um let's say
we would do this for ethereum we would
say Okay conditional we we might go this
rout road map or that route map um and
then um we want to use this futy
mechanism so essentially people can say
conditionally to this route map I I buy
eer and conditional to that I sell but
then to to practically do that you need
to you need to believe that the going
back to this correctness of of prices um
I mean yes 6% is in a day but but I mean
we really or what is really the fair
price of Isa right now and I think there
is there could be a range of some people
believe it should be 10,000 and some
people would believe it's could be less
than a thousand so uh so if you are in
the camp of it should be 10,000 then
kind of probably probably in even in
both uh in both decisions you would say
well I want to be long eer I want to
hold eer and if you're in the camp of
well this is really not worth it it's
just just worth 10,000 and again in both
sides so you need that person that says
well the price is pretty much right now
and really that decision makes a
marginal difference for me to um uh to
hold the asset and then let's say let's
say there's a really good proposal and
you really like that so you go along on
that now you hold this conditional yes
now the next day some external
completely unrelated event happens where
the whole crypto Market crashes by 50 %
you hold this uh yes
proposal and hold it under a price of um
well the price from yesterday um you
still think the proposal is good but now
your incentives are to um for the
proposal absolutely to not pass because
then you would hold all the dollars and
not the asset at a price that's now 50%
um uh or where the real asset is now 50%
cheaper from from what you bought it so
not sure if anyone could follow but but
those are kind of the challenges I I I I
see so so 20 years ago we had a burst of
applications of prediction markets
including in corporations so I think we
saw typical failure modes there that are
instructive about
today typically if you went to work with
a company about setting a prediction
Market you would say well what are your
most important issues and and you know
numbers you'd like to track and let's
set up markets on those and they would
usually say that's a little sensitive
let's do something a little safer and
they would pick safer topic and then
they'd get accurate estimates on them
and satisfied users but they go yeah but
we didn't really care about those so you
know that would be one outcome or you
know they would say talk about something
important and then management couldn't
resist having opinions that disagreed
with the market and the market gets
proven right and the manager went wrong
and they're just really mad and want to
kill it so for for example the US
government missile test agency had uh
prediction markets on which tests would
actually go forward so they put up they
try to make a lot of of tests and a lot
of them don't actually happen because
they have to coordinate a lot of
different parts of the military make a
test happen if one part isn't there the
whole thing has to be scrapped and a lot
of money is lost and so they wanted to
know which things would actually happen
and they actually were able to better
estimate which tests would actually go
through it and maybe Sav money by
cutting back earlier but then it was
more legible that they knew ahead of
time that it wasn't going to work and
that was a management problem so they
didn't want that anymore they'd rather
pretend they don't know how these things
are failing
yeah uh like I guess I'm going to like
talk about this from more like consumer
product building perspective um L like
the future Aly side and I think
definitely like and historically it's
it's absolutely true that marketplaces
are like very hard like uh products to
to boot trap and to activate like the
atomic like Network effect uh I think
that like uh it's definitely like uh to
incentivize like market makers or
liquidity providers especially for
things like pop culture markets right I
mean you can always build the the model
for for like elections or Sports markets
or especially in Limitless cases like
the financial markets right you can use
the the volatility to understand how to
price them and so it can be attractive
to institutional market makers because
it's essentially like a short-term
retail option flow um but at the same
time you know you may look at Poly
Market how much they spend per month to
incentivize market makers to come like
into their Autobook uh actually I spent
a lot of time previously and like I I
spoke to Robin about it in Berkeley like
kind of obsessing about incremental
Improvement m ments in the amm uh which
we see like for example like Paradigm
just launched the P PM amm right we
actually going to spin up a contract for
it to see how how much of of improvement
is it uh but I definitely think that
challenge is like how do you incentivize
the market makers either you you use
cash or you use your token or what but
it's still a huge expense uh for for
bootstrap in like the initial Network
yeah but uh maybe over time it will be
will be worth it all right brilliant
thank you so much CJ thank you Kelvin
thank you Robin and