>> Fahad Saleh: Okay. Should we

launch?

All right. Welcome to from

whiteboard to mainnet. This is a

podcast brought to you by

Columbia University Center for

Digital Finance and Technologies

and also the Ethereum

Foundations Academic

Secretariat. Today, we're going

to be talking about

decentralized autonomous

organizations or tao's, for

short. And so I'm your co-host

Fahad alongside Theo and we have

four awesome guests here. Today,

we have three academics and one

one person who's an industry

now. So we're gonna talk both

about research and we're going

to talk about the practical

applications of it. So let me

briefly introduce our guests at

the top here. So we have Jungsuk

Han from Soul National

University Jongsub Lee also from

Seoul National University Tao

Li from the University of

Florida, and then we have

Michael Zargham, who's the

founder and CEO at Block Science

and Research.

Directorate megatov. So what we

want to do here really is, we

want to start by talking about

some work that Jongsubh Jungsuk

and Tao have on Tao's and

specifically looking at sort of

looking at it from an economic

perspective. And then we're

going to transition into having

a broader conversation about the

implications and how to sort of

properly design voting

mechanisms in the context of

Tao's. So let me just dive right

in and I think, you know, the

first thing to really think

about before we get into sort of

thinking about any research is

to understand, kind of at a

high level, how TAO'S differ

from traditional firms because

Tao Jongsub and Jungsuk are all

professors of finance. So

they've studied at Lent and

written on at length, what we

call, corporate finance, which

is the analysis of traditional

firms. And so when we start to

think about Tao's, we want to

understand In foremost kind of

how they're different.

from from traditional firms. And

that also, then informs exactly

how researchers start start to

do formal analysis

about them. So, so, first of

all, yeah, what are the primary

differences?

between a traditional firms and

dows? And also how does that

enter the framework of

analysis? And so, you know,

Jungsukj jongsub or Tao? Any of

you do you want to Take that

one.

>> Jungsuk Han: Yes, maybe I can

explain briefly about that. So

if you think about corporations

in traditional sense, they have

leadership such as CEOs and

board members, they make

decisions for the shareholders,

But but in that case,

inevitably, there is a conflict

of interest with one the

leadership of the company and

then the owner of the farm

shareholders. So we call it,

the principal agent problem

um, the leadership is making

decisions on behalf of

shareholders, but then they

might have their own On agenda,

they have they may not have a

line incentives so this is a

critical problem and

traditional organizations.

On the other hand, Tao

decentralized autonomous

organization. They don't have

central leadership at

least in the pure form, there's

a various degrees of Dow,

there's hybrid ones, which

actually has some human

leadership, but in pure formed

now, it doesn't have any central

leadership. It is Organization

based on blockchain.

or a smart contract on

BLOCKCHAINS. So the, the all the

decisions are made by voting

according to the tokens. So

they, it doesn't really require

any human intervention.

Therefore we don't have a

principal agent problem.

So that that is the kind of key

difference between Tao and the

traditional aggregations, of

course. There are many other

differences for example, in case

of Tao the users and then the

the voters.

they are actually the same body

in chemical corporations

consumers, who are using the

services and goods and they

shareholders, these are

different bodies but in case of

Tao, it could be actually the

same same body.

But as I mentioned, the critical

difference between Tao and

Corporation is the absence of

principal agent problem.

>> Tao Li: Yeah, so I think, you

know, basically they were there

were, they were also many other

differences. Some of them are

captured about our model as

well, for instance, you know,

if we talk about traditional

corporations, we often talk

about cash flow rights right

control, you know, institution

investors stuff like that. But

here in terms of the Tao

setting, when, when we talk

about

governance tokens, typically we

value is have any tied to

platform usage or

network effects rather than

traditional cash flow claims,

which is, you know, a very

sentient element in our model

Um, yeah. So and also, I would

say, in terms of the legal

background, or those, that's

not really capturing our model,

because our model is not

focusing on that element. But I

think that's, that's also very

important difference. Is that

corporations typically would

rely on courts on fiduciary

duties. You know,

listing rules, etc, but here in

the dove space and is as this

point, we have very thing legal

infrastructure in place and

often times people are just, you

know, relying on the smart

contract which is which is very

different from the traditional

legal.

>> Fahad Saleh: Michael, do you

want to add a little bit of

context?

>> Michael Zargham: yeah, I

would say one thing I've learned

from working with and in a bunch

of Dows is that it's worth

noting that the principal agent

problems in practice

Don't totally go away. They show

up elsewhere, um, the natural

way this happens is that

because you have a primarily, a

smart contract, as a locus of

coordination, where there's some

voting that body that ends up

making voting decisions, isn't

really operational. It can't

really do anything. And so it

ends

up having to whether it's field

proposals, or procure services

or decide, which members of the

community are going to be

empowered compensated or allowed

to do certain things.

Ultimately, you end up having

the organization itself as

principle and some agent of that

organization acting in

fulfillment of some commitment

that they made through some

voting based interaction. So you

still get a principle agent

relationship and you still get

principal agent problems. It's

worth noting that Main

challenge in Tao's, as I have

seen, it is the lack of clear

separation

between operations and

governance, which is normally

codified via the shareholder,

basically owner or shareholder

kind of senior executive

management. kind of staff, you

know, thin bottleneck there and

so the tao's are releasing that

bottleneck a little bit but that

also creates a cognitive strain

because now you have the

attention cost on governance

decisions over a much. Certain

set of things often a much more

granular set of day-to-day

operational activities, and

then you see failure modes

around the failure to engage the

lack of expertise or

misalignment amongst the voting

population if they are engaged.

And so, I think it's worth

noting that Dows as such are

fulfilling the same function as

firms as kind of sites of

collective action or lokai of

coordination. They have a

different architecture and that

new architecture is more like a

joint constraint satisfaction

problem. We've got a lot of room

to learn how to use computers

to do that effectively, but I

like the distinction that was

made in terms of the the

architecture compared against

that kind of traditional

bottlenecking at senior

management.

>> Theo Beutel: Thank you,

Darwin. That's important to add.

Um, yeah, I guess we can agree

that

the cows or diverse mechanism

that is used righty but coming

back to maybe the

basis of the study I believe

there's a certain type of style

that was the basis. I'm curious

to learn more from the office

about your primary insights. So

so you should be building a

theoretical model of governance

feature, featuring strategic

token trading and the token

based voting and and then you

investigate conflicts which on

face of interest. So could you,

perhaps, share, what is the

most notable insights? You've

found out the course of your

investigation.

>> Jungsuk Han: Yes, maybe I can

share some of those insights

about our model. This is

actually related to the the

earlier question about, what is

Tao? And then I imagine the

that.

That Tao is organization with

our central leadership.

Therefore, it is

absent of principle Asian

conflict, but as Michael

mentioned there, there does

exist some

some could exist principal agent

problem because there's a human

interface but theoretically, if

there is no human interface, if

it's really pure form, we may

not have any human intervention.

Therefore, no, principal agent

problem, but in reality, of

course, there could be some

human human part that they could

easily

create some problems. But let's

just go back to just theoretical

idea that that

always purely smart based smart

contract based organization.

So, in that case, now, the

decisions are all made by voting

and then whoever kind of

captures the voting could

actually

The outcome of all this decision

making. So that's where this

ownership concentration of

token comes into play.

Often, there are large token

holders. What? Which we call

Wales. So if there are

whales who have substantially

large amount of tokens, the

whale can capture the distance

making, and if the whale doesn't

have online incentive with other

users, the whale may

pursue their own private benefit

at the cost of other users. So

that that is the the critical

problem of Tao. Even though that

thou have less of The

principal agent problem from the

traditional corporations, but

now has other issues with this

cons of interest between large

holders and a small holders, of

course, traditional corporations

may have that, but then the Tao

it is now this is actually

critical problem. So what we

study in our theoretical model

is how this kind of situations

could be avoided. Given that

trading mechanism in the market.

So often we think about

quadratic voting mechanism which

can mitigate this

problem. So quite a reporting

mechanism is saying if someone

wants to vote more it becomes

more and more expensive as the

Amount of voting increases so it

could increase quadratically.

so

often this can result the issue

of large holders swaying, all

the outcomes, however, at the

issue with the civil attack. So,

one can make many addresses and

then make votings dispersed

across all this erases. And then

in that case, the

voting cost doesn't increase

quadratically because all the

small addresses will have

rather low voting cost.

So how can we actually go around

this problem? What we show in

our model is actually the

trading mechanism

Could be the solution for this

problem. Namely the token in

liquidity. So when you think

about liquidity or liquidity,

it is liquidity. Usually the

good thing, the definition

literally, when you think about

it is easiness of buying and

selling certain securities in

this case token. So it if

buying and selling tokens are

easy. If That should be good.

however, in terms of governance,

actually, this could be an issue

because if

there are whales who don't have

enough tokens to change the

outcome, but then a close to

it, then wells can easily. buy

more tokens and then change the

outcome. And then they can

they can pass a proposal then

maybe harmful to other users,

but then then may benefit

themselves. So this could be an

issue. But then, as I

said, quarterly voting may not

work here in case that they try

civil, okay? But

then in case this is don't buy,

let's say tokens in which are

trading on the

market. Then the liquidity

becomes like speed bump when

when the the whale wants to

Take buy more tokens as they buy

more and more actually becomes

very expensive. It doesn't

matter whether they have many

addresses or not.

assured amount of tokens. There

they are, buying the market will

push up the price and then

making the

Making the the voting very

expensive for them. Effectively

this becomes quite a bit of

boring. So what we show

theoretically in the model is

that

the token in liquidity is

effectively becoming qualitative

voting and that which may result

all this some of these

governance issue. So that's one

of our the

Theoretical results. And then we

actually have other results

about the low-ton commitment

and so on. But then maybe I'll

just, you know,

>> Fahad Saleh: Yeah.

>> Jungsuk Han: start here in

and listen to others. Yeah.

>> Fahad Saleh: so I want to

unpack that a little bit and

then maybe you can bring a few

more people in. So

you sort of talked about two

things there, one was quadratic

voting and one was illiquidity

and you mentioned that the

liquidity could look like

quadratic voting and so maybe.

But I want to put quadratic

voting for the side for a

moment, and talk a little bit

about the liquidity because I

guess one way to think about

what you're saying is that if

I'm already a large holder, if

I'm already a whale, I could buy

a little bit more in order to

become pivotal in a particular

vote. And if it's if the market

is very liquid, then that may be

very, very easy for me to do and

that's going to cause the

problems that you're

describing. So I'm kind of

wondering though, then and this

this may be even the question

for Michael because maybe is a

bit more in terms of like what

we actually see in practice is,

like, do we see for instance,

people, just buying directly

ahead of votes

Holding that, anybody has any

point in time at some point had

to be purchased, right? And so

really, it seems to me what

matters is kind of like whether

they're doing a significant

purchase at a, at a particular

point in time, right? So for

instance, like, if I'm always

forty percent and then I just

want to become, I don't know,

let's say it's a majority vote

thing and I need 50% or

whatever, right. And then so I

just I just tend to buy whatever

11% or whatever When I right

before a voter something like

that, then then it's more. Then

it's not about like I'm asking

the full 51% position. It's

about amassing, just this

incremental position. So do we

see this behavior in practice

where large players

will suddenly sort of top up

their positions just for the

sake of a vote? I'll just leave

that for the entire room. I

don't know if anybody wants to

pick up on that.

>> Michael Zargham: There are

some cases of where that has

happened. I wouldn't necessarily

say it's a widespread practice

so that would be better

appropriate for an empirical

study. I've had some personal

experiences where I've been

involved in votes where that

very clearly happened one that's

quite old. Now that comes to

mind was an old Aragon vote,

which really looked like it was

going in a particular direction

and the whales dropped in at the

very end and swung the vote many

years ago now. So hard to recall

the specifics. It's an emotional

memory, funny enough, but I

think the point here is probably

that if a vote is important

enough, if it has enough bearing

on the outcome for a particular

whale or class of whales, you

do see some of that behavior. I

think it emerged probably most

strongly in the vote escrow kind

of emissions routing process.

There was another example that

comes to mind where someone kind

of totally captured a stream in

the balance or protocol at one

point. I think there was a

basically deadpool and someone

managed to capture all that

liquidity and then route a ton

of rewards to it. And again,

this is very much governance

attack territory at least in my

opinion though because it

complied, with all the code and

the smart contracts. There was

shark divisions about whether it

was considered legitimate

behavior at all. I think this

kind of kind of, I'm gonna call

it gaming the metrics is always

going to be prevalent and you

see this around other

mechanisms like explicit vote

options as well. So I think one

Property of Tao's empirically.

Is that? There's a

financialization of governance

authority it manifests in a

variety of ways but just because

something's financialized

doesn't mean those methods. Are

always exercised because there's

cognitive costs attention costs.

You actually have to really care

for like minor day-to-day

votes. The likelihood of this

kind of financial activity in

order to swing outcomes by wills

is pretty minor. In fact, half

the time they don't vote at

all. If they are voting, then

they have to have a reason to

really care about the outcome

to put extra again, financial

and operational labor into

making trades and positioning

themselves to improve the

outcome. So I would say like

broadly speaking, the binding

constraint here is actually how

much people care about the

outcome. And so, the thing that

that was often do Is have many,

many votes. And so it's

interesting to look at in which

circumstances what kinds of

activities major changes almost

like constitutional level

parameter changes are probably,

the only thing that are going to

merit that kind of behavior

>> Tao Li: Yes, yes. File, you

know, I I personally want to

second the Michael's points

that oftentimes those you know,

governance attacks, don't

happen. But I think when they

happen the damage could be very

large for instance I guess you

know some of

the people in the room probably

are aware that in 2022 where you

use the flash

loans to buy a tokens that worse

about, you know, one billion

dollars to gain about two

thirds of the voting stake in

Beanstalk, and and then, you

know, this will propose a

malicious prop.

Go to drain about 180 million

dollar worth of CRYPTOS from the

from the asset pool of the

platform. And I don't think this

is an isolated case. There were

they were a couple other cases

even before this one. So

although those events are very

infrequent but when they happen

the damage could be very large.

>> Michael Zargham: So, I think

there's a really important

distinction that we should make

to about

the properties related, to kind

of resistance to attacks versus

properties associated with

governance, as steer like

governance mechanisms as literal

steering. So you have

constellation of good faith

stakeholders with different

interests, who are kind of

advancing positioning using the

mechanisms as they were

intended to advocate for support

their, you know, whipping vote.

So to speak their

communicating, with each other,

to try to get people to support

things or they're spending

money. In order to increase

their influence in order to

drive an outcome, which is

showing skin in the game. Etc,

etc. So like

broadly normatively just um,

separating the behaviors that

are you know again attacks in

the sense that someone wants to

explain the system pull money

out in a way that is not

pursuant to the purpose of the

Tao versus like participation

in the Dow and the exercise of

social and econom. Mechanisms

as they exist to advance the

interest of the particular

stakeholders at hand. And I

think the reason for separating

those is that from a mechanism

design standpoint. I would, I

would author very different

requirements and I

would test against both sets. So

the the tests for the

requirements associated with

steering mechanisms, they look

kind of like signal processing

our market design problems.

You're structuring like Okay,

well you don't know what

people's opinions are, you

shouldn't tell them what they

should be but if mechanisms are

Exercise to express preferences,

then the mechanism aggregates

those preferences into a

decision. According to a

process, that's transparent,

legitimate codified outcome is

deemed the decision of the

group. That's effectively tao as

bureaucracy. However, on the

smart contract is implementation

of the bureaucratic process.

The other side of this though is

that when you move to these

formal kind of code-based

systems, is that you create room

for gaming those mechanisms and

exploiting them against that

interest. And so you can use

different techniques to

discourage prevent or otherwise

kind of reject things that are

determined broadly to be

illegitimate and I'll stop for

the moment but

I have some other work actually

academic paper related to a case

study or we explore how like

one down, differentiated those

two mechanisms,

>> Fahad Saleh: So, if I can

just follow up the, the Michael

on what you were saying, because

so okay, let's see. We're

talking about the first piece

which is steering. I think you

were describing it as the

steering case. It seems to me

like one thing that academics

particularly in finance are very

familiar with going back to the

corporate finance literature.

And so on, is that in some

sense, the, the set of

participants who happen to be.

shareholders to affirm or token

holders to a Tao, is not the

whole universe of players. And

there are other, there are other

players, there's other welfare

to be concerned and considered

and so the classical example,

here is something like

the person in charge of the fur

has some private advantage from

implementing a policy that is

advantageous for that

particular person. But is

actually socially not the

optimal thing. And and so then

Is sort of like broader welfare

implications that are not so

good about that, right? So for

instance, like if you take the

the space of voters as fixed and

you say like Okay what's the

best outcome for all of them,

That's a slightly different

question than saying, Okay, what

is the best social outcome?

Which which really? And I think

this gets a bit more into some

of the work in the paper here,

right? They're thinking very

hard about things like Oh people

can actually

buy tokens in the setting and so

in some sense the set of players

is not like some exogenous fix

set. We have to kind of think

about the fact that there's this

there's this other margin. And

so I just wanted you to reflect

because when you were talking

about the steering mechanism, it

sounded very much. Like if we're

if we're thinking about micro

economics it sounded very much

like a game with a fixed set of

players who have preferences.

And so if you can just maybe

illuminate it a bit because I

think I misunder Yeah.

>> Michael Zargham: yes,

necessarily mean that a fixed

set of players, but to be clear

like, you at any given time,

when there is a vote, there is a

>> Fahad Saleh: Yeah.

>> Michael Zargham: collection

of votes and they represent the

interest. So again, you know,

I'm a control systems engineer,

my PhD is in distributed

optimization. I'm comfortable

with open systems and evolving

sets of a members and games that

are dynamic games games that are

in an open world setting, I'm

actually not

>> Fahad Saleh: Yeah.

>> Michael Zargham: a very big

fan of economic game theory to

me at forked off of the kind of

aerospace and defense variance

of game theory. and like, the

50s and 60s and went very

academic. Whereas the, you know,

the other stuff being arrow in

defense, when very dynamic into

your point, involves

open environments and

interacting with complex change.

Sorry, engine point being

though, I'm not assuming that

this is a fixed set or like a

canonical microeconomic game

structure. I'm actually saying

like there's information in the

world about preferences.

That those that information is

incident on this system through

these voting mechanisms and the

to the point of splitting the

problem apart, it's the same

mechanism. But you need both

like effectiveness properties

which are related to whether it

channels the information

incident on it into decisions

that are, you know,

considered effective and

legitimate versus the more

defensive side, which is

supposed and adversarial actor,

high tries to Jack those same

mechanisms to say drain a

treasury. It's not a different

mechanism. It's different

requirement. So if the author

formal requirements and write

property type proofs about those

things or at least demonstrate

through simulation scenario

tests both of the form, you

know, use as intended

essentially no adversarial

actor. Just can it process the

information incident on it into

decision? And does that make

sense? And when an actor who is

adversarial shows up and tries

to hijack, that how resistant is

it to that

hijacking and that can include

things like the the cost of

achieving a certain

amount of power. So if 51%

attack or essentially there's a

variety of different techniques

you can use, but ultimately

you're you're writing properties

that

say hey How hard, how expensive,

how much time? How much money

does it take to induce an

adversarial outcome? And that is

something that will vary by the

but also by the liquidity, by

the the markets by the

distribution of the Holdership

and so you don't necessarily

get like an a priori result, you

might get a functional result,

that tells you

quote, how hard it is. Given the

current, you know, token

distribution and the current

market prices and estimates of

the price impact of trades.

>> Jongsub Lee: Let me add a

little bit about going

discussion because just for

clarification in our paper, we

just try to highlight potential

conflict of interest between two

you know, types of token

holders, right? The big whale

and then small users.

but you know, we just want us to

start the discussion start

discussing about, you know, how

they're conflict of interest

affects in a tao's in

resilience, but in fact, we are

discussion is more toward, you

know, past the optimal form of

ownership distribution, right?

So maybe just one big whale

versus small, you know, users,

you know, in that case, maybe

it's a dictatorship or

autocracy. that's definitely

the bad in a situation. But also

at the same time in a complete

democracy like a small users

then they don't participate.

Maybe they're too small. So

they don't have any strong

leadership to lead the Tao so

that case may not be ideal

either. So I think that you

actually, you know, is some

optimal allocation of the power

balance, you know, kind of power

structure among, you know,

several whales. So then maybe

some, you know, pluralism time,

you know, situation, three or

four wells. They actually check

in balance between each other

so that, you know,

One will cannot control the

entire houses but this actually,

you know, a couple of numbers

of whales. They are they have a

strong participation incentives

in the voting mechanism and

then, you know, discussions. So

that may be, you know, in

reality it could be a better

form of Tao, power balance, or

power structure

but our paper for clarification

is not, it's not touching on

this, you know, more advanced

issue but we just want to

highlight you know, when a

single whale actually can

easily accumulate the voting

power and the steer that thou,

you know, in a way to

personally benefit, not the

benefiting for the other users

then what time of ages problem,

you know, they could arise and

how to mitigate such problem

through the, you know, kind of a

kinds and design type in a

contracting, You know,

solutions. So, definitely I

think the

>> Michael Zargham: The.

>> Jongsub Lee: we need to

actually make more deeper

Deeper discussion about what

could be the better power

balance within the Tao system,

you know, but that kind of in

the research is actually ongoing

and then we may actually have

to answer those questions that

don't

>> Michael Zargham: I think the

one thing I'm trying to do

though is highlight that you

actually can't carve out.

one problem when you're doing

mechanism design in a

particularly in a Dow setting

where those mechanisms are

effectively serving multiple

functions or have multiple

purposes and and potential

threats at the same time. So

like when we talk about the the

category of let's call it

requirement, which

is like resistant to exploit by

a single actor with a whale

position that is a requirement

and it's one I totally respect

and studying it deeply and

understanding like how bad it

can get and or what mechanisms

or approaches to mechanism

design mitigated. It's super

valuable, but it's actually

can't be decoupled from the

other questions that I've been

surfacing. So as the industry

voice, you know, and I talk a

little bit. I'm trying to

highlight how this relates to

practical design decisions and

so the way that I'm framing it,

at least is that when you look

at a particular mechanism,

that's gonna fill this slot It

needs to be resistant to several

different kinds of attacks. It

needs to be

useful for at least one and

often multiple kind of purposes

and again, I'm highlighting the

kind of big governance change

type purposes which are like,

Hey, can we make major parameter

changes that are viewed as the

kind of the fundamentals to the

Dow and then they're also used

often for more micro more

Operational decisions. Great

attention issues. So you have to

worry about

requirements around attention

and interest, relevance the

effectiveness of the changes

visa to be the the tao's, you

know, ability to perform its

purpose. Pay for things,

whatever it's doing various bite

down and you'll also have to

worry about the various

dimensions of exploit attack

conflict of interest etc. But

since those are all about the

same mechanism, you have to be

able to say, all right, Here's

a category of mechanisms. Here's

the circumstances, it's being

deployed into and from each of

these angles do. Assessment. So

it's a split from like a depth

for his assessment of a

particular, kind of attack, or a

can take particular kind of I'll

call it safety or resilience

property that we want versus the

breadth first, which is

for any given mechanism. It has

to satisfy that and and and and

other things if you go too deep

on one thing, you end up with a

mechanism that is like, maybe

really

good against that, but it's

effectively over-optimized and

it can't perform or Isn't

resilient relative to the other

requirements and we talked

briefly in the preamble about,

you know, quadratic voting. And

I like I point out often that

it's not a great use case, for

student anonymous environments.

It's hyper specialized to

reduce the effects of

to reduce the effects of having

high amounts of money. But it

sacrifices it's effectiveness in

a pseudonymous environment. And

in fact, in it, kind of

exacerbates, the effect of

social media influencers,

because social media

influencers, influence a large

number of individuals. And even

if they are discreet

individuals, it magnifies the

effects and you see that in some

of the get coin stuff. And so

the point I'm getting at

here is that like any particular

property assessment has to be

placed alongside

the other. Let's say three to

five core properties and

assessed in parallel. And so

the mechanism design problem is

making the best across all of

those rather than necessarily

being amazing at anyone and

like, trade-offs, always end up

showing up. And so again, it's

not a particular criticism. I

appreciated the paper I

just I was trying to kind of

provide the how do you use this

information in practice? And

the answer is you place it

alongside of your other

requirements. you do some

trade-off studies. And you you

do the best you can give in the

situation you're in.

>> Fahad Saleh: Let me just

maybe add some context before we

transition on, we might be

getting a bit too much in the

weeds of methodology here,

actually. So okay, one thing to

note though is that, when you're

thinking of an optimal

mechanism, you do need kind of

a well-posed objective. So I

think economists tend to think

about particular objectives,

like optimal welfare, for

instance, and by the to be

clear, something like optimal

welfare can capture multiple

properties. Like, for

instance, security is not

irrelevant to optimal welfare

considerations. and so Michael.

When you're talking about

different properties, I think a

lot of times one of the

difficulties like economists

have when they talk across to

engineers is that sometimes,

maybe not. I shouldn't put all

engineers one category, but for

instance, I know in computer

science, there's many times

particular properties that you

want your, let's say, stepping

outside the Tao context. Let's

say you want your consensus

protocol to satis, I want to

satisfy safety. I wanted to

satisfy liveness. I may want to

satisfy a bunch of other things,

right? But of coming up with an

optimal. ISM requires kind of a

single metric and and you could

have a metric that for

instance, weights, you very

simple. One would be like, I, I

have 10 properties and I just

count the number of properties

my mechanism, satisfies and, and

that's essentially how I value

the mechanism. Now, in that

case, I may have multiple

mechanisms of being optimal or

something like that. But, but

the point is that the idea

Having different properties that

you're that, you're interested

in to satisfy is not exclusive

to the idea of having a single

objective function because you

can objective function that

essentially collects these, they

might have to might have to

wait it or or do something like

that but and I think, yeah.

Yeah.

>> Michael Zargham: You it's a

pretty basic thing, right? It

comes to your point. It comes

up in engineering traditional

engineering all the time, right?

You have a bunch of properties.

You have things that are hard,

requirements that are

essentially booleans like, Did

you, or did you not not satisfy

this, These are constraint set,

then you have objectives. But if

you have a multi criteria

objective

>> Fahad Saleh: Yes.

>> Michael Zargham: problem,

then you have to have an

aggregator function, you can do

like min. we're all style. You

can do some you can do a true,

your choice of aggregator, then

given that you can still apply

weight. So I like things like

geometric programs, where

they're multiplicative.

like, that's because you can be

like, softmax and stuff with

that, and they're still like

quasi, convex, you can still

solve them up like with

computers, but the gist of it is

that you ultimately need to

construct something that

produces the Pareto surface

where although you have weights

or parameters, a way of

selecting, the relative

importance of your many

objectives, Once you actually

start doing that, you can reveal

Pareto surfaces, you get a

sense of what the optimal

surfaces and then your trade

study is making decisions about

like where on that parade of

surface, you want to be the

thing that drives me crazy is

when people pick things that

aren't on the Pareto surface,

and I feel like there's a lot of

that.

>> Fahad Saleh: Okay, well, I I

think we're conceptually

agreeing here. One of the

values, by the way of having a

practitioner in on the

conversation is precisely. It

can help the academics.

Understand what is more

practically important and what

should be considered that maybe

is not but but I think that's a

longer conversation that we can

have afterwards offline. Theo,

I think you wanted to bring in a

related topic here, right?

>> Theo Beutel: Yeah. Thanks

actually young so bad as the

earlier mentioned, the whales,

I think it's worth about

discussing allegation as well,

so many that was in

practice. Use delegation

mechanisms, which I suppose de

facto create at the sort of

sorts of whales who have voting

power, like other wells, but

actually do not have the

control, including the financial

group of trading these tokens.

So to what degree do you think

you're

results from the theoretical

model? Are transferable to tao's

practice, that use dedication

models

>> Tao Li: So in a few, yes. So

basically delegation does reduce

the ability to trade a gut, you

know, around the governance

votes, right? So basically

you know it is harder for the

for the delegates to buy votes

etc. But still I think some of

the economic logic does apply

you know, some of the economic

logic from our model

still applies. Because you know,

even without

transferable, voting power knows

those dedicates can create

persistent concentration. And

if, if the, the decades have

different expectations or

different preferences about

certain governance, outcomes

versus others as a users. They

actually could still, you

know, steer, you know, voting

outcomes in the way that's

beneficial to the 2D dedicates

versus as a, as a users. So, you

know, you would still have this

Find incentives between those

dedicated so-called dedicated,

whales and users. So, yeah, I

mean, you know,

so however I think I think there

were other dimensions that that

are not available in our current

model, is that for dedicates you

could you know, make things more

transparent because

a lot of those dedicated to care

about their reputation, right?

So basically you could you could

make the model involving the

negation more transparent than

what we have in our current

setting. Yeah.

>> Theo Beutel: Organization.

Which is yes. Anyone want to add

to that.

>> Jongsub Lee: You also.

like the allegations of actually

one way we fixed the

participation problem, right?

Because in our model, you know

there is no, you know, such

thing like a Directly modeling,

you know, some kind of lack of

attention or lack of

participation. Type issue, we

actually encounter in the real

world, the Tao's.

So the allegation on behalf of

the other is actually the

delegating party in a

connectively participating in

the voting process is so that,

you know, they can overcome

this, you know, the real world

problem.

So. But but at the same time in

a given, the participation, you

know, one value eight, you

know, delegating party, you

know, can have conflict conflict

of

interest from the others maybe

against some you know the vast

majority of the users then the

same problem. Like we, you know,

describe in this paper like a

big steak, you know, older

verses, you know, you know, many

many diffuse, you know, small

holders, you know, or some other

delegates in who try to

represent them actually, there

could be conflict of interest.

So how to actually intervene

and then try to actually restore

the resilience of these Tao

system? You know against such,

you know power you know that

power imbalanced gain, you know

so that actually mimics an hour

our model in that part actually

makes the real

world situation, I think. But in

reality there is actually more

complex layer or problems

including the participation

issues and so, the conflict of

interest issue, we Describe in

detail in our paper. So I think

that we need to actually you

know

learn step by step. You know

those you know vast majority of

variety of issues, you know as

Michael said there are so many

different issues in the Tao

space so the one that kind of

design cannot, you know, fix

them. All one size doesn't

feel all, you know. So you may

need to prioritize list all

kinds of problems agency issues

in that specific space and then

try all other than in terms of

the product, in US,

significance of each problem.

And then, trying to think about,

you know, What's the

multi-dimensional mechanism

design to fix those problems to

a certain extent? We are paper,

is just a starting point of the

One of the biggest in an agency

issue, maybe conflict of

interest issue, you among token

orders even in the absence of

central literacy, you know, who

might

behave on behalf of himself or

herself, there could be some

different types of agency

problems in this Tao space,

which is actually Dalia Canal

acknowledge by Michael in the

beginning. Right? There are

still agency problem in this

business so I think our paper

is kind of starting point to

describe such issue but there

are a lot more, you know, going

on, you know, how to make them.

you know, having strong

participation incentives and at

the same, how the coordinate

them in the desirable way. So I

think that those are the

important issues we need to

solve, you know, academically

and also practically, I guess.

>> Michael Zargham: So I think

practically the way I would

imagine using your work is to

use it to develop both

requirements descriptions of

those conflict problems so that

they could become either

constrained or objectives for

our design discussion earlier,

right? So, you can assess

whether a particular design is

likely to produce or the

circumstances under, which it's

likely to produce that class of

problem and you could also use

it more for pools and empirical

tools for trying to measure our

identify signatures for our

predicates, for those problems.

And that moves it away from

being a mechanism design, focus,

because I think the mechanism

design

>> Tao Li: Yeah.

>> Michael Zargham: problem

itself ends up being well,

Frankly, I tell most people not

to try to design you voting

mechanisms, it's kind of like

crypto, don't roll your own, the

cryptography, don't really your

own. Use a tide tried and tested

mechanism for which, you know,

the properties and for which the

properties are appropriate for

the situation, that doesn't mean

no one should be researching and

developing new mechanisms,

Please continue to do that.

That like, in practice using a

new.

a new governance mechanism is

fairly a good idea. And that

the, the key is that the

research that is into governance

mechanisms is often most

fruitful in helping us describe

the desirable properties of a

design, and to assess the

current state of the living

system, and that as those

things, mature, it does end up

leading to situations where

those new mechanisms do get

tried out. We how they work in

practice and then we get a sense

of when and where, and how to

use them. And, you know, I

realize that maybe a little bit.

unexciting, But like, there are

reasonably good libraries of

mechanisms, I think Ori Shimoni

put together a great like,

library of mechanisms. I'm sure

Tao can

share a link and that when it

comes to the academic research

around algorithms and

mechanisms the first class

learnings that make their way

into industry for, you know,

seasoned professionals are how

to write down the requirements.

So you did tell certain kinds

of attacks. You detail certain

kinds of failures you write

proofs and do analysis of those

cases and then I write down in

my mechanism design work. All

right, here's another thing. I

want to check for, in the list

of things, I want to check for.

And if I'm doing an empirical

study of an actual Tao in life,

that I'm looking for whether or

not, it appears to be an

issue again deriving, metrics

from that research, as well as

in a more advanced case looking

for predicates. And I think

predicates are important because

you're looking for the prior

states that represent the risk.

For the potential for that

failure mode. Because most of

the time, once there's a

failure, it's too late and so

understanding how to detect

predicates and intervene in

advance is a major element of

kind of organizational or

institutional resilience and

something that I think still

need to develop.

>> Jongsub Lee: I was actually.

>> Theo Beutel: so, Sorry.

>> Jongsub Lee: regarding that.

I want to add this one thing

because maybe Jungsuk, you know,

can add more, you are surprised.

When you actually found in

our paper such that the targeted

illiquity like a simple locking

period for the important whales

in the Tao system. They turned

out to be quite powerful, you

know, governance device. So

maybe we don't have to think

about the complex solutions.

Maybe we can just simply say,

Hey, you have a large stakes,

Then you should show the

Interest in this Tao system over

the long run than just signal,

you're in a good intention

through the long locking period.

And when I talk about this

locking periods, as a solution,

even in reality in the venture

capital space, you know, that's

an outside our, but, you know,

When there is a significant

information, asymmetry problem

and potential, you know more

hazard and adversial action, the

test simple role and that simple

solution. Actually restored a

trust, you know, between you

know, many, many different

parties with the potential

conflict of interest and

importantly in our paper, we

show that such idea like a

lacking period as a targeted in

liquidity. For certain groups of

whales, that could be a

powerful, you know,

device to solve this conflict of

interest problem. So maybe

expanding such idea. Simple

yet, you know powerfully

economics, you know and apply

them to the real world Tao, you

know maybe could be away you

know until that academic

findings and practical

solutions can meet together at

certain point. So maybe jungsuki

you could add because you know,

we thought about this issue for

a long time, right?

>> Jungsuk Han: Yeah, I was

about to actually make a comment

about that and thanks for

inviting me to if additional

comments so

what we're doing is not so much

about how it should be, it's

more about how it is. So we are

not really designing any

mechanism

there, but we are doing is we're

just trying to explain how it is

now and then it may actually

work as it is. So

At the moment. If you know, the

many tao's or adopting token

based system and then it was

tokens are traded on the market.

So we're not saying it, they

have to design this and their

way, but then if those tokens

are trading on the market it

just happens that those

illiquity is on

their side, especially when the

governance is contested where

whales are.

trying to capture the, the

outcome of the the protocol. So,

so in that case, indeed we

empirically find that that when,

when the governor's contested,

the, the Tokeny

liquidity, he's actually a

boosting the, the growth of the

platform. So we

actually verify that

theoretically and empirically

and as jongsub just mentioned.

A lock-in period of tokens.

this is actually doing this kind

of same mechanism as the

token illegally in a way because

those whales who are locked in,

it is as if having sort of a

greater eliquity only design for

them. so,

what was happening there is they

there are they are so they're

there, incentive is more aligned

with users because of their

local commitment. In that case

in. And then this is what we

find in the model and then

indeed in our empirical result,

we all so find the result that

imposing more long-term

commitment in the form of

locking and other.

Are the forms actually boost the

platform growth. So so yeah.

In a way kind of this is what we

find both the theoretically and

empirically and we're

explaining how it is rather than

where, you know, where it should

be like that.

>> Michael Zargham: Have.

>> Jungsuk Han: So, so maybe

there should be that better.

>> Theo Beutel: Actually.

>> Jungsuk Han: than, at least

that's what we find. Yeah.

>> Michael Zargham: Yeah. So

>> Theo Beutel: In here.

>> Michael Zargham: Cows that

you need to empirically. So,

like just essentially auto

ethnographically like balancing

out because there's in my

perspective you've got like,

theoretical kind of mathematical

level analysis. You have

empirical at the level of data

collection and then I always try

angulate with kind of

ethnographic methods. I work

with researchers and RMIT in

Australia, Ellie Rennie, Kelsey

Navin, and Ellie's other

students. And I found that

without that triangulation,

it's very hard to like really

make sense of one of these socio

technical environments. And so,

the question is really like, Did

anyone participate in any of the

Dows that you studied and how

does your like experience and

participation line up as the

third leg of that stool? With

the mathematical and empirical

results that you found

>> Theo Beutel: Well actually

Saga, maybe let me give us a

question back to you because

this is a really good one and

it lines well with something

else managing up. So the data

collection for the study ended

in 2022, right? So and the Tao

space is evolving fast. So

maybe Zargham could you

briefly describe some major

changes you observing over the

course of that period? Because,

of course, yeah, no space has

changed and go to education has

>> Michael Zargham: Man.

>> Theo Beutel: and use the

>> Michael Zargham: Yeah, I mean

the thing that

I've noticed in most recently

that is like changing things is

that everyone wants to involve

Llms and

Get. Actually, There was a

little bit of discussion of that

in the paper. I linked, which

we can probably share in the

notes around attention economies

This is related to this problem

of who makes decisions, but I

yeah, I mean, there's probably

nothing more impactful in my

lived experience, since we're

kind of bridging off of that,

then the sudden like desire for

people to kind of assess and

participate, either individually

through the use of just like

talking to chat, GPT or Claude

or Gemini, or whatever people's

preferred models are to the

development and deployment of

systems that are kind of rag

based and our have access to

let's say forums and or you know

pulling on chain state that's a

little bit more advanced, I

don't see as much of that. But

like that the LLM craze has

like really captured the

imagination, no doubt

participants. And I see it,

particularly in the face of the

binding attention. Constraint,

the cognitive constraint, and

then there's also the fact that

people are increasingly building

tool, that actually can

directly interact with smart

contracts and for folks who are

interested in principal agent

problems, I actually went on a

different podcast and AI one.

You, I don't know some months

ago and talked a bit about

Principal agent problems in AI

systems where you really have to

think about whether the AI

agent is, in fact, your agent or

someone else's in terms of like,

who's interested advancing. And

although that wasn't a crypto

focused conversation it was

informed by my experiences,

endows and with crypto.

community members, you know,

both using tools that have been

provided for them in service of

their

financial or governance

interests. As well as the

observation that the

exploitative actors are

increasingly automated actors

who are programmed to just hunt

for opportunities to arbitrage.

And I think that's actually an

interesting factor to your

paper about like these kinds of

a lot misalignments and exploits

because Present, there's

nothing really to stop or to

constrain a AI based agent from

kind of entering a Dow

governance environment and

exercising automated market

makers, and then voting power to

say it steal funds. And you

know, that's a little bit hazy.

But I would say there was a

recent study I saw apologies, I

don't have it prepared to quote

about the the increase in the

this kind of exploit on an

automated basis. I'll see if I

can find it and share it. if

you want to add it to the notes,

>> Jongsub Lee: Actually

interest.

>> Theo Beutel: Preventable.

>> Jongsub Lee: in you. One of

my students who just joined the

you know Colombia Ior

Department. Actually, he wrote

paper with the Agostino kaponi.

About you know, what? If the

agency AI participates in the

Tao voting process in

How does the AI in Agency, AI

you know, how does it do

compared to the human? You

know, based building and I think

for sure they will be the

growing

participation by Asian taois in

this voting process. So there

could be another in a conflict

of interest.

Between human controller versus

agent AI, or even a cross-agent

AIS. So I I fully agree with,

you know, Michael's war is

actually this in a Tao spaces,

getting more complicated, you

know, by emerging it with, you

know, AI, you know, the best

world. So now how to restore the

resilience of this system, you

know what might be the, you

know, everlasting happiness

mechanisms. I think that, that

will become more and more

important I guess in this

complex work, Yeah.

>> Theo Beutel: The forecast

we're coming at time. I think

this is a really great way of

signaling to both builders and

researchers that there's a lot

more to build to experiment on

around our governance and and

surprisingly little best

practices

perhaps, but also to researchers

to take a much closer look also

interdisciplinary research

including of ethnographic

studies, as Arkham said to make

sense of this. Very exciting

field of government that is

still a merchant.

So I would like to thank all the

authors that you can tell Lee

and Michael

Zargham for joining, thank you

Fahad for for hosting the

session. And please share the

link on YouTube with everybody

who may be interested and thank

you everybody for joining

today.

>> Tao Li: Thank you. Thank

you. Bye.

>> Michael Zargham: Thanks. And

thanks for your work, guys.

>> Jongsub Lee: You guys.

>> Shyam Sridhar: Okay, the

public stream has stopped. So