My name is

assistant professor the school of

complex adaptive systems here Arizona

State University uh enrolled member the

d tribe and I'm going to be talking

about my work and going through a bunch

of projects that are ongoing uh

incomplete and at various stages of

development. All right. So, I'm going to

start off by introducing myself. Then,

I'm going to talk about some of my

different projects. And if there's time

at the end, I'll get into some of my

peculiar interests and some provocations

to encourage discussion. This is me 10

years ago. I got my PhD here at Arizona

State University at the Center for

Biology and Society. And I wanted to

know what's the meaning of meaning? But

that's too broad a question uh to do a

dissertation on. So, I narrowed it down

here. into what's the meaning of meaning

in the context of behavioral experiments

aimed at discovering physiological

mechanisms

and I feel like I found some clarity in

trying to answer that question but I

still want to know more so that's

ongoing this is a little brief map of my

journey after ASU I was a visiting

graduate fellow at the Minnesota center

for philosophy of science then I was a

posttock at the University of Kentucky

and then I was a posttock at the Santa

Fe Institute before coming back here uh

and starting in August last August 2024.

And now my office is right here in this

building where the people who are in

person are sitting. It's all nearby here

in the ECA.

And uh my research at this point

basically has two main areas. One is the

history and philosophy of science.

That's what I've been doing the longest.

And then the other one is research

relevant to indigenous data sovereignty.

And I'll get into sort of what that is

later on in the talk. And the way I see

it, the sort of connecting

tissue between these two areas of my

research right now, it's methodological

and it's me using the same methodology

to clarify the meanings of complex

concepts.

So, I'm going to start out with the

history some some history and philosophy

of science stuff I have going on before

moving on to the indigenous data

sovereignty stuff.

Uh so last semester uh I collaborated

with Pedro Marquez Zacharas and Max

Stressowl

on sort of coming up with something to

submit to this event that was happening

at the Minnesota Center for Philosophy

of Science called Philosophy of Science

Past, Present, Future. And you can see

that the call was asking for people to

reflect on the current state of

philosophy of science and its history

while setting an agenda for future

research. So I got thinking about sort

of philosophy of science history and

philosophy of science and

what's been happening where is it going

and where do I see myself in that story.

So just a little brief background here

for people. History of science and

philosophy of science can be separate

things. There's departments that are

just history of science. There's centers

like the Minnesota Center for Philosophy

of Science. They're just doing

philosophy of science uh at least

nominally.

And what's the basic difference between

these two sort of areas of inquiry?

Historians of science tend to make

narrative arguments about why science

happened the way it did. And they're

much more likely than philosophers to

bring in contextual factors like a

scientist's biography, their life

history, how that influenced the kind of

science they did, the technology that

was available to them, politics,

economics, culture, place, tradition,

all as sort of influential factors

shaping science.

Philosophers of science traditionally

are into reconstructing the logic of

scientific practices, scientific

theories and scientific explanations and

then assessing those theories, practices

and explanations according to sort of

logical norms.

Sometimes they bring philosophy problems

to science. So for instance a classic

philosophy question is what is the

truth? What's reality? And they'll sort

of take these questions that have a long

tradition within the western

philosophical cannon, bring them to

science and sort of come up with

arguments about like well what does it

mean to say that science is getting at

reality or that it uh generates true

statements

and then sometimes they bring science to

philosophy problems. So for instance,

you know, philosophers have been uh

trying to figure out what consciousness

is for a long time and some philosophers

of science will say, you know, recent

work in neuroscience, for instance, is

probably relevant to this long-standing

philosophical question. And so they'll

try to bring empirical evidence from

science to bear on the philosophical

questions. And I'm someone who believe,

you know, I do both of them. I like

doing both of them. And I believe to do

a good job at one, you're going to have

to engage in the other to some degree.

So I'm like an integrated history and

philosophy of science guy.

Uh and so in thinking about the history

of history and philosophy of science, uh

I was looking at sort of different

trends that have happened historically

over the last 200 years or so. And I

came up with this spectrum across which

you can categorize some things

happening. And one end of the spectrum

is the stance that scientists and

philosophers are basically

indistinguishable

like doing the same kinds of stuff. And

then on the other end of the spectrum is

this view that philosophy is separate of

or outside of biology.

Don't let them touch each other. They're

totally different things. And so there's

some different um styles or movements

and where they fit on the spectrum in my

opinion. And by biological philosophy,

I'm talking about a continental European

tradition, maybe people like Shelling,

where they are looking at sort of

developments in the life sciences.

They're thinking about the theory of

evolution and natural selection, and

they're like, what does this mean for

man's place in the universe? Like that

kind of philosophizing. And then there's

historical epistemology. This is like a

mainly French tradition. You're looking

at scientific concepts.

uh and they still see, you know, look,

we're different than the scientists

we're looking at, but it's not quite as

separated as at the other end.

Philosophy of biology, I would say, you

know, that's what's happening in most

places today comes from an Angloanalytic

tradition. They're closer to seeing

themselves as

interacting with scientists and working

on problems that matter to scientists.

And then at the far end the early 20th

century organicist and theoretical

biologists uh who you know saw

themselves as scientists but were also

saying a lot of very abstract

theoretical very philosophical things

and um that's where I see myself on the

spectrum currently the kind of history

and philosophy of science I'm doing. Uh

and then I started thinking it'd be nice

to get some kind of empirical evidence

to bear on this question of what is

going on in the history and philosophy

of science as a discipline. And so I

thought how would I do that? And here

was the entryway. I picked a

professional academic society called

ampersand HPS stands for integrated

history and philosophy of science. So

it's a bunch of people who like me think

you got to be doing both at the same

time to do either well. Um and they're a

pretty new organization. They had their

first meeting in 2007 and they meet once

every other year. So they're coming up

on their 10th meeting here uh sometime

this spring.

And what I did is I collected and read

every abstract for every presentation

that's happened uh in the first seven

meetings. I wanted to do them all, but I

severely underestimated how long this

would take. Also had trouble getting all

of the abstracts. They're not all just

out there on the internet. So I'm, you

know, hounding people to send me things.

uh but I can present some of the results

from analyzing the first seven meetings

of integrated HPS. And so one of the

things I did is I came up with a coding

system where after reading a bunch of

them I thought about what are the main

things people are doing these

presentations or at least claim to be

doing since I didn't watch the

presentations themselves just the

abstract describing.

Um and this is a list of things I came

up with. So one presentation can do

multiple things simultaneously.

So like programmatic meta history and

philosophy of science. These are

presentations where they're like making

arguments about how you should do the

history philosophy of science

or a sort of H for P case standing for

history for philosophy case. This is uh

using a historical case study from some

time in the history of science and using

it to justify more general philosophical

claims usually about how science works.

So they're like, you know, this is how

this kind of scientist does things.

Look, here's a case that shows it.

And these three are the most popular

things that historians and philosophers

of science are doing.

uh pra concept that's there it's mostly

like a historical narrative argument but

the narrative focuses on abstract

philosophical concepts so it's sort of

like telling the history of a concept

and then P4 big was popular uh this is

sort of like history of science is

important whatever topic they're working

on is just important for its own sake

and what this really represents in the

literature is uh like the fascination

with big figures in science. So like

Isaac Newton for instance, no one feels

the need to justify getting into the

extreme minutia of anything Isaac Newton

ever did because it's just assumed that

it's going to be important because it's

new. And so there's a lot of history and

philosophy of science that falls into

that kind of category.

>> Hey, Kelly.

>> Yeah. What's philosophical cleanup?

philosophical cleanup

uh is that there's some episode in the

history of science which is sort of

widely regarded as confusing or uh

messy. People like don't know what's at

stake or what's even going on. And then

the philosopher comes in is like I'm

going to clean up this situation. I'm

going to draw a bunch of distinctions

and say this is this was this this was

that. And uh you know they may not solve

the problem but they'll at least be like

here's at least a framework for thinking

clearly about what happened in this

episode because everyone's using you

know often the same word maybe in

different ways across a whole bunch of

different disciplines that study science

like a sociologist of science historian

of science trying to philosophers trying

to step back like here's the once and

for all way of thinking about what was

happening

And I haven't had a chance to turn these

into graphs yet, but this it's just the

numbers on it for different meetings. Uh

like I said, one presentation can do

multiple things.

And you know, when I talk think about

myself and what I'm up to, this is

basically what I do as a historian,

philosopher of science, the

philosophical cleanup. Uh Paul was just

asking about new historical evidence. I

like to go into the archives, find

something that people have never talked

about before and then use it as evidence

in some kind of argument. I like telling

the history of concepts and uh you know

I'm very sort of anxious that the things

I do matter to scientists. I think that

that's important.

And so an example is this paper that I

wrote. Uh it does all the things

highlighted there. That's the style of

HPS it is and I'm very happy that uh

it's my most cited paper and almost all

the citations are from insect navigation

experimentalists. So it did make contact

with scientists predominantly.

So when are HPSers thinking about

what sort of span of dates within the

history of science? These are graphs

that are specific to each meeting.

I also compiled them into one where you

can see general trends. You can see that

uh you know the 20th century by far the

most popular time to be thinking about

science

and that's basically true for me too. I

fall into this trend. But I'm trying to

expand on both ends. I'm trying to get

closer to the present and I'm also

trying to push back into the late 1800s

right now. My research

What sciences are HPSers thinking about?

So again, one presentation could be

about multiple disciplines. Uh and the

first thing to note here is that the

x-axis is logarithmic. So you know it

looks like physics is ahead, but it's

actually really really far ahead.

There's like the complete domination of

physics in integrated HPS. Um biology is

next with half as many. And then after

you know physics, biology, chemistry,

Newton, just the person is the next most

popular thing. So that's what I mean

about like why the what was it? P4 big

category is so popular

and you know complexity not on there

doesn't appear but I'm going to change

that. I'm doing history and philosophy

of complex system science. And so one of

the projects I have going on in this

area is asking the question what

happened to cybernetics.

So it's one of the sort of forerunner

disciplines I would say of complex

system science and there is consensus

around that. People agree it's also a

sort of forerunner to today what we're

calling dynamical systems theory or

control theory.

uh and it sort of really made its first

splash in the public with this book

manifesto published I believe in 1948 by

the American mathematician Norbert

Weiner cybernetics or control and

communication in the animal and machine

and you can see by the subtitle that I

had sort of vaunting ambitions from the

start so says a study of vital

importance to psychologists

physiologists mathematicians

psychiatrists etc so cybernetics made a

lot of promises for a lot of different

areas of science but within theh

behavioral sciences, which are what I

like to think about. One of the big

promises they made was that they were

going to use newly formalized notions of

information, feedback, and control to

create a general, maybe universal theory

of behavior that would apply just as

well to humans, animals, and machines,

any kind of behavioral system.

And so, this is a sort of run through I

like to go through just to emphasize the

contested nature of cybernetics within

the history of science. So this is a

encyclopedia entry from the USSR 1956.

It says, "Cybernetics is a reactionary

pseudocience arising in the USA after

the second world war and receiving wide

dissemination in other capitalistic

countries."

Here this is a quote from one of

Kennedy's top aids that he wrote to the

president. It says, "Based on CIA

reports,

in October 1962, President Kennedy's top

aid wrote in an internal memo that

quote, "The all-out Soviet commitment to

cybernetics would give the Soviets a

tremendous advantage." He warned that by

1970, the USSR may have a radically new

production technology managed by closed

loop feedback control employing

self-eing computers. If the American

negligence of cybernevs continues, he

concluded, we're finished. So this is

probably familiar to a lot of us right

now. China and AI for instance repeating

itself history repeating itself here.

Also we have uh Salvador Aend's

government in Chile socialist

government. Uh he creates something

called cyersin. It's this room and it's

supposed to be a sort of central

planning and control zone for the

economy. And so it's supposed to be

hooked up to factories to keep track of

production, uh, stores to keep track of

demand, and to keep all of his people.

And it was largely created by this this

crazy English guy named Stafford Beer.

He was a cybernetician.

He consulted for Aendai's government.

And he got into a fight with some sort

of US government officials in print. And

one of the things he says to them is

perhaps it's intolerable to sit in

Washington DC and to realize that

someone else got there first in a

Marxist country on a shoestring. As to

the horror of putting computers to work

in the service of the people, I would

sooner do it than calculate overkill,

spy on a citizen's creditworthiness, or

teach children some brand of rectitude.

Cyber sin was destroyed uh in the next

reg regime change in Chile. Here we have

a continental philosopher

Ponti from the phenomen phenomenological

tradition. He says in the ideology of

cybernetics, human creations are derived

from a natural information process. It's

self-conceived on the model of human

machines. If this kind of thinking were

to extend its reign to man in history,

if we were to set out to construct man

in history on the basis of a few

abstract indices, then since man really

becomes the manipulandum he takes

himself to be, we enter into a cultural

regimen where there is neither truth nor

falsity concerning man in history into a

sleep or a nightmare from which there is

no awakening.

Then here we have a television show from

the 80s called The Greatest Thinkers.

They did one episode on cybernetics and

Norbert Weiner.

It's like I don't have Oh, it's just

I also don't have audio. That's all

right. They don't say that much

specifically

except that's it's going to be a really

big deal for the future. They use the

phrase complex systems in the episode.

Where did my cursor go?

I'll skip the next one clip from here

too. But the host just concludes the

episode by saying uh cybernetics and

complex system science is the next step

in human evolution.

Here's a historian and philosopher of

science more recently from 2010 also

looking at cybernetics. He says that it

was rep it uh it stood out in the

history of science because it it pursued

a non-modern ontology that rejected the

people things dualism and the detour

through representational knowledge.

Uh the English documentarian Adam Curtis

has a documentary series called All

Watched Over by Machines of Loving Grace

where he looks at cybernetics. Says that

this is the story of the rise of the

dream of the self-organizing system and

the strange machine fantasy of nature

that underpins it. And then there are

even more recent papers talking about

cybernetics leading to sort of

neoliberal capitalism.

And so to sum up here, depending on who

you ask and when you ask them,

cybernetics was something that was going

to produce a universal theory of

behavior. It was capitalist

pseudocience. It was an engine of

socialist economic planning, a

dehumanizing nightmare, the next step in

human evolution, missed opportunity for

a new way of doing science, strange

machine fantasy that worked our view of

nature, harbinger of the rise of

neolithical technocrats. And so I bring

up this list here because I think you

know that these many perspectives

could also be sort of leveled against

complex system science today and that

depending on who you ask people might

have these opinions of complex system

science and and that's no coincidence,

you know, because it's coming out of the

cybernetics movement.

But if you ask most academics today and

they've heard of cybernetics, they're

likely to say that it's a failed

movement and that it's dead.

Nevertheless, many complexity scientists

continue to see the concept of

information as sort of harboring

revolutionary potential in the

behavioral sciences

that it can help us solve big problems

revolving around behavior and

decision-m.

So I'm on the case trying to find my own

answer to uh you know what was

cybernetics? What did it mean?

Why does it matter to us today as

complex systems people?

And the basic framework that I use when

I do this that I'm also going to be

bringing to my other work in indigenous

data sovereignty is that scientists do

science, scientists make claims, people

use the claims to guide their future

action and the connective tissue between

these steps is interpretation

justification. Right? Whatever the

scientist does is supposed to justify

their claims and for those claims to be

able to guide action, they need to be

interpreted. And I focus on these

connecting tissues to make sense of

everything else going on in science. And

another way to show this is a here's a a

framework is like capturing the way I

think about science. It's a research

program developing over time. There's an

initial state of doubt. Scientists

design an investigation uh to produce

evidence that will ameliate that state

of doubt. Sometimes they're successful

and they the results of their

investigations they say justify a new

belief. The new belief is targeted at

the initial state of doubt and then once

they have this new belief it guides

their future research in new ways and

you know causes them to have new doubts

and the process continues on.

And so this belief fixation, new belief

formation stage is usually the only

stage that's publicly accessible uh to

people because scientists make claims in

research articles or they go to

conferences and they give presentations.

And so that's the sort of handhold I

usually use to grab hold of a problem in

the history and philosophy of science.

But then I try to get at everything

surrounding that claim to make sense of

the concepts that were in the claim.

All right? And so, as I said, it's

iterative. The process keeps going.

There's multiple research programs

happening at any given time. So, they're

running in parallel. And the claims of

one research program can influence the

future research actions of another uh

research program community. And the

reason it can do that is because

these scientists are existing in a sort

of interpretive cloud with each other.

They've received similar training. They

have similar implicit assumptions. And

so they're able to read the research

reports of their peers and uh it gives

them new ideas for research in a way

that it wouldn't for other people. So

for instance, like if my uncle read a

research paper, he's going to have very

different ideas about how he got his

future action than someone who's working

in that same scientific discipline.

uh and I like telling big picture

narratives about these interpretive

clouds, these traditions by focusing on

the minutiae of experiments.

These are some of the favorite concepts

I've been thinking about within the

context of the history and philosophy of

complex approaches to behavior,

behavior, motivation, instinct,

information, cognition. They may seem

sort of straightforward or like you may

say, "Well, I know what those concepts

mean." But I think you don't really know

what those concepts mean. Uh, and so

just for motivation and instinct, here's

a recent publication I've come out at

the end of last year that deals with

both of these concepts in the behavioral

sciences.

And just a point about why any of this

matters. So scientists, you know,

they're not born scientists. They become

scientists. And before they were

scientists, they were part of a whole

bunch of other communities and cultures.

All right? And so there's this

reciprocal relationship between broader

society and popular culture and

scientific research communities. The

ideas from one area inevitably filter

through to the other and then back

again. So the example I usually use for

this is that at one point the idea of

dopamine as an important

neurotransmitter for feeling good or

having pleasure that was just some

technical sort of niche thing happening

in a laboratory somewhere. And today the

language of dopamine hits the pervasive

in the culture. And so that's how you

know scientific work on behavior colors

how we think about ourselves, how we

think about others.

And so scientific concepts that promise

to control and predict behavior concern

everyone I argue because they're bound

to reenter society and color the way we

deal with ourselves and others.

All right. So that a little piece of the

history and philosophy side of the

research that going on right now. going

to switch over to indigenous data

sovereignty ethics and policy. How did I

even get into this area of research?

Happened in 2001 when I became a

consulting bioethicist for the native

biodata consortium. It's the first uh

nonprofit bio bank and research

institution led by

indigenous scientists and sort of

intellectuals. And it's located on the

sovereign land of the Cheyenne River

Sue. That's also a first for an

indigenous bio bank just to be located

on sovereign indigenous land anywhere in

the United States. It's never happened

before.

And so they put me on all kinds of

projects since then. And one of the

projects I was working with Morona

Vanali and Fernando Fischer and they

said, "Well, what would it look like if

you could try to wipe away

sort of like western assumptions and

philosophies and come up with a white

paper on how to do indigenous genomics

research that was based on indigenous

philosophies and cosmologies from the

beginning.

And that that was a hard

problem to think about.

Sort of put me on this direction I'm at

now where so I'm already a guy who

clarifies complex concepts. That's what

I've been trained how to do. That's what

I like doing for my historian in Wasburg

science side. And so I'm bringing that

over into the context of indigenous data

sovereignty. I'm thinking about concepts

like data. For instance, how does

something become data?

has a lot of philosophical implications

to that question. What determines the

meaning of a datim?

Sovereignty another complex concept

rights human rights uh are sort of

invoked everywhere in the indigenous

state of sovereignty literature. So I

started thinking looking into the

history of this idea thinking how useful

is it for the goals indigenous data

sovereignty

and uh so if I have time I'm just going

to get into I have projects going on all

three of these concepts right now but

I'm just going to try to get into the

data and the sovereignty ones. So data

uh the stage of this project is that

there's a paper that's under review. And

so what I sort of note in this paper is

that proponents of indigenous data

sovereignty

they say that the concept of data is

contested. It's valuel laden. It's

philosophically complex without ever

really engaging with what an IDS sort of

view of data should look like.

So they'll say things like the concept

of data is imbued with a host of

meanings within and across contexts. To

some it is simply information while for

others is the very pulse of a revolution

or the idea of data is a broad concept

but in the context of this chapter we

define data as information that may be

recorded in various forms.

Right? And so from the sort of

philosophical perspective of trying to

answer questions like this which I

believe are sort of central to any

philosophical account of data uh

defining data in terms of information

doesn't really get you anywhere. Uh

because information has the same

philosophical ambiguities as data. It's

also you know what's the difference

between information and not information?

What makes information about anything?

These continue to be philosophically

mysterious questions.

uh and so what I want to go through is

two different views uh that sort of

offer answers to those two central

questions about what data is and what

determines its meaning.

And so here's the first one. It's one

that I don't like and I argue against in

the paper called the correspondence

view. It says data are reflections or

snapshots that straightforwardly

represent some aspect of the world. So I

have a camera and a mirror here because

that's the analogy that data are like

little mirrors or little photographs out

there and they just like represent some

aspect of

right and so it's pretty clear that it's

this correspondence relationship

whatever it is that determines the

meaning of data. And sometimes to

articulate what this correspondence

relationship is, people draw on

mathematical ideas like homorphism or

isomorphism where they just say things

like, you know, it preserves the

structure of the world somehow and

that's why the data is about this aspect

of the world and not that other aspect.

And so when you think about data in this

way, it leads you to ask questions like,

is our camera, our mirror, our recording

device, is it good enough to accurately

represent the way the world really is?

Are we clever enough to interpret these

reflections and representations? Right?

So on the correspondence view, the sort

of two main areas for failure are that

scientists are using faulty measuring

devices or that they're stupid. But if

if they're smart and they have good

measuring devices, then we're off to the

races and we're going to be learning

things about the world.

The other view of data um coming out of

the pragmatic tradition, let's call it

the pragmatic way. That is something I

endorse and I think that it's a good

view of data for realizing the ends of

indigenous data sovereignty. It says

things only become data when someone

uses them as evidence to support claims

or actions. So I'm drawing on the work

here of another philosopher of science,

Sabina Leonelli.

And what this view of data does is it

reintroduces human agency into the

picture.

Causes you to ask questions like what do

we want to accomplish by quote unquote

representing the world via data? What

sorts of claims are we trying to

justify?

What relations are created by using

something's data? Right? So on the

correspondence view

sort of like scientists are innocent

passengers being carried along the line

of inquiry by the facts.

The pragmatic one we foreground

scientists agency intentions and values

in the scientific process.

And so I got three reasons why I think

that this pragmatic view of data is the

best for indigenous data sovereignty.

First reason it gives a better

perspective on the future trajectory of

science which is important indigenous

data sovereignty because I should step

back I guess I never said what that is

or defined it loosely even uh it's a

pretty recent I would call it

intellectual political movement and the

basic idea behind it is that indigenous

peoples in their history of interactions

with colonial forces uh there's a

similar story that plays out that

indigenous peoples had something that's

valuable, it gets extracted by outside

colonial forces and the indigenous

people don't get anything in return and

sometimes are hurt in return. Right? So

a lot of people are saying that you know

the next thing where this is going to

happen is data that data is like the new

oil. It's the new gold and there's going

to be a data rush on indigenous peoples

and they aren't going to get anything in

return to improve their material

conditions. in the indigenous data

sovereignty movement sort of saying we

need to to leverage this notion of

sovereignty, the idea that indigenous

peoples at least in the United States uh

have some version of sovereignty

to make sure that we benefit from the

value of our data.

All right. And so what how does the

pragmatic view of data lead to a

different view of the trajectory of

science? This is just a sort of you know

rinky dink network graph thing. It

doesn't actually represent anything

right now. But the basic idea behind

this is that the nodes are discoveries

and they're connected by edges to other

discoveries because in the process of

science discoveries make new discoveries

possible.

And on the correspondence view you have

this view of science progressing where

all the data is already out there with

human independent meanings. It's sort of

like a scavenger hunt view of science

and scientists are in the process of

discovering those meanings. So the nodes

are sort of waiting out there for

scientists to connect the dots.

uh the pragmatic view of data, there's a

lot more contingency because you have to

take into account the sort of things

scientists value because the things

scientists value determine what they're

willing to call a problem, what means

they're going to use to try and solve

the problem and then what they're

willing to accept us in a solution to

that problem.

So there's just way more nodes all of a

sudden because you know there's way more

variables basically in what's happening

in a given scientific investigation.

And when you think about know scientific

progress in this way it leads you to ask

questions like well how many problems

could people possibly solve using the

same data?

And this is just speculative but I think

humanity's capacity for generating

problems and accepting solutions is

infinite. So the problems that could be

addressed are infinite and so the

meanings of data are infinite.

Uh but the main point here is that

science could have progressed

differently and the pragmatic view of

data really underscores that

contingency. it can still progress

differently. And the indigenous data

sovereignty movement needs institutions

that can bend scientific progress

towards its own goals. And another way

of saying that is that they need

institutions that are going to support a

tradition of biological inquiry as

guided by indigenous values and concerns

when it comes to these moments of

identifying problems, picking methods

and accepting solutions.

Uh and the native biodata consortium is

such an institution. you know as a bio

bank they preserve data for future use

they create and enforce rules about who

can use the data and they selectively

facilitate use of that data. So another

way of saying that under the pragmatic

view here is that they're investing in

the future meanings of data which are

unknown because we don't know what uses

people will come up with for them. Uh

they're controlling the current meanings

of data by controlling how they're used

now.

And then another question all comes up

here is well how

ought they

control current uses of data.

And this is the second way that I think

the pragmatic view of data is going to

help indigenous data sovereignty. It

provides a more penetrating vision of

science that's fit for indigenous

judgment. When for instance if you're

the native biodata consortium and you

have to make a decision, oh this group

wants to use this data for this purpose.

thumbs up or thumbs down to put it in a

very simplified way.

So, here's an example that uh I made up

so it would be clean, but it's very

similar to things that have actually

happened. We got a plant varietal here

with droughtresistant traits found only

on sovereign indigenous lands, outsider

scientists,

uh and they want to study the plant,

right, for this trait. So, they're going

to need to extract this biodata off the

indigenous communities land. And what

narrative is the scientists going to use

to justify that extraction to their

funders, to the indigenous community, to

themselves?

Say something trying to understand the

genetic basis of dropresistant traits.

Why? To help solve problems of global

warming, right? There could be famine in

the future with global warming. And

understanding the genetics behind

drought resistance and agricultural

crops could be really important for

feeding people and preventing famines in

the future.

And so these twin goals are sort of like

forever being claimed by scientists.

They want to understand the world and

they want to improve the world.

You might say something here like, you

know, it just happens to be the case

that this plant on indigenous lands is

part of the solution to a humanitywide

problem. I wish it wasn't like this.

Everything's messed up. But this is the

situation we're in now.

And the indigenous community is put in a

situation where it's like you can either

stand in the way of progress that's

going to help everyone or you can be

selfish and like not let someone study

this plant,

right? But when you take the pragmatic

view of data, it sort of changes this

phrasing. You're forced to say, well, I

want to use this plant on indigenous

lands as part of the solution to a

humanitywide problem. And that I want

opens the door to a series of further

questionings

that

puncture the veil of these generically

virtuous goals. So I'm not arguing here

that scientists are dishonest about

wanting to understand the world and

improve the world, but the these are

just sort of too vague to really be

inputs for good decision making about

whether a scientist should be able to do

something with data.

So for instance, I think understanding

is a fake goal. Uh and you know to see

how it's a fake goal, just think about

you know how will you answer a question

about how do we know when the thing is

understood? How will the scientist

demonstrate that they've achieved their

goal of understanding? And the answer to

this question is always going to come

down in my opinion to the scientist's

ability to do something relevant to the

thing they're trying to understand.

Right. So in this case with the plant

it's probably something like the

scientists can claim they understand the

base gen basis of droughtresistant

traits when they're able to manipulate

that trait by manipulating something

about sort of the genetics of plants

and that's an actual specific goal right

it's not just I'm trying to understand

the world now we're talking about things

the scientist is actually trying to do

similar for improving the world you know

start to think well you know what's it

actually within a scientist power to do.

So they don't legislate trade

agreements, they don't marshall the

forces of industrial agriculture,

uh they don't control supply chains. So

to say that they have this goal of, you

know, stopping famines in the future,

it's sort of like a tire manufacturer

saying they have the goal of building a

luxury automobile. It's like what you do

might be necessary for that, but it's

far from sufficient.

So third reason, this is uh the shortest

one here. I think that the pragmatic

view of data is more in line with

certain at least North American

indigenous philosophies. And in so far

as indigenous data sovereignty is about

indigenous peoples using their own ways

of knowing, their own cosmologies to

inform the way they control the use of

their data. I think it's important to

try to get at that somehow, which was

the project that originally put me on

this path. Remember, was trying to come

up with this white paper that's based on

indigenous philosophy.

And uh I haven't explored this that much

yet, but the basic idea here is just

that the pragmatic way of thinking about

data really emphasizes relationships

and so does a lot of indigenous

philosophy, especially when it comes to

the the task of defining things, which

is always very important to

philosophers. And so indigenous

philosophies uh that I've been looking

at in southwest of America are often

going to define things in terms of its

relationship to other things. So for

instance, you know, I have the medicine

wheel here because that's often used as

a I don't know, visual metaphor for this

way of thinking. But to be a person, you

know, it depends on your relationship to

things like other people, the place

you're in, your own thoughts, your own

body. And you can contrast that with a

more traditional western way of defining

things. Got Aristotle here as a

representative of it. And that's of

defining something in terms of necessary

and sufficient properties or conditions

for the realization of that thing. And

so on this way of defining things, you

know, things possess properties. And so

to be a person, you have to be a kind of

thing that possesses certain essential

properties such as maybe rational

thought being five people. I don't know.

Different people come up with different

lists.

All right. So that's the end of the data

one. What about this concept of

sovereignty? This one is even newer in

the developmental stage of research. I'm

just trying to write some grant proposal

about it right now. Going to be

collaborating with Trevor Reed. He's a

law professor here at Arizona State

University, a member of the Hopi tribe,

has a PhD in ethnomusicology as well as

a JD focusing on federal Indian law. And

all of that's relevant to the way that I

want to get at this question of like

what would it mean to clarify indigenous

notions of sovereignty.

So just some notes here uh to foreground

this problem. Sovereignty it's not just

one concept. There's many different

concepts of sovereignty just within the

western European political tradition.

And these concepts don't stand alone.

they sort of travel in packs with

related ideas like uh views of human

nature, views of nationhood, views of

human rights, ideas of individual and

collective freedom.

And so different sovereignty concepts

support different visions for how

humanity ought to organize itself and

make decisions as a corporate entity.

And the question I'm asking and pursuing

here is well, how do we clarify

indigenous conceptions of sovereignty?

And there's really, you know, some major

philosophical problems sort of uh

waiting to jump out at anyone just even

within the the way I'm phrasing this uh

research aim. And so one of the big

problems is just a general issue of

comparing concepts. So here we got two

things, not concepts. We got a screw and

a banana. And we can compare them

because we can characterize them in

terms that sort of apply to both that

are appropriate for both. So like

hardness, how hard is the banana? How

hard is the screw? The idea of hardness,

the operations

we perform to assess hardness are the

connecting bridge that make the

comparison between a screw and a banana

possible. Same with something like

taste, color, etc.

But there's no consensus way to

characterize concepts. Uh different

philosophical traditions have like

radically different ways of doing this.

And so as a result, it's like unclear

how to compare concepts. For instance,

the concept of a screw and the concept

of a banana because the concept of a

banana isn't yellow. It doesn't taste

like a banana, right? It doesn't have

these sort of properties that make

comparison possible.

And my solution to this problem right

now uh is that I believe that every

concept has a pragmatic dimension which

I is a way of saying that all across

time and space people use concepts to do

things for reasons. I think that's

general enough to apply. I'm not making

too many prior assumptions uh when I say

something like that. And so the

different variables and factors

surrounding a person using a concept to

do a thing for a reason can provide the

sort of connected bridge that will make

comparison possible.

So this is my visual example try to get

at this right now. Like we can compare

these things

via the framework of problems and uses

because in this case, you know, they can

both be used to attach two pieces of

wood. And so we can start to talk about,

well, this one's better than that one in

terms of attaching two pieces of wood or

because it attaches them in this way.

And so with the this problem I'm trying

to get at indigenous conceptions of

sovereignty, we have the issue that like

right from the outset uh sovereignty is

a western concept. And so you don't want

to assume that there's going to be some

concept in indigenous philosophies and

cosmologies that corresponds to

sovereignty in a straightforward way.

And this pragmatic dimension of concept

solution helps us get around this issue

because we can reframe it. It's not it's

no longer a research program about

indigenous conceptions of sovereignty.

It's about this problem or use frame of

reference of how to organize human

collectives, which again I think is a

problem that's

universal across time and space with our

species that we live in groups. Uh

figuring out how to do that isn't

obvious. And so I think any group of

people is going to have developed

conceptual tools for confronting this

issue of how do we organize ourselves

and make collective decisions. And so

then the question is within the

indigenous philosophy cosmology what set

of concepts have been developed for

addressing this problem.

And then furthermore, I think it's super

useful when two different philosophical

conceptual systems come into conflict.

And I know this through my work as a

historian and philosopher of science

that scientific debates are some of the

most enlightening episodes for

philosophers and historians because

scientists are forced to sort of make

their assumptions more explicit and they

attack each other's weak points and they

emphasize their own strengths. And so

it's sort of like opening a window into

the conceptual workings of science that

usually remains closed. And I want to

take advantage of conflict in the same

way

with this project.

So you know whereas a lot of times with

a project like this people would

endeavor to get rid of all colonial

influence to try to recover like an

untouched philosophical state in

indigenous peoples. I'm trying to sort

of flip that on its head and leverage

what I was just talking about with

conflict between systems as well as the

well doumented textbased nature of legal

conflicts. So I'm going to use legal

conflicts as the sort of handhold to

grab onto just like I use scientific

claims from research reports as the

initial thing I grab onto and then I

look at everything surrounding that to

make sense of what was happening there.

And so I think you know indigenous

peoples

had concepts that they used to address

the problem of how to organize

themselves, how to make collective

decisions prior to contact. And no doubt

those influences

uh were present in the way that

indigenous peoples sort of made

arguments in the western court context

uh which were often about sovereignty

and ownership of property. And then I

want to look at sort of how the

different ways they confront these

concepts play out historically. I'm

still working on the details of this. I

just put this here so you can see the

sort of connection here and how I'm

trying to bring the methodology from the

history and philosophy of science into

this new area.

All right. Uh so I just got 10 minutes.

I'll zoom through this and it's short.

Just peculiar interest provocations. I

like Adobe building. I would like to

incorporate that into my work eventually

somehow. I like hydraulic models of

neurohysiology. I think it's a really

interesting way of thinking about brains

and behavior. Uh it still invokes this

idea of a representation but it does it

in a non digital computer way which is

the norm currently I think to think

about like discrete variables that

computers have or a circuit board. Um,

these are more like analog computers.

And I like when scientists use this

model of thinking uh when they

investigate brains and behavior. I like

puppets. I was once making a uh online

series of classes about the history and

philosophy of animal behavior research.

I was using puppets, but I

underestimated how long it would take me

to write the scripts and just get all

the resources together. Like I had voice

actors with the puppets. But I'm

teaching a new class next semester here,

history and philosophy of complex system

science. And maybe I'll find a way to

get the puppets involved. It's a New

Mexican fences. There's something going

on here. Uh huge amount of variety and

diversity, more than I've seen in any

other state in the US. And it's not just

poverty, which I think a lot of people

probably jump to, that they're just

using whatever materials are at hand.

Very interesting. I got a whole

collection of photos of New Mexico

fences. And then something I've been

doing lately is just ending

my presentation with a list of

provocations to get the audience going

and asking some questions. Though

instinct concepts are unfairly maligned,

learning is overhyped. Brains are not

obviously just computers manipulated

symbols repetition to sort of constrain

the scientific imagination just as much

as they pathways for investigation.

I think meaning is determined by use.

Probably know what I mean by that now

since I keep endorsing pragmatic

approaches to problems of meaning.

As a result of adopting the pragmatic

view, I think desire, purpose, and drive

are the most mysterious ingredients of

meaning. Think correspondent theories of

truth are European mysticism.

Behavior is the only solid foundation

for theorizing about brains and minds.

Human rights are fake and insidiously

undermining the indigenous data

sovereignty movement. I didn't get into

that this presentation. And the

trajectory of scientific progress is

extremely contingent, more so than is

commonly appreciated.

I don't think that last one's a

provocation.

Thank you.