JACQUES LEZRA: Please join us
for this last session panel.
I'm going to take two minutes
to do some mechanical stuff.
SPEAKER: Housekeeping?
JACQUES LEZRA: I suppose
it's housekeeping.
I'm going to grind out a
description of the journal
Political Concepts, which is an
online journal, which we invite
all of you to visit, and to
parasitize for your classes,
and to circulate.
It contains a
lexicon information
of these political concepts
that have been presented
at the different political
concepts of conferences
over the years.
We're in Volume 5.1, I believe,
which is The Trump Edition,
as Adi mentioned yesterday.
We would very much like
to be able to consider
for publication there the
proceeds of this conference.
So if you have presented a
paper that you're happy with
and even if you presented one
that you're not particularly
happy with, please
send it to us,
and we will butcher it
and put it up there,
if our readers like it.
The journal Political
Concepts has
taken concrete physical shape
in the form of one book, which
I will now hold up.
And if you want to see
it, we'll pass it around
for your pleasure.
It's published by
Fordham University Press.
Political Concepts,
A Critical Lexicon,
we think of it as a
lexicon information.
This one has 12 or 13 entries.
And pass it around
for you to look at.
The next one should
appear at the end of '19.
It is called
Political Concepts 2.
We are masters and really
commanders of originality.
This one is subtitled
Thinking with Balibar,
and it collects some of the
essays that were presented
at last year's--
was it last year?
Two years ago's Political
Concepts Conference
on the work of Etienne Balibar.
Because I have it in front
of me and because it's
sexy in the extreme,
I'm going to read
you the table of contents, so
you'll know what's coming--
the introduction by
Warren Montag, Balibar,
The Philosophy of the Concept;
Anthropological by Bruce
Robbins; Border
Concepts, [INAUDIBLE];;
Civil Religion by Judith Butler;
Concept by Etienne Balibar;
Contre Counter by [INAUDIBLE];;
Conversion by Monique
David-Ménard; Cosmopolitics
by Emily Apter;
Interior Frontiers
by Ann Stoler;
Materialism by
Patrice Maniglier;
The Political by Adi Ophir;
Punishment by Didier Fassin;
Race by [INAUDIBLE];;
Relation by [INAUDIBLE];;
Rights by Jay Bernstein;
Solidarity by Gary Wilder.
It's going to be a wonderful,
very thick volume, indeed.
Finally, just two further
housekeeping notes.
The 2019 edition of the
conference Political Concepts,
which is usually held
in New York this year,
exceptionally-- and I hope
not for the last time--
is going to be held in Paris.
So if you happen to be in
Paris at the end of May,
you should come.
The following year will
be in spring of 2020.
And it'll be at the New
School for Social Research
in New York.
And now it's my pleasure
to introduce the speakers
at this last session.
In order, they are, again,
with the usual parsimony and
characteristic stenographic
quality of our introductions,
Yarden Katz.
He's a department fellow in
Systems Biology at Harvard
Medical School, an affiliate
of the Berkman Klein
Center for Internet and
Society at Harvard University.
He'll speak first.
Then a joint presentation
by Peter Galison,
who's the Joseph Pellegrino
University Professor in history
of science and
physics and director
of the Collection of
Historical Scientific
Instruments at Harvard,
and Noah Feldman, who's
the Felix Frankfurter
Professor of Law and director
of Julis-Rabinowitz Program
on Jewish and Israeli Law
at Harvard Law School.
Yarden, who's there.
YARDEN KATZ: Thank you
very much to the organizers
for having me.
So I chose
Entrepreneurial Science
because it seemed to me to
be politically urgent, not
because it's the most
intellectually stimulating.
So if what I'm about to say is
banal, I apologize in advance.
So what is
entrepreneurial science?
We can ask instead, who is
the entrepreneurial scientist?
And for that, we might need
to know who is the scientist.
In his book, The
Scientific Life,
the historian Steven Shapin
tackles this question.
Shapin chronicles the
lives of scientists
and how they've changed from
Aristotle's day to the present.
His final chapters are about
the scientific entrepreneur.
Shapin paints the scene.
It's a sunny afternoon
in San Diego,
and we're at a stylish cocktail
party at the University
of California.
There are scientists,
venture capitalists,
intellectual property lawyers,
all mingling harmoniously.
"The gathering,"
he writes, quote,
"is a sign that the
university is fulfilling
one of its major
acknowledged functions
in a late modern
economy, building
bridges between knowledge making
and wealth making," end quote.
Here, Shapin says,
quote, "Business
is business, and your gender,
religion, or parental wealth
matter less."
For Shapin,
entrepreneurial science
is the obvious next phase in the
progression of scientific life.
Entrepreneurs are
the risk takers
that interconvert
knowledge and wealth.
For example, Shapin praises
the biotech firm Genentech
for commercializing
the production of drugs
using recombinant DNA
techniques originally developed
by academics.
Genentech's product
and patents are indeed
often held up as a success story
of entrepreneurial science.
But Shapin omits one
part of the story,
a part so big it was written
up in the Washington Post,
but small enough that it
can be glossed over safely
in scholarship.
On New Year's Eve in
1978, a group of men
sneaked into a laboratory at the
University of California, San
Francisco.
The men were from Genentech.
Frustrated that they couldn't
clone the gene needed
to make human
growth hormone, they
came to campus to steal it.
They grabbed the vial
from the freezer,
they published a Nature
paper, produced a drug,
and made billions.
20 years later,
one of the thieves,
Peter Seeburg, by then a famous
professor at the Max Planck
Institute, wrote a confessional
in Nature Magazine.
As a witness in
the ensuing court
case between Genentech and the
university, he said, quote,
"It was dishonest.
I regret it.
But that's the way we did
it 20 years ago," end quote.
Theft didn't make it
into Shapin's account,
but in footnote
number 20, he cites
a literature that
he describes as,
quote, "complaining
about universities
and entrepreneurship."
OK, so in this vignette, we
have the beginning of a theme.
We have violent theft from
what looks like a commons,
and we have professional
historians naturalizing
entrepreneurial theft.
My perspective today will
be different from that
of the professional historian.
I'm writing from the middle
of scientific inquiry.
My aim is to articulate
some of the violence
of the American
scientific enterprise,
not just the violence it
delivers upon the world,
but also the violence
done to scientists
who are participating in it.
I consider
entrepreneurial science
to be an important concept, even
if not the most analytically
accurate, in this project.
But there are some caveats here.
Powerful arguments
for the disunity
of science by Peter
[INAUDIBLE],, among many others,
compel us not to talk about
science like it's a monolith.
Different scientific communities
have different fabrics.
My focus here will be on
academic biomedical science,
but I consider the
biomedical arena
itself to be a
kind of laboratory
for entrepreneurial
science, a place where
the most destructive tools
are developed and later
perhaps exported elsewhere,
not unlike how tools of state
control are first
tried on non-citizens
and then applied at home.
But there is another
danger still here,
the risk of producing what
Stefano Harney and Fred
Moten called laments
for the university.
I take to heart Harney and
Moten's premise that, quote,
"It cannot be denied that
the university is a place
of refuge, but it cannot be
accepted that the university is
a place of enlightenment.
And this tension
will be with us."
So let's rewind.
Let's probe entrepreneurial
science by asking instead,
who is the entrepreneur?
The term entrepreneur is
attributed to the 19th century
French economist,
Jean-Baptiste Say,
who became an icon of
free market ideology.
Say defined the
entrepreneur as one
who, quote, "shifts
economic resources out
of an area of lower and
into an area of higher
yield and productivity."
It's a sanitized formulation
of exploitation in some sense--
taking or stealing
what's available
and using it for self-interest.
Perhaps unsurprisingly,
in 1828, a French ship
carrying enslaved
Africans to Martinique
was named entrepreneur.
Say admired the white
European settlers in America
who apparently
brought agriculture
to the indigenous
population, thereby
creating higher value for all.
As he wrote to Thomas
Jefferson in 1803, quote,
"The United States are
the offspring of Europe.
But the children have more
merit than their fathers.
We are elderly parents raised
with stupid prejudices.
You will show us the right
way to free ourselves,
for you did more than
just conquer your freedom.
You affirmed it."
In English, the
usage of entrepreneur
rose sharply in the
1970s and early 1980s.
You can imagine an engram here.
I'd like to revisit
this defining period
through a somewhat
forgotten text.
In his 1984 book, The
New Politics of Science,
David Dickson
analyzed what we might
call entrepreneurial science
and ways to resist it.
By contrast to many
science studies scholars
who focused on the so-called
politics of the device,
Dickson recognized the
top down initiatives
to reorganize the
scientific enterprise.
He wrote as important
changes were taking place,
making his account invaluable.
Dickson traces moves by
the Carter and Reagan
administrations to elevate
the role of corporations
in academic research,
while slashing
publicly funded programs.
He reminds us of
Reagan's science advisor,
George Keyworth, who spoke in
1983 of the need to impart a,
quote, "better sense
of reality," end quote,
to basic researchers
by putting them
in touch with the marketplace.
There were legislative
changes that
made it easier to patent
academic work, the rise
of so-called public, private
partnerships, the expansion
of a university administration,
increased competition
for funds, and so on.
Each change is
sometimes exaggerated,
but the whole, or the
sum, is significant.
But it isn't only
that academic science
was being recognized at
the time as indispensable
for profit making and the
imperial aims of the state.
These structural
changes were meant
to erode the already
limited democratic control
over the spheres of
professional knowledge.
For Dickson, this affair
was hybrid all the way down.
As he wrote, quote,
universities and industry
have teamed up to challenge
the democratic control
of knowledge.
In other words,
universities were not
being meddled with by some
nefarious external entities
called corporations
and the military.
Rather, the three spheres,
academic, corporate, and state
military were partners in crime.
Today, universities act as
micro neoliberal states,
enforcing what Noam Chomsky
called investors rights
agreements on behalf of
entrepreneurial faculty
and corporate partners.
A recent case with
UCLA is illuminating.
With public funds, UCLA
chemists developed and patented
a prostate cancer drug.
The university sold the
patent to a company now owned
by Pfizer.
The company went to court
in India, as they always do,
to challenge a law that would
have allowed the manufacture
of cheaper generics.
UCLA enlisted in
the legal battle
and is now helping
the company make it
so Indian cancer patients
would have to pay over
$100,000 a year for treatment.
Activists, including
medical students at UCLA,
have been challenging the
university for several years
with no change.
So how does this work?
The entrepreneurial endeavor has
two main epistemic ingredients,
as analyzed by Phil
Mirowski and Wendy
Brown, who are both building
in some way on Michel
Foucault. "First, there's
the concept of the self
as entrepreneur, the individual
as a portfolio builder,
whose worth is constantly
re-evaluated on some imagined
market.
Second, there is a notion that
centralized power, normally
the state, must create the
conditions for said market
to make decisions."
As Phil Mirowski pointed
out, such a monolithic market
is assumed by
neoliberal theorists,
like Hayek, to be a better
judge than any person
or human collective.
Scientists are also expected
to build portfolios consisting
of publications,
citations, patents, data
sets, pieces of software.
Digital platforms are
constantly being introduced
to evaluate these portfolios and
create the mirage of a market.
It's easy to see this
entrepreneurial epistemology
at work.
Let's take a local example.
Neuroscientists from
Brown University
teamed up with MIT Press
and Peter Fields Foundation
to form the Discovery
Engine, which is, quote,
"the first and only quantifiable
measure of discovery."
It's yet another
more computationally
sophisticated metric for
identifying in real time
those publications that are,
quote, "actionable" and, quote,
"truly change our
understanding."
The metric is to be used
by funders and universities
to rank individuals,
institutes, and fields.
Yet it's promoted as
open and democratic.
Similar thinking is used by the
National Institutes of Health,
the NIH, the largest sponsor
of biomedical research
in the world.
The NIH has started quantifying
the so-called return
on investment by measuring
citations per dollar
of funding that they award.
By this view, we pour
in dollars in order
to maximize citation
count as output,
as if it were a macroeconomic
statistic like GDP.
This fosters a mode
of inquiry that
is premised on what I call an
empty feedback loop, whose only
goal is to produce
maximally citable products.
The different interest
logics and histories
of scientific
communities are erased.
This mode of inquiry wouldn't be
sustainable without propaganda,
a dimension that feels
to me somewhat neglected
and that I'd like to dwell on.
Propaganda is part and parcel
of entrepreneurial science,
propaganda produced
by hybrid alliances
across corporate media,
university press offices,
and scientific journals.
Consider the heated dispute
between MIT and UC Berkeley
over the patent to the genome
editing technique, CRISPR.
Whole wings of the
university were
recruited to a war of narratives
over the rightful so-called
inventors of CRISPR.
The dispute unfolded
on social media,
in the pages of The Economist,
as much as in the courts.
Arguments crafted by
intellectual property lawyers
flowed into the official social
media accounts of universities.
Science journalists regurgitated
institutional narratives,
but never scrutinized
the premise
that there is a rightful
inventor of CRISPR.
The burning question
was, does genome editing
belong to Berkeley or MIT?
The CRISPR affair
may be exceptional,
but the vehicles of
propaganda aren't.
Entrepreneurial science
depends on a pipeline,
where publications and
prestigious academic journals
become university press
releases and are then recycled
as news by science journalists.
Dedicated science journalism
is actually fairly recent.
The New York Times, for one,
didn't have a science section
until the 1970s.
But from the start,
science coverage
was about raising public
support for science.
In 1894, HG Wells, the famous
novelist, and journalist,
and eugenicist, wrote
in Nature Magazine
that science must be
popularized in order
to avert the danger of, quote,
"supplies being cut off."
The tightening link between
mainstream media universities
and scientific
publishers has shaped
the actual technical genre
of scientific writing
in ways largely anticipated
by Bruna Latour.
Under the label of
storytelling, an expert industry
has emerged recently to
ostensibly tell scientists
how to write better.
But scientific storytelling
offers a narrow version
of story.
Storytelling is really
a marketing discourse.
It is concerned with
crafting narratives
that rise through the
webs of social media
and glamor scientific journals,
like Nature and Science.
Storytelling experts
may speak of, quote,
"narrative analytics."
Storytelling advice is published
in prestigious scientific
journals and taught in
science graduate programs.
Journalists from
the New York Times
even come teach
elite scientists how
to frame their projects in a
way the press can run with.
The most entrepreneurial
scientists
cultivate such relationships.
These phenomena should make us
see universities and journals
differently.
Elite universities,
like MIT and Harvard,
are not just
universities, but also
real estate agents
who own hotels,
and in the case of Harvard, even
logging farms in New Zealand.
Likewise, Nature Magazine is
not just a scientific journal.
It's a full blown
media outlet operating
on a continuum with CNN.
And Nature Magazine is
not just a media outlet.
It's also an
advertising consultancy.
Through a platform
called Nature Index,
the magazine ranks
institutes and fields
by elaborate metrics.
For a fee, Nature Magazine will
help organizations climb up
the magazine's own rankings.
While fungible and
mostly meaningless,
these metrics affect
promotion and funding.
Some universities pay tens
of thousands of dollars
to faculty member per
publication in a top tier
journal.
Others pay per citation.
Contrary to Nature Magazine's
imperial reporting,
this isn't only true in China.
Metrics essentially
function here,
I think, as a kind of glue
for entrepreneurial science.
They offer a loosely
shared language for impact
across seemingly
disconnected arenas--
corporate media, corporate
scientific journals,
and academia.
So I think a curious
contradiction emerges here.
The actor network theory
described by Latour
became part of the
science curriculum.
Put another way,
entrepreneurial scientists
are consciously and
crudely Latourian,
in the old sense of Latour here.
They openly write about
getting the optimal story
out using networks of
alliances, while carefully
tuning for the metrics.
They teach the importance
of considering hierarchies
of authority in every
step of the research,
from choosing the project
to writing the paper
and promoting it
in social media.
And yet, the same
scientists also
promote familiar
fantasies of science
as detached from politics.
Consider the discourse
around the March
for Science following
Trump's election.
Initially, so-called diversity
issues were part of the agenda,
but even that came under attack.
Harvard psychologist
Steve Pinker,
our good friend,
declared on Twitter,
quote, "Scientists'
march on Washington plan
compromises its goals
with anti-science slash PC
slash identity politics slash
hard left rhetoric," end quote.
This is Twitter, so, you
know, few characters.
While there were
important exceptions,
the mainstream March
for Science essentially
heeded Pinker's warning.
The march focused on what
was deemed universally
important, like the threat
of cuts to the NIH budget.
In short then,
entrepreneurial scientists
broadcast a vision where
they are shrewd participants
in some type of actor network,
while also portraying science
as objective and apolitical.
This entrepreneurial
turn, of course,
is not just an
infrastructural change,
but it actually
shapes the substance
of scientific theorizing.
As platform companies
like Google and Facebook
move aggressively into
academic biomedicine,
they leave their imprint.
Take the Human Cell Atlas, the
latest big science project,
for instance, which is
explicitly fashioned
after the Human Genome Project.
It's funded by
Silicon Valley moguls,
and it capitalizes on
their computational tools.
But it's about more
than just tools.
The Human Cell Atlas
describes itself
as developing a, quote, "Google
Maps for the human body."
This framing
exemplifies to me how
a rich history of feminist
theorizing about biology
gets continually marginalized.
The Cell Atlas
Project is essentially
an imperial cartography
of the body.
The map metaphor that
it employs is static.
It presumes a universal
set of cell types
to be unearthed in
positivistic fashion.
Yet, far richer dynamic
models for thinking
about cells and
organisms have been
developed by feminist
biologists and critics.
The most obvious here is
developmental systems theory,
as articulated by people
like Esther Thelen,
Linda Smith, and
Fausto-Sterling, Susan Oyama,
and so on.
Yet entrepreneurial
biologists are generally
unaware of, and sometimes
poorly reinvent,
this line of thinking.
OK, so what I've
described so far
can be seen through the lens
of neoliberal epistemology,
as interpreted by critics like
Phil Mirowski and Wendy Brown.
In short, academic work is
restructured in the image
of a mythic marketplace.
Yet, there is a trap in
these forceful critiques
of neoliberalism.
First, these critiques
put us to work
as interpreters and chroniclers
of neoliberal theorists,
like Friedrich Hayek
or George Stigler.
In doing that work, we
risk imbuing their project
with coherence and power
that it, in fact, lacks.
Second, in becoming expert
critics of neoliberalism,
we begin to see it everywhere.
Perhaps it occupies
our imagination.
Maybe we lose sight
of the resistance,
as Bonnie Honig argued
in Public Things.
I think that
neoliberal epistemology
doesn't need to be critiqued,
so much as deflated.
The neoliberal framework
where a singular market
governs all decisions is
at best an aspiration.
No space inhabited
by human beings
is fully neoliberalized
in this way ever.
After all, we can ask what
scientific insights have ever
been obtained through so-called
information processing
by the market?
None, it seems to me.
It's a silly fabrication.
More critically, even
under neoliberal pressure,
scientific work is filled with
acts that the historian Peter
Linebaugh called commoning.
Commoning is what
makes resources
available for collective
use, a part of the commons.
You can see it all the
way from small things,
like the way enzymes
are organized
in the freezers of
molecular biology lab
to bigger systems of reagent
and data sharing and even
publishing, even in its
current corporatized form.
If acts of commoning
were to stop,
the laboratory would collapse.
And the social bonds
between laboratory members
crucial for its
function would erode.
But neoliberal epistemology
blinds us to commoning, partly
because it only
acknowledges two entities,
the individual
entrepreneur and the state.
No other collectives, including
the laboratory, are admitted.
And yet, active commoning
in the laboratory
should not be confused with
having a robust commons.
As Eugenia Zuroski
put it, quote,
"Academic labor is in
general multifaceted.
And every one of those
facets is currently
being exploited by
institutions," end quote.
The laboratory is, in fact,
a prime site of exploitation.
Principal investigators--
PIs, as they are called--
build little empires on the
backs of students, postdocs,
and technicians.
The most entrepreneurial
labs produce,
in fact, so many papers
that the PI can't possibly
even read them all.
The system is
stacked in such a way
that PIs can play dice with
their subordinates' futures.
Only a handful need to
succeed for the PI to thrive.
The denominator rarely counts.
The PI is therefore made
in a patriarchal image.
PIs are employers with
nearly unlimited powers
over their employees, although
universities and funding
agencies insist on
characterizing the relationship
as one of mentorship
and training.
Rampant sexualized
violence in academia
makes clear that these
relations proceed
with little accountability.
As a result, laboratory
workers continually
experience what Lisa Siegel
has called embodied anxiety.
They also experience, as
Ruth Mueller has put it,
more limited epistemic freedom.
To cope with this state, the
entrepreneurial laboratory
is dependent on hidden
and often gendered labor,
the caring for peers in
precarious conditions.
That's the kind of
labor that isn't
reducible to GDP styled metrics
that entrepreneurs invent.
So to summarize, what is
entrepreneurial science then?
If you ask me tomorrow, I might
give you a different answer.
But today I think of it
as the mode of inquiry
that arises when
you try to maximally
exploit the available
commons, while violently
hindering acts of commoning.
OK, so what about resistance
to entrepreneurial science?
This is really a
question about movements,
and I think that we
can't begin to address it
without considering
the $1.5 trillion
of student debt in the US,
hanging over the heads of 44
million former students.
When people can't afford
education or health care,
concerns over academic
science can seem detached.
Resistance, therefore,
demands that we
expand our scope, as David
Dickson urged us to do in 1984.
Dickson was aligned with
groups such as Science
for the People, who saw
efforts to transform science
as part of a global
solidarity struggle
to be pursued in collaboration
with other movements
and groups, such as the
Young Lords in their case,
or the Black Panthers.
Any effort to
change science would
require us to challenge, quote,
"the distribution of wealth
and power in US
society," end quote.
But Dickson also
wanted activists
to recognize that the conditions
under which science is produced
are intertwined with the
substance of the science.
A science that is
entrepreneurial in process
will produce racist,
gendered, and class theories.
That's why a movement
to transform science
would need to, quote,
"democratize the laboratory."
Openings for this move
can emerge unexpectedly.
For instance, the
recent media discussion
of Elizabeth Warren's
quest to prove
her Native American identity
with DNA testing or the Trump
administration's efforts
to erase trans identity
by an appeal to a so-called
objective birth sex.
Both of these are enabled
by longstanding racialized
and gendered biomedical science.
Perhaps when discontents
with these developments
are more fully linked to
the exploitative conditions
in laboratories
and universities,
the scientific enterprise
could be changed.
But in the meantime, recall
Harney and Moten's adage.
Quote, "It cannot be denied
that the university is a place
of refuge, but it cannot be
accepted that the university is
a place of
enlightenment," end quote.
Their next sentence
is less polite.
Quote, "In the face
of these conditions,
one can only sneak
into the university
and steal what one can."
Thank you.
[APPLAUSE]
PETER GALISON: OK, so
we'll proceed in two parts.
First, I'm going to
introduce the problem
and say a few words about
the system of state science
contract during the Cold War.
Then Noah will take
over and talk a bit
about what we have in mind
by the neoliberal moment
in the state, in the
science economic formation
relationship.
And then we'll discuss the
transition, the two of us,
at the end of that.
The argument is that we want
to look at three interconnected
moments of the condition
that we find ourselves
in now and in the Cold War.
That is to say changes in the
notion of a scientific self,
the economic regime, and
the epistemological virtues.
That is to say what the specific
content oriented virtues are,
approach virtues are to the
scientific knowledge itself.
We take on board
very much and are
sympathetic to the
kind of presentation
that we just heard, which
I think is terrific.
And of course, have learned
from the intellectual historical
work of Phil Mirowski on
the notion of neoliberalism,
and his colleagues and
the work that they've
done on neoliberal approaches
from STS, and of course,
of our much valued colleague
at Harvard, now unfortunately
retired, unfortunately for us.
Steve Shapin, who's
been interested
in the scientific persona, and
questions of trust and charisma
have been the locus for
much of his concerns.
So for example,
what scientists did
to gain the trust
of entrepreneurs.
Those are not so
much our approach,
although they're a
valuable, constitutive part
of what we're doing.
We're interested
in this liberal--
by liberal, we mean
sort of the scientist
as a liberal professional that
begins in the 19th century,
continues into the 20th
century, and contrasting that
with the rise of something
like a neoliberal configuration
of what a scientist
does to form him
or herself in order
to be able to do
a certain kind of science,
as opposed to simply gaining
the trust of people
on the outside.
We're interested
in the scientist's
direct participation in
the political economy
and what that does to the
science itself, rather
than the influence in a
kind of astral imposition
on the science from
an outside force.
We don't see the university
as separate from the economy,
but as in it.
The goal, in some sense--
I mean, this is a kind of
encapsulated, monstrously
oversimplified version
of the argument,
but the goal in some ways of
the science of the Cold War
was to find an
explanation that was
encoded in a lapidary form
in a mathematical expression.
This was the goal, for
instance, of Steve Weinberg,
who wanted to find a unified
field theory of everything.
And he said, one day, I hope
and expect to be able to wake
up and find the
Lagrangian of the world.
And that would be the string
theory Lagrangian that
would explain everything else--
this in a cartoon fashion.
In the 1980s, you
had this picture
of a proton or a neutron, and
you made a Lagrangian for it
that showed its little BB-like
constituents of quarks.
And then in more
recent times, they
were connected by these
springs, the so-called gluons
and the Lagrangian of
quantum chromodynamics.
It's written down
mathematical form at the top.
And the history
of a certain kind
of conception of science at
its most prestigious over that
period from 1945 to 1995 was
a progression in the ambit,
in the remit of science,
especially in physics,
as capturing that
explanatory lapidary
formation of the Lagrangian.
And we want to look at
the transition or the--
I shouldn't say transition.
Because it's not like that
kind of science is gone.
But it's been supplemented
and in some ways,
pushed somewhat aside by a
different picture of what
the goal of science was.
And that was to come up
with predictive models that
would use deep learning, neural
networks of multi layers.
You would have certain inputs.
And then layer upon layer
of different cost functions
and weighting
functions would modify
that to produce a prediction,
whether it was in genomics,
or astrophysics, or the
neurosciences or other domains,
and give you a
prediction of something.
In the commercial domain that
consisted of, for instance,
things like if you
like this on Netflix,
you'll like that in the future.
But that doesn't trouble
anybody too much.
It does trouble people
in the sciences,
where it's become a big
debate over whether this form
of predictive
completeness-- that
is to say that the prediction
ought to suffice into the day.
That if we can do
that, why are you
bothering us with a demand
for explanatory structures?
The Cold War really--
of course, we really are
looking at a long war
from 1939 to 1989.
And over that period with the
growth of big science at places
like Los Alamos,
Oak Ridge, Hanford,
you had a new contract
formed between scientists
and the state.
And whether it was GOCO--
Government Owned,
Corporate Operated--
or, after the war, the Office
of Naval Research and then
the National Science Foundation,
the Atomic Energy Commission,
which becomes DOE, and all
of the analog structures
in the biological and biomedical
facilities, that scientists
and through their universities
made a contract with the state
and were funded by it.
It was highly economic,
but it wasn't market
dominated in its totality.
And so one of the things
we want to caution about
is that in the engagement
with this market driven
neoliberal regime that
we're going to discuss,
not to see a government
funded contract
system with too much nostalgia.
It's not an elegiac
or a lapsarian story
that goes from the
perfect independence
to a devotion to market capital.
And of course, Brookhaven--
planning for the post-war
era began in the war.
Before the guns
stopped firing at all,
the members of Manhattan
Project, the Atomic Bomb
Project, were already planning
an interdisciplinary postwar
laboratory that they were
forbidden from naming,
but it was absolutely
modeled on Los Alamos.
So Brookhaven, which becomes
the first reactor laboratory,
and then a nuclear physics
laboratory, and then
a particles physics
laboratory, came out
in a direct institutional,
personnel-dominated,
interdisciplinary,
government-funded contracted
system that was created
in World War II.
Graphite research reactor
in the early days,
then the Cosmotron, one
of the first of the big--
you can see it's not very big--
accelerators there.
And then that became a model for
the Stanford Linear Accelerator
Center, not organized
in a circle,
but in a line to create
accelerated protons,
and later, electrons, to study
the interior structure of atoms
and their constituents.
And this is roughly
what it looks like now.
And then that, of course,
became a model for Fermilab,
in Batavia, Illinois,
outside of Chicago,
which, for a long time,
was one of the biggest
accelerators in the
world-- no longer, replaced
to a great degree by CERN.
There were studies there.
There were thousands of people
employed in these laboratories.
And it led in the end-- sorry
for the bad reproduction,
but of plans for a
superconducting super collider
in the 1990s that would
have cost tens of billions
of dollars.
It eventually was about
several billion dollars
were spent on it.
Between $1 and $2
billion were spent on it
before it was canceled at
the end of the Cold War.
No coincidence.
And in the end of that
laboratory, all that's left
is the hulk of some
big holes and tunnels,
is the residue of that
moment of instability,
where the arguments
for it were that it's
a little like a defense project.
And we're going to put
construction forward
in every congressional
district in the country.
It's a little bit of
a national project
to restore the pride and
national symbolism of bringing
particle physics to its best
point in the United States.
And then it was in
conflicting terms.
It was simultaneously
advertised as
an international collaboration.
And these instabilities
eventually--
I mean, clearly
sort of manifested
a kind of panicked moment
at the end of the Cold War,
as physicists tried to figure
out how the arguments that
had sustained this very
prestigious branch of science
in the Cold War would
survive as the Cold War ended
and as the sort of trans
political consensus in Congress
had begun to fall apart
as to whether this would
be supported.
We'll now turn to what happens
as the SEC begins to collapse,
and government funds for these
big physics and big science
projects begins to fall apart.
Noah.
NOAH FELDMAN: Thanks.
So to pick up the story
where Peter's leaving it off,
I want to try to offer
a tale of two laws.
This is meant slightly cheekily.
These are emblematic laws that
as you'll see, one of them
is not a law at all.
The first is Moore's law,
which you're all familiar with,
which is first
formulated in 1965,
is essentially a quasi
scientific prediction
that technology would
allow the doubling
of the number of circuits
on a silicon chip
with a certain velocity--
say, every two years.
Now it's worth
noticing, first of all,
that this is often described
in scientific law-like terms.
Even by its own
terms, it was meant
as a prediction
about the function
of economic incentives,
not merely of technology.
So the quote from Moore's
article-- and by the way,
when he wrote this,
he was the director
of R&D for Fairchild
Semiconductor.
He says, quote,
"The minimum cost
is rising rapidly while the
entire cost curve is falling."
That's the sort of money
quote from his article.
So it's always, in
its initial form,
a quasi economic prediction.
It's significant to us
both that it's economic
and that it is their prediction.
But it's also been
treated by actors
within that particular
economy as a law.
And it has also, more or less,
been empirically sustained
since 1971.
And there's lots of
discussion about its decline,
but it's still
very much in play.
Now Moore's law enables
two developments
that are hugely
significant for us
in terms of two
domains of science.
The first is, broadly speaking,
the domain of machine learning
and AI.
And our view here is
consistent with that
of many experts in
the field, according
to which the major
developments in neural networks
are not developments
of a greater
sophistication in software.
In fact, many of the
crucial algorithms
were developed quite early.
Rather, the tremendously
greater computing power
is what has enabled
the use of neural nets
to facilitate powerful
machine learning.
That, among other things,
has led to the development
of a domain of science.
And I think that we do
think of machine learning
and artificial intelligence
as a domain of science, which
is largely happening outside
of the university context
altogether, right?
So the major actors here
are Google, and Amazon,
and other major players.
There are university departments
that are, in some sense,
trying to catch up.
But this is a major
domain of science
that is now developing
largely in the private sector
and in which most of the
most significant developments
are protected under the
intellectual property
regime of trade secret.
They're notably not patented.
I'm going to come to
patents in a moment.
But they are protected
by trade secret.
And this is a growing and
significant domain of science.
The second sphere, which
is in direct relation
to the growth of
machine learning,
is what you might call, as a
shorthand, big data biology.
So this includes genomics,
or the broader forms
of what are sometimes
called the omics forms
of biological reasoning.
It includes a lot of
contemporary neuroscience,
and it can be
expanded more broadly.
But our main observation here
is that these developments
are taking place primarily
in the life sciences
and are primarily driven by
big data forms of analysis.
That is without Moore's
law, it wouldn't
be possible to do these
forms of science at all.
This then becomes
the domain of science
in which a lot of the
most exciting developments
are presently thought
to be occurring.
The second law is the
Bayh-Dole Act of 1980.
This has the benefit
of actually being
a statute enacted by Congress.
And I'm sure you all know
this, but just to remind us.
The Bayh-Dole Act essentially
allows and encourages
universities to
patent research that
is taking place
with federal funding
inside of those universities.
Now it's not that Bayh-Dole
invented university patenting,
but it did emblematize
and also facilitate
the emergence of a broader
set of social practices.
I'll state those,
and then I want
to say something about
the ideology of Bayh-Dole.
In practice, what
this has led to
is that universities,
especially fancier universities,
have offices that specialize
in patenting new developments
by often their most
prominent scientists,
though not inevitably.
The scientists then
start startup companies,
which license the patents
from the university
on favorable terms.
And the university then
becomes effectively a partner,
often a silent partner, in
the running of these startups,
so that there is a near perfect
overlap of interests then
between the scientist
entrepreneur--
to use the terms that
Yarden was using--
and the university in terms
of its overall interests.
There's more to be said about
whether economic interests
prevail here or whether
it's the university's
interests in retaining
these scientists who
stand to make a lot
of money themselves,
but that's for
further discussion.
Now a crucial word about the
ideology of Bayh-Dole and its
relationship to the
term neoliberal--
one of our worries
about neoliberal--
and we're both very curious
to hear people's thoughts
and reactions on this--
is that it's in certain
ways, a very useful term.
But it has the
drawback of sounding
like when you use
the word, that you
hate the thing you're studying.
In fact, I labor to think
of anyone who's ever
said anything positive
about something
and called it neoliberal
simultaneously.
On the other hand, to
call it wholly marketized
or market incentive
driven usually
signals the opposite-- that
you really like the thing.
So we're interested in
whether anyone has any ideas.
We're open to suggestions
for a terminology that's
less thoroughly saturated
by various ideological
commitments.
But notice the following
thing about Bayh-Dole.
It would usually
be characterized
as a standard instantiation
of neoliberalism, right?
It's privatization oriented.
What's the original
congressional justification
for Bayh-Dole?
It's that the old Vannevar
Bush model of pure science,
which notably for Bush
himself, was supposed
to lead to downstream
economic benefits
for companies that would
capitalize on the science,
had turned out not to
favor US domestic interests
sufficiently.
Because anybody
in the world could
take pure science that
was out there, and then
turn it into a product.
There was a lot of worry
about Japan in this period,
in the late 70s and early 80s.
In contrast, imposing an
intellectual property regime
on what was still a government
funded basic research,
was supposed to allow a
capture of the profit that
would be gleaned from those
downstream results for what
were presumed to be US
companies in association
with US scientists.
Now notice how complex that
is from the standpoint of what
is the supposed notion of
marketized neoliberalism.
On the one hand,
it is privatized.
But it's about privatizing
within borders,
which is in some tension
with the classic picture
of neoliberalism
as trans border.
For another point,
patents themselves
are a form of state-enforced
regulatory monopoly,
which is itself in tension
with broader market approaches.
So notice that that's
just one example,
and one could multiply that
1,000 fold of moments where
there's a series of ideological
tensions within the category
that one could easily and
offhandedly call neoliberal.
So I'm not saying don't
call it neoliberal.
I'm saying if you
call it that, you
have to be attuned to and aware
of these inherent tensions
and contradictions.
Now this all generates,
among other things,
a culture of a
scientist entrepreneur,
but it also generates
institutional features
that go with the
scientist entrepreneur.
So a good one is
the Broad Institute,
which we've already heard Yarden
mention, which was involved--
well, actually, before that,
I'll get to Craig Venter here.
So an emblematic figure for
this scientist entrepreneur
is Craig Venter.
This is a famous picture of
Venter from the cover actually
of Forbes Magazine,
wearing his lab coat
and his suit coat to capture the
idea of what a businessman is.
You can notice that this
is before the moment when
being a successful entrepreneur
meant you didn't wear a suit
and tie.
So it's a very dated
image in that regard.
He should be
wearing a turtleneck
on the other half of him under
our contemporary picture.
But Venter's entrance into
the Human Genome Project
race as a private actor
leading seller marks
a significant moment in which
entrepreneurial science began
to directly conflict with,
or compete with, I suppose,
is a better way to put it,
the more traditional state
funded model of the
Human Genome Project.
From there, one can move on, I
think, to the Broad Institute.
And among other things,
the Broad Institute,
founded in 2003, 2004, with
a grant from one donor, Eli
Broad, and later expanded by
an even larger grant from him,
so that his total grants
approach $700 million,
becomes, although theoretically,
an MIT Harvard collaboration,
a kind of quasi independent
scientific institution
that, among other
things, engages
in a series of
for-profit activities,
such as genome
sequencing, in which it
competes with other market
actors and generates revenues.
We've got a little clip
here of Broad's CRISPR CAS-9
propaganda, to use
Yarden's formulation.
I think that's enough probably.
The key point is here
the tone of voice.
That tone of voice is an
emblem of the corporate, right?
It's an embodiment.
You could watch the
whole thing, and you'd
get a better picture of it.
But it's an embodiment of this
idea of corporate structure.
And the CRISPR fight--
and here's our observation
on the CRISPR fight--
it's not only that
it's propaganda.
As we agree with Yarden, it's
that a major scientific fight
is being fought out not
primarily, or solely, at least,
over who will win the Nobel--
the Berkeley group or
the MIT Harvard group--
but over who will
win the patent fight.
And the press is equally or more
interested in the patent fight,
and so are the scientists.
So this is a picture
in which the rewards
for successful scientific
action have changed.
The Nobel desire is still there.
We're not denying
that it's still there.
But it's accompanied
by, and to some extent,
being supplanted by a fight for
winning what will essentially
be a business race
over patenting
and then licensing
of the patents.
OK, so now we come to
what we're both, I think,
more excited by
than the story we
gave you so far,
which is the question
of epistemological
virtues and what this
does to conceptions of science.
And I just want to note
that that is connected
not only to the political
economy story we're telling,
but also to the shift from
physics as the kind of model
of the hierarchical highest
good form of science
with the epistemic virtues
of explanation and law
like the Lagrangian
accounts, towards biology
and in particular,
big data biology
with its epistemic tendency
towards prediction,
and intervention,
and engineering.
So let me turn the
floor over to Peter
and start talking about that.
PETER GALISON: Well, in
the history of philosophy,
or at least, Anglo
American philosophy,
there's an important
moment where,
for instance, Nancy Cartwright,
among others, began to say back
in the 80s in how
the laws of physics
lie that we've been
wrong to emphasize
the scientificity
of explanation.
But that's not really
what was important in,
indeed, definitional science.
What really made a
difference was prediction.
But more than that, in
the spirit that we've
been referring to
epistemic virtues,
something that's
interesting me a lot,
for example, in
the collaboration
with Lorraine Gaston over
objectivity, and precision,
and pedagogical utility,
that these don't pull
in the same direction often.
And just as in ethics,
where conflicting virtues
is the rule, not the exception,
in philosophy of science,
it was often taken
that if you could--
one virtue, you
would get them all.
It was more accurate.
It was more precise.
It was more pedagogical.
It was more predictive.
It was more explanatory.
It was more fundamental.
And what Nancy Cartwright
said was, no, that's not true.
That in fact, if you push
on the fundamental laws
of, say, Newton or Maxwell,
you can't build a radio.
You can't design a rocket.
You can't do all the
things we want to do
and that the predictive side of
the scientific, technological
emphasis was really
what mattered.
Now this has taken a new turn
and in a way, much more severe
and I think more troubling
in the present moment
when you see, for example,
people saying if we can predict
something with AI or other
neural networks piled
on top of one another,
that then that was enough.
And I think both of us see
that as having its locus in,
for instance, neuroscience,
and genomics, proteomics,
sequencing problems,
this whole range
where young researchers are
just used-- that's what they do.
And they're not that
interested in sorting out
fundamental explanation
because they
want to get on to the
next prediction that
might lead to new drug
developments, or therapeutics,
or other things.
NOAH FELDMAN: The extreme
epistemological example
of that is the genome wide
association studies sometimes
optimistically described, albeit
simplistically, as hypothesis
free, where you've got
your genomic sequences.
You run it through the
most sophisticated,
statistical machine
learning tools,
and you find your associations
and whatever those are.
Of course, you have to
maintain a high degree
of statistical
significance to avoid
it being data mining,
which is what it is.
And then you test it
as to whether it works.
So I want to be clear, we're
not saying that that's bad.
We're identifying it as
something that directs you
towards the questions--
the tool that directs you
towards the questions
the tool can solve,
which might be potentially
drug identification.
It seems like Yarden is
skeptical about whether it's
capable of doing that.
But imagine that it is, and it's
certainly the way it's seen.
That's one way to
make the intervention.
And then notice
one further point.
It's also what
makes you the money.
And here, we're not talking
about the little consulting
money on the side of the
mid-20th century scientist
who does some
consulting for Raytheon,
or even the pretty good
money of someone who
leaves the university
to start a company
to make something that the
government will then buy.
We're talking here about
the outsized startup wealth
that Steve Shapin points out is
contiguous with doing the kind
of work that we're focused on.
PETER GALISON: And then
there's a back reaction.
Even it's not as if
there's an island of, say,
physics or other parts
of fundamental science,
or astronomy, or astrophysics
that's exempt from this.
You begin to see astrophysical
sorting out of galaxies.
The different kinds of galaxies
is increasingly deferred to AI.
Or you see the massive data
that comes out of the CERN Large
Hadron Collider being approached
by these deep learning
algorithms, or making images
which are famously used
and contentiously used, for
instance, in facial recognition
and surveillance technologies
that have been much debated
both in China and in Europe
and the United States.
Those are also used
to try to make images
of astrophysical phenomena.
So there's a tremendous--
these sorts of big data,
petabyte scale data, inserted
into these layered neural
networks with an
emphasis on prediction
classification, rather
than explanatory structures
is something that's
begun to move outside
of one particular branch.
NOAH FELDMAN: And if one
thinks of the scientific self--
just to go back to these three
categories that Peter began
with--
the scientific self
here, you might sort of
think of George Church
as a good example.
He's been redefining himself
for more than a decade
now as a genome engineer.
His talks are about
how analyzing genomes
isn't very interesting.
Making genomes is
the thing to do.
That is the way of the future.
In that picture,
the various strands
we're talking about
very much come together.
It's a making an
intervention model.
It's simultaneously
a model of not only
metaphorical entrepreneurship,
but literal entrepreneurship
in which he's got two or
three startup companies
running at the same time.
And it's also a how can I
make the world a better place
through my intervention.
Now, we're not criticizing.
I don't think any of
those three things
in the sense that making
the world a better place is
an attractive life aspiration.
But it is notably
different from I'm
seeking to explain the
fundamental laws of nature,
which might or might not make
the world a better place.
It's a more directly
interventive picture
of the scientific self.
It's a more activist picture.
And our point is it's totally
consonant with the idea
of the entrepreneur.
And one thing we've
struggled with a little bit
is how much of this
ideological picture that we're
talking about in the context
of the scientific self
be seen as derivative
of economic interests.
Neither of us wants to have
a very crude view, according
to which the way you're going
to make money definitively
determines what you think.
But as I've said to Peter,
when you're literally
talking about someone who
is working in his or her lab
on a project sanctioned
by the university, which
simultaneously could make said
person billions of dollars,
it's not some large
stretch of ideology
to imagine that that may affect
the way the person thinks
about his or her daily praxis.
PETER GALISON: So there's
a larger question here
that haunts all discussions
of neoliberalism.
Etienne Balibar has written
very interestingly about this.
How does one think
about the complex
of forces of what might
resist this neoliberal moment?
How do we think
about nationalism?
How do we think
about alliances--
strategic alliances,
essential alliances?
What are the politics?
I mean, it's not certainly--
we're not in a
position to simply wish
this neoliberal
configuration that's
much wider than the sciences
away simply by not liking it.
But rather, it may be
the kind of attentiveness
to the contingencies and the
choices that are made, not just
from the outside that
reshape the university,
but from the way
the universities
are structured
themselves that I think
demands our attentive
and critical assessment.
NOAH FELDMAN: Yeah, and
just to come close--
I guess, we're close
to closing on that--
many of the proposals
with respect, for example,
to AI's real world
effects when there
is concern in the
general public run
in the direction of
strong state regulation
to prohibit various
manifestations of a technology.
That's often the
instinctive response.
Maybe that's an
appropriate answer.
And it may very well
be the only answer
in certain concrete spaces.
Certainly, the structure
we're talking about
is great enough
and powerful enough
that it's unlikely to
be blocked by anything
other than interventive
state regulation.
On the other hand, that
interventive regulation
we have to recall would
still be controlled
by whatever political
forces captured the state.
And there is a
tendency to imagine,
I think among people who
are thinking of forms
of resistance, that in
their perfect scenario,
they and their viewpoint
captures the state.
And having done so, they
get the outcomes they wish.
But an equally likely
outcome is the outcome
in China, where the
state is already
actively interventive
in all of these things,
happily uses the
forms of technology,
for example, in facial
recognition, which
is going to soon be completely
universal, within China,
operates through
state-owned enterprises.
So firms that are quasi
public and quasi private,
but they, nevertheless,
achieve these things.
And that's the scenario
that is at least as likely.
And so, the hope for
state regulation,
at the end of some
public action period,
just needs to be taken, I
think, with a grain of salt
and interrogated with respect
to what the possible outcomes
might look like.
They're not all
the utopian ones.
So I mean, just
a closing thought
on the politics of this,
they're very complicated.
We're trying not to be
nostalgic for the state-run Cold
War-driven nuclear
funding of the Cold War.
We're trying not to be techno
utopians, saying that this
is where it's all going.
You can hear from
our presentation
we don't tend very
strongly in that direction.
But that is a genre that's
out there, especially
among the scientific
entrepreneur actors.
We want to identify
these phenomena
and call them out in
order to able to be
able to be critical about them.
But we don't think that there's
some obvious or simple set
of fixes, whether
regulatory or technological,
that would reverse
what is, in many ways,
at least in our view, a
manifestation of science that's
very much affected by bigger
political and economic trends
out there in the world.
PETER GALISON: I
had just one comment
on that is sometimes you
have the option of doing
something or doing nothing.
The idea that we could
go back to massive state
funding of science in its
medical, technological,
scientific components
is not going to happen.
I mean, the withdrawal
from state small asset
and state big asset of
funding in the United States
to both state and
private universities
has been a hugely
important force
in creating the
situation where people
want to have
laboratories that have
a dual identity of
corporate and academic.
So I think that these--
and you see that--
I mean, we focused almost
entirely on the United States.
But you see these,
as Noah mentioned,
in China and also in many
parts of European universities.
I mean, when I give talks,
people say, oh yes, let me
show you the laboratory.
It's just like what
happens in America.
This laboratory is supported
by Oréal and we're making
nanospheres.
Why are you making that?
Well, because Oréal wants
it for their sun cream.
And I think that there
is a way in which there's
no day pass from
these sorts of forces.
We are in the midst and need
to figure out where we've been
and where we want to head.
[APPLAUSE]
LUKAS RIEPPEL: Thank you.
We have plenty of time to talk.
And I would propose
that we spend
half hour, 35 minutes talking
about these presentations.
And then, very naturally, segue
into more general conversation
about the last two
days, if it happens.
Questions?
AUDIENCE: OK, this is a
question for Peter and Noah,
although it perhaps also
touches the subject discussed
by Yarden.
I don't want to
divert the discussion
from the very contemporary
and very urgent
political and epistemological
issues that you're raising,
but I ask the permission
to ask a question, which
is more limited, is more
a question of history
of ideas and philosophy.
I have no doubt that what
you have been describing--
I don't know if
it's a revolution,
but it's certainly a dramatic
evolution in the social status
of science, scientific
agents or workers,
which does not only
articulate institution
research, institutions'
labs, for example,
and business structures,
but also in fact,
essentially impacts the
activity of the scientists
themselves, the
scientific community.
And therefore,
inevitably transforms
the very idea of science, which
works as their guide or ideal.
So that certainly is--
and you gave a
kind of chronology
with emblematic moments
and even pictures.
So this being said, what I
am wondering of suggesting
is that the great
dilemma with which you
are ending between an idea of
science, which is essentially
linked to the search
for explanation,
and therefore, as its
ideal has and nourishes,
so to speak, the
hope of reaching
ever more fundamental
and more universal types
of explanations, what the old
times called laws of nature.
So the opposition
between that type
and what you describe as a
scientific activity for which
prediction and then, of
course, applications is
the essential value, let's say.
So I wonder if this
is not something
that, in fact, already
existed and was thematized,
or if not as a conflict,
at least as a tension.
I wouldn't say with the very
beginnings of modern science,
but I would say with the moment
with the Industrial Revolution.
I mean, with the moment in
which an organic articulation
of science and technology
becomes obvious and central
and works in both direction.
And since I don't want
to be very, very long--
I'm just sorry this is
parochial once again.
But I'd remind us that the
central method, the formula
around which the founder
of positivism, that
is, Auguste Comte, founded
his philosophy of science,
was the following formula.
So it's the French translation.
Science generates prediction.
Prediction generates action.
So maybe this is a
little too linear
to give an account of
what you are describing,
but nevertheless, I mean, the
central idea of positivism
is clearly the idea that
the search for explanation
is a metaphysical
kind of interest,
which would fall under the
critique of Nietzsche very,
very easily.
And the rational and
positive aspect of science
is the search for prediction.
So I couldn't help
thinking of that
not only because it's my
intellectual training,
et cetera, but because I am sure
that a fundamental change has
occurred.
But it would be tempting to
tell the story as something
like the tension was there
for a very long time.
And finally, we see the
victory of prediction oriented
scientific activity over
explanatory oriented
scientific activity, unless
this is too simple dichotomy.
PETER GALISON: I
would say I think it's
a very interesting comment.
And I think that there are two
distinctions that are important
here.
One goes back certainly you see
between Descartes and Newton.
when Newton made his theory,
many of the Cartesians
who followed Descartes
said, but you're not
explaining why gravity works.
You simply give us this role
of M1 times M2 over r squared.
It's not explanatory.
AUDIENCE: Fundamental.
NOAH FELDMAN: Yeah,
that's where he's going.
PETER GALISON: And that tension
between explanation prediction
is certainly something that
comes through over time.
Then there's this a separate
issue around positivism,
anti-positivism, which seems to
me intellectually historically
distinct, but overlapping.
And what's distinct about
it is that it wasn't as
if Descartes' vortices
were observable.
They wouldn't meet the standard
of a rigorously Kantian
scientist.
But in the history of
positivism, anti-positivism,
that's been
something that's also
worked through the sciences.
In recent times
since World War II,
there was a big battle
between east coast
and the west coast
between California
and the east coast
of United States
over what the nature of
fundamental physics was.
Should you just say what
goes in what goes out,
or should you have an
account of all the fields
all the way down?
And that was the
battle with Weinberg
on one side and other people
and Steve Chu on the other.
So I think that this
idea-- both of them
wanted prediction, but
under different conditions.
So I think there's the
prediction explanatory tension,
which I agree.
It goes back a long way.
And then there's the positivism
anti-positivism, which
also goes back a long way.
And then there's the question
of what's happened recently.
And there, I think
quantity becomes quality.
And as Amazon, and Alphabet,
and Google, and all these places
are putting billions of
dollars into this research,
it transforms
everything around them.
It transforms the university.
It's transformed Silicon Valley.
It's transformed Stanford.
It's transforming Cambridge,
England and the whole--
so I think that's something
where the ideas have a--
I think I would take these two
tracks in the history of ideas,
positivism and anti-postiivism,
and prediction explanation,
but then see, this
whole thing exploded
into a scale that was
unimaginable generation ago.
AUDIENCE: [INAUDIBLE]
Would you say
that [INAUDIBLE] plus
artifical intelligence in fact
has changed not
only the practice,
but the idea of prediction?
PETER GALISON: I
think it's changing.
Yes, I do.
I think it's changing the
sort of accepted epistemology,
not without contestation,
not without battles
that are being fought,
each of these disciplines.
But yes, I think growing up now,
if you're a 22-year-old coming
out of university and going
into your graduate studies,
you see the landscape of what
scientific work is differently
than, say, somebody
who was 42 or 62.
NOAH FELDMAN: And I just
would, as a footnote.
I don't think we think that
this is a definitive victory
for this side.
It's just an episode.
But it's a significant
episode, in which
this particular epistemic
virtue of prediction is playing,
I think, a very,
very heavy role.
And I would just
add that it's also,
it's contiguous with the
way that market ideology
thinks about future
oriented decision making.
I'm not saying
it's caused by it.
But it's contiguous
with it and parallel
to it, because it's
the way you think when
you have a startup company.
So the same exact undertaking
that leads you to use
genomics to predict
drug discovery,
then you put out to the market.
And then you say to the market
there is some probability
that I'm going to
successfully discover
a drug which is going to work.
And then the
market, on the basis
of that same measure
of probability,
invests in your company.
And then you become
spectacularly wealthy.
And again, I don't mean
a few extra dollars.
I mean spectacularly wealthy.
And that has some impact on the
way the ideology of the praxis,
I think, develops.
AUDIENCE: If I
[INAUDIBLE] talk to yours,
it seems as if the [INAUDIBLE]
descriptor right now
is fudging.
You wouldn't say that the
economic motivation spurs
a certain way of looking--
a certain-- or favors
a certain [INAUDIBLE]
or a certain way of
looking at things.
So looking for what the
application would be
is a major factor, when
before, if it happens, fine.
If not, fine.
NOAH FELDMAN: I mean, I'm
trying not to fudge it.
As I said, I do believe
that if you're someone--
and I'm in my 40s.
If you're in your 40s, and
you have your first big lab,
and you're doing
your first work,
I think your success
as a scientist,
your cultural capital, your
success as a scientist today,
certainly in a Harvard
medical world--
Yarden, you can disagree
if you disagree--
is it's identical
as to whether you
will have a highly
successful company
or whether you will make
important scientific findings.
Theirs are now overlapping.
To have the one is
to have the other.
And almost nobody
is seen as having
only important
scientific findings that
made him or her famous without
a company that goes with it.
So yes, I think that they're--
but what I meant
about contiguity
is that the structure
of prediction
is parallel in
some important way,
but as between the prediction
of a scientific outcome
and the prediction of--
and that's what I
meant by contiguity.
AUDIENCE: Yeah, but
that doesn't answer
the question about motivation.
NOAH FELDMAN: Well, why can't
it be-- so my informants
tell me that they
get up every morning,
and they go to the
lab to do good science
and find things out.
And they would
like to be famous,
and they know that
the way to be famous
is also simultaneously
to be rich,
and they would like to be both.
And that seems like a defensible
account of their motivations
to me.
I think they both want to
make scientific outcomes,
and they want to make
the world a better place.
They do want to make the
world a better place.
They want drugs that
will affect lots
of people in an improving way.
And also, they would like
to be rich as a consequence.
I think that seems
comprehensible to me.
And it doesn't seem
inherently contradictory.
I have no reason not to
believe them when they
say those are their motives.
AUDIENCE: [INAUDIBLE] This
is kind of a false belief.
The flip side of
the question is,
is this new sort of
corporatized university,
or the university
half of the equation,
essential to what's
going on here, right?
So clearly-- and you've
argued over and over again.
I believe you.
The making money part
of this is central.
Is the sort of
doing good science
in a kind of being famous
sports sort of way, which
is the sort of so-called old
way of thinking about this,
is the fact that this is a dual
sort of thing a central aspect
of what you're talking about?
Or is it just this mode
of transition where--
or another way to ask
it, what function is
the university serving in
this new model you're seeing?
Is it a matter of education?
Is it a matter of prestige?
Is it a matter of a sort
of state-sponsored breeding
ground for ideas that
can be harvested?
PETER GALISON: So I think we see
there are a number of actors.
It's not just
venture capitalists.
It's also big pharma.
It's not just universities.
It's also these university
affiliated research centers
like the Broad.
I mean, the Broad
is not a university.
It has ties to MIT and to
Harvard, but it isn't--
it isn't under--
AUDIENCE: A direct
function of those ties.
PETER GALISON: Yes,
and I think then
the Broad, or the
universities, more generally,
are also actors in this.
And what are their motivations?
So one of the motivations
is also to make money.
It may not be because they
want to get rich the way--
I don't think
institutions should
be seen as replicates
of individuals,
as if they have a
psychology the same way.
But with withdrawn
other sources of income,
like federal grants, or
donations, or whatever it is,
they want to recover
that in other ways,
and maybe for completely
laudable reasons,
maybe for venal reasons, but
maybe for prestige, maybe
to run their scholarship
program, maybe
to keep their humanities
departments open,
maybe to retain their
professors so that they don't
get completely devastated by
recruitment to Amazon, Google,
Alphabet, and so on.
So I think that the
motivations are complex,
and the universities,
because of Bayh-Dole
and the subsequent legislation
that's followed onto that,
are themselves
actors in this space.
And whether they're
essential, how
well they'll do 20
years from now--
I mean, I know at
Stanford, they used
to be able to take the cultural
capital of being Stanford
and bring in anybody
they wanted in this area.
But now they can't.
There are people that
are down the street who
are making $1.5, $2
million in the AI sections.
Stanford can't hire them.
So I think that
it's complicated.
They're in both a supportive
relationship with Silicon
Valley and with the
AI industries in China
and elsewhere, but they're
also competing with them.
And how that plays out
in the long run, or even
the medium run, even in
10 years, I don't know.
AUDIENCE: [INAUDIBLE]
YARDEN KATZ: Yeah, just
a minor comment about,
if I understood your
question correctly,
was about what's the role
of the universities in this
or why are they in the equation?
AUDIENCE: Well, is this
a transitional phase,
or is there something about this
other institution-- you know,
so the [INAUDIBLE].
Don't trust the [INAUDIBLE].
Not that one should
trust [INAUDIBLE] either,
but it's still funny there
is this other institution.
Oh, sorry.
It is funny that there is
this other institution that
seems to be kind of central to
the political episteme you're
describing.
But its function seems
less clear in the way
you're describing it.
LUKAS RIEPPEL: Do you
want to say anything?
Go ahead.
YARDEN KATZ: Yeah, so I think
there's a very concrete role
the university is playing now.
And I think you can see it
with something like the Broad
Institute.
I mean, full disclosure, I was a
postdoc at the Broad Institute,
so I know that place.
It is, but it isn't tied with
the university, as Peter said.
But let's focus on
the way that it is.
All the people at the Broad
Institute who are leading labs
are faculty members
at Harvard or MIT.
Graduate students come in
from those graduate programs
and work there, and
they might do work that
ends up being in a startup.
So what's cheaper, paying
someone in biotech world
or having a graduate student?
I think the answer is clear.
And I think there
is another flow.
There's a flow
going where things
get worked on in
academia that are ignored
by the corporate sector,
and then many decades later,
get picked up.
I think CRISPR is
a classic example.
Some of the Spanish
biologists who
worked on detecting originally
in the genomics literature,
detecting these CRISPR
sequences in the genome,
wrote papers that
nobody cared about.
And they weren't highly
cited or whatever.
And there's a series of
these discoveries that
needed to happen for
something like CRISPR
to get so corporatized.
And I think the people
who are the leading
scientific entrepreneurs
understand that.
So for example, Eric Lander,
who is the director of the Broad
Institute, wrote an op-ed in
the Washington Post with Eric
Schmidt, the CEO of Google,
saying we need to save
the miracle machine--
miracle machine being the
state sponsor of science.
And they said miracle machine
is critical for medicines
and armaments.
That was their phrase.
So this is a funny
configuration, right?
You have the CEO of this
corporate academic hybrid,
Eric Lander, working with
the CEO of Google to say,
let's save the state
sponsor of science.
That's weird, and to
me, that's an indication
that the state sponsor is
itself acting in accordance
with a kind of market logic.
But sometimes you'll get a
grant from the NSF or the NIH
to work with a biotech company.
So there isn't
really a distinction
between state funding
and corporate funding
in that sense.
Just because one is
funded by tax dollars
doesn't mean that much.
NOAH FELDMAN: Just to follow
sympathetically to that,
I think the bottom answer
is yes, the university is
absolutely essential
to this picture.
Not that you couldn't do
without the university,
but it would be
much more expensive.
So from each of the
actor's perspectives,
from the perspective of the
corporations or the future not
yet existing startups,
the best thing to do--
so the perspective of
the capital itself,
embodied in actual people,
venture capitalists who sit
on the capital and decide
where to assign it--
from their perspective,
the best thing
is for scientists
in universities
to apply for government
funding, for them
to be allowed by Bayh-Dole to
then effectively start startups
inside with the
research that they've
done inside the university.
None of this has
cost the VCs a penny.
And when they have an idea
that is potentially of value
to capital, then
capital comes in,
chooses the ideas that
are best of the many ideas
that are out there, rewards all
concerned, and everyone gains.
And the universities
certainly gain,
and they gain somewhat in
money, because they're usually
silent partners.
But they mostly
gain in prestige.
It's tremendous prestige value,
and let's make no mistake
that especially for the
University of Stanford
or Harvard, which already
has vast amounts of money,
the cultural value, the
capital value of prestige
is, I think, in these
contexts as or more
important than the money
they actually walk away with.
This is also a rich
get richer story,
where those universities can
maintain and vastly expand
their dominance over other
research institutions
by accruing the scientists
who will go there in order
to do the research in order
to get the money in order
to win the prizes and
start the companies.
YARDEN KATZ: Just to
add one minor thing
to that, that's why I think--
speaking to your
point about prestige,
that's why places like
Google and Microsoft
fund academic
researchers, not just
people on the technical
science side, but also
social scientists.
And I think they keep
funding them for this reason.
AUDIENCE: I have
three [INAUDIBLE]..
So Yarden, I'm in deep, deep,
deep solidarity with your talk,
and I agree with pretty much
everything that you've said.
But I'm going to ask a
cranky question anyway.
Well, some cranky,
but again, it's
a crankiness with some
of your interlocutors
rather than with you--
and it's a tedious
point-- which is
I'm wondering whether
the neoliberal university
that Wendy Brown, Phil Mirowski,
Moten, and Harney, and so
on talk about, is not the
American neoliberal university,
right?
In that, I mean, the university
is a space of refuge,
not a space of enlightenment.
I am in solidarity with it,
but it's a deeply bothered
solidarity because I
come from a country
where now in the last two
years, students have been
arrested from their dorm rooms.
Progressive faculty have been
targeted in very specific ways,
ranging from cutting their
paycheck to legal action.
And the university
vice chancellor
has been assassinated
for being a nationalist.
So refuge looks
pretty good to me
because I'm seeing
a country where
the university isn't a space of
refuge, anything [INAUDIBLE],,
right?
And this isn't a rationalization
for neoliberalism,
and no, I'm not saying that
neoliberal universities are
bad, but it's better.
That's not where
I'm going with it.
But also in terms of
thinking about privilege,
for instance, right,
absolutely we're
dealing with a privileged
space when we're talking
about the American university.
But I've been wrestling for a
few months with a provocation
that an Indian biologist
interlocutor made
to me, which is he asked me,
how do you account for the fact
that in crude terms,
a majority of faculty
at American universities
tend to be more politically
progressive than the population
at large, scientists included,
whereas a majority of faculty
at Indian universities,
especially
scientists, tend to be
more conservative than the
population at large, right?
And there are many,
many complex answers
to that, including also
the different structure
of the university and so on.
But you're dealing in
India with a university
that's not neoliberal.
And one of the big reasons
there is cost, right?
So again, I mean, the
neoliberal university is awful,
but the [INAUDIBLE] university
is kind of really awful, too,
right?
And then I'm thinking
about what it
would mean to think about
the American university not
as a neoliberal university--
what is it called?
[INAUDIBLE] university and
whether they're the same thing
or slightly different.
And I'm thinking of corporation
in the very formal sense
that Thorstein Veblen
describes the corporation
as a formal coalition
of ownership.
So I'm thinking that
it's the first thing that
happened when I came into this
room was me signing a consent
form for video recordings.
And on the one hand, this
is an ethical acknowledgment
of my free will to be recorded,
but on the other hand, what I'm
signing are the rights to
the use of my recordings
over to a private
corporate entity, right?
And I'm thinking about--
and I'm perfectly happy
to do that because I
don't see anything that's
threatening to my stead.
But I'm thinking
about what that means
in the context of
a few weeks ago.
I was with friends
and comrades of mine,
none of whom threatened
the Indian state,
but were at the
memorial gathering
for a comrade who had
died a few years ago.
And suddenly, all of them were
starting their presentations
by saying, I could
be arrested for being
an open Maoist for saying this.
Right?
And so what does
it mean to think
then about the entanglements
between a corporatized
university where
property, in some sense--
and it's in these
authoritarian times, when
sort of work discourse and so
on can travel in ways that I
was happy to sign that form, but
many people who are my friends,
now it's in their interest to be
very, very controlled about who
gets to hear what they say when
on and on what terms, right?
So I guess where I'm
going with this is saying,
yes, the neoliberal university
and yes, the violence
of the neoliberal university.
But it seems like
the university today
is a violent space in
multiple kinds of ways,
and that inhabiting
the university
and developing a
politics towards it
might involve also thinking
in really specific ways
about the different kinds of
violences that we inhabit.
YARDEN KATZ: So I have
a couple of thoughts.
I'll be quick.
First, I wouldn't put
Moten and Harney definitely
not in the same with
Brown and Mirowski.
And I wouldn't put Brown and
Mirowski together either.
But I just want to emphasize.
I mean, the first part of their
phrase is it cannot be denied
that the university
is a place of refuge.
So I think they would be
in agreement with you,
but I think what they're
inviting us to not do
is not to fall prey to this
liberal discourse of defending
the university, which we hear a
lot of, or a call for a return
to a kind of state
sponsored utopian science.
So I don't really see a tension.
I mean, the reason I'm talking
about this or the reason
why I chose this
concept is because I
think the university is
worth deep engagement with.
I wouldn't engage that
way with Google or Uber
for very obvious reasons.
To your second point
about diversity and people
in universities,
depending on the place,
being more or less
progressive, I
think it's a tricky one
because if you spend
time in business
schools or law schools,
it's a different story.
I think this rhetoric
of this narrative
that people in academia in
the US are more progressive,
I think, really breaks down.
There's the neoliberal
progressive discourse
of diversity, but that's
a different thing.
A case that's been
on my mind recently
is actually the investment
of Harvard and MIT
in wind and weapons
manufacturing companies
like Raytheon and
Lockheed Martin,
as they're making the bombs
to demolish Yemen them
hosting bin Salman, greeting
him as a progressive and so on.
So yes, they'll say nice things
about we need sanctuary cities.
But then they do that.
So I'm not sure that's--
yeah, so I think it's
a complicated one.
To your point about corporate
versus neoliberal and Veblen,
I love Veblen.
I love his text
on the memorandum
on the American university.
And it's from 1918, that book.
And there's been a series of
articles that go back to Veblen
and say isn't this a critique
of the university that
could have been written
yesterday, but it's from 1918.
And he's talking about the
kind of business invocation
of the university and
business leaders coming in.
And so in that sense, I
totally agree with you.
And with Veblen--
Veblen didn't use
the term neoliberal
because it wasn't really
coined in that sense then.
And what he's describing
is something different.
He's describing a kind of
business corporate culture.
And that's why I would
shy away from the term
like neoliberal science
or neoliberal university
because I think it's
only one piece of a very
complicated puzzle.
Yeah, so just to go
back to something
I mentioned, I talked about
the NIH quantifying return
on investment, for instance.
And they use this growth
rhetoric from economics.
And you can say that's a
different kind of thinking
from the purely neoliberal
market as information
processing style of thinking
associated with Hayek.
So there are all
these contradictions.
There are multiple economic
and corporate discourses.
So just saying it's just
a neoliberal university
doesn't cut it.
So I agree with you.
Finally, to your point
about entanglements,
I agree with you.
I don't have much to add.
Sorry for taking so long.
PETER GALISON: But I
think that it's always
important to remind ourselves
about the heterogeneity
of the situations that we
face in universities even
within the United
States, if we were
talking about these questions
of the Broad and so on.
I mean, two days ago, I was
giving a talk at UMass Lowell,
and some of the people
said, our students
are wondering whether
they can get out
of living in their cars.
Our students are worried
about whether they're
going to make it through the
winter, or their families
where there's meth dependence
or opioid dependence.
The situation of the community
colleges in the United States
and para faculty,
and the difference
between state universities
and prestigious parts
of the State University system
and the non-prestigious parts
of the State University system.
I've talked to
people in Milwaukee,
and they say they look at
University of Wisconsin Madison
as if it was a foreign planet.
And I think that's true within
Europe and within other parts
of the world, too, whether
different places in Africa
or different places within
Central and South America.
And historically, when
I teach my students
about 19th century,
or even pre-World War
II, or the rise of Nazism
in Germany, and I say,
well, the students
in 1930s in Germany
were among the leaders
of enthusiastic backing
for Nazism.
They go, really?
We thought university students
would have been on the left.
And there were some,
of course, but doctors,
the so-called liberal
professions in pre
'33 and shortly after
post '33 Germany--
these were elite institutions.
And the elite more or
less made their peace.
So I think that the idea
that university students
or university faculty are
bastions of progressivism
is a thought that's almost
unformulatable before, say,
1963, '64.
It just wouldn't have made
sense to people before then.
Europe, 6%, roughly speaking,
in the richer parts of Europe,
18-year-olds went to
university, up through the 70s.
Now it's in the 40s.
But that's a gigantic
transformation.
So I think that your point
is deep and important
for us always to
remind ourselves
about when we talk
about the university,
we're talking about a
lot of different things.
There are 500,000 or 600,000
faculty members in the United
States, but they're
not faculty members
like at well-heeled state
or private universities.
And the same is true for in
Western Europe or in England.
The difference between
Oxford, Cambridge and the poor
and everybody else, and then
between the upper levels
like Manchester of the red
brick universities and the lower
level technical universities.
So I think these are important
to remind ourselves about
and that we are talking about--
in our talk, we're mainly
talking about, like,
the people who are involved
in the atomic bomb project.
Well, yeah, I mean,
there were thousands
of people involved in it, but
there were tens of thousands
of people who were
not involved in it.
So I think that we have
to be aware of that,
but we can also see what these
transformations have done to--
YARDEN KATZ: Sorry,
I can add one thing?
This is the answer I should
have given you, which is,
this is why I tried to focus--
maybe it was too quick--
focus on commoning
and the commons,
and this focus on creating local
spaces within the university.
And I think it's important
to do that first of all
because as I tried to
argue, these big theories,
like the neoliberal market
or whatever, they blind us
to seeing these acts that exist,
the little places of refuge
in the university or what
Moten and Harney would call the
under commons.
So I think it's important
to do it for that reason.
But also because I don't want
to get in this argument about,
is it the neoliberal university
or the corporate university?
I have no stake in that debate.
I don't want to contribute
to making neoliberal science
a more coherent term that it
takes underneath its umbrella
more of the phenomena.
I just don't want to talk
about it in some sense.
So commoning and
the commons for me
do the work of giving
you a different cross
section through the phenomena.
AUDIENCE: Thank you all for
the wonderful presentations.
I have a question
which I hope will
connect the different parts
of the discussion today.
And that's with one
of your statements
that you said the
physics biology is now
the main science.
So my question is to do with
the impact of the biologization
of science in relation to
ancestry discourses in relation
to identity in the present.
And I have in mind DNA research
and also archaeogenetics,
as an archaeologist.
And I have in mind also you're
in Harvard's recent book
by one of your colleagues
called Who We Are
and Where We're Coming
From on the basis
of archaeogenetics data.
So that's an area that we
haven't discussed so far,
and I think is
crucial for all of us
and the majority of
people on the table.
I was wondering what are your
thoughts in relation to this.
NOAH FELDMAN: So I'll
say something about it.
I just read the book,
and I know, right?
So I think there's a couple
of points where it absolutely
confirms what you're describing.
How many people around the
room have read this book
or heard of the book?
Yeah, a few?
Basically, it's
self popularizing
by a professor of genetics at
Harvard Medical School, David
Reich, whose lab has been at
the forefront of the ancient DNA
project, which is primarily
of historical orientation.
It's moved away.
His lab has moved
away from the research
program of seeking to do a
genetic analysis to treat
disease.
They haven't given up
on it, but that's not
their research project.
Their research project
is now broader questions
of human history, primarily
through the extraction
of DNA from ancient bones
found at multiple sites
around the world.
So in one sense, it
captures the phenomenon
that we're talking about.
It's biological.
It's necessarily driven
by computer technologies.
It's highly statisticalized.
And the main value added
is not from the technology
of extracting the
DNA from the bone.
So that's an important input.
Without improvements in that,
they can't do the input.
But the output is really
driven by sophisticated use
of machine learning.
So the book is written
in a tone of triumph
from the standpoint of what DNA
analysis can do, relative to--
he does say in association
with archeology, history,
and anthropology.
But a consistent and recurrent
theme throughout the book
is this is a
revolution-- his word.
And we can do things that could
never have been done before.
And we can therefore recover in
some sense factually-- again,
his word--
an account of the past that
wasn't present previously.
Intensely criticized,
unsurprisingly,
by primarily cultural
anthropologists
and very much I think of
the moment with respect
to these things.
It is, as it were,
the pure humanities
analog of the big genomics,
where the money is.
Here, it's not money,
but it is prestige.
And there is money in
the 23 and Me version
of this, which he
interestingly condemns and is
uninterested in
because he thinks
it oversimplifies and isn't
very scientifically interesting.
I would just say it also shows
you the book's reception.
It also shows you that
there is some vulnerability
to these discourses.
I mean, he's in a deep polemical
struggle right now with Native
American groups, whom he spends
a whole chapter engaging with
not successfully, very
much talking past them,
with the industry side of
it, which 23 and Me is a big
successful business and
not coincidentally started
by the ex-wife of one of
the founders of Google--
just to show the complex
interplay of these things.
And they're not
so happy with him.
But the kind of
triumphalism of biology
as queen of the sciences, not
all dissimilar from the way
those of us in social
science have encountered
economics over the last
25 years, or the way
that social psychology
was in the 60s
and 70s and its early
70s in its heyday.
This is a kind of game of who
wins that is very familiar,
and of the moment and
will certainly not last
indefinitely.
But I think it is very
emblematic of what
you're describing.
AUDIENCE: [INAUDIBLE]
What do we do
about the very disappointing
reports of western scientists
wagging their finger at the
Chinese geneticists trying
to engineer the fetus
of twins, so it would
have an immune system to HIV.
But that was--
I'm sorry, I suppose
you consider me western,
but that was just, as
I say, disappointing.
NOAH FELDMAN: Which way
are you disappointed by?
The research or the criticism?
AUDIENCE: The criticism.
NOAH FELDMAN: In what way
were you disappointed?
AUDIENCE: I would encourage
such practice by--
I suppose why he has
all of China behind him.
But I think he's
done a good thing.
NOAH FELDMAN: [INAUDIBLE]
I wrote something
about this very brief,
but just a short piece.
And I'll just tell you.
I think the view that
you're expressing
might, over time, come to be
a more broadly expressed view.
At present, I think
it's not the view
of most people in the
scientific community who
are very concerned about
the ethics from two angles.
One, they're worried
about off target effects.
That is to say, this was
a CRISPR technology model.
When you do gene
editing, there's
still not scientific
certainty about the long term
consequences for other
parts of the genome.
And once you've done it,
it's in the germ line.
So there's a kind
of worry about that.
That, I think, is a kind
of empirical problem.
Over time, if people keep
breaking the ethical norms
and doing this, we're
going to find out
about the off target effects.
And if they turn out not to be
so bad, as some in the field
expect, then that concern
will begin to go away.
If they turn out to be bad,
that will become major.
The second is the worry about
so-called designer babies,
which is the main line
in the ethics literature.
And there, again, I think
the field is pretty divided.
There are some
people who say this
isn't going to be a
serious worry because most
of the traits that people
are interested in selecting
for in their designer
babies are going to turn out
to be determined by so many
single nucleotide polymorphisms
that it will, at least
in the medium term,
be too difficult to
CRISPRize them all.
But then others in the George
Church school would say,
it's not a problem.
We can do 600,000 snips and
eventually be able to do this.
If that's the right view,
then there will be serious
long run ethical concerns about
the consequences for society
of people, outside of ethical
norms, designing fetuses.
And I would just add that
the Chinese government is not
happy with him.
And he may be a folk
hero to some in China.
But that wouldn't surprise me.
But the Chinese
scientific community
has also condemned him.
Last, but not least, it's not
clear whether he really did it.
The guy said he did
it, so it remains
to be seen whether
he actually did it.
YARDEN KATZ: So there's a
lot to say about this one.
I'll just say one thing.
I think that elite
American scientists
have been laying the groundwork
for this kind of thing
to happen.
So you had people like George
Church saying, for years,
CRISPR has no off
target effects at all.
It's a perfect tool.
And people were
saying it'll never
induce a response
from the immune system
when you deliver
it to a patient.
And both of those things
turned out to be not true.
And I think that the Chinese
case and the reason why
it's featured so
much is that it lays
the groundwork for an American
version of this project,
which is going to be,
quote, unquote, "ethical."
Like, look what the
bad Chinese did.
We're going to do
it, but we're going
to do it better with the help
of professional ethicists.
Like, George Church has
a professional ethicist
in his lab, who's
on his payroll.
So I think-- and also George
Church was quoted in one
of the articles about
this as saying--
his quote was, I
looked at the raw data,
and it looks real to me.
And I think that
phrase, the raw data,
doesn't make any sense here.
But to me, that's just
another indication
that they're laying
the groundwork for this
to be an American
practice, which
is going to be distinguished
from the bad Chinese practice.
There are many issues
with this project.
There's the stigma of AIDS
in China and why would
you want to do this anyway.
There's the genetic
determinism underneath all
of this CRISPR discourse,
is if you mutate
one nucleotide or
delete one gene,
then you will get the
phenotype you want.
It's operating under this
horrible genetic determinism
that we know doesn't work.
Yeah.
AUDIENCE: It's just wonderful.
I have a few remarks.
About motivation,
you were concerned
about the motivation of the
scientist to do this or that.
And I think this is
a displaced concern.
The question is not what
motivates a young scientist
student--
fame, or wealth,
or something else.
The question is, what
is his or her options,
if he does not want
fame or wealth?
At what cost?
He could pursue another
goal, like [INAUDIBLE],,
something like this.
Would it be encouraged?
Can he stay in the lab?
I think this is the point.
There is a new structure
that constrains
the options, the choices
of the young scientist.
So this is one.
Then you said, Noah, you said
at one point, everyone gains.
Of course, I guess you meant
everyone in the room gains.
NOAH FELDMAN: Yeah, I
didn't mean in the world.
AUDIENCE: Yeah, no, I know.
I just want to take it farther.
So clearly, everyone in the
room gains at the expense
of so many others--
extreme unequal
distribution of [INAUDIBLE]..
You know.
I don't have to tell you.
But what you said
about, I wanted
to connect this with
the anecdote that you
[INAUDIBLE] about these two
people from Broad and Google
signing this paper together.
So they are actually giving us
the reason why the university
should exist at this time.
University is actually
the mechanism,
the apparatus that
helps to channel money
from the state to the business.
So it is important that the
university would remain,
so we can pay very little
money to do the work for us.
So it's a form of exploitation.
But in order for this
to be a university--
this is a thought.
This is a speculative
thought now.
In order for this
to be a university,
it can't just be the Broad
Institute, and this institute,
and that.
Science has to include
the humanities.
So we, the humanities,
are now what
enabled the existence of this
mechanism that channels money
from the state to
the corporation.
So we should create.
PETER GALISON: I
mean, one thought
that this provokes in me is a
very unscientific observation
that I've made at a
lot of universities,
is that the universities
can, in some ways,
serve to regulate
the relationship
between their students,
postdocs, faculty,
and the outside corporations
that want to do research there.
And the power that
they have to do that
depends to a certain degree
on the wealth and the forces
that the university commands.
If you're a poor
university, you can end up
being highly pressured.
Because as you say, choices are
never completely open, right?
We're always making choices
in a world of constraints.
And if you're a
university-- and I've
seen several universities
in Europe like that--
but they really feel as if
they have no choice, given
budgets that have been
diminished by the state
to accept whatever conditions
the outside corporations
put in.
And that can mean a whole
range of difficulties
for students and faculty.
I mean, one issue that
comes up is corporations
often want secrecy,
corporate secrecy-- not
national security secrecy,
but proprietary secrecy.
And if a student is obliged
not to disclose their research,
say, for two years, while the
company tries to make this
into a product, the student can
be left on the side of the road
as a casualty of that.
That is to say that their
research then no longer can
be published if
other people have
gone on and done similar work.
And they've simply been
obliged contractually
by the university's relationship
with the corporation
to keep the publications quiet.
This did occur in the Cold War
where, Berkeley, for instance,
had an agreement that there
were students getting physics
degrees from University
of California, Berkeley
at Lawrence Livermore Lab, who
could not publish their thesis
and the physics
department, other
than those who had Q
clearance, nuclear clearance,
could not read their theses
because they were classified.
And it led to a big revolt,
and it led to a crackdown
by the government on them.
And many of the faculty
left because they
wouldn't sign loyalty
oaths and so on in the 50s.
So I mean, I think
that we now see
a kind of corporatized version
of some of the constraints
on research that
existed in the Cold War
under very other different
national security conditions.
But I think it's now, in a
way, much more widespread.
A number of universities
that did classified research
with graduate students
and postdocs in the 1950s
is small compared to the number
of universities in Europe
and the United States--
North America, I should say--
that are under pressure
from corporations
for fiscal reasons.
I mean, so everyone is
operating under the real world
of choices, which I think is
the import of your question.
What are the real choices
that a student has?
What are the real
choices the faculty have?
What are the real choices that
the universities feel that they
have, faced with budget cuts?
Suppose your budget's cut
from the state, small s.
Do you raise fees, or do
you get corporate donations?
If you get raised fees,
you diminish the diversity
of your incoming students.
If you take
corporate money, what
are the conditions
that are imposed?
It's tough.
And I don't have some sort
of blanket solutionism here.
I think that these are the
questions, though, that
will haunt our universities
in the coming years very much,
it seems to me.
LUKAS RIEPPEL: I see by
the little blue sheet
that our time is up.
So I invite us all
to thank our hosts.
[APPLAUSE]
