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Welcome to the Becker's Healthcare podcast. I'm Chris
Sosa, your host. I'm very happy today to
be joined by doctor Giovanni Bialimonte.
He's a professor of pediatrics, biochemistry, and molecular
biology and a researcher at Tulane University.
He also chaired his task force on the
use of AI in research, which is our
topic for our discussion today.
Doctor Bialimonte, thank you for joining us today.
Thank you for inviting me, Chris. I really
appreciate it.
Wonderful. So doctor, you've been, researching
a number of topics for better
part of thirty years now.
But for those in our audience who may
not be,
intimately familiar with yourself and your organization, could
could you please introduce yourself and let us
know a little bit about that?
Yeah. I'm a physician scientist, basically, and I've
been practicing respiratory medicine
clinically for about three decades.
And about two decades, I've been
generously funded, for my research,
in several areas,
of biology and respiratory
diseases by NIH.
I
I added also a significant component to administrative
duties over time,
serving as division chief first, the department chair
for many years.
Then I spent seven years at Cleveland Clinic
as the president of the Cleveland Clinic Children's
Hospital.
And most recently, I joined, Tulane. I worked
for six years. I served as vice president
for research.
Recently,
I stepped down for that and started my
first sabbatical in my career,
which I'm, thoroughly
enjoying.
And, the sabbatical has given me, the opportunity
to to to
evolve
new areas of research,
but also,
to,
go deeper into my ongoing interest as
now several years old,
for artificial intelligence,
quantum computing,
and advanced technologies
applied to health care that, as you know,
I'm sure everybody will agree on this. I'm
gonna completely
change the the the the landscape,
of how we
think and how we,
manage and how we deliver health care,
for many, many years.
You can say that again, doctor Bienle. There's
so much to discuss. And as I mentioned,
you chaired Tulane's task force on AI and
research.
So let's start there. So could you please
take us through simply how the task force
evolved,
which I know could take a lot of
time, but that's okay. We got time. And
just highlight the the most significant findings from
the last couple years.
Well, you know, it was a great experience
because I had the opportunity
to interact with a lot of,
brilliant minds, and most of them actually
with the little to do with health care,
including,
engineers,
mathematicians,
and the like. And so open,
several
different angles
to read,
you know, to read what the opportunities are
and what the risks are for for for
this new technology.
And,
and we wrote a blueprint that
summarizes,
some of these concept that emerged. And,
to make a a very short summary,
there is no doubt that,
the specific area that we, were interested in,
which was research,
is gonna be impacted dramatically
in any component
by by the introduction
of artificial intelligence,
already is.
I predict, and I'm a little bit radical
in this, but I predict that,
virtually every single component
of what today is the administration
management
or grants, for example, is gonna
become,
virtually independent from human input.
And the reason for this is that most
are
repetitive tasks that the computers
will do already do in some part,
with with the in a fraction of the
time,
with minimal cost
and with the incredible visibility.
For example, the preparation of a grant,
the the assembly of a grant,
the submission of a grant, the verification of
a grant,
some other functions
that
already a lot of investigators
are dealing with, but they're gonna become more
and more,
stringent. For example,
recently
in the last years, we have seen a
significant increase in the cases of
plagiarism or,
publication
of, of,
data that were not,
either accurate or completely fabricated.
And the reason for that increase is is
quite simple.
A lot of the fabrication of data
could escape at UNI, but will not escape
at the visual intelligence and computerized.
And today, there are plenty of softwares that
allow
people to actually verify
whether,
something has been,
simply,
built on somebody's imagination
or whether it's real data. So there are
millions of different aspects
that artificial intelligence
another one, for example, I do epidemiologic research
and population research.
And,
the current study that I'm running is the
first one in which we're gonna use artificial
intelligence
algorithms to analyze the data.
And, already, we're seeing a lot of,
driving,
phenomena that,
very unlikely
it's very unlikely that we could have picked
if we were just using our
brains.
So
in an extreme world, basically, I will say
that,
a lot of experiments
may become
obsolete,
because it can be can be reproduced
in digital formats,
and
and,
and therefore,
problem solved in a fraction of the time.
And so all the all those things are
great, and I expect
a significant
acceleration
in the development, for example, of,
new drugs,
of,
new therapeutics.
I suspect that one of the areas of
immediate progress,
and and substantial progress is gonna be in
robotic surgery,
which already is, is evolving and so forth.
It's gonna it's gonna be a a complete
new
word. I I a friend of mine,
sometime ago said that
to apply for, med school or law law
school today
is is stupid because by the time you
graduate,
the computers are gone and the and the
robots are gonna do
the work of doctors
and,
lawyers. It's a little bit extreme, but
the the this history of artificial intelligence
has shown us that,
things that
sound stupid, sound impossible,
become
very possible and very,
almost simple,
within years. And so
I think that definitely the new doctors and
the new lawyers are gonna
be collaborating primarily with the with the computers
and robots,
and the the the the scope and and
and the and the applications of their work
is gonna be completely,
revolutionized.
At the same time,
it was an excellent opportunity to collaborating with
my colleagues
to assess
what I think needs to be central
in the in our analysis
of, artificial intelligence
and new technologies, and that are the risks
that are associated with this, technology.
And frankly,
this is becoming a a main focus of
my of my interest.
And one of the things that we did
was we tried to categorize,
the different types of risks that are associated
with the with the the introduction of, for
example, Gen AI.
And it specified that at the time we
basically were discussing these matters,
everybody was concentrating on Gen AI.
Today,
most people concentrate on Gen AI with it
is a totally different
universe,
and and,
and, it's gonna
make most
or all of our conclusions,
irrelevant
because Genetec AI
is not just an evolution
of, Gen AI. It is a it's a
a a change,
a
drastic, complete
change in the way
we are gonna interact with the with the
with this technology.
At at the time, talking about GenAI, we
identified
the the major
types of risks as
intellectual property risk, for example, and the confidentiality
breach.
These technologies
are gonna make almost impossible to keep,
data,
confidential,
safe, and so forth, not with the current
technologies.
That is gonna create a lot of problem
for the,
respect of,
intellectual property. It's gonna create a lot of
problem
with
the attempts to block,
individuals that are trying to get into critical
databases.
And that becomes, can become very problematic
because,
I give you an example.
We know very well that there are very
large databases already in existence,
containing genomic data on on individuals.
And, and this new technology is gonna make,
are gonna make almost impossible to
keep this safe,
unless we develop a new,
very complex strategies
for, to secure those data.
Another element is the biased and the balanced
coverage.
It is true that, some people see in
AI, a democratic force that is gonna put
everybody in the same level. That that is
not
necessarily gonna happen. There is a very big
risk that,
the GI systems are trained,
on a large amount of data, and the
data is not,
heavily distributed,
does not give
a fair,
weight to all the components of society.
So that can
actually increase the risk of,
inequalities.
Another element is, the the cost.
Attention intelligence costs a lot of money, and
it's gonna break a lot of banks, and
it's gonna
be out of the reach of a lot
of people.
And one of the most critical area of
cost is gonna be energy.
It's not, by,
serendipity that,
China's,
run a very aggressive
campaign for many years to increase their ability
to have large sources of energy. Because,
this is, an incredibly
unprecedented,
unprecedented
requirement
on the,
power,
need needs,
that we had before AI.
Another one is the,
ecosystem volatility.
So in other terms,
we were used to change
and upgrade systems
every
certain number of years.
Pretty soon, we are gonna go into the
weeks.
And, a lot of technologies are evolving at
a speed that that is unprecedented.
And, therefore, that is may create problems because,
you know, you acquire a certain technology and
becomes,
deja vu within within months. So that creates,
again, a significant cost problem.
And I left for last, the one that
I think is most concerning
in terms that the more we rely on
artificial intelligence, the more we are at risk
of the so called hallucinations.
Artificial intelligence
is not perfect.
I think it's gonna become
less and less imperfect over time, but,
you understand that, you put,
a lot of vital functions of the society
and even human beings in the hands of
artificial intelligence,
you know, when you have an hallucination that
can cost
a lot, not only in terms of money,
but also in terms of of human lives.
So,
I think the the best
part of this experience was the understanding
of the very delicate balance,
very delicate balance existing between the advantages of
this technology
and the disadvantages of this technology.
And and,
again, all these considerations are gonna go on
a different scale
when,
Agentic
AI is gonna be, is gonna become more,
prevalent.
And that is gonna be Agentic AI is
gonna be the introduction
and and the need needed bridge
into,
embodied AI, which means the production robots.
Those two are the much more disruptive
potential on our society and our technologies and
our, operations
than Gen AI. Gen AI depends on us.
Gen
AI depends critically on the input of data,
on the on the programming.
The human component is still dominant
in Gen
AI. In Genetec AI,
that flips.
And that is where, I think,
that that is the reason I say that
we have not seen not even the beginning
of this revolution. When we are gonna see
the revolution,
it's gonna be when a GenTIC AI is
gonna become more sophisticated, more prevalent.
And, I have reasons to believe that 2026
is gonna be an historic year because
the 2025
was
kind
of
eventful.
It was, seemed like, you know, a a
breaking point,
but I think it was just an introduction
to what is gonna happen in 2026
and 2027
when
the technology that has been maturing over time
is gonna come to full fruition.
And at that point, really, the world is
gonna change in ways that are
in great part unpredictable.
Thank you for laying all that out, doctor.
There's so much that's exciting and scary at
the same time and really unavoidable
in terms of how AI is gonna affect
all of us, including,
health systems and health care in general.
I do wanna ask I'm curious. So
given how much you've been embedded in AI
and its research,
what would you say your comfort level is
with AI in terms of how how well
do you trust it? You mentioned hallucinations.
And and what do you think
has to happen for humans
to trust it more than they do now?
Does that make sense?
Yes. It does. It's a great question.
And,
I may surprise you, but hallucinations are not
the part of AI that scares me the
most.
The part of AI that scares me the
most is
the risk
of
skill reprogramming
and skill down regulation in humans.
And I give you an example.
I'm old enough that when
I was in school, they you know, I
became very good at
mathematics.
I didn't like it at all, but, you
know, I knew how to do,
basic calculations at least,
by end with no support.
And then we start getting the
calculators,
and then the calculators get better and better.
I don't know if today I I will
be able to run
a square root analysis
or even basic mathematical
skills.
Why? Because I don't need to.
Now if you expand that to
all the incredible
potential
of artificial intelligence
and to the knowledge that,
I don't think there are many students today
that don't rely on artificial intelligence and Gen
AI
to to do their, their their work.
I think that we risk to,
generations of people who are gonna forget how
to read, they're gonna forget how to think,
they're gonna forget how to calculate, they're gonna
forget how to
strategize,
because all those things can be done very
quickly and very easily by,
by this tool.
And so,
the the this this is a risk. In
fact, I
I'm I'm
in a very tough positions because I'm really
trying to understand all aspects,
relevant to my area of interest,
concerning AI, Gen
AI,
and and the related technologies.
But I try to use it
the the least I can,
if it makes any sense to you. Oh,
certainly. Certainly. Because
I want my brain to go keep working.
And and and and,
and,
I don't want to be in a situation
like the same way I lost my
calculations still. I think, for example, I don't
write,
my penmanship
is not the same as it was.
I don't need it.
I don't I I am afraid even that
my memory
is gonna,
be,
is gonna,
be reduced
because that's the nature of, Darwinian
systems
and evolution.
So in a world where all those things,
all the things that we do, all the
expression of our,
of our intelligence
can be achieved in a much easier way,
What is gonna be left?
That that is that is an enormous concern
that I have. Another concern is,
what this is gonna do to our workforce.
And
there is a little bit of
pride in me because, at the con at
the Baker's conference,
a couple of years back,
when everybody was
cheering,
and, we're partying and we're so excited about
all the potential of artificial intelligence,
I said, be careful because it's gonna kill
a lot of jobs.
And I I got criticized, and several of
my colleagues said, you know, you're you're being
over pessimistic.
Well, it was very interesting,
yesterday.
I follow closely
the that was,
meetings, the the
to hear that CEO, the largest
bank in the in the world,
I believe, or in The United States for
sure, that is,
Jamie,
Dimon
of j j JP JP Morgan Chase.
And Jamie
basically said exactly the same things.
Jamie, in in a nutshell, said that if
we do not I'm not very careful with
the implementation,
the launch,
the use of artificial intelligence, particularly in the
in the in the new generation of artificial
intelligence
algorithms,
we're gonna lose an enormous number of jobs,
and we have to be proactive in thinking
what these people are gonna do. For example,
in the work in the world of health
care, as I said before, the opportunities are
endless.
But when you look at any,
large health care system,
there is a certain small number or a
fairly small number of doctors.
All the rest are people that actually do
highly repetitive
tasks. You know, the doctors do highly repetitive
tasks. But Sometimes. Yeah. When you look when
you look at, for example, verification of insurance,
checking of the patients,
analysis
and submission
of the claims,
all the work
we already know can be done much, much,
faster, easier
by system that don't get sick,
and and they're very cheap.
And another thing,
that, Jamie said,
yesterday is
But, unfortunately,
this is not a a process that can
be modulated that much. Why?
Because let's assume that you are the CEO
of a of a larger care system,
and you decide
for your
principles that you don't want to get involved
with in AI,
and not in the implementation AI in your
health care system,
you're gonna be killed on a financial basis
because all your competitors are gonna leap in
front of you and achieve the same performance
or much higher performance
with much lower cost.
So,
this is not gonna stop. There is no
no no possibility of stopping this. So I
think that one of the most challenging
aspect of,
particularly, Genentech AI,
is going to be
before
we launch on very large scale these technologies,
we have to start thinking about
what to do with people.
All the people that
are going to lose their jobs. You know,
one of the things I noticed, there is
a lot of attempts. I understand
to reduce the,
how can I say, the panic?
Mhmm.
But but,
I also think that we need to be
realistic.
There are very few things
that,
robots, artificial intelligence
are not gonna be able to do.
One of the most shocking experiences as a
physician was I'm a a a respirologist,
and,
you know, for many years, I thought that
you always needed a a physician to do
a bronchoscopy, for example, any type of endoscopy.
Today, there are several systems,
that do bronchoscopies,
in a totally robotics
way,
requiring minimal,
additional effort from humans.
And, you know, it's just a matter of
time that they're gonna be completely independent.
And,
there are already,
hospitals in Japan where the entire and also
in China, where the entire staff, nursing staff,
and physician staff is made of robots.
It's just the beginning.
When you project those trends and you realize
that the technology is there,
we better be at least be ready be
ready, for example, to a world in which
humans probably are not gonna work
five days, but only,
three days a week.
If that.
And one says, well, great. I mean, the
more time for us. Yes. But then we
have to find the way to pay these
people.
And already in Europe, there are a lot
of, there's a lot of discussion about,
providing
basic salaries,
you know, from the state.
In France, for example, they have a project
like that because they already know that a
lot of people are not gonna have a
job. So and you cannot have a the
majority of the population will have a job
No. Because they get very angry. And that
is the reason of the revolutions around the
that occurred,
around the the the first industrial revolution.
But the first industrial revolution was nothing in
the present to what we are walking to.
You know, there were now machines that were
able to do the work of hundreds of
people.
Now we have computers that are gonna be
able to do the work of tens of
thousands of hundreds of thousands of people.
And you already see several companies that are
laying off,
big segments of their workforce. They are doing
it gradually.
But, again,
you just
projected this trend
forward,
realize the speed at which, artificial intelligence is
growing. When you see the difference between the
first
version of chat GPT and and the current
version of chat GPT are two completely different
words.
Then you realize that we have a significant
problem. And I am I feel a little
bit vindicated in a way that that that
CEO of the largest bank in The United
States, yes, they said exactly the same things.
And what they did what they did was
be careful.
We need to time
this process. Otherwise, we're gonna have a big,
big significant social problem in our hands,
which is gonna be very dangerous from on
a political level and a social level.
Doctor, that's all just fascinating. I mean, I
especially,
key in on a part where
so much of it comes down to how
much we're willing to give up
in terms
of thinking
and strategy.
Right? And certainly the human element is is
very important now, and we
to put it out there, I don't expect
any of us to have an answer to
this question in this moment, but we have
to decide how much of it is is
worth it. Right? So it's it's just
fascinating
and scary, and it's it's, again, still exciting
in a lot of ways.
But don't don't forget the element of greed,
though.
I I wouldn't.
It's impossible.
Again,
artificial intelligence is gonna have major financial implications.
So the risk, which is what, Jamie,
Timon said, yes.
The risk is that basically people go
looking,
go forward. They're looking exclusively at the bottom
line,
and that is gonna be devastating.
And and then I basically ended with the
with a a word of of
of
hope,
saying that humans are still gonna be relevant
and important.
There is no doubt about that, but our
many humans
are gonna be
relevant.
And he he talked also about,
reskilling.
Yeah.
And,
Chris, I'm I'm afraid that they're taking the
issue with scaling a little bit
too lightly because Yeah. It's not easy to
get a 50 year old, that has done
a certain job all his life or all
her life and basically convert it
into a Google
engineer.
And there is there is a certain For
sure. There is a certain limit. I mean,
for the new generations, maybe. But what are
you gonna do with all all those people
that
I don't think I remember one thing that,
you know, I I found very interesting.
I I was,
at the Cleveland Clinic.
I participated to the launch of, an upgrade
that, of Epic.
I remember distinctly
that a lot of the older physicians just
quit.
They said they want to to deal with
the you know? They were very comfortable with
paper charts.
Obviously,
we know that,
you know,
electronic medical record systems are much more efficient,
much I mean, enormous advantages.
But I'm old enough to remember when we
didn't have that, and, you know, a lot
of people spend most of their career. It
was a absolutely
curl a cultural shock
when when,
electronic medical systems were introduced. And, again, I
think there were a lot of problems when
the first,
EMS
were implemented.
So we have to
continue,
I think,
at least make every attempt to put the
human being at the center
because artificial intelligence,
Gen AI,
and all the
derivatives
are going to be helpful and useful only
for as much are gonna make people happier.
And so to put the humans at the
service of the machines is gonna be a
a a major strategic,
ever.
That's well said, doctor Villalemonte.
And and certainly as it relates to health
care,
you speak to any health care leader, and
they
always say that the patients and their staff
is front and center. And we have every
reason to to believe that's true. Right? I
I believe that when when they tell me
that. They they wouldn't be in this this
business, this area, this sector, otherwise. Right? So
so that is encouraging, certainly.
Lastly, doctor, I simply wanna ask you. You
are on a sabbatical now as you mentioned.
Well deserved, clearly.
But
what do you think is is next for
you? I mean, you have plenty that you
to draw on. So so what do you
look forward to doing in the next year,
five years, whatever,
time span,
you know, you you see appropriate? Well, if
I don't retire, which is supposedly,
I definitely want to continue my research. I
want definitely want to continue to do what
I've done all my life, which is taking
care of patients, which I still
enjoy for as long as the robots are
gonna allow me to.
But in terms of this particular field of
interest,
I am particularly
excited about
how these technologies
are going to,
talk to each other, how they're gonna interact.
And particularly
at the
crossroads
between artificial intelligence,
particularly agentic AI,
quantum computing
that is gonna
change
dramatically
the speed of calculation. Therefore, it's gonna increase
enormously the ability
of artificial intelligence to function.
And,
I believe clouds
that basically are gonna allow these
technologies to talk to each other.
And as you know, a lot of hybrid
clouds are are,
proprietary.
So Yeah. That's where the competition is, in
my opinion, is gonna be. Not that much
on the quantum side, not that much on
the,
Ajentic AI,
but to have the clouds,
where most of the data are gonna be
stored or all of the data, and they're
gonna be allowing this, this crosstalking.
That is where that is where I think
the competition is gonna be, and that's where
we are gonna see the most
extraordinary
manifestation
of this technological,
progress.
Again, a lot of excitement, but
but also the I think we have to
be realistic,
when this, this perfect storm is gonna is
gonna is gonna hit.
I hope that we are prepared
because
it's not gonna be the same world. It's
not gonna be the same society. It's not
gonna be the same
organization.
It's not gonna be the same culture. It's
not gonna be the same way of doing
things.
I hope the very same, doctor. Thank you
so much for bringing all your your decades
worth of challenge and
expertise and insight on on AI to our
Becker's audience today.
As I've mentioned before, we love seeing you
at conferences. I'm sure we will again.
Yeah. Enjoy your sabbatical, and,
thank you again, and until next time. Thank
you very much, Chris.