ROMETTY: So, look, good morning to everybody. Thank you for allowing IBM
to spend some time with you. I had a chance outside, there are a
number of you that are IBM clients, and so I would be remiss if I didn’t start by
just thanking you for that and thanking you for the relationship you’ve had with
us and allowing us to serve you. So, I get some time to spend today
to talk about my favorite topic here. And on one hand, I have to tell you,
those of you that know us, I mean, healthcare has been important; and I would say, even central for the purpose
of IBM for a long time. As you know, we are a big consumer, those
of you that where we’re your client, we are a big consumer of healthcare — in
fact, $2 billion a year for our employees — and we look at that as an investment in
their health, in their health and well being. We’re also a big advocate for change. Whether it was Bridges to
Excellence; or, most recently, you might have seen something called the
Health Transformation Alliance — HTA — announced with a group of companies
to promote outcomes-based healthcare. And, you know, an innovator
and a solution provider. As I said, we’ve served this
industry for decades. But I also want to talk about some
of our “moonshots,” I call them — and I’ll tell you later why
I call it “moonshots” — whether it’s our Watson for Oncology or the
work we do for Johnson & Johnson and Medtronic. I say all that all on one hand, because
on the other hand I am here today for a different reason. Not as a user, as a consumer; I am here, I hope,
to both assert and persuade you that the future of healthcare is something we call cognitive. These are systems that learn, and we
believe and I believe in my very heart that this will help transform healthcare
along with the work you’re doing. It will — and I’m going to talk about this — reinvent how you do discovery,
reimagine how you do delivery. And in the end, it will transform
the whole area of wellness. And as Merrill said, that is why, to us,
healthcare, it’s one of the industries that I have bet the future
of the IBM company on. Now, let me start, though, with…I should
describe what I mean by this “cognitive era.” So, to get some audience
interaction, let me ask you a question. How many of you would say you
either work for a digital company or your company’s becoming digital in some way? Okay. This is almost like a trick question. I mean, everywhere in the
world it is the same answer. It gives you a chance to move
and get a little bit looser here. Everywhere — it doesn’t matter
where I ask that, public, private, government, doesn’t matter. Now, this idea being digital, it’s in part
why we’ve built a set of capabilities. We’re the world’s largest…you were just
talking about big data as Merrill was, the largest leading big data analytics company. It’s why we’ve brought this idea
of cloud to the enterprise, public, private, hybrid, HIPAA compliant. It’s why we’ve done reimagining
work in a secure world with Apple and are the largest enterprise security company. But analytics, cloud, mobile. Those are all very important for you to be
part of a digital society, a digital company. But I would ask you something. When everyone’s digital, then what? What is it that will differentiate you? I always think of digital as a
foundation, but it is not the destination. And it brings me to what I believe is,
and boy, there have already been a number of transformative shifts in this industry. But I believe it is the most disruptive and the
most transformative, yet it is in front of us — and it is this world of cognitive. So, I want to start by just describing
what it is, because I would call it an era. It is a dawn of an era. And maybe simply put, think of digital business and digital intelligence put
together will give you cognitive. Now, so let me tell you there’s two reasons
why — before I get right into healthcare, two reasons why — this is truly
an era and why it’s happening now. The first one, you talk about this — and
I’ve seen your agenda for years — it’s data. But it’s data that is “visible and
invisible,” is how I would describe it. There’s endless reports and endless discussion
about the exponential growth of healthcare data. The last numbers I saw said in
2011 the amount of healthcare data in the world was 150, what
they would call exabytes. Which, for those of you that do not
know the math of exabytes easily, it is three million times all
written books in the world. Now, they say this year will end at
one zetabyte, which will 10X that — so, 30 million times everything
ever written in the world. Now, I didn’t say it was used well, okay? There’s just a lot of it. But that would be traditional data,
fits in rows, columns, tables. All right, that’s part of
what’s driving this era. But the other more interesting part
is what I call the invisible data. Some people will say big data, 80 percent
of it is what they call unstructured. So, think of that as doctors’
notes, wearables, x-rays, social media, the weather, sensors, sound. And today, systems can hold all that data
but they actually don’t know what it is. You couldn’t tell, you couldn’t
say, well, what was that movie, what was every piece of it about? Not unless somebody tagged all that data. That’s what’s changed. That invisible data will now be visible. And when you combine those together in this
profession, you know, weather, obvious things, weather influences asthma; exposure to crime has
a lot to do with your mental or physical health. And this is why we’ve put together
something called the Watson Health Cloud. We’ve done this with partners, some of
you in the room, an ecosystem out there. It is structured and unstructured data
available to you, HIPAA-compliant. And we’ve spent $4 billion of
acquiring companies to help here. Companies you may know: Phytel,
Explorys, Merge, Truven. Then, public sources: Apple
Research Kit, de-identified data. So, think of clinical, medical,
cost, quality data. Think of things like peer reviewed out of
Medline; or, think of all the different kind of therapy guidelines, tracking
of pathways that are all in there. In fact, I would tell you, I believe it’s the
largest nongovernment trove of data out there. So, one big driver now of what’s
different is this not just big data, it is visible and invisible data you can use. Now, you say, well, how can I use it? That’s the other part that has changed in
this era, and that is what I would say, you’ve got to have something different;
you couldn’t program enough systems in the world to understand that data. And that is the advent of cognitive computing. Some people shorthand this
to artificial intelligence; that would be doing it a disservice. These new systems, they work in a natural
language and they have domain knowledge. I always say they understand,
they reason and they learn. So, they form hypotheses, just
like when you’re asked a question, your brain does this very fast, forms
hypotheses based on what you know. You decide if you’re confident or not. If you are, you speak the answer; if not, you give all the reasons why you’re
not sure of what data you need to know. That’s how they work. And they never stop learning. This is the really important part: they never
stop learning, which means the earlier you start with them, the more benefits
you get out of them. And unlike most IT systems that go down in
value with time, these go up in value in time. So, this is what, in fact, you might
have seen and known as IBM Watson. We started this over a decade
ago in IBM Research. We made a choice five years ago to
debut this technology on the Jeopardy! game show. I don’t know. Does anyone watch Jeopardy!? Not watch it all the time, okay,
that would be sort of silly. But yes, okay, so. This idea, then, but boy,
has it come a long way. So, at that time, what we showed
Watson doing was question and answer. Think of that as one thing,
five technologies under it. Today, Watson does 30 things, seven
languages, 50 technologies under it. And, we’ve been teaching Watson to see. In other words, you have to
see for the medical profession. You’ve got to be able to see and
understand x-rays, images, what are they. So, healthcare was in fact
Watson’s first career choice. And he has other careers now, by
the way, but that was his first. And he has gone, long ago quit playing games, that is long ago, and he’s
through medical school. So, now I tell you that is cognitive. If you just think of it as systems that
learn, they never stop, they understand, reason and they grow with interaction. That is this new era that’s here. I can’t think of an industry more
perfect than healthcare for this… Which brings me to why I say and
I hope I’m going to persuade you, that the future of this industry will be
cognitive and that it’s even here today. You know, it’s no coincidence,
when we did Jeopardy! five years ago, the first clients that
came to us, it was doctors and scientists. They said I saw this. Don’t ask me why they’re watching Jeopardy!. [ LAUGHTER ] I saw this…taking a break. I saw this, I can apply this to what I do. And this is about augmenting what
they do, which is really important. And so we just did a study and we said, if
you knew…assume you knew the word cognitive. We asked healthcare providers…or, in a
whole ecosystem, not just even providers. We said, if you’re familiar, 81 percent
said it would be critical to the future and 95 percent said they’re going
to go ahead and start investing. Now, I got the pleasure…I was
telling someone outside here, I got the pleasure last week I spent
a day with a number of the doctors, 15 who have been training
Watson in a particular area. They’ve been at it for a couple of years. And I said, you know, why do you stay with this? So, I mean, this is…you’ve got lots…you
are specialists in your field in the world. And one of the answers I thought was
really interesting, he said, you know why? Patients will demand this. Patients will demand this. And I get calls already, I
want…because you can’t answer the question on “have you looked at everything.” Not that Watson can say he’s looked at
everything, but it is, as they said, a learned colleague and an informed second
opinion for a doctor to converse with. So, where do we see this application? I want to just give you examples in
three areas, as I said when I started. One is about how to reinvent discovery. Let me start there, because think about a system
that learns, looks at data, forms connections. What is it great at? It’s great at looking for hidden connections;
and therefore, if you could take your hypotheses and test them faster and reach conclusions, you can see the impact it could
have on discovery everywhere. So, it would be for genomic
medicine; that’s obvious. Drug discovery. Or, alternate uses for existing
drugs, repurposing. Or, almost any innovation. So, one of them I think is a compelling
example is clinical trial matching. Today, five percent of cancer patients
are in a clinical trial — only five. Those of you that deal with, you
know it’s a very complex area, very difficult to both ID
and get enrollment lined up. So, we started working with
Watson on clinical trial matching. Of course, he’s got to be trained to completely
understand everything about an EMR, labs, reports, tests, you name it, as well as
protocols, guidelines, compliance, et cetera. So, we first started with Mayo
Clinic on clinical trial matching: breast, lung, colorectal and gastral. And then most recently they’ve
gone into production, meaning for breast cancer patients
going everyone what’s the right kind of clinical trial if that’s
the path they choose. With Novartis, we’ve gone the other direction
— take something you’re trying to test and identify the people that
are a good match for it. So, you could see how you could
really have a breakthrough here, because it would be the faster you
can enroll, the faster you can close, perhaps the faster you can
bring something into practice. Another example, different disease. We just announced last week work with Pfizer. And you’ll see a theme here. We are not alone in any of this. This is about an ecosystem. We believe we’ll do our part. But as I heard Merrill’s opening comments,
this was, you talked about competing, different groups, that isn’t the future
we envision; we envision an ecosystem of people working together and
we see it already happening. So, this is work with Pfizer on Parkinson. And as I said last week, so what we’re doing
is collecting the data on sensors, mobile, machine learning, real time, so you can
understand the progression of the disease and therefore it will speed the
development of new therapies. So, that’s reinvent in how you do
discovery, which I could go on with examples but I think you sort of see the feeling on this. The next, and I think perhaps
maybe the most exciting of all three, is how to reimagine delivery. So, better connections between
a doctor and a patient. But value-based outcomes, which
I know everyone is working on, as well as extending how healthcare is delivered
beyond traditional kind of walls and borders, which is obvious with cloud and mobile. And then, personalized treatments. So, best example is Watson for
Oncology here that we have been leading. And as widely reported we began that work with
Memorial Sloan Kettering, the Cancer Center, which, we started feeding Watson
every known piece of data to man, which he’s ingested on this topic. And integrated all the latest research; and in
fact, it’s had decades of longitudinal data. And up to now in just one or two forms
of cancer, 15,000 hours of training by the best oncologists in the world. So, how does it actually work? If I can maybe share that,
maybe it will resonate here and you can sort of see where else it could go. So, what Watson first does is it
analyzes a patient’s medical record, which has structured and
unstructured data in it. So, things that fit nicely in rows
and columns but things that do not. Next is, it identifies treatment plans. That would be with clinical
experience, external research. And I’ll come to more of the
data he uses in a second. And it will look for, what do I know
enough, do I not, percent confidence, not, what more tests do you need to run. And it will rate and rank the treatment
options, with supporting evidence, because a doctor doesn’t want a black box. It’s, tell me why, why do you believe
something, and then I can make my own judgments. And the corpus of information Watson’s
using, well, first off is that 14,000 hours of curated data from Memorial Sloan
Kettering, 300 medical publications, 200 textbooks, 12 million pages of text. I mean, you’ve got to remember,
he does not forget. You know, the medical students,
they fall asleep. You know, this does not happen
with Watson, okay? As long as there’s electricity
he does not fall asleep. So, this idea has really now come to
fruition, so around the world being deployed. Bumrungrad, you might not know them. They’re the largest private
medical care facility in Thailand. They see over a million patients a year. They are now rolling it out; and
in fact, the doctors will tell you that it is making their practice
much, much easier. Manipal Hospitals, India’s largest private. They will treat 200,000 people with cancer
— not patients; just with cancer alone. And they’re at an inflection
point in India on cancer. I mean, the rate is growing much
faster than there are oncologists here. And their CEO says that it will take
cancer care to a whole new level in India. Two weeks ago, four big cities in China. In fact we’re now to the point
even within MSK themselves — one of the best facilities in the world —
they’re saying they’re going to deploy now with their fellows and take
it to 12 more cancers. So, you’ve got the work that’s been informed
by cancer by Cleveland Clinic, by MD Anderson, and the list goes on, not
just Memorial Sloan Kettering. So, we think we’ll do, like I say, our little
part here to help change how delivery happens. And I get the pleasure today to make
an announcement around part of this, because that’s through the eyes of a doctor. Today we’re going to announce a partnership
with the American Cancer Society, and it is to do the Watson
Patient Advisor for Cancer. So, it’s to understand the needs through
the eyes of patient with different cancers at different stages in different
treatment plans. And it’s about guidance: guidance on
symptoms, on support, on wellness activities that you can take, on education that’s out here. Now, eventually we will also integrate this
with Watson for Oncology that a doctor uses. But this is what it’s all about, and
so you’ll see it through both sides. And so, Gary’s going to join me right after this
and we’ll talk a little bit more about this. So, just completely changing
how you do delivery. And by the way, it’s not all cancer. We just happened to take the most
difficult thing to start with. But take as an example the
work with Johnson & Johnson on healthy knees and more joints, too, coming. But it’s how to manage that end to end. Okay. Then the third area is to transform wellness,
because you can have a learning system. And this is where I really see a big
ecosystem developing, because Watson lives in the cloud so it’s accessible to everyone. And it will spur innovation that comes
from existing companies and startups. And you see this everywhere. So, one of the first is UnderArmour. Anybody have some sort of tracker
on their wrist in this room? Let’s see. Aha, the people in the front, because they
walked further to get a few extra steps. This is… [ LAUGHTER ] It’s amazing how some people, that
changes behavior, and some, you know, they’re like, that’s interesting. Okay, so, now… [ LAUGHTER ] But for many, it is about improving performance. Underarmor has the records of 160 million users and they’ve been doing an
app to be just like me. So, in fact, I have the UnderArmour app. You, too, by the way. It has trended many times as the
number one app in the app store. So, whether or not you use their band…I
feel like I’m doing a commercial for them. Or, your Fitbit or whatever it is,
because Fitbit’s also very good, but you can download this
app and Watson will be there. So, we’ve just started. We’re ramping up. I like to share my favorite piece
of advice I got from Watson, was that if I would walk 2,000 more steps a
day my waist would be a half inch smaller. Okay? So, okay, don’t laugh, I don’t know why you’re
laughing, but that is not a really good reason. But that’s the idea — suggestions
that apply to you personally. There’s also, by the way, they
say in their database most women like me sleep seven hours a night. I’m like, yes, well, that’s very funny
that’s not going to happen either, so. But that’s the idea of what’s coming. Now, we also did work, speaking
of sleep, and it’s just beginning with the American Sleep Apnea Association
as well there’s an app now done with Apple Research just completed. Because as you know, apnea, those that know
that disease, it influences a much broader range of other things, like heart disease,
hypertension, obesity, cancer. Quite a list, as well as,
obviously, motor crashes and the like when you’re driving your car. So, what this is this is an app
that both collects biometric data, pushes surveys, test your alertness. Now, what we’re creating already is a huge
trove of data open to researchers everywhere to then apply really wonderful
analytics to understand what to do. I’d also put in this idea of a big
ecosystem in wellness, Medtronic, the work we’re doing around diabetes. And we had our first already
medical breakthrough. Working together monitoring glucose real
time, they’ve been able to predict the onset of a hypoglycemic event three hours in advance. Now, three hours in advance,
you can do something about it. Never done that far in advance. So, you get this idea. So, I clearly see you can reinvent
everything around discovery, reimagine delivery and then transform wellness. Now, I think there’s also
things every one of us can do. So, before I close, let me just share with you
something we’re announcing today in our company as a great idea, because I think there
are many things that people do to help in individual areas, but something
that would transcend all these themes and help what I call reach
the last mile in healthcare. We’re announcing something called the IBM
Health Corps, C-O-R-P-S, Health Corps. This is modeled off of what
we have been widely recognized for something called the Corporate Service
Corps, which was modeled off the Peace Corps. And thousands of IBMers have gone to
thousands of communities around the world over the last decade, but they focused on
doing work to help them with an economic or an environmental issue in a community. Well, we’re going to change that program. We’re now going to focus it entirely on helping
them increase access to care around the world and the underlying related
you may have obviously social, environmental factors that underpin that. That could be water, transportation,
food safety and the like. But every team will have a new teammate. And who do you think that might be? Watson will be on the team. Now, we’ve done two pilots,
really interesting already. We’ve done a U.K. pilot in one of
their bureaus and it was on obesity and on early mortality as a result. And Watson has ingested all of the field
notes, the caregivers, all of their notes and has in fact designed
fitness solutions for many. A different example was South
Africa, we worked for a nonprofit, the African Health Placements Group. Now, as I said, they’re a nonprofit in
Johannesburg and they have a lot to do with hiring people that give
care in the last mile. In this case, we worked with them
on a better app to hire people who would do a better job faster
so you get to people sooner. And then, here in D.C., for those of you from
D.C., we will very soon, in fact next month, start a project with Unity Healthcare. And they, by the way, are the largest
health center that is in this country. Half their patients are on depression,
anxiety, behavioral health issues. And this is a blueprint that integrates
behavioral health with primary care. And then, in fact, it’s the ground work
for how to have effective treatments and interventions and reduced cost there. Now, obviously what Watson does, and I just
want you to think a moment on this whole idea and our reach and the span we’re going to get — because remember, you don’t
program it; it learns. So, just like he’s learned on oncology,
think about the lessons he’s going to absorb from the front line of healthcare here. Individual communities. It will be a repository of community health
learning that I think the world has not seen. It will be global in everywhere that it’s from. So, let me kind of wrap my sort
of introduction to this morning with just a couple of other points with you. One is that, you know, Merrill
you said it in the introduction. Healthcare is dramatically…has the
opportunity to dramatically change. We understand something about dramatic change. Our own industry is dramatically changing. But we also understand something about
the promise of this precise moment. This industry has very talented people,
very committed to patients’ lives. And that is a commitment that we share. This is why we have invested in Watson Health and it’s why we’ve declared
it as one of our moonshots. And I will tell you we also believe
that this idea of this cognitive era, these systems that learn, it will drive
this industry to value and outcomes based. It will enable personalized treatment,
and it will allow collectively the ability to tackle some of the greatest challenges
that our world has seen in healthcare. And at the same time, because
of these attributes, it will inspire a whole nother generation
of entrepreneurs in the healthcare field. So, I tell you, no one can do it alone. I said it when I started; we believe very much
this is about an ecosystem working together. So, we’ve taken a different approach. It is about an open ecosystem. And when I say “open,” it’s standards based. That means it’s regulatory compliant,
it’s cloud based, open to all. And that is in fact why we’re
excited to join you here today. So, I thank you for your time and I look
forward to do a little bit of Q&A here, and I look forward to what
we’ll accomplish together. So, thank you. [ APPLAUSE ] Merrill, what…just get off
the stage for a second there. I’m going to introduce him properly. Okay? So, let me introduce both of them first. He’s sort of jumping on the gun here. But Gary Reedy, who is as you would
think the…as you would think? As you would expect, I made this big
announcement, the American Cancer Society, the CEO of the American Cancer Society. All of you know them. It is about their mission to eradicate cancer. And I should tell you — I’ve spent time — great tenacity and grace for
this very important project. And I should say he served as the volunteer, as
the chair of the volunteer board of directors as well and on many different
commissions on this topic. And then you met a second ago, but Merrill
you didn’t introduce yourself, did you? I missed, oh, just a teeny bit. Merrill Goozner, who is the editor
of Modern Healthcare Magazine. Thirty years a journalist,
if you didn’t know that, and with the Chicago Tribune
he’s the economic correspondent. NYU, he is the Professor of
Journalism there and the author of the $800 Million Pill,
the Truth Behind New Drugs. So, let me now bring up my
two friends here for the Q&A. [ APPLAUSE ] GOOZNER: Thank you, Ginni. ROMETTY: Yes, give you a
little bit of introduction there. [ APPLAUSE ] Thank you, my friend. All right, let’s… GOOZNER: Thanks so much… ROMETTY: Ooh, geez. [ LAUGHTER ] ROMETTY: Didn’t try that earlier. GOOZNER: Thanks so much for
that really interesting talk. You know, we’re here to talk a
little bit about the partnership that you two have formed and announced today. Nothing is scarier in healthcare
than getting a diagnosis of cancer. Gary, tell us, this idea of a patient
advisor, okay, why is that important and how does this fit into
all the other partnerships that the American Cancer Society has formed
with groups around the country over the years? REEDY: Yes, thanks, Merrill. I’ll tell you, you know, the American Cancer
Society will be 103 years old next month. And for that… ROMETTY: So, you looked for someone older? REEDY: Well, that’s right, 105, right. ROMETTY: That’s right. REEDY: So, you know, during that whole time
we’ve been leading the fight against cancer. And collectively, to Ginni’s point,
we’ve made incredible progress. The mortality rates in the last two
decades have dropped about 22, 23 percent. But the issue is, is this year
there will be 1.6 million Americans who will receive that diagnosis of cancer. Now, when you receive that
diagnosis, your reality changes and you immediately start searching for
reliable, trustworthy, credible sources of data. And the American Cancer Society is
seen as a reliable source of data. As a matter of fact, in 2015, we had 1.2 million
people call our 24/7, 365 hotline number. We had 30,000 chats and we had
@@110 visits to our website. So, there are people out there
looking for reliable information. The nice thing about this partnership is
now it’s going to become personalized, because with IBM, we’re creating an
advisor for cancer patients, for survivors and for caregivers that will
deliver personalized information and guidance when and where they need it. So, the advisor will be able to anticipate
what the needs of different patients are — patients with different types of
cancers, at different stages of cancer and at different times in treatment. And so for an example, let’s say
that there’s a breast cancer patient who is experiencing unusual levels of pain. She could ask the advisor
what’s causing the pain. And she would receive personalized
information on both symptoms and self-treatment options based upon the
experience of other patients like her. So, the advisor will be looking at
the data, massive sources of data from both ACS and from IBM Health. The great thing about the
advisor is it’s dynamic. So, it becomes much more personalized
the more that people engage with it. And if you will, it becomes smarter
each time it’s asked the question. So, to Ginni’s earlier point, this is so
critical for patients when they’re faced with that diagnosis, to feel like they do have
a source where they can go get reliable data. But now this is data that’s somewhat
personalized based upon the experiences of other patients. GOOZNER: Ginni, if I’m hearing that properly,
he’s really talking about turning cancer care into a learning system —
and you used that phrase. IBM is obviously bringing a lot to bear to this
with Watson and the technologies that you have. Let me just step back from
all of that for a second. Why healthcare and why cancer within healthcare? These are the toughest nuts to crack in terms
of taking information and translating it. You’re a very big company. You’ve got your fingers in every pot. So, why healthcare? Why cancer care within healthcare? ROMETTY: Yes. This is, you know, I go back
and think about IBM’s history. And so when we just mentioned 105 versus
103, but you learn a lot in that timeframe. And I would say we have got not only
just a track record, but it is… You know, when people say, what is your mission? You know, to an IBMer they’ll
say “it is to be essential.” And that means, you can’t
call yourself essential; only the world or others can call you that. And if you look at some of the things we’ve
done, there’s the little bit of the history about why I call this our moonshot. You go back in time, IBM’s had the chance to
participate in what were at those moments some of the most complex things
ever done in the world. And so, it’s in the DNA and that when it was the
first censuses to be performed around the world. The second thing was, you know, I
still get goosebumps when I look at the photos of landing the man on the moon. If you look in the control room, you will
see many shirts with IBM…many chairs with shirts on them that say IBM on them. So, it is this bit of the company
that is all about grand challenges and this has been one, and this is one. And this is one I think that we’re not alone. Others have been done alone, right? This will be done in partnership
that we’ll be able to do. And to do those grand challenges, you
really do have to have an understanding of really complex systems and how they work. I mean, that is at the heart
of what we do understand. So, this track record, this
ability to understand how to operate in by the way, regulatory environments. You have many different complexities
in this health world that you have to know how to work on. And then, of course, obviously
the amount of data, the complexity of the system that is there. But I would say one more thing, and I
think this is actually quite important as everyone decides who to work with. We believe strongly this should
be a win-win proposition — that data has to be handled properly. In many cases, when it’s obviously a patient, anonymized appropriately
— or even with a company. The future for everybody in this
room is going to be around data. And therefore, our belief is we will curate
and bring you some data, put it in our cloud. You bring some of yours. What you get with our analytics
and your own, that is your finding. That is your economic benefit. And therefore I say it’s a win-win. This is not about bring us
information, thank you, we’ll take it and we’ll get the economic value out of it. This is about both of us
having a win-win proposition. And I believe we’re one of the only
ones out there that have that viewpoint. And I think that will spur the
innovation that will happen. And I think you can see it already in the number
of clients that I listed of what we’re working on together, because they can see
how we can both have a win-win, because the basis of every
company in this world… I mean, you know, years ago I would
say that information will be the basis of competitive advantage
for every company out there. And sort of coin that phrase, it will
be the world’s next natural resource, where there’s a lot of it but
value will only accrue to people who actually go ahead and know how to refine it. And you see this with oil, you have countries
that have the most oil are the poorest. And so, it’s a matter of knowing what to do with
it, and that’s why I think it will be relevant to not just healthcare, by the
way; every single one out there. GOOZNER: Gary, as we think about the
American Cancer Society over the years, there’s been such a huge emphasis on prevention. Otis Brawley, your chief medical officer,
a man I’ve interviewed many times, this is one of his big, let’s not
forget about prevention in all this. Yet when we hear about the moonshot against
cancer, Vice President Biden, you know, the terrible tragedy in his family with cancer. We often hear through the
media — my industry — seems like the miracle cures or how
do we advance treatments and cures. How does this all fit in, information
fit into the prevention side of things? REEDY: Yes, I think, you
know, it’s a great question. One of the things that really excites me
that we really need to get the word out and help people understand is individuals
can reduce their risk of getting cancer by 50 to 60 percent just by individual
choices that they make. So, I think when you can apply cognitive
learning to everything that we know, you know, both physicians will be able to
identify patients who are at higher risk of getting cancer and take the
appropriate course of action. For patients who already have cancer,
they’ll be able to identify their risk of developing other types of cancer. So, I think the way that you can use, I
mean, there’s so much big data out there now in healthcare as both you and Ginni said,
and it’s continuing to grow exponentially. But to thank goodness we have the technologies
now that we can analyze and look at that data and pull out all these little findings we
haven’t seen in the past to where that we can, I think, have greater impact going forward,
both not only in providing treatment, but also providing insights on
what we can actually do to prevent. And like Ginni mentioned, maybe we’ll all
get messages from Watson saying, okay, you need to do this today or do
that tomorrow if you really want to realize that 56 to 60 percent reduction. ROMETTY: This is an interesting point, because
you know, as you know well and as was just said, that the point is not destiny
that you will have this. It isn’t your genetics alone that position you
for this; it’s everything else that happens. But that is the most difficult thing to manage,
and it’s true whether it’s cancer or diabetes. It’s what happens in that, as I know
with Medtronic, we always talk about, what happens in that 90 days
between doctor visits, right? REEDY: Right. ROMETTY: …that’s really influencing things. And that’s why I think you’re going to
see this advent of all these other kinds of wellness ideas that people have. But they’ve got to be made simple, otherwise people will be
overwhelmed with this information. And it’s also why you need this
era; you’ll be overwhelmed instead. So, it’s going to go through some ups and
downs to get there, but it has the chance of personalizing it so that overwhelm…because
you can go out today and look on the Internet and find endless articles
on cancer and what to do. But the issue is it’s endless,
and that’s the problem. It needs to be targeted. GOOZNER: So, as you ingest all this
information from patients, from physicians, it’s in the headlines almost every day
now, we’re seeing huge security leaks. And nothing is more precious than information
about your own healthcare and the fear that it may get into the wrong hands. Ginni, what do we do to protect
this information as you take it in? How do you reassure the general
public that this is not something that they actually need to be afraid of? ROMETTY: Yes, look, I think
that’s a serious topic and not one that you can just dismiss
and say, nah, no worries. That is not what it is. And this would be another reason
why I feel we’re at the right time and the right moment to help in this industry. Our history is airlines, banks,
everyone that’s had personal information and had to have it protected. I always say, you know, we do 90 percent of all
the airlines in the worlds; banks in the world. Actually 70 percent of all critical
information goes through us in some way. So, you have to look at security
at different levels. You protect an infrastructure,
applications, data. And privacy is always the point, and again,
the most simple point on privacy is people have to make choice, which this
industry understands well. You have to consent or not to how
information will be used and in what way. And my best sort of analogy to leave you with on this topic is that…and I
actually think it comes from this industry in other pieces of how to think of it. I say it’s like an immune system. If you want to think about privacy and security
in this industry it’s like an immune system. It’s advanced to, you can’t
just put walls and borders around information and think it’s protected. How does your immune system work? You know there are bad things inside. It is inevitable that this will happen. Something will go wrong with information. So, the way an immune system works, if something
goes bad, your immune system goes to it and tries to block off any further
harm to any other part of your body. That’s in fact how modern day security systems
are going to work, and that’s why they, too, are around big data and Analytics
constantly looking for things that are not quite right,
projecting what it could be. And that from your industry and this
industry will be projected on to security. And things like, you know, again,
you know well, epidemiology. You know well things like the world…why
was the World Health Organization and the CDC formed? When something went wrong
those organizations are to confine the outbreak going somewhere else. All those same approaches apply to
the area of privacy and security. GOOZNER: Let’s switch gears a little bit. I want to talk a little bit
about precision medicine. This is the gee-whiz aspect of this. This is the research and development side. You know, we talk about big data and all the
information we’re getting about genomics. And we’ve made some progress, and the majority
of drugs that now come out of the Food and Drug Administration that are targeted at
cancer are what are called targeted medicines. In other words, we’ve learned a
lot about the mechanisms of cancer, the cellular processes in cancer. This is really a 30-, 40-year effort going
back to the original moonshot against cancer that President Nixon announced back in 1971. And we’ve invested huge amounts of government
money in researching the mechanisms of cancer, and now we’re actually being
able to use some of this. Do you see precision medicine
as being the magic bullet; or, is this something where we actually are going to
have to have companies working together in order to have multiple targets with multiple
drugs, which really turns cancer more into a long-term manageable disease, rather than
that sort of…the “moonshot” sort of conjures up the magic bullet, and which
are we talking about here? REEDY: Yes, well, I’ll tell you, I think…I
mean, I can’t think of a more exciting time to be involved in the cancer
fight because of what’s happening from a precision medicine perspective. And to your point, it’s really
we’re seeing the results of over 40 years of work getting to this point. But today to be able to analyze which
genes are actually mutating and then to hopefully have a therapy that
you can target to that mutation that will stop the cancer
from advancing is terrific. I think that going forward the big
challenge, to answer your question, I don’t think that precision
medicine is the magic bullet, but I think it’s getting us towards that time
when we can look at cancer as a chronic disease. But I totally agree with Ginni and actually
what you’re suggesting is that to get to that point we all are going to have to
collaborate together and work together. You know, I think from a scientific perspective, one of the biggest challenges right
now is looking at the cancer cell where there may be multiple molecular
targets and then trying to decide how to design clinical trials with either new
drugs or current drugs to attack those targets. And to do that, that’s going to take a lot
of companies working together to get there. I think once we’re able to do that, then
we can actually start talking about cancer and most cancers becoming more
of a chronic-type disease. So, I think we’re well on our way, but to get
it across the finish line we’re definitely going to have to collaborate and work
together to make that happen. GOOZNER: There may be folks in this audience that follow the medical literature
pretty closely. For those of you who do, you know there’s a
big debate about information staying in silos and not getting access to clinical trial data. Ginni, how does IBM Watson
overcome that barrier? We’re talking about precision medicine. We’re talking about ingesting
huge amounts of data. We have a lot of silos out there and people
are storing their data in those silos and they have a lot of reasons not to let it go. How are you going to overcome that challenge? ROMETTY: Yes, well, that has a
lot to do with my point earlier about a win-win proposition here and why
people would be willing to share it — because it’s not just patients;
I mean, it’s organizations that had this information in different places. And if you make that a win-win —
which I think we’re well on our way to doing that — that will help here. But you know, I go back to what we
just said here and that the fact that precision…it is not a
silver bullet, because honestly, when you said people have multiple different
mutations, this is not a black and white answer. It will never be a black and white answer. And that’s why I always say,
and you need these new systems that will do and deal with the gray area. In fact, that’s kind of one of my favorite
ways to describe something like a Watson — that it isn’t dealing with black and
white, Q&A; it’s dealing with issues that have, that it’s a gray area. There’s not a right and wrong answer always. And it could have to do with your own beliefs. It could have to do with
what you want to experience in a treatment, what you’re willing to do. Do you care if you lose your hair, or you don’t? You know, many things people have views about. And what I think this allows people
to do is to have that choice. And if they see the value for that,
they will then allow that information from a personal basis to be shared. And then, individually companies that have
different pieces of it will therefore contribute because they get something of
value in turn for themselves. So this is not a winner takes all, as
you’ve seen in industries right now. It is not a winner takes all. It will be about value accruing
to all different parts of the value chain, most
importantly to the patient. And therefore, you know, I was thinking, you
mentioned different cancers, breast cancers. One in eight women will get breast cancer. But there are…this audience
will know better than I. I can’t remember if the number is 400 or
800 therapies that could be out there. How do you do that kind of matching
without this, without this kind of help? Otherwise you’re relying on the
experience of which great doctors but no human could really deal with that. I mean, and that’s why I think we’re seeing
with even the best in the world starting to say, you know, I think I actually need help, too,
because I can’t remember, even I’m an expert, everything that there is out there. GOOZNER: Our time is almost up. You know, I would be remiss,
I’m a journalist, right, and so we’re in an industry
that’s undergoing an incredible… ROMETTY: Are you going to give us
a “gotcha” question or something? GOOZNER: No. No, I was about to just simply say, we’re in
an industry that’s undergoing tremendous change because of the…you know,
everybody is in the digital space now and we are definitely in the digital space. Healthcare, we work closely with
CEOs at our magazine and our website. We talk to them all the time. Healthcare people will tell you we
are undergoing tremendous change. Information technology industries,
your industry is undergoing change. Ginni, I would like to hear
you talk as a last comment, what is it like to be…what does it take to
be a leader in times of tremendous change? What’s the most important
traits you have to have? ROMETTY: Yes. This is something I’ve both
learned, experienced many times. I say when you’re 105, and
even in my time I’ve gone through probably three major eras within IBM. And a couple thoughts come to my mind, and I
think they transcend any industry, actually. So, your industry, for one, but
it’s everyone’s industry, right? Every industry, you can make
a disrupter in right now. And as I always say to the teams, my first two,
you know, don’t…do not protect your past. And I think that that is, if
you really internalize what that means, you’ll take different actions. Do not protect your past and don’t
define yourself as a product. If you define yourself as a
product versus a solution, it will confine what you do into the future. But perhaps the most relevant that I think
of in a venue like this, particularly, is something I learned from someone else. And then, of course, I searched where he
learned it from, and I found it was Napoleon. But so… [ LAUGHTER ] …it goes back way in time. And it was, he always said, you know, a job of a leader in these times
is to paint reality but give hope. And I think that that’s very relevant here,
it is to paint reality and give hope — because I think there’s a reality
of the industry and where it’s at and you mentioned the inhibitors. But it is about this very clear vision. And more than just hope, this very clear future
that you described and are moving towards that is, it’s really there
within the years to come. It’s not overnight; it’s in the years to come. And I think the most important thing
we can do is stay focused, all of us, on that role to both paint
reality but give hope. And people will move towards that. GOOZNER: Fascinating. As editor of a newsroom, I’m going to
remember that: paint reality but give hope. Let’s give a warm round of applause
to our two speakers this morning. [ APPLAUSE ] Ginni Rometty, the CEO of IBM; Gary Reedy,
the CEO of the American Cancer Society. Thanks so much. [ APPLAUSE ]