Read Transcript EXPAND
When you took over in 2012 it was mainly thought of as a big iron company making big old computers and since you've taken over that's down to about 10 percent of what IBM does. So tell me what you move the company into and why.
I always say people you don't always see us but you do rely on us because we operate almost 100 percent of the banks in the world. The airlines 70 percent of all the business data comes right through us.
We've had to reinvent herself era to era.
And arguably this has been the most extensive but this era it's been about how do you refashion a company all around data.
Are you worried about government regulation of data ownership.
I think the most important words entered jumps in my mind.
It's funny not regulation first.
So why do I not drown out worried or worry.
The tech industry is quite capable of being so self regulating itself it puts its mind to it.
Do you feel that your competitors in Silicon Valley are doing as good of a job.
I think every company's got to step up to this or there will be regulation.
We don't want.
All right. And so and that's why I say the word responsibility comes to my mind.
Do you think that some of the tech companies in Silicon Valley Facebook and Twitter and all are causing a backlash on trust.
Hey looked with the builders of this stuff.
We believe the purpose of it it's to help man do a better job augment.
Mankind. I don't mean that as men or women it's to augment what man does versus purpose.
Because if you believe that you will build certain things and you won't build other things ownership of data.
So whether people have trust as well.
Wait a second you have to give you my data.
Do you own my data.
And even more important than a data is when you train in artificial intelligence it's about training and engines.
That engine got train.
Who did that engine belong to now.
Did you take it to my retail competitor.
We say we can guarantee you the way we built it.
Your personal data is used to train this. It will not go to the next guy right.
We also said.
For trust AI can't be a black box.
It has to be explainable.
And we learned that in our early days when we would work with doctors and it would say well here's a recommendation.
If I give you a condition what your first question is how did you figure that.
How did you figure that out.
What data went into it.
And so we had to build it that he can answer those kinds of questions.
And therefore it's is helping me.
So this explain ability is a really big deal so that when you said about trust I think you got to believe and lived those kind of principles for people to trust.
You just mentioned the difficulty sometimes of doing big data especially when it comes to medicine cancer doctors doing recommendations in the Wall Street Journal pushed back a bit on Watson No division you have based on the computer that won Jeopardy saying it wasn't doing quite as well in the kanta.
What's the difficulty there and how are you.
I don't agree with that article one bit for lots of reasons.
I think we can actually have an impact on healthcare.
We will not solve cancer.
And that's what an article is backing.
We're not going to solve cancer.
We can do our little pieces here to really advance this.
First off medical data doubles every.
How can anyone deal with that. If you've ever dealt with anyone very sick.
My mom had cancer your first questions are Where are you sure.
That's it. Are you sure that the only treatment I should the right treatment. There's nothing else.
Are you sure that everyone goes through these things right.
Then you look at how much is spent in almost every country in the world protecting us.
And then what's the.
But look at the percentage of our own GDP spent on health care and what the real effectiveness is of it.
So there is a problem I don't think anybody would disagree with the problem part but you could help with the diagnosis and the treatment.
And so working with Memorial Sloan Kettering the Cancer Center here in New York City we've now trained the AI with their doctors and specialists on 13 different cancers which make up a 70 percent of the cancer types out there.
And it has to help a doctor with diagnosis and possible treatments degree of confidence.
What other tests should I useetc.
That's one area.
But drug discovery with Pfizer different immune.
And you'll see this AI play out with what are the different kinds of combinations of drugs that can be formulated and molecules oncology is another Mayo Clinic is now using it for clinical trial matching. So it took 30 minutes eight minutes maybe now you can do all breast cancer through clinical trial matching and we're shortly and soon going to be able to come out with predicting in advance hypoglycemia.
So these are all pieces that really do in the end make a very big difference. But healthcare does not change overnight.
You talk about public private partnership.
But what is the role of government.
Both the federal government and state governments.
I think two things the role of government so I and we have invested a lot of time in getting some of the right policy frameworks out there for education and public private partnerships.
So I think the role of government is around where there is funding set the right kind of policies that are going to incent skills to be built in the right areas.
But then I say when it comes back to the education itself this is where I think the problem is so large Walter it won't be solved with just the government doing this by itself.
Even in our industry andI.T. there's a half a million jobs open in theU.S.
and we're only producing 10 percent of that is coming out of universities.
So you've got to get people prepared without a university degree or accelerate that which is why it's going to take both.
But are you worried about sort of a public disinvestment in education and in career education by government.
Portent an imperative for the country that the government continue to foster these kinds of programs whether they be higher ed and then as well elementary secondaryetc.
So I'm not as worried as long as we all keep focused and put pressure on this.
You know I know business roundtables one of our big agenda items is on this.
So is not my word constant focus and diligence on it is what I think is one of the things of the Business Roundtable has been talking about too is a lack of federal investment in research and development that really flourished in the late 1940s and brought us the Internet the microchip semiconductors and look at it is.
It's a critical part that there be and remain. If you think of what has led this country it's business technology innovation and part of that's come because the government has been sort of the pioneer in a different model in the US's while the government invests in research.
It does it with private sector.
And so then the private sector can more readily commercialize it.
Other countries India they envy the system that we have like this in so we've got to be careful not to pull that back in the wrong areas because this is still a race around skills in these technologies and this to me is something theU.S. does not want to fall behind on by any stretch.
Do you think China may be going faster as it isn't just China whether it's China whether it is the European Union whether it is France and Germany.
Everyone sees this opportunity now that says hey look you've got to have technology innovation to lead in skills as a currency in every country.
And one of the things that sort of helps innovation too is immigration.
Yes. And that helps with the skills as well.
You were one of the CEOs who met with President Donald Trump.
Some of the others met with you to say we've got to change some of these immigration policy.
How successful were you at that.
And he's still pushing that.
You know I always say ideas have no passport and so skills you've got to get people to move around and you've got to be able to bring the best skills to what the problems are.
Whether it's dreamers whether it is immigration.
And if you go back in time to what has made this country successful it is having the skills here it's the investment.
And so have we made some progress.
I think we've made some progress I we've got to make more progress. Things like the dreamers.
We've got 30 in IBM and we've ArcSight 30 dreamers working dreamers and been strong proponent about why we have to allow for these kinds of things and have taken all of our kids out can't say kids are young IBM hours out to Washington to meet people so there's a name and a face.
And these are really productive citizens of this country about what they are doing for companies.
And so I think immigration is a really you've really had any impact on the White House.
Well we're clearly more is left to be done.
So our job is not done here right.
I feel we've had good impact on education and we're going to keep working on things like immigration here because they are really important.
And what about trade.
Aren't you worried that we're putting up too many trade barriers.
I mean that would really hurt IBM.
Look I'm a strong believer in free trade and strong believer that when you have debt yes you should have fair trade.
I don't think anybody would disagree that there has to be fair trade strongly believe those should be negotiated strong negotiations at a table with allies with parties to get that to happen.
We've got global supply chains and are capable of doing that.
I think there are other smaller ones that don't have that possibility.
Yes it's not it is not a huge issue for us again back to remember we are 10 percent physical hard goods and 90 percent software and services many done in their countries of where they are today.
But in a broader picture for our economy you want to have free trade across. And you want to have that be fair trade as I said if you look at what our trade agreements looked like before Walter they were not ready for this 21st century.
They were not digital.
So they needed modernization.
There is no doubt trade agreements needed modernization for this day and age to be able to thrive in Asia. AnyI.T. data innovation driven world.
Now you're one of only 24 women CEOs in the Fortune 500 and even more amazingly that number has been going down.
Why do you think so and what should we do about whether the number is 20.
It doesn't matter the point.
Should it be higher of course it should be higher.
And so what we spend all of our time doing is not only.
Getting women into the workforce Walter the issues keeping them in the workforce.
And that to me is one of the biggest things we've worked in. I give you one I think a great program.
It had to do with once women leave for various reasons in can be a man too by the way.
But to take care of children elder parentsetc.
What we found was difficult to get them back in.
They're like no no no I'm sure time has passed me by. Three years four years it's technology I can't be Zwier this idea he said.
Let's put together kind of a return ship.
You can stay for one day you can stay for three months four months and a refresher on all of this.
And honestly we've had people go OK one day.
This is right. This was crazy.
I'm fine Turk others more months catch up.
And so that is actually the biggest reason why you don't see more women moving up and up and up.
It's this ability to stay in the workforce through these life events.
That to me is one of the most important things you can do that creates a pipeline for the kids.
LUDDEN We have more policies like that. If we had more women CEOs it seems both the chicken and egg.
I don't think it is.
No I know many of my male colleagues as committed to this topic as I have.
People look for a big bang answer to this topic.
It is the accumulation of a thousand decisions you make.
And so when jobs are made available do you insist that the slate has women and men on it or diversity not just men and women. Right.
So this is racist as many different things.
It is a thousand of these decisions that you have to stay with day in and day out that then make the difference.
Well as a historian I'll give you some credit and IBM because when it was the mark one computer one of the first computers ever being built built at Harvard it was Grace Hopper Mabus the legendary programmer who was putting it together.
And nowadays summit the world's fastest supercomputer.
It seems that it's being run by two engineers both of whom are women.
So you get a better work product on the other end with a diverse workforce.
There's a reason to do this.
The reason is you get better better ideas better productivity better work you mirror the population.
And in fact it's especially true when you're building all of these tools AI AI and the like.
That they mirror the workforce doing that mirrors the population it's going to serve.
Tell me about your mother.
Well my mother single mother raised all four of us.
I was 16 at the time when my father left and left her kind of left all of us.
She hadn't had a college degree didn't have the skills to go back to work.
Time no food and really was by watching my mom that I learned probably one of the most valuable lessons I take to work today which is never let someone else define who you are. Never.
And when my mom showed all of us by her actions after this had happened she was no way going to be defined as a single mom someone on welfare or whatever it was.
She went back to school.
I had to help out the oldest but she went back to school she got a degree she got a great job.
All four of us.
I mean I would say I'm the underachiever of the group.
All four went to college have advanced degrees did fantastic and it was just by watching my mom.
She never complained she never cried.
She just said this isn't how the story is going to end.
And don't let someone else ever do this to you. And I think it's true for companies it's true for people it's true for countries.
And I said yesterday that your view of diversity in the workplace encouraging a workforce that was more diverse.
You know it's actually had a really big impact on my view about skills and education but it also had a lot to do about women in engineering and I ended up going into engineering and would have taught me about skills was look you just had to be able to problem solve. And one of the best in my view degrees out there to learn how to do that is engineering your patron saint.
I hope is Ada Lovelace and the 1838 comes up with the concept of grasshopper or purpose computer Ada Lovelace had at the end of her paper when she said machine will be able to do everything except think it was 100 years later that Turing took on Alan Turing took on it. Lady Lovelace's objected and said no machines will be able to think.
Someday they'll replace us.
Whose Side Are You On.
Ada Lovelace or Alan Turing.
I'M STILL ON A levels is much as we invest in these technologies.
That idea the replacement that we are if at all decades away decades and decades this idea we're in a stage where there are still so many things you and I are able to do with this marvelous thing in our heads with only 25 watts of energy or whatever it is right that we are able to do and so don't lose sight of that.
I mean that's why I think today the job is around making things letting you and I do the kind of thinking and judgment that we should be doing and then putting these technologies to work on what are some really hard problems whether it's systemic risk logistics whether it's drug discovery solving cancer.
So that's why I'm I believe this is an era it's not just a few years writes Not just data.
Because actually that's not what makes you win it what makes you win is that whoever can learn the fastest.
And that's what these technologies are gonna help you do is learn Ginni Rometty.
Thank you for joining us.
Thank you Walter.
About This Episode EXPAND
Christiane Amanpour interviews Billie Jean King, former world number 1-ranked tennis player and founder of the Women’s Tennis Association; and John Kerry, former Secretary of State. Walter Isaacson interviews Ginni Romety, CEO of IBM.LEARN MORE