tv Bloomberg Pursuits Bloomberg September 30, 2017 2:00pm-2:31pm EDT
megan: above all else ginni rometty is an innovator. ginni: we have estimated a market of $2 trillion to make better decisions. megan: she is creating jobs and standing on principle in a time of political controversy. she is not towed by criticism. ginni: people shoot. megan: coming up, a conversation with ginni rometty. ♪ megan: i sat down with ginni
rometty at a conference at the new cornell tech campus in new york city and asked her about ibm's commitment to developing artificial intelligence, or cognitive computing. ginni: we will need help with decisions with the complexity of what is out there, and it doesn't matter what profession you are in. it was this idea that you could help any division be better. i am always reminded of a statistic that studies have been done that, when asked, what percentage of your decisions are right, what percentage would you guess? megan: 100%. [laughter] ginni: studies, on average, one third are great decisions, one third not optimal, and one third are wrong. when you think about that and how much we have estimated a
market to make better decisions. that is why we are calling it cognitive. when we think about man and machine not man versus machine, this is an era that will play out for decades. megan: a lot of people know watson. can you talk to us about watson and make it more real world for the people in this room to understand what they are using it for? ginni: we viewed an era where you would not program machines. they would understand reason and continue to learn, not program. everything you know today is programmable. an entire era has been programmable. this is the beginning of a new era. that, to us, is a big difference
in between what we might experience and what i call consumer ai general-purpose versus business. what we set out to do is build an ai platform for business. i think it comes alive with better examples. when i say for business, there will be two big differences to consumers. one is, as an example, if you are on your phone and ask, give me the best song in 1950. you don't think about, who voted? why did they pick that song? you might say, is this the right diagnosis of this type of cancer? you want to know the data, the evidence behind it. the idea that for business ai would be vertical, meaning you would train it to know medicine, train it to know underwriting of insurance, train it to know financial crimes, train it to
know oncology, train it to know weather. i will come back to some of these. that would be a big difference. when you train for a vertical, it is as if there is billions of data points. we have been trading on regulatory. those of you and thinking, gdp are in europe. ok, it is a regulation. you need to train and interpret something in small amounts of data. vertical knowledge and then the second thing we realized, and i think this is, if i am a company like i am, this is the most important difference. if i asked you, and i think megan knows the answer to this, guess what percentage of the world's data is searchable, what would be your guess? the answer is 20%.
the other 80% lives with those of us who have established businesses. my view was that data has a lot of gold in it. that leads me to the second big difference. if that is a data and it is my ip in my competitive advantage, i don't want to be training -- because remember, it is training. i am training out an algorithm. i want to be sure those algorithms become mine. in other words, i want a platform that is my ai, if i can say it that way. those are the two big differences between what i call consumer and business. it knows a domain and profession and you can protect your insight, not just data. i was telling megan there are so many examples. about a billion people will have the decision impacted by watson
in some way. financial services. it is interesting to watch. some of the big mistakes in europe have adapted more quickly to this. customer call centers. credit mutual. you take thousands of emails in a day. you don't sort them by keyword or urgency. they are sorted by importance, sentiments of the client, their customer stats. that is what they use watson for. we also own the weather channel, not the tv. anything you view on your phone is ibm when you are doing your weather. we now introduce watson internet with hurricane irma and harvey. we helped a million conversations on how to prepare for the hurricane. then, it was half a trillion interactions with watson to help 140 airlines reroute.
ginni: ibm is an $80 billion company. when people say why hasn't this grown ibm by two, i think that is an unrealistic expectation. it is an era and you teach these systems. watson is exactly where we thought it would be. a great example, and i think when you are a pioneer, people shoot. not deadly, but they shoot. health care, as an example, i remember when we did our first oncology teaching watson. the first cancer, it took the doctors a year. this is another key point about professional ai. doctors don't want a black-and-white answer, nor does any profession. when you interact with ai, you
don't want to say, here is an answer. a doctor wants, ok, giving the possible answers. tell me why you believe it. can i see the research, evidence, percent confidence? that is what we are doing. the first cancer took almost a year. we are down to less than 30 days. watson will have been trade will causes percent of the world's cancers. i find that criticism out of line for what it is we are working on together with doctors. i want to focus the story on this. we are fortunate in this country, if you got cancer, you will go to a cancer center. in america, only 50% of americans will go to cancer centers. go to china and india and you have one apologist for 1600 patients. your chances of world-class care are literally zero.
this idea, those are gold standards. it illustrates one of the principles of ai in the future. you must know who taught it and what data, and you must be transparent. in my trip to india, a woman had cancer a doctor had never seen. without watson she would have never have an idea of what the treatments are. i think you have different kinds of situations that will be in this world. this is a question -- this is why i am so positive about this world will have more tough problems solved with ai and issues. there will be issues, and they are serious. we will come back and talk about field education, but the unsolvable --
megan: when you look at ai, do you feel like we are going to little point where it will displace more jobs than it creates and we are not doing enough to create this skill, coding, programming, stem education to push forward the jobs in the future both in ibm and externally? ginni: d believe ai will be the course of this? megan: i think ai will displace jobs and we will see mass migration to the service sector and i am not sure we are ready for that. ginni: what i believe when it comes to complete several placement it will be a small job percentage. when it comes to changing a job, what you do, it will be 100%. therein, if i park in that thought, that says different skills. everybody is going to have to have a different skill. this issue of skills is front
and center to this country and many countries in the world right now without ai. we already have a world that is bifurcating between have and have-nots. a lot of that is based on educational skills. this country has 5 million to 6 million jobs open. that is about skills. this is not being caused by that. one of the most important things we can do is be clear, not only in this country, around the world, fundamentally, we have to revamp education for this era of man and machine. that means you can't insist on every person to be productive in society needs to be university or phd graduate. it is not true, by the way. ginni: there is so little innovation in the education center. why is that? megan: this is one of the things i have worked with the
administration the most on. in the united states in 2015, half of young people did not have an associate or college degree. i am far more optimistic on this, that public private partnerships can solve this dilemma. it is not just about us. it is called pathway to technology. it becomes viral, driven by governors and states. i remember when president obama came to the first one, he goes, hey, where is all the computers? we were like, this is not what we teach these kids. we are teaching them about math problem-solving that is going to transcend any technology they deal with. by the way, we coined it so you are a new collar job. very simple formula, curriculum,
math, science, give the kids a mentor, and then you give them a chance at a job. we will be up to 15,000 kids, and 300,000 companies have volunteered. that is the great thing about this country. we don't look to somebody else to solve this problem. the idea scaling this type of new collar apprenticeship and credentialing, and we have some great -- the legislations on the table in the u.s. for some of this, i am optimistic we are going to make a dent in it. to me, that is a fundamental problem. ai, when i went to davos in january, we published something. all of us have a responsibility. i think it is our responsibility come if we build this, to guide it safely into the world. be clear on the purpose, work with man. we aren't out here to destroy man.
be transparent. who trained it, who were the experts, where did the data come from? if the consumer uses it, held him he is using it. as well, be committed to skills. purpose, transparency, and skills. the root quality of inequality is in skills and education. we have it within our hands to make a difference. megan: up next, ginni rometty doesn't like to be praised or pigeonholed just because she is a woman running one of the world's largest tech companies. ginni: people need role models. whether i like that or not, you have to take that on board. ♪
♪ megan: you are part of president trump's business advisory council, which disbanded in the wake of charlottesville. you said at the time that it was no longer fit for the purpose for which it was created. what did you mean by that? ginni: i can tell you how important i think engagement is. even with my own workforces, as i described to them, ibm ceos have engaged with world leaders, in june i was with prime minister abe in japan. the all have the same similar issues we deal with. there are important policies, not politics that matter. i am passionate about skills and
education, and trade digital area and diversity and -- trade for a digital era and diversity and inclusion. it is our job -- we are blessed to have that. this strategy was what i was asked to be a part of. it wasn't a council. it was asked to get input. i think we had a positive impact on this issue about education. i expect the ministration to do more things aligned with that. we had good input on other issues. what he meant by that then was that that was that was the purpose for. if people believe that by becoming in any of these vehicles it means you can condone charlottesville, no, we did not. that is what i meant by that. we would continue to engage,
because it is incumbent upon us. it transcends any kind of electoral cycle. i have 380,000 employees. it helps to explain. it has always been about policies. megan: one of the things ibm has been engaged on is the transgender bathroom bill. you were communicative with your employees. how are those decisions made about what you engage on what issues, policy issues to delve into, and how personally involved are you in those decisions? megan: i am personally involved, because when you are -- our history of diversity goes back. 1943, ibm had its first woman vice president.
i had been surrounded by a culture of diversity inclusion for my professional life. this is a matter of war that intersection is, on what you need to be a thriving business. you can speak out on everything. by the way, i don't think speaking of the most important parts. it is doing. this is a key point. we spoke out in north carolina and texas. we had large parts of our population, which we have embraced strongly our lgbt population that were afraid about their place. in texas, we did 150 meetings without the representatives, members. it is about what you do to
communicate to people why these things are important. it is not about -- it is about getting in there, communicating why it is an issue, grassroots efforts. that is what we have done on the select issues we think drive home what our values are. that is one that is reinforced. we can't have a workforce afraid of coming to work, and therefore that is why i am -- on that one we were focused on it. 1 keeping on the topic of diversity, one thing i am watching is you talk about your journey as a female leader. i think there is a lot of women who have sympathy with not wanting to be known always as the female ceo, but that having become more important to you during your career, can you touch on that? ginni: i occasionally will speak to this. early in my career, i would say, don't reference me being a woman. this is not about me being a woman. i am on my own merit. until, at some point, i
realized, wait a second, people need role models. whether i like that or not, you have to take got on board. what i learned from my mom, i watched my mom, yes, she struggled. i'm a proponent for programs in the world that are there for a safety net for people. when she had no money and we had to go on food stamps, but i watched the pain in her face. she couldn't wait to get off of those. show us, go back to school, get a degree, get a job, that we would be ok. what she taught us is don't ever let someone else define who you are. only you define who you are. the world would not define her
as a woman whose husband left her, unsuccessful, never educated. she wasn't going to let the world do that. we all -- she never said these words, by the way. it was only by watching that we internalized that. i think it is true for our country and the company. this idea that you define who you are. maybe we have come full circle in that. this isn't 1, 2, 3, 4, 5 generations. we are reinventing it for another generation. the part that has never changed about ibm is innovate technology and apply it to business and society. we are basing it on ai, data, the cloud. they will form the new platform of the future. i am betting that the incumbent companies are going to come roaring back, because they realize they have advantages. it is in the data, the know-how. they are going to marry at the data in the world, and that will
be the base of the competitive advantage. the new ibm is not only the technology platform. it helps you do that. that is us defining who ibm is of the next generation. to me, and that way, that comes full circle. megan: you were not going anywhere. what do you want your legacy to be? ginni: i am the steward of this great company for my period of time. it is just to leave ibm reinvented for the next era. it will impact society, there will be jobs, a better future, and it will be about reshaping ibm for the next era. in our luckiest moments, when we start at health care. megan: think you so much for being here in sharing this. thank you all for being here. [applause] ♪
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