The IBM chief dares to imagine what Watson will be when it grows up, and reaffirms her pledge to hire 25,000 people over the next four years.
By Megan Murphy
September 20, 2017 5:00 AM CDT
IBM Chief Executive Officer Ginni Rometty was interviewed on Sept. 13 in New York City by Bloomberg Businessweek Editor Megan Murphy. Following are excerpts from their discussion, which appear in the Sept. 25, 2017, edition of Bloomberg Businessweek.
Megan Murphy: Artificial intelligence. People may not know that IBM doesn’t call it AI. They call it “cognitive computing.” Tell us why that is.
Ginni Rometty: I have actually had to explain this to my husband as well, because he said to me, “Ginni, of all words, why cognitive?” It was really a very thoughtful decision. The world calls it AI. There’s so much fearmongering about AI. When we started over a decade ago, the idea was to help you and I make better decisions amid cognitive overload. That’s what has always led us to cognitive. If I considered the initials AI, I would have preferred augmented intelligence. It’s the idea that each of us are going to need help on all important decisions. I’m always reminded of an interesting statistic: When you’re asked what percentage of your decisions are right, what percentage would you get?
What would it be?
A study said on average that a third of your decisions are really great decisions, a third are not optimal, and a third are just wrong. We’ve estimated the market is $2 billion for tools to make better decisions. That’s what led us all to really calling it cognitive and getting through to people that, “Look, we really think this is about man and machine, not man vs. machine. This is an era—really, an era that will play out for decades in front of us.”
The world discovered IBM’s Watson after the computer system beat human competitors and won $1 million on Jeopardy! It’s named after your company’s first CEO. What does Watson mean for the future of AI—and for your business?
Everything you know until today is programmable—an entire era for decades has been programmable. Watson would be the beginning of a new era where you didn’t program. Machines would look at data, understand, reason over it, and they continue to learn: understand, reason and learn, not program, in my simple definition. That to us is a very big difference between what you might experience in what I call consumer AI—that is, general purpose—vs. business. We set out to build an AI platform for business.
There would be two big differences between business and consumer AI. For example, if you were on your phone and searched for the best song in 1950, you don’t think, Well, who voted on that? Why did they pick that song? But if you asked for the right diagnosis of a type of cancer, you’d want to know who trained the computer, what data and what was the evidence behind it. It would be the same for business: AI would be vertical. You would train it to know medicine. You would train it to know underwriting of insurance. You would train it to know financial crimes. Train it to know oncology. Train it to know weather. And it isn’t just about billions of data points. In the regulatory world, there aren’t billions of data points. You need to train and interpret something with small amounts of data. Guess what percentage of the world’s data is searchable? What would be your guess?
The answer is 20 percent. The other 80 percent lives with all of us who’ve established businesses—and my view is that data has got a lot of gold in it. It leads me to the second big difference between consumer and business AI. If that’s my data, and it’s my IT and my competitive advantage, I’m training algorithms, and I want to be sure those algorithms become mine. I want a platform that’s my AI even if it operates in a cloud. Business AI knows the domain and the profession, and it can protect your insight. Not just your data, your insight.
Now, some of you may or may not know this, we also own the Weather Channel. Any of you on your phones, that’s IBM you’re hitting when you do your weather. Now introduce Watson into that. Over the weekend of Hurricane Irma—a new weather forecast every 15 minutes recalculated across all 3 billion points of the earth—we helped a million conversations. It was interactive conversation, natural language on how to prepare for the hurricane. We also had half a trillion interactions with Watson to help 140 airlines reroute.
IBM’s Rometty on Real-World Accomplishments of Watson
You touched on some of the criticism of Watson that’s been out there: that it’s still too dependent on humans, it can’t learn fast enough, and it hasn’t been transformational enough to live up to some of the expectations both of IBM and how it’s being marketed. How do you respond to those critics?
IBM is an $80 billion company. So when people say, “My goodness, why hasn’t this thing grown IBM by two?” I think that’s a very unrealistic expectation. You teach these systems. Those of you that work with them, you and they have to learn and teach. Watson is exactly where we thought it would be. When we did our very first oncology teaching with Watson—the very first was lung, breast, and colon cancer—it took the doctors a year to train Watson.
This is really another key point about professional AI. Doctors don’t want black-and-white answers, nor does any profession. If you’re a professional, my guess is when you interact with AI, you don’t want it to say, “Here is an answer.” What a doctor wants is, “OK, give me the possible answers. Tell my why you believe it. Can I see the research, the evidence, the ‘percent confident’? What more would you like to know?” The first cancer Watson took almost a year. We are down to less than 30 days now. By the end of this year, Watson will have been trained on what causes 80 percent of the world’s cancers. And so I find that kind of criticism completely out of line.
I remember when my mother got cancer. My first reaction was, How do I know that this is the treatment? How do I know that this is the best thing? A 70-year-old truck driver in Florida going to get a new job had a recurrence of cancer. He was absolutely devastated. This is what I saw Watson do for him. The doctor showed him, “There are people like you with this cancer. Here are the kinds of treatments they get.” The difference in mindset is night and day. And then, on my trip to India, I met a woman whose doctor had never seen her kind of cancer. Without Watson, he would never have had the idea of what the treatments are.
Memorial Sloan Kettering [Cancer Center] was one of the first that taught Watson. It’s the gold standard, and it illustrates beautifully one of the principles of AI in the future. You must know who taught it and what data is in it—and you must be transparent about it because that matters in these decisions. That gives you a long, long, long answer, but this is why I’m so positive this world will have more really tough problems solved with AI.
And the dystopic view of AI?
When I went to Davos in January, we published something called Transparency and Trust in the Cognitive Era. It’s our responsibility if we build this stuff to guide it safely into the world. First, be clear on the purpose, work with man. We aren’t out here to destroy man. The second is to be transparent about who trained the computers, who are the experts, where did the data come from. And when consumers are using AI, you inform them that they are and inform the company as well that owns the intellectual property. And the third thing is to be committed to skill.
“It’s about what you do to communicate to people why these things are important. It’s not about a tweet”
Do you feel we’re going to get to a point where AI will displace more jobs than it creates and we’re not doing enough to push forward with the jobs of the future?
I do believe that when it comes to complete job replacement, it will be a very small percentage. When it comes to changing a job and what you do, it will be 100 percent. “Whoa, different skills. Everybody is going to have to have a different skill because it’s going to be a threat in all our jobs.” Let me just park that thought. I want to come back to something I think that’s far more important and is related. The issue of skills is front and center in this country and many countries in the world right now without AI. We already have a world that’s bifurcating between haves and have-nots, and a lot of that is based on education and skills. This country has 5 million to 6 million jobs open. That’s about skill. This is not being caused by AI. We’ve got to revamp education for this era of man and machine. And that means you cannot insist that every person needs to be a university or a Ph.D. graduate to be productive in society. You cannot. It’s not true by the way. We’ve proven that.
You started a six-year high school program. This is a program where they take people through four years of high school, two years of a college equivalent, and then hopefully give them preference in getting into the workforce, again to work with IBM.
In the U.S., in 2015, half of our young people didn’t have an associate’s degree or a college degree. That’s the problem today: the number of people that need to be retrained. I’m far more optimistic that public-private partnerships can solve this dilemma. There will be a hundred pathways to technology becoming viral, driven by governors and states. I always remember when President Obama came to the first one, he goes, “Where are all the computers?” We’re like, “That’s not what we teach these kids.” We’re teaching them a skill about math and problem-solving that’s going to transcend any technology they deal with. The first part is a very simple formula: a curriculum of math, science. The second, give the kids a mentor and then you give them a chance at a job. We will be up to 50,000 kids, and 300 other companies have volunteered. I have a whole bunch of these kids over in Silicon Alley where we have our Watson headquarters.
You were a part of President Trump’s decisions advisory council which disbanded in the wake of Charlottesville. You said in a letter to IBM employees that it was no longer fit for the purpose for which it was created. What did you mean by that?
It’s about policies, not politics. I’m passionate about skills and education, about being competitive in trade for a digital era, and of course, diversity and inclusion. We’re blessed to be able to have an influence, and it’s our job to do that. So this strategy and policy forum is what I asked to be a part of. It wasn’t a council. It was asked to give input, and I felt we’ve made a very, very positive impact on this issue about education and things that can be done. I expect the administration to continue to do more things aligned with that. We had some very good input on many other issues.
That is what the purpose was. If people began to believe that by becoming and being in any of these vehicles it meant you condone Charlottesville, no, we did not. There was nothing to condone about Charlottesville. But we would continue to engage, because it’s incumbent upon us. It transcends any kind of electoral cycle everywhere in the world. I have 380,000 employees. So it helps to always explain why we believe these things. We’re the only tech company that makes no political contributions, no PACs. Never have, never will. We’re the only one that can say that.
You come from a background that’s a bit different from most people’s. Your father left home when you were young, leaving your mother. You talked about food stamps, entitlement programs, getting back on your feet, and those lessons that your mother taught you. When you look at the country and some of the anger and, frankly, that a section of the people feel for this establishment, are we headed in the right direction?
For this country itself, I would never count America out, never. And I think you need to look no further than the weekend of Hurricane Irma. When things don’t go right, people help each other. I didn’t hear a single person say, “Well, what did my government do this weekend for me?” IBM pledged $4 million, and we’re not even counting all the volunteer work that we’re doing. Everyone looked out for each other. We had people buying boats going in and helping people. It’s a country that when there’s a problem, people look to each other before they look somewhere else. This is the culture of America.
But you have to pay attention that people have to believe they have a better future. That’s what people ground themselves in. We pledge to hire 25,000 people over the next four years. It’s important to me to go to the middle of America where companies are not necessarily always putting high-tech jobs. We will do it. Like others, I’m very bullish on this country.
“Don’t ever let anyone define who you are. Only you define who you are”
One of the things IBM has recently been engaged on which people may not realize is the transgender bathroom bill. How are those decisions made about what issues to engage on?
Our history of diversity goes back to 1943, when IBM had its first woman vice president, so I’ve been surrounded by a culture of diversity and inclusion my whole professional life there. This is a matter of where what you need to be a thriving business, to be competitive, intersects with your values. You can’t speak out on everything. By the way, I don’t think speaking is the most important part—it’s doing.
But we spoke out. Why? We had large parts of our company’s LGBT population, which we’ve embraced very, very strongly, afraid about North Carolina and Texas. In Texas we actually did 150 meetings with the state House of Representatives. It’s about what you do to communicate to people why these things are important. It’s not about a tweet. It’s about getting in there, rolling your sleeves up, communicating why it’s an issue, undertaking grass-roots efforts. That’s what we’ve done on the select issues that we think really do drive home what our values are. We can’t have a workforce afraid of coming to work.
You’ve talked about your journey as a female leader and about being a role model. There are a lot of women who sympathize with not wanting to be known always as a female CEO. How has that become more important to you during your career?
Early in my career, I would have always said, “Please, don’t ever reference me being a woman.” This is not about being a woman. I’m on my own merits here for many, many years. Then at some point, I realized wait a second, people do need role models, and whether I like that or not, you do have to take that onboard. I watched my mom. Yes, she struggled, and I’m a proponent for programs in the world that are a safety net for people. When we had no money and she had to go on food stamps, I had also watched the pain in her face. She could not wait to get off of those. She went back to school to get her degree, get a job so that we would be OK. The world would not define her as a woman whose husband left her, as unsuccessful, never educated. She wasn’t going to let the world do that. What she taught us transcended what a woman leader, as well as just a leader, is. Don’t ever let someone else define who you are. Only you define who you are.
We have come full circle, me and IBM. I say to people, “Look, we’re the only 106-year-old tech out there.” So this isn’t one generation, two generations, three generations, it’s four or five. And we’re the team reinventing it for another generation. The part that’s never changed about IBM is to innovate technology and apply it to business and society. That’s our core, even when those technologies change.