♪ announcer: from our studios in new york city, this is "charlie rose." charlie: we begin with politics. president trump will meet with chinese president xi jinping at trump's mar-a-lago resort this thursday and friday. it is their first meeting and a crucial diplomatic test for the meeting of the world costs two largest economies. on sunday, "the financial times," published an article about the willingness of the white house to act unilaterally against north korea, in the absence of cooperation from beijing. joining me is gillian tett, the u.s. managing editor of "the financial times," and one of three editors from the paper sat down with president trump in the

oval office friday afternoon. this is the cover. look at this. gillian: it is the president of the united states. we don't often get a chance to speak to him. we are very grateful that we did. charlie: it made headlines because of what he said about north korea. a question you asked? gillian: i did ask a question about north korea because i think it is critically important. we spent much of the last two years worrying about syria, iran, russia. for understandable reasons. but what's happening in north korea is critical, and frankly it needs to be talked about. charlie: are they talking about it? do they seem to be not only talking about it, but working? everybody you talked to says the key to north korea is going through china. gillian: the key is indeed china, because about 70% of their energy is coming from china. if they turn off the tap, north korea will have a problem.

it does look like china's leverage over north korea has diminished a little bit. charlie: and the reverse is true. they seem to be less willing to do everything north korea says or wants. gillian: certainly at the moment, china is less willing to do everything north korea wants. it does look as if relations are deteriorating a little bit. the recent assassination that took place in north korea was quite symbolic. it means most of the chinese educated officials in north korea are no longer within the inner circle. there's no doubt that the u.s. administration believes china is critical to rein in north korea. it will be absolutely center stage of the meeting in mar-a-lago thursday. -- thursday and charlie: along friday. with trade and south china. gillian: yes. the critical thing to understand is increasingly people are saying these issues should not be looked at in isolation. on friday, the white house released news about its big

trade review. they are having tough conversations with china about the trade issue and they have been beating the drum that quite a bit. but the question people are asking is could the white house use the trade talks as part of a bargaining chip to try and get some grand deal over the korean peninsula? hard to see at the moment, but it is in discussion. charlie: back to north korea. what did you ask the president? gillian: i asked whether he was concerned about north korea, whether he thought there could be some kind of meaningful discussion, and if the chinese are not willing to play ball, what were they going to do? charlie: and he said? gillian: he indicated -- charlie: he indicated, or he said? gillian: he said he was going to talk with the chinese, that he hoped they would play ball and be cooperative and work together. he said if that happens, that could be very good, dropping hints about the trade issue. but if it wasn't, it was going to be bad.

that theted -- said u.s. would go it alone. charlie: did he say "that's all i'm going to say"? gillian: that was all he was going to say. he did not indicate if that meant militarily or sanctions. frankly, i don't think he knows. a lot of people would say, could the u.s. go it alone? could the u.s. take military action to contain north korea? the answer is come at the moment, not easily or not without a huge loss of life on the korean peninsula. could the u.s. use sanctions? it has been trying to do that for some time and it has not worked. there are not an easy options for the u.s. to go it alone. charlie: does the president believe north korea, if it has icbm missiles that can deliver a nuclear warhead to the united states, is his biggest foreign-policy challenge? does he know that? does he say that, does he

believe that? gillian: i would guess until recently president donald trump , would not be able to locate pyongyang on a map. i think he does understand the gravity of the issue. one important detail about what's going on in the white house is that the nsc is working on a review on the problems in north korea and the options for response, and have accelerated it to make sure the review was in the president's hands before the meeting at mar-a-lago. it was probably in his hands on friday. we also interviewed the deputy. she made it clear she now thinks, the nsc thinks, it is entirely possible that north korea will have an intercontinental nuclear ballistic warhead that could hit north america by the end of president trump's first term if

the current trajectory goes unchecked. that is a scary thought. i was in san francisco and los angeles last week. charlie: that's why president obama said to him, your biggest challenge will be north korea. gillian: what i found amazing is i was in san francisco and los angeles last week, and i said to a number of people, silicon valley, everything is growing, it is all sunshine, it is wonderful. i said to people, are you worried about north korea? and i might have well said, are you worried about planet pluto? i do not think people have understood the threat at all. did you talk about one china policy? gillian: not so much one china policy, but the wider question of the asian region. we did not get into details of what his policy would be. the most intriguing comment he made was, "it is possible they could be a very big deal, that they could be some kind of bigger deal. i would not be at all surprised if we did something that would be very dramatic and good for both countries."

charlie: sounds like some kind of a grand bargain. gillian: you can dismiss that and say it is a donald trump off-the-cuff statement, or you can say that actually, if you want to be optimistic, the severity of the north korean threat means that not only the u.s. is concerned, but china is concerned, too. maybe this can be the issue that breaks the logjam and forces the two huge countries to work together not just on the immediate issue of north korea but on a wider resolution in the south china sea, korean peninsula, and the trade front. and also climate. it sounds hard to believe, but there is a seven-point plan floating around which would try to bring about some kind of wider bargain across the korean peninsula. probably wouldn't be acceptable to the japanese, let alone south koreans, but it is floating around. when donald trump says, "i would

not be at all surprised if we did something dramatic," maybe he has seen that plan. charlie: what was his overall demeanor? was the calm, soft-spoken? his demeanor was positive and cheerful. he seemed to be in a good mood. he was keen to be charming but also fun. charlie: charming, is that a british expression? gillian: [laughter] we arrived, he had a spot for the button on the desk. charlie: friday afternoon. gillian: it was like something out of "dr. strangelove." he pushes the button and calls up a diet coke. he used it to someone a diet coke. he makes jokes sometimes. we had diet cokes. he showed us a picture of andrew jackson. he showed us around the office. he was very keen to be hospitable and gracious.

charlie: what do you make of his presidency so far? gillian: his presidency has certainly taken the world aback. it has been unconventional, often frustrating and baffling. it is been exhausting for a journalist to cover it because we deal with tweets that all day and night. however, as we wrote in our piece today, he is imperious, he is an unconventional president, but there is a method in the madness. charlie: what is the method? gillian: first of all, to enable him to connect with the voters he thinks brought him into office. secondly, it is to destabilize or surprise the people he regards as his rivals like the media. thirdly, he wants to be unconventional. he wants to be a different type of resident. charlie: he believes in chaos and disruption?

gillian: i don't know if he ever sat down and created a philosophy that way, but his instincts are to be unconventional. i asked him whether he regretted any of these tweets that has been coming out. he says he doesn't do regret. he also says he's convinced the tweets won him the election and what gives him the power of the presidency, and he's not going to stop anytime soon. charlie: how did it win the election? to be disruptive? gillian: it enabled him to connect with the public. at one point in the interview he turned around, and said, "tell me how many followers i have on twitter." they came back and said 100 million and then corrected it and said 101 million, and he was pleased. charlie: why do think he is still sensitive about any questions about winning the election? he constantly refers to how well he did and all of that. any psychological insights? gillian: as we wrote in the piece, he opened the interview by saying, "i won, you didn't." it's an indication of his

mentality. he puts the media in the camp of people with whom he has been battling over the last couple years. i think he still feels the need to assert his position. again, many people would say that's part of the unconventional strategy. some people would say that shows a man who doesn't feel secure in the job yet. others would say that is what is being human and part of what has enabled him to connect with voters is the fact that he is a no holds barred, tell it how it is, very human president who changes his mind in an unfiltered way. charlie: do you believe the economic progress we have seen, especially the markets, will continue? gillian: that is interesting. during the course of the interview, we asked him about his plans.

we spoke to a large array of people in the white house. they repeatedly said confidence is surging, stock markets are up. the mood has changed dramatically. people in the white house regard that as a strong sign of what they have achieved. they could be right. maybe there's going to be a self reinforcing upsurge in animal spirits that will get the economy growing again. but one thing is very interesting. and it is something that is worrying the fed. there is a big split between what they call the hard data and soft data. soft data is about sentiment. it is about consumer confidence and business competence. that is definitely rising. hard data -- charlie: there would be tax cuts and less regulation. gillian: exactly. or they are fed up with the last years of too many regulations and worried about quantitative easing. hard data is not nearly as optimistic.

that may be a time lag, maybe the hard data will improve. charlie: hard data? gillian: things like auto sales, gdp. none of the figures have been that positive. they've been ok, but not great. the question people are asking, is this just a time lapse effect? when businesses and consumers see the president's policies coming through, the underlying data will improve, or is it the case that people have drunk the kool-aid around the presidency? and there will be a very nasty bout of disappointment going forward? charlie: there is this idea that we, everybody, got his election wrong. you can't really say anything is bad now, because in the end, like the election, he will prevail. gillian: at one point in the interview president trump waited out that he predicted brexit and lots of other things. morely he had a lot

correct predictions than the media. certainly the white house thinks they are on the right track, that many american voters are with them, business confidence is rising. charlie: but there's also this, which they obviously know. he does feel a strong connection to the people who elected him, or at least he gives expression to that. yet some of the things he is doing, the proposed budget and health care, hinder, takeaway things that that very constituency has considered important to their lives. gillian: i could not agree more. there is a paradox. he has been elected supposedly as a man of the people. he's not a man of the people. he's a billionaire, as he keeps telling us. he's not behaving like somebody who wants to put other people's interests first in terms of the poorest people, in the sense

that the tax cuts will end up favoring the rich, not the poor. his discussions about health care reforms are things that would not help the voters. charlie: the people in his cabinet and his advisers are all very rich. gillian: exactly. there is this extraordinary paradox. you could be cynical and say that is one reason why he keeps expressing the tweets and talking like the people. charlie: how about this tweet about president obama having been part of wiretapping trump tower? gillian: we didn't discuss that particular one -- charlie: you didn't raise that? was that on purpose? gillian: no, it's because you go into an interview, and you talk about tweets. we were about to talk about it, then we started talking about north korea. frankly, issues like north korea and china are so important that,

as with any interview, you go where the conversation goes. charlie: he faces a congress in which he has said he will take on the freedom caucus. gillian: exactly. one of the very interesting details we asked about. what about health care reform? is it dead and buried? everybody in the white house was keen to stress it is not dead. there are negotiations still going on. president trump himself stressed that if the freedom caucus would not play ball, he would turn to democrats instead. charlie: he said that to you? gillian: yes. that he would get a bipartisan deal. if we don't get what we want, we will make a deal with the democrats and we will have a very good form of health care. it will be a bipartisan form of health care. charlie: so he's prepared to take them on. gillian: judging from what he said. he is. charlie: one other interesting

things that came out of problems with passing health care, that the freedom caucus members are not intimidated by him. gillian: that much is very clear. i think he will be ruthlessly pragmatic in this. we were told several times negotiations are underway and they will continue. we were told the reasons they had not conducted the vote was not because they were scared of losing, but because they wanted to keep the door open to more negotiations. like so much going out of the white house now, it is hard to tell what is actually true or not. charlie: from the moment you walked into the white house from the moment that you left what , did you learn that you didn't know, or what perceptions do you have that were not confirmed? gillian: i think they basically come down to two or three. the first is the issue of north korea is center stage right now and very important.

i know it was serious before hand, but i came out aware that it is actually really serious. charlie: and they are on top of it? gillian: they plan to make it the centerpiece of the summit at mar-a-lago. i think until two or three weeks ago, people were looking at it more in terms of the trade deal. the currency issues. also, they would reaffirm he really does believe that tweeting, his unorthodox style, is working. he's not going to change it. charlie: even though -- gillian: every journalist who hopes the stops, no chance of that. charlie: even though it creates distractions that get in the way of his message? gillian: we asked him that. i don't regret anything because there's nothing you can do about it. if you issue hundreds of tweets and once in a while you have a clinker, that's not so bad. that's what he said. charlie: but it is bad if he distracts from the central message. gillian: he said, "i have over 100 million followers, between

facebook, twitter, and instagram. i don't have to go to the fake media." charlie: what is the fake media? gillian: you and me. charlie: broadly anyone who , writes things that he doesn't believe? gillian: anything against him in the voters. in some ways it was like roosevelt with the radio in the 1930's. charlie: kennedy with television. gillian: exactly. he wants to go directly to his base. the fake media is anything that gets in the way of that. we have had many presidents who have used new technological platforms to connect with voters. and get around established interests. every time it happened, people have complained. roosevelt in the 1930's, there was a huge outcry from the mainstream newspapers about the idea of doing a radio broadcast. charlie: there has been more military engagement.

gillian: exactly. charlie: i was talking about president obama, but he continued that. his secretary of defense has put in more people closer to the front lines, more people taking in iraqi soldiers and others. gillian: absolutely. charlie: at risk of being killed. gillian: absolutely. we have an increasingly militarized government. however you want to put it. we have military figures sitting at the core of the government, pledges to increase military spending. this came up a lot, but there is a need for military spending above all else. and there's clearly a focus on war. there is a determination to talk about war in an abrasive way we have not seen for quite a long time. he also says in the interview that he wants to have alliances. he goes out of his way when you ask him what surprised me from the meeting, he goes out of his way to stress that he says nice

things about the chinese leadership, he says nice things about angela merkel, he tried to deny he didn't shake hands with her. he said he did not hear the reporters questions. in some ways, what you are starting to see from president trump is a pattern where he talks tough and aggressively, and then backs down. charlie: someone suggest that has been his strategy. if you look at "art of the deal," that's what he lays out. gillian: he's not a details man. he was talking about china, and says look where we are, we have an $800 billion trade deficit. we fact check him, and it's actually over $500 billion. trade deficit with all the countries. if you are looking at signs of how he operates, strong posturing, strong words, not detail focused, not giving you policy prescriptions.

this was not a carefully crafted manifesto. it's about as far away as you can possibly get in style from president obama. he is the ultimate anti-wonk. charlie: [laughter] thank you. gillian tett from "the financial times," with the big scoop. we will be right back. ♪ charlie: siddhartha mukherjee

is here. he is an assistant professor of medicine at columbia, and a cancer physician and researcher. he is also a very good writer and pulitzer prize-winning author. his latest book comes out in paperback of this month. he writes about the future of automated medicine in a new piece for "the new yorker." it is called "the algorithm will see you now." i am pleased to have siddhartha mukherjee back at this table. welcome. siddhartha: thank you, charlie. charlie: with some sense of fraternity, tell me how this came about. siddhartha: this piece came about because it is a conference you organize every fall, and i was talking at this conference to sebastian, and he told me he had been working on this thing in ai and medicine. my ears perked up.

i said, what are you doing? he began to describe sort of an early version. it wasn't there yet. it instantly caught my attention as a physician. what if we could use these powerful technologies, deep learning paradigms, to start doing diagnosis? what would happen to radiology or dermatology? what would happen to doctors once we engage powerful computers to aid in diagnosis? charlie: so it began with a what if? siddhartha: yes. charlie: what did you discover? siddhartha: one of the questions raised almost immediately for me, once we enter this space, where do we start and where do we stop? as the conversation proceeded

that afternoon at this conference, it became clear to me that the ambitions of these diagnostic technologies was wider than i had imagined. for instance, sebastian talked about a mirror that would photograph you every day, and using these technologies, map every growing mold in your body. or sitting in a bathtub where you would have a scan performed with granular detail and figure out what was growing and not growing. charlie: so if there was a malignant cell, you could see it grow? siddhartha: that's the ambition. but it raised questions. number one, could this be accurate? could you accurately train a machine to recognize a melanoma and distinguish a melanoma from a benign skin lesion? that was one question. the second question, i think it

is very important -- what if you overdiagnosed? what if you were sitting in the bathtub or this hall of mirrors, constantly being surveyed, like big data is watching you? what would happen? would we start intervening on cancers we would not bother with. cancers that are harmless. as an oncologist, it raises the question of diagnosis. where are we going? are we going to overdiagnose? are we going to start invading in the body in a way we did not expect? as machines learn, they will keep telling us. charlie: help me understand the difference. i always believed all knowledge is good, the more you knew, the better you were. causes you you know to take too many tests? siddhartha: exactly. i would say all knowledge isn't good in medicine.

there are things you don't need to know about. charlie: i'm not talking about need, i'm talking about what harm does it do? siddhartha: overdiagnosis causes severe harm. you can cut up pieces of the body, biopsy them, there is an economic cost, you might be chasing cancers that, we now know from autopsies that many people will die of cancers that are incidental. for example, a person dies of an automobile accident, you do an autopsy and you find all these cancers. this has been documented. many of them are incidental. they would not die of these cancers. imagine if a machine was telling you i found cancer here or there, but it may not tell you if the cancer will metastasize or become aggressive. you have the possibility of entering into this hall of mirrors. we have to think about diagnosis very clearly.

the paper that tipped me off is "the study of nature," which is can you teach a machine to learn how to distinguish a benign skin lesion from a melanoma? what is amazing is, you can. you don't need to give it rules. that is what is astonishing about it. in medicine, the way you learn, there are two ways. i talk about this in the article. one way is facts. people say this fact is true. melanomas have these characteristics. if you see these characteristics, they are asymmetric, they have funny borders, the diameter is big. those are rules. that is a rule-based learning. but if you really think about how doctors diagnose, the doctors often make a transition from rule-based learning to a pattern-based learning. we begin to pick up patterns.

we begin to figure out, we can't figure out exactly, but that looks like a melanoma, or that doesn't look like a melanoma. that looks like cancer, that does not look like cancer. this patient looks like she has significant heart disease, this patient doesn't. what's amazing with deep learning algorithms, you don't teach them any rules. you just give them examples. here is a melanoma, here is a not melanoma, you figure it out. charlie: that's what ai is about. you learn, and you go by the experience. siddhartha: absolutely. it is a knowing how. the machine, we do not know how the brain works, but perhaps this is how the brain works. by adjusting weights imbalances -- weights and balances along these categories. i give the example about a child learning. this is a dog and that is a wolf in the piece.

how does the child know? the child knows by using 100 categories of dog and 100 pictures of a wolf, and beginning to make their own judgments about what characterizes a dog and what characterizes a wolf. we don't say to a child, here are the rules for dog. and these are the rules for wolf. we say here is an example of a dog, here is an example of a wolf you figure out the , difference. charlie: they are doing this in deep mind. that's exactly what happens. it offers the most far-reaching, some will say, because you are actually allowing the machine to learn. you are not just feeding it a huge amount of data.

siddhartha: right. it figures out how to adjust its own weight and balances, and ultimately capture those categories with a great degree of accuracy. this is what astonished me. going back to that conversation ai groups, ie began to see the real results. the real result is that the machine outperformed seasoned dermatologists. jeffrey, who is considered the father of a certain kind of deep learning, he thinks these machines will outperform radiologists. then add to that genetic diagnosis. the idea that now we can look at genes and figure out whether it is truly a cancer to metastasize. we have begun to enter a powerful diagnostic era. charlie: it can determine early on whether a gene has the

possibility -- siddhartha: they will be able to determine whether a lesion, a pathological lesion, a melanoma, has the possibility of becoming aggressive and metastasizes rapidly. it is very significant in prostate cancer. prostate cancer is a great example. some cancers will never be aggressive. others can be extremely aggressive and metastasize to bones, causing disease. it would be astonishing if a combination of deep learning plus genetic technologies, plus real doctors can distinguish this. charlie: some of this is being used in the case of radiologists? a kind of ai is being used? siddhartha: yes, the kind of ai

that is being used so far, trying to investigate this i sat through some of these demonstrations. the ones that are in real clinical use, really being workhorsed, it's hard to call them intelligent. they are artificial, but not intelligent. charlie: what is it that they have? siddhartha: they have speed, they have mechanisms to spot. they can guide you to spot an area. for instance in mammography, they can guide you. but what they cannot do -- that machine, the first generation tools, even if it has seen 4000 images, it's not smarter than the one that is seen zero images because it is a rule-based. if it is this big, flag it. but the important distinction here, the radical advancement, is that the new machines are not

told any rules. they figure out the rules for themselves. that's what is important. we are not telling them what to think. they are doing it by themselves. that is what is astonishing. charlie: what does algorithm teach them? siddhartha: i am more on the medical end, but as far as i understand it, it allows them -- if you say here is category one and category two, the algorithm spots features in category one and two, extracts those features categories and , begins to build a mechanism to distinguish category one and two. it extracts the features. thisis amazing about it, took me by total surprise, it

cannot tell you -- it is not easy to go back and ask the machine, what are those features? you can do that to a human being. you can go to a dermatologist and ask her or him, what are the features that you are picking up? they can give you answers, whether right or wrong. what is astonishing, the machine knows, but it cannot tell you. that's what's amazing. it's a black box. charlie: where is all this going? are we going to now go to any doctor and therefore, he or she is going to be in partnership with whatever the latest developments are in artificial intelligence? it becomes their partner in diagnosis? siddhartha: most people think more than that. they will be a partner in diagnosis, a partner in treatment.

in a discipline that is information rich and pattern rich, the costs of which the -- of making mistakes are very high, we would begin to use computers as an extended arm. it would be an entirely symbiotic relationship. and gene sequencing and other technologies, we will become symbionts in medicine. it is not just relegated to diagnosis. thisie: when i tell you you might say it has no relevance at all, but i am constantly amazed about how the accumulation of huge amounts of data is serving every end. there's a story in "the new york times," today or yesterday on how golfers are now able to accumulate data like never before in terms of understanding what they are doing wrong and

how to play the game better. siddhartha: that's correct. but i want to take you toward the end of the piece, where i raised the question about the data. big data, in this case, is absolutely necessary to teach the algorithms how to distinct between the categories. to thousandit example the melanoma and 2000 examples of nonmelanoma, it will keep learning. but what it is not good at is it can't help us answer why. it doesn't help us understand the patterns behind the patterns. that is where human beings still have -- charlie: whether it is likely to change? siddhartha: that's a big question. i gave you the example of a child who establishes between a dog and a wolf. a dog question, why is

different from a cat? we open up our own black boxes. i will give the example in this of a baseball player who knows exactly where the ball will land, because he'll or she has thrown the ball a million times. if you say landed exactly there, it will. knowhat person may not newton's laws. they do not know why the ball is landing at the spot. using their mental and physical algorithm, they have become absolutely expert in landing the ball at that spot. the question i raised in the piece is, as we depend more on the baseball player model, will we start losing the physicist, the person who takes a step back and says, the reason the ball landed there is because there's a hidden law behind all of this?

charlie: i assume the reason that's important is so you can therefore apply that physics to another area. siddhartha: absolutely. that is the reason in medicine you can apply that fundamental knowledge to figuring out how do you direct the immune system against the melanoma you just spotted? why does the heart behave in this way? how can you make new medicine? there is a seduction of big data, that there are certainly new solutions. but at the end of the piece i raise a question -- online, you can find a piece called "ai versus md." that's a bit of a joke, because in the end, it will be ai plus md. we are going to fuse. there is a sense in the medical community that there might be a

loss. not only in the problems of overdiagnosis, but the possibility that we will lose a kind of way of thinking. if we become very reliant on these devices. but on the other hand, they can be great benefit. imagine being able to diagnose melanoma with a great degree of accuracy, or some other cancer. where time is significant. siddhartha: and time costs money. charlie: still, i go back to the point, if you can teach a computer how to learn, so the machine knows how to learn, and the machine learns on its own, will they be able to learn about the laws of physics? siddhartha: you are asking perhaps the deeper questions in deep learning. from the standpoint of medicine,

which is where i would come from, it would remain a challenge to figure out deeper laws of physiology. it is a question the deep learning people are working on. i know this from having spent a significant amount of time about -- talking to them about machines learning about medicine. charlie: i will close with this. i did a piece about artificial intelligence and watson, the ibm variation of this. what is amazing to me is that you go to most companies in america that are the least bit sophisticated, and they now have dedicated, significant development funds to figure out how ai influences their business. siddhartha: and medicine has got to be one of them. charlie: you go to most investment firms, they are looking at places and trying to

put together funds that look exactly into ai. it is perhaps the most discussed single topic in terms of the future of the kinds of areas in which you can talk about, but it has enormous focus right now from a whole range of people who understand its power. and those people who understand how far that power may go. siddhartha: genetic technology and ai, these things are changing what human beings will be like in the future, there's no doubt. something to know about, and particularly in medicine. charlie: thank you for coming. i want to point out, his remarkable book now out in paperback. back in a moment. stay with us. ♪ charlie: last week president

, trump signed an executive order designed to unravel president obama's climate change initiatives and revive the coal industry. president trump made it clear they have no intention of living up to the commitments laid out in the 2015 paris agreement. china appears poised to step into the leadership void created by the president. joining me is barbara finamore, she is a senior lawyer and asia director at the national resources defense council. we are pleased to have her here

tell me the impact of what the president has done as a consequence of these executive orders. barbara: trump has announced a slew of new executive orders designed to dismantle the obama administration's energy, climate, and clean air actions. charlie: lay out what he has dismantled. barbara: he has called for rolling back the clean power plan that sets limits on what power plants in the united states can emit in terms of co2 emissions. it's not clear he will be about to do that anytime soon, however, because he has to follow the law in the same way it took to develop those regulations, he will have to put it out for public comment and give good reasons for why this needs to be dismantled. also, he needs to defend that action in court. that may take time. during that time, it is expected renewable energy business in the

u.s. will be the fastest growing in the electricity sector. trump has also called for -- charlie: that's a good thing. barbara: that's a very good thing. it is unclear what kind of impact his actions will have. he's trying to prop up the coal industry. despite exhaustive analysis by many, showing that it is not going to come back the coal , industry is not coming back. charlie: the gist is to create jobs. barbara: but he's ignoring the fact that today in the u.s. the solar industry alone employs roughly twice as many people as the oil, coal, and natural gas industries combined. it's not really going to grow jobs. in fact, the main impact of what trump has announced is that he is going to put the u.s. in danger of losing out on the

biggest new global industry of any kind, which is the transition to clean energy. charlie: tom friedman wrote a column about that, that very idea that china will become a leader where the u.s. should be and was poised to be. china is coming on strong itause of the huge size of issues and its problems, it is forced to accelerate alternative energy resources. barbara: that's true. china is the leader in renewable resources and energy. $88 billion last year compared to the united states, 58 billion. it plans to invest another $361 billion in renewable energy by 2020, creating 13 million new jobs. that is the story trump is missing. the renewable energy industry is where to go to create new jobs. charlie: when you look at his decisions, is it likely he will pull out of the paris agreement?

barbara: there seems to be internal debate. rex tillerson says it's probably best if the u.s. keeps a seat at the table. charlie: not only that, exxon up,l, the company he headed makes that clear. barbara: a whole slew of companies have made that clear. understand the u.s. has to take a leading role in moving forward. charlie: what happens to the paris agreement if the u.s. pulls out? barbara: if trump announces he wants to step back, it will probably take several years. probably until the end of his administration. it is clear many countries will move ahead despite what the u.s. does. a dozen countries who have joined the paris agreement since trump was elected. china has said they will carry ahead with their commitments no matter what the u.s. says. charlie: will they moved to the

forefront of being the most rapid developer of alternative sources of energy, and at the same time being the leader of this effort to do something about climate control? barbara: that's right. there are two aspects of that, one is cutting out china's reliance on coal, the leading source of its air pollution. at the national people's congress session earlier this month, the premier announced cutting back on china's excess coal capacity is a national priority. china is doing that in a whole range of ways, including cutting back on 280 million tons of excess coal mining capacity, and the new permitting for cold coal plants a dropped to percent last year. china put a cap on coal. that is 58% of its total energy mix by 2020.

charlie: clearly because of the size of who they are and what they do, the idea of leadership is thrust upon them. is it something they want to own? do they want to be the leader? barbara: yes, they do. there is a whole slew of reasons they are acting on climate. one is their own studies. scientific studies show china is one of the countries most abominable to the impacts of climate change. sea levels rising to highly populated areas. it feeds 22% of the world's population on 70% of the arable land production is going down. air pollution is a key problem. it's one of the worst in the world. 366 million people die every year from air pollution. china also sees acting on climate in its economic interests. it is in the midst of a fundamental transformation of the economic system to one that is reliant on coal fire heavy industry, to one relying more on the service sector.

charlie: moving from exporting economy to a domestic consumption economy? barbara: that's right. it recognizes it has to deal with its massive overcapacity of coal plants. they were building two or three per week at one point, but now they are not running half the time. if china does not get rid of this overcapacity they face up , to $1 trillion from stranded assets in economic losses. charlie: how much of the innovation in alternative fuel is taking place in the u.s.? barbara: the u.s. has always been a leader in the development of the technology. the brains behind the technology development. that can still go on if the trump administration continues to fund research and development on those. what china has done is take that and, through economies of scale, take the lead in manufacturing, even though there are still many

jobs in the united states in the solar industry. the u.s. and china have something called a clean energy research center, where the two countries have put their best scientists together to jointly develop new technology on things like electric vehicles, carbon sequestration, and have shared intellectual property. that is the way to move ahead. charlie: can you argue -- the question is whether the u.s. is prepared under the present administration to be a global leader in alternative fuels and other aspects of that, and therefore lead what is considered one of the new emerging industries of our time? barbara: the u.s. can lead. if trump wants to, he can use funding to retrain the workers

in the coal industry. it is a dying industry. not because of obama's environmental policies, but because of increasingly cheap natural gas and renewable energy sources. they can use these funds to train workers and to fund r&d, for new technologies of the future. and that we continue to assert leadership. we are competitive at this moment. charlie: thank you for coming. a pleasure to have you here. thank you for joining us. see you next time. ♪ >> you are watching bloomberg

technology. a check of your first word news. president trump blamed the obama administration today for the "weakness" he said led to an -- a chemical weapons attack by syria. strike obama failed to -- it would cross the u.s. redline. secretary of state rex tillerson is condemning today's attack in syria and pointing the finger at russia and iran. tillerson said today the two nations bear great moral responsibility for the deaths in syria. at least 58 people were killed in today's suspected chemical attack including 11 children. , the un security council has scheduled an emergency m