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Speaker 1: Live from our nation's camera. How do we reopen this economy?

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Speaker 1: The latest on how this pandemic is impacting farmers. What

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Speaker 1: does this do for the United States relationship with China?

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Speaker 1: Floomberg Sound on the inside, the influencers, the insides. We're

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Speaker 1: responding to this crisis and manufacturers are stepping up like

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Speaker 1: never before. We're looking at seveny Kennedys for different vaccines.

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Speaker 1: How do we make sure a pandemic of this gale

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Speaker 1: never happens again? This is Bloomberg Sound On with Kevin

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Speaker 1: Surrelate on Bloomberg one and one oh five point seven

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Speaker 1: f m h D two seven Intelligence Committee Chairman Richard

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Speaker 1: Burr stepping down as chairman of the all important Intelligence Panel. Meanwhile,

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Speaker 1: President Trump heads to Allentown, Pennsylvania. Our very own Bloomberg

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Speaker 1: opinion column is Eli Lake is going to be weighing

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Speaker 1: in on both fronts. All of that, plus General Flynn.

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Speaker 1: We've got some new polls out from Morning Consult. Eli Yolkley,

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Speaker 1: political reporter from Morning Consult. It's gonna break down. Do

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Speaker 1: Republicans want to wear masks? Do Democrats want to go

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Speaker 1: back to work? We're gonna ask him all of the

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Speaker 1: polarizing questions and what it all means for Joe Biden

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Speaker 1: with these new Tara Read allegations, have they had any

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Speaker 1: impact on the race. And we check in in with

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Speaker 1: in the battleground state of Wisconsin. We've got the chairman

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Speaker 1: of the Wisconsin Democratic Party, Ben Wickler. He's gonna phone

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Speaker 1: in as well to tell us about what's going on

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Speaker 1: over there. We continue the conversation as we've been having

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Speaker 1: this week and dabbling into the issue of contact tracing.

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Speaker 1: Is it the future way to keep us safe, to

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Speaker 1: get Americans back to work or is it a scene

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Speaker 1: out of George Orwell? Lots to get through. We're running

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Speaker 1: all the topics. And my name is Kevin Cerillian, the

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Speaker 1: chief Washington correspondent from Bloomberg Television and for Bloomberg Radio.

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Speaker 1: Did you see the big story today? Senate Intelligence Committee

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Speaker 1: Chairman Rich Burr, he's out, he's out, and he's the

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Speaker 1: Republican chairman of Senate until he's gone. He's seven down.

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Speaker 1: And Diane fine Stein, Senator Democrat from California, she's talking

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Speaker 1: with the FBI about her husband's stock trades. I was

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Speaker 1: going to talk about General Flynn with Eli Lake Bloomberg

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Speaker 1: opinion columnists. But Eli, my friend, thank you for joining us.

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Speaker 1: I mean, what do you what do you? I gotta

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Speaker 1: get your take on Burne fine Stein. Well, we had

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Speaker 1: a I mean, we now know that there's an FBI

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Speaker 1: investigation into the suspicious sale of stocks UM that Richard

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Speaker 1: Burr made apparently after receiving UM an intelligence briefing. Uh

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Speaker 1: he told many before. Uh we all sort of continu

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Speaker 1: absorbed how bad the coronavirus pandemic was. And so as

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Speaker 1: somebody who was now under federal investigation, I think he

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Speaker 1: has not recused himself from the UM Senate Intelligence Committy,

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Speaker 1: where he was the chairman. And just to put this

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Speaker 1: in perspective for us, I mean, Eli, like no one

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Speaker 1: knows the intel world better than you to put this

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Speaker 1: in perspective for us, this is massive. I mean, this

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Speaker 1: is a huge deal. Um. I think it is. I

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Speaker 1: mean I think it's a big deal. I do think

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Speaker 1: that it's not an Intel story per se. It's it's

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Speaker 1: you know, if if indeed it's the charges are correct

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Speaker 1: and he's and this is an example of corruption, then

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Speaker 1: you know he may have violated the law. And uh,

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Speaker 1: you know, I don't think his political prospects are that great.

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Speaker 1: Right now, it should be said that, you know, the

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Speaker 1: Senate Intelligence Committee is producing I guess his final report

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Speaker 1: on the Russia Trump stuff. Um they black's earlier this

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Speaker 1: month or last month. It's hard to keep crack of

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Speaker 1: the days. They came out with their fifth report, which

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Speaker 1: confirmed what almost everybody knew, which is that Russia did

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Speaker 1: indeed interfere in the election. They a hacked emails, and

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Speaker 1: um they supported the intelligence community judgment that they did

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Speaker 1: so to benefit Donald Trump. There are people in Magaland

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Speaker 1: who have a problem with that. I know that the

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Speaker 1: House Intelligence Committee, not you know, found that there was

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Speaker 1: other intelligence that didn't support that. I don't think you

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Speaker 1: need access to state secrets to understand that if the

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Speaker 1: Russians hacked Trump's opponent and then helped publicize those emails,

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Speaker 1: which they did, then they were favoring Trump. Doesn't What

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Speaker 1: has never been proved. What has not been proved despite

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Speaker 1: on the other side of this, is that there was

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Speaker 1: any coordination or conspiracy between Trump and the Russians on that.

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Speaker 1: The closest that we've come on that is that there

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Speaker 1: were some communications between Roger Stone and Wiki leaks UM,

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Speaker 1: which is not only not a crime, but doesn't really

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Speaker 1: tell us a whole lot about the initial series of collusion,

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Speaker 1: which has been discredited. So and just to be clear here,

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Speaker 1: he's still going to be on the committee. But when

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Speaker 1: the FBI is investigating the head of the the Senate

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Speaker 1: Intelligence Committee, not a good look for for Senate Intel

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Speaker 1: Committee Chairman Richard Burr. Okay, moving things along, to moving

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Speaker 1: things along. You've got this great piece out on Bloomberg Opinion.

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Speaker 1: You write quote, Ever since Michael Flynn resigned as President

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Speaker 1: Donald Trump's national security advisor three years ago, the president

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Speaker 1: and his allies have taken a keen interest in the

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Speaker 1: practice of unmasking. Now his administration has revealed the names

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Speaker 1: of the Obama officials who learned Flynn's name and intelligence reports.

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Speaker 1: But the information is hardly a smoking gun. Okay, you

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Speaker 1: always call it like it is, especially on matters pertaining

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Speaker 1: to all of this stuff, for lack of a better work. So,

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Speaker 1: this issue of unmasking, what what is it going to

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Speaker 1: move the needle at all? Obviously Republicans are talking about it.

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Speaker 1: What explained this and and why it's important for this

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Speaker 1: for the dynamics of our current political system. Well, just

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Speaker 1: as a to to I was, I think the first

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Speaker 1: person to write about Susan writs have made dozens of

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Speaker 1: a mass and crest back in Seen, and I always

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Speaker 1: thought this was an interesting story because, you know, I'm

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Speaker 1: a bit of a civil libertarian and if you have

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Speaker 1: protections against you can't have warrantless wire tapping anymore, at

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Speaker 1: least of Americans. So when their phone calls are caught

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Speaker 1: up in the surveillance of usually a foreign target, then

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Speaker 1: their names for when their intelligence reports are distributed intelligence

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Speaker 1: community are anonymised. They're blacked out, and then a senior

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Speaker 1: officials can request the name of the US person. Uh,

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Speaker 1: and that's called unmasking. So it's a little bit misleading,

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Speaker 1: and that it wasn't that, you know, the thirty nine

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Speaker 1: senior officials who were on this list of who made

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Speaker 1: these requests didn't say, can I see Mike Flynn's name?

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Speaker 1: They said, this is an interesting conversation, and who is

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Speaker 1: the US person? And it turned out to be Mike Flynn.

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Speaker 1: Now I think that that's it tells us a lot

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Speaker 1: that you know, lots of people who are outside of

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Speaker 1: the intelligence community we're on this list, including Chief of

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Speaker 1: Staff Dennis McDonough, Vice President, Joe Biden, uh US Ambassador

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Speaker 1: United Nations, Samantha Power, And at least I did not

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Speaker 1: know that those kinds of officials usually made these kinds

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Speaker 1: of unmasking requests. There was a mini controversy many years

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Speaker 1: ago during the George W. Bush administration when it came

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Speaker 1: out in John Bolton number him his confirmation hearing to

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Speaker 1: be the U. S. Ambassador to the United Nations, that

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Speaker 1: he had made some unmasking requests. I think there were

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Speaker 1: three unmasking request. It was treating this huge scandal at

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Speaker 1: the time because the question was, why is John Bolton,

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Speaker 1: who is the undersecret was Under Secretary of State for

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Speaker 1: Arms Control and Non Proliferation, Why was he at that time,

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Speaker 1: you know, trying to find doubt the identities of U.

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Speaker 1: S citizens and these intelligence reports. And that was one

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Speaker 1: factor that led to him failing to get that nomination.

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Speaker 1: Fast forward and we find out that there were thirty

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Speaker 1: nine officials who ended up making these requests having to

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Speaker 1: do with Flynn, and I'm told that there were lots more. Now,

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Speaker 1: if you look at the raw numbers that have been

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Speaker 1: published by the n s A, it looks like there,

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Speaker 1: you know, weren't as many unmasking as there were saying

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Speaker 1: twenty eighteen. But that doesn't really tell us a lot,

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Speaker 1: because the question is, you know, why were these sort

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Speaker 1: of non intelligence officials asking for all that. All of

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Speaker 1: that said, I'm sorry, we gotta go go ahead. But okay,

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Speaker 1: all that said, none of this tells us who leaked

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Speaker 1: Twinn's name in January. That is the abuse of power,

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Speaker 1: not and the unmasking could help us find that out.

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Speaker 1: But we don't know the context of these intercepts and

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Speaker 1: whether this was the famous call the Twin had with

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Speaker 1: Kissley active Russian impactive ELI, like, thank you so much.

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Speaker 1: That's that's that's right there. More. Next, if you're listening

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Speaker 1: to Bloomberg kind of I want this is Bloomberg Sound

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Speaker 1: On with Kevin Shirley on Bloomberg and one oh five

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Speaker 1: point seven f m h D two. I'm Kevin Surly,

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Speaker 1: Chief Washington correspondent from Bloomberg TV and from Bloomberg Radio. Friday, Folks,

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Speaker 1: hanging there, We're getting through another week of the pandemic,

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Speaker 1: another week President Trump in Allantown and Allantown, Pennsylvania, back

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Speaker 1: in my old neck of the woods, uh, touring a

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Speaker 1: plant talking about reopening the economy. When will it reopen? Pennsylvania,

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Speaker 1: of course, a key battleground state, key key battleground state

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Speaker 1: in the election. Coming up later on in the program,

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Speaker 1: we're gonna talk with Eli Yoakley, political reporter for Morning Consult.

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Speaker 1: He's following all of the polls, Trump, Pence masks, Republicans, Democrats,

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Speaker 1: unmasking our Eli Lake gave us the download on the

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Speaker 1: unmasking issue, new numbers on the impact coverage of the

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Speaker 1: terror reed allegations I've had on Joe Biden. But I

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Speaker 1: want to stick with another battleground state. First time on

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Speaker 1: the program, Ben Wickler, chairman of the Wisconsin Democrat Party. Ben,

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Speaker 1: have you been able to get any fried cheese curds

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Speaker 1: since this thing started? No? And it killed me too.

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Speaker 1: I missed, I missed. Yeah, that stinks. You gotta get

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Speaker 1: some curbside, Ben, true, curbside curbs that alright? So the

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Speaker 1: Supreme Court just struck down the states stay at Home order. Uh,

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Speaker 1: And I'm curious what you make of that number one?

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Speaker 1: And how's it? How's how are things looking out in

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Speaker 1: Wisconsin with the reopening or the shelter in place? Give

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Speaker 1: us the load umb so with COSIN had been doing

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Speaker 1: things that we're working. We had a pretty hardcore state

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Speaker 1: Safer at Home order, it was called here in our state.

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Speaker 1: And case counts had been going down, hospitalizations had been

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Speaker 1: going down. Tacting capacity have been going up, contact traces

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Speaker 1: they had been going up. We actually had reached five

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Speaker 1: out of six conditions for phase one of our phase

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Speaker 1: reopening that the governor had set out, and then the

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Speaker 1: Republicans and our state legislature sued to our state Supreme Court,

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Speaker 1: and we have a very partisan, kind of polarized the

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Speaker 1: Supreme Court, where four of the conservative justices decided to

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Speaker 1: strike down the Department of Health Services authority to have

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Speaker 1: any kind of emergency ordered that that might supersede other laws.

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Speaker 1: One of the Republican justices actually crossed over and joined

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Speaker 1: the more progressive Supreme Court justices and said that this

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Speaker 1: was judicial activism and had no basis and law. But

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Speaker 1: nonetheless the Supreme Court decision went through and instantly all

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Speaker 1: of the stuff that was keeping people safe fell down.

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Speaker 1: Last night, the Tavern League of Wisconsin, which is the

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Speaker 1: association of bars and caverns and restaurants, UH, they put

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Speaker 1: out word you can reopen immediately and bars did. I

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Speaker 1: was talking to uh, a state representative today who told

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Speaker 1: me that in his hometown they were standing room only

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Speaker 1: crowds in the bars there at least, Yeah, I mean

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Speaker 1: all over the state. So individual counties and cities now

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Speaker 1: are making their own rules. Madison and Milwaukee both said

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Speaker 1: you can't reopen yet. You know, we're gonna reopen with

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Speaker 1: limited capacity down the road. But but it was a

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Speaker 1: wild West, and there are photos and videos online and

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Speaker 1: people packed, you know, elbow to elbow. I it makes

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Speaker 1: me just gravely concerned for what's going to happen to

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Speaker 1: coronavirus in the state. And to me, this is this

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Speaker 1: is politics going too far. It's politics trying to trump science.

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Speaker 1: Unfortunately for US, fence always wins that fight. Well, I

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Speaker 1: fascinating Ben Ben's on the Ben Wicklers on the line there,

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Speaker 1: it is Kevin's really Ben Wicklers on the line. He's

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Speaker 1: the chairman of the Wisconsin Democratic Party. And we're talking

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Speaker 1: about the Supreme Court of the State striking down UH,

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Speaker 1: the state's stay at home order. UH. And And I

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Speaker 1: mean when I saw the images of these packed bars

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Speaker 1: in the state of Wisconsin, I mean, you know, Governor

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Speaker 1: Larry Hogan, Republican from Maryland. I mean, he's easing some

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Speaker 1: of the restrictions on Friday, but he's still saying the

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Speaker 1: advisory is a stay at home order. I gotta be

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Speaker 1: candid here. I mean, it is No one that I

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Speaker 1: talked with on either side of the aisle is saying

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Speaker 1: go run into a packed bar. It's I mean, it's

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Speaker 1: it's remarkable, it really is. And frankly, even the Republicans

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Speaker 1: in the state legislature, we're asking for a stay of

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Speaker 1: seven days to try to reach some kind of deal.

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Speaker 1: What the Supreme Court did was eliminated all the safer

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Speaker 1: at home orders and then said to plent any new ones,

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Speaker 1: it requires the Republican led state legislature to sign off

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Speaker 1: on rules proposed by the executive branch. Now that is

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Speaker 1: not a situation any other state is in. Normally you

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Speaker 1: empower the executive to make emergency decisions. Um. But in

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Speaker 1: this case, the state legislature wanted to have a veto

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Speaker 1: over public health measures and asked for a little extra time,

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Speaker 1: and the Supreme Court didn't even do that at the

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Speaker 1: strikedown and went into place immediately. And it's it is

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Speaker 1: a dangerous situation to have there, The governor staid on

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Speaker 1: TV last night, it's the wild West. Everyone, you know,

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Speaker 1: they're essentially no rules. Uh. And individual cities and counties

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Speaker 1: are trying to come up with their own rules in

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Speaker 1: the in the absence of any guns from the state. Well,

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Speaker 1: the domino effect that this could have on other states, Uh,

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Speaker 1: as you've got, uh, Tony Evers, the Wisconsin governor, UH,

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Speaker 1: it's it's really I mean, I don't know. I mean,

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Speaker 1: I guess we're living in unprecedented times. Ben. Let me

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Speaker 1: ask you just in a couple of minutes that we

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Speaker 1: have left, Ben Wickler, he is the chairman of the

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Speaker 1: Democratic Party of Wisconsin. Let me ask you about the race.

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Speaker 1: Of course, Wisconsin such a key battleground state for Joe

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Speaker 1: Biden and for President Trump. What's the latest, what are

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Speaker 1: you hearing? The most recent public polling from the Market

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Speaker 1: University Law School is that Joe Biden is three points

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Speaker 1: ahead in the must win battleground state of Wisconsin. And

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Speaker 1: that's actually pretty consistent with what we've seen for a while.

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Speaker 1: He has had an edge here, and I think it

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Speaker 1: reflects the fact that a lot of folks have gotten

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Speaker 1: really nervous about how Trump is handling the coronavirus pandemic.

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Speaker 1: That said, this state is going to be close. And

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Speaker 1: you know, anyone who um like we doesn't think Trump

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Speaker 1: deserves another four years in the White House really has

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Speaker 1: to throw themselves into organizing, into contributing, contacting folks they

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Speaker 1: are in relationship with by text and email because we're

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Speaker 1: gonna need every absentee ballot we can possibly find. And

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Speaker 1: I know that the Trump campaign is pouring resources and

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Speaker 1: energy into the state too. The whole election could hinge

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Speaker 1: on what happens in Wisconsin. And that's why we're organizing

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Speaker 1: at a level we never had before this early. Uh.

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Speaker 1: And I'm in Madison right now. We're gonna have turned

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Speaker 1: out through the roof here and we're going to be

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Speaker 1: organizing in rural areas, suburbs, and cities across the state.

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Speaker 1: It's so fascinating to talk to someone where like things

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Speaker 1: are reopened, because here in Washington, d C. Everything is

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Speaker 1: shut down and it continues to be shut down in

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Speaker 1: the minute that we have left. I do want to

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Speaker 1: ask you what are you hearing from your constituents about

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Speaker 1: how China is going to play in this race? Because

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Speaker 1: we always cover trade on this program in Wisconsin, such

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Speaker 1: a key trade state, what do you how what are

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Speaker 1: they saying about China through this long period where the

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Speaker 1: pain of the trade war with China was just hammering,

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Speaker 1: especially farmers and manufacturers in our state. We lost thousands

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Speaker 1: of manufacturing guns before COVID, and the idea was that

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Speaker 1: there would be a light at the end of the

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Speaker 1: tunnel when when President Trump got his deal with China

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Speaker 1: and the light has been completely extinguished. China is not

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Speaker 1: importing US agricultural product products right now. There's an economic

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Speaker 1: freefall there. So it is really a uh, you know,

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Speaker 1: football pulled away from Charlie Brown situation, and folks are

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Speaker 1: bolks are fed up. This is a a I think

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Speaker 1: it's a tough road for Trump and folks are ready

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Speaker 1: for change. Ben Wiggler, chairman of the wiscads sind Democrat Party.

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Speaker 1: Hey go eat a fried cheese skirt. Find one, okay,

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Speaker 1: because I need them and they don't have him in

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Speaker 1: d C. Thanks for listening. More. Next, I'm Kevin Sirley

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Speaker 1: Bloomberg and righted one one. You're listening to Bloomberg Sound

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Speaker 1: On with Kevin Sirelate on Bloomberg and one A five

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Speaker 1: point seven FM h D two. I love that song

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Speaker 1: Little You Two, Little You two. On a fat day.

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Speaker 1: I'm Kevin Sireli, Chief Washington correspondent for Bloomberg Television and

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Speaker 1: for Bloomberg or Radio. You know, I was up on

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Speaker 1: Capitol Hill when was it yesterday? Interviewing Congressman Jim Jordan's

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Speaker 1: Republican from Ohio. He's the one who refuses to wear

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Speaker 1: a mask during the hearings. And I asked him about it,

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Speaker 1: and he says he believes that everyone should be back

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Speaker 1: in the halls of Congress, that they should all be there,

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Speaker 1: no more virtual hearings. He wants everyone back, he wants

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Speaker 1: he wants lawmakers back. He wants them, you know, passing

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Speaker 1: by partisan legislation to hammer home against China. Uh. And

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Speaker 1: it got me thinking just about how the mask has

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Speaker 1: become such a polarizing issue. Eli Yoakley is on the line,

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Speaker 1: good Friends of the program, political reporter for the morning

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Speaker 1: consult Eli, when did the mask get so political? Hey,

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Speaker 1: Kevin's good to hear from you. Look, it's everybody saylidays.

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Speaker 1: It's like I'm still here, We're all still No It's

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Speaker 1: I don't know how political it is. Right now. I

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Speaker 1: mean we were just political. When you've got Lawmaker sand

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Speaker 1: they're not gonna wear it because they don't believe that

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Speaker 1: they should work the Ohl saga with Pence. It's the

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Speaker 1: mask is political. ELI. Well, listen, when we talked to

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Speaker 1: two voters and we talked to two thousand this week,

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Speaker 1: we found that about seven and ten um think the

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Speaker 1: President and Mike Pins should be wearing face masks, including

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Speaker 1: about six and ten Republicans. And so when you listen

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Speaker 1: to the American people on this, they're pretty sold on

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Speaker 1: the idea that when Mike Pens and Donald Trump are

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Speaker 1: traveling across the country as they're talking about doing. I

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Speaker 1: know Donald Trump's out and in Pennsylvania today, they want

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Speaker 1: to see him wearing a mask. I think it's a

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Speaker 1: big question looking forward to some of these rallies and

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Speaker 1: stuff that Trump that's talking about, or at least some

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Speaker 1: of the public events that he's doing, UM, this idea

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Speaker 1: of whether or not he should be wearing a mask

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Speaker 1: when he's in these big crowds of people. UM, there

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Speaker 1: are some there are some differences among Democrats and Republicans

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Speaker 1: when it comes to their effectiveness. Though we've had but

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Speaker 1: it's not big. Still, about three and four Republicans say

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Speaker 1: they think masks are effective, compared to eighty five percent

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Speaker 1: of Republicans. So when you talk to voters, when you

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Speaker 1: talk to people out in the country, Uh, this this

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Speaker 1: controversy that's playing out among some folks in Washington is

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Speaker 1: not quite breaking through. Well, what is breaking through? Is

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Speaker 1: it Tara Read? What's breaking through? Um? We're seeing Tara

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Speaker 1: Read breaking through at some point. And on Joe Biden. Um,

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Speaker 1: it's hard to get stuff to break through right now.

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Speaker 1: Um if you turn on TV, as you know, or

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Speaker 1: he's not turned on the radio. I mean, all the

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Speaker 1: talk in the media is about the coronavirus. And um, somehow,

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Speaker 1: some way, the story about Sarah Read has broken through

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Speaker 1: to voters. We've seen about sixty four percent have heard

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Speaker 1: something or a lot about Joe Biden's denial and her

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Speaker 1: claims and so. Um, and you've seen that reflected into

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Speaker 1: his favorability ratings. And we saw notable drops across the board.

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Speaker 1: But particularly I'm interesting to us among women, including those um,

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Speaker 1: thirty to sixty five year olds who are called suburban

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Speaker 1: moms sometimes who who were a big factor in democratic victories. Um.

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Speaker 1: Last time around UM. But at the same time, I mean,

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Speaker 1: the presidential rates is pretty flatline right now. I mean,

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Speaker 1: it's not been good to bad for Donald Trump. It's

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Speaker 1: been pretty equal. As we've gone through the coronavirus outbreak.

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Speaker 1: Have you guys done any pulling on mail and voting.

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Speaker 1: There's been so much talk recently about whether or not

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Speaker 1: we should change the way that we vote. Other states

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Speaker 1: have you know, kind of been grappling with this. But

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Speaker 1: as we head in to November, UH, and hopefully that

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Speaker 1: there that this pandemic clears up by then and that

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Speaker 1: doesn't come back in the fall. But our voters even

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Speaker 1: where of that is that on their radar yet? UM.

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Speaker 1: We have looked at this and it's something it's pretty popular.

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Speaker 1: I mean, this is one of those things that on

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Speaker 1: TV and in Washington seems pretty controversial, and he asked

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Speaker 1: folks on the country about it. It's it's not as divisive. UM.

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Speaker 1: We pulled on this earlier this month and found just

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Speaker 1: over half of Republican voters support following UM mailing voting

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Speaker 1: this year, UM generally, and then it went up ten points.

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Speaker 1: Asked just about the pandemic. This is not a controversy

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Speaker 1: when we tested it that it has broken through to folks.

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Speaker 1: Are you there, Eli, do we still have here? Do

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Speaker 1: we lose the life? I am here. Can you hear me? Yeah?

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Speaker 1: I can hear you. Now go ahead and finish your time.

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Speaker 1: I was just I was just saying, this is one

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Speaker 1: of those controversies that has not broken through to folks.

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Speaker 1: The fact that most Republicans support it um in our

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Speaker 1: polling UM and even more supported during a pandemic UM,

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Speaker 1: I think says this has quite a bit about it.

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Speaker 1: I mean, this is a very popular posal that that

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Speaker 1: folks were talking about. Okay, And here's where I want

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Speaker 1: to take the rest of this segment, because you guys

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Speaker 1: did a poll that really got my attention about China,

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Speaker 1: and what you found is that three and four Americans

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Speaker 1: three and four Americans blame the Chinese government, the Communist

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Speaker 1: Party of China, for America's high death rate in due

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Speaker 1: to COVID nineteen. So when you break this down amongst Republicans,

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Speaker 1: it's but I want to look at Democrats because I

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Speaker 1: don't think that the media is paying enough attention to

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Speaker 1: this to be candid. And I probably shouldn't have said

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Speaker 1: that seventy one percent of Democrats blame China, the Chinese government.

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Speaker 1: They don't. They blame the Chinese government, shi Jingping's government

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Speaker 1: for the high death rate of COVID nineteen seventy one

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Speaker 1: Democrats seventy one Democrats and all adults at seventy That's fascinating.

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Speaker 1: That's fascinating, and that's why. The senior policy advisor to

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Speaker 1: O Biden's presidential campaign gave an interview to Reiter's earlier

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Speaker 1: this week and said that the Biden campaign is putting

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Speaker 1: together a list of policies for how they would deal

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Speaker 1: with Shijing Ping elive, big deal. Um, you know, whatever

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Speaker 1: you ask about blame and sort of the head to

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Speaker 1: head question. Um, more voters generally blame China than blame

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Speaker 1: Donald Trump for the spread of coronavirus and the United States.

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Speaker 1: This is clearly something that is h that's on the

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Speaker 1: minds of the American people, and something that we've seen

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Speaker 1: Donald Trump leaning into this campaign. I mean, I think

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Speaker 1: this week they had the vet they called it Beijing Biden.

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Speaker 1: The Trump campaign did trying to attack Joe Biden for

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Speaker 1: being soft on China. They're dishing it back at the

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Speaker 1: presidents in terms of this coronavirus. You know, before I

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Speaker 1: came on air, I spoke to a senior source in

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Speaker 1: the Trump political re election UH campaign who really hammered

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Speaker 1: that point home. And that's gonna that Onslaught, I can

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Speaker 1: tell you, is only just beginning to increase, especially in

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Speaker 1: terms of going through the Biden world record. I mean,

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Speaker 1: I talked to Democratic strategist who say that they're willing

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Speaker 1: to have that debate every single day of the week.

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Speaker 1: But I want to move away from politics for a second,

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Speaker 1: because earlier this week I was at the State's Department

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Speaker 1: and I interviewed the Under Secretary of Economic Affairs, Keith Kroc,

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Speaker 1: and he foreshadowed what President Trump said on Fox Business

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Speaker 1: Network earlier today. And this has significant market implications, which

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Speaker 1: is all of those Chinese businesses that are trading on

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00:24:28,400 --> 00:24:33,000
Speaker 1: the US exchanges that don't have to go through something,

428
00:24:33,040 --> 00:24:36,400
Speaker 1: oh I don't know called Starbanes Oxley, that they're gonna

429
00:24:36,400 --> 00:24:38,399
Speaker 1: be taking a look at that and whether or not

430
00:24:38,560 --> 00:24:42,120
Speaker 1: that is going to be okay. So from a broader standpoint,

431
00:24:42,400 --> 00:24:44,879
Speaker 1: when you've got Biden World forecasting that they're going to

432
00:24:44,960 --> 00:24:48,520
Speaker 1: put out a policy proposal that's more that's more tough,

433
00:24:48,560 --> 00:24:51,800
Speaker 1: on China, and you've got the Trump administration now openly

434
00:24:51,800 --> 00:24:56,000
Speaker 1: floating some financial reforms coupled with the non partisan issue

435
00:24:56,800 --> 00:24:59,880
Speaker 1: as it relates to higher education, diversifying the US supplied

436
00:25:00,160 --> 00:25:05,760
Speaker 1: and pushing for international standards from Europe to try to

437
00:25:05,880 --> 00:25:10,040
Speaker 1: get the Europeans back on the same page, to disentangle

438
00:25:10,560 --> 00:25:15,560
Speaker 1: on five G from China. Uh Italy Uh. It's it's

439
00:25:15,600 --> 00:25:19,560
Speaker 1: it's quite telling that from a longer term US perspective,

440
00:25:20,200 --> 00:25:22,879
Speaker 1: Democrats and Republicans have a lot more in common and

441
00:25:22,920 --> 00:25:26,520
Speaker 1: putting the focus on China than I think gets reported.

442
00:25:26,560 --> 00:25:31,200
Speaker 1: Sometimes you like, yeah, I mean we saw that. We've

443
00:25:31,280 --> 00:25:34,360
Speaker 1: We've seen people talking on both sides for a few

444
00:25:34,440 --> 00:25:38,320
Speaker 1: years now about how this is a rival to watch um,

445
00:25:38,400 --> 00:25:41,600
Speaker 1: and I think voters are taking note of all this talk. Um,

446
00:25:41,600 --> 00:25:43,359
Speaker 1: this is gonna be a big deal in the in

447
00:25:43,359 --> 00:25:46,320
Speaker 1: the campaign. UM. The point that the Biden people make

448
00:25:46,320 --> 00:25:49,040
Speaker 1: that I think is interesting and Demo cart has generally

449
00:25:49,080 --> 00:25:51,440
Speaker 1: been making is um to try to mip this in

450
00:25:51,520 --> 00:25:55,320
Speaker 1: the bud is to blame Trump for the early failures

451
00:25:55,320 --> 00:25:57,679
Speaker 1: in the response to coronavirus. I mean, they're shifting a

452
00:25:57,680 --> 00:26:00,240
Speaker 1: lot of the focus there and they're not really aiming

453
00:26:00,320 --> 00:26:02,600
Speaker 1: China and that they're they're putting this all on Donald

454
00:26:02,640 --> 00:26:06,760
Speaker 1: Trump's plate. Um. I mean in research shows how significant

455
00:26:06,840 --> 00:26:11,040
Speaker 1: his his his his words, and his actions have been

456
00:26:11,080 --> 00:26:15,600
Speaker 1: in this. And we've seen pulling in our shop noting

457
00:26:15,640 --> 00:26:19,440
Speaker 1: a increase in fears among Americans generally and among Republicans

458
00:26:19,440 --> 00:26:23,720
Speaker 1: in particular. Whenever Donald Trump said something about coronavirus. It

459
00:26:23,760 --> 00:26:27,439
Speaker 1: wasn't until he declared a national emergency, we saw fears

460
00:26:27,440 --> 00:26:30,280
Speaker 1: surge in a big way. Um and so Um, You've

461
00:26:30,320 --> 00:26:33,040
Speaker 1: got two competing things here going on with on one hand,

462
00:26:33,119 --> 00:26:35,240
Speaker 1: or Democrats are sort of leaning into some of this

463
00:26:35,400 --> 00:26:37,240
Speaker 1: China talking. On the other hand, they really want to

464
00:26:37,280 --> 00:26:41,000
Speaker 1: put this at the feat of the president. Yeah. Great, well,

465
00:26:41,040 --> 00:26:44,920
Speaker 1: said Eli Looakley, political reporter for Morning Console. Hey, Morning Consoles,

466
00:26:44,920 --> 00:26:48,080
Speaker 1: shaking things up. Appreciate you coming in, coming on to

467
00:26:48,560 --> 00:26:51,479
Speaker 1: break down all of the latest polls on masks, on China,

468
00:26:51,840 --> 00:26:54,480
Speaker 1: and of course on terror. Read I'm Kevin. Severally download

469
00:26:54,480 --> 00:26:56,600
Speaker 1: the Boombergs Down on podcast on Apple kinds of Bomberg

470
00:26:56,640 --> 00:26:59,280
Speaker 1: dot com, or by downloading Boomberg Business App. You can

471
00:26:59,320 --> 00:27:01,560
Speaker 1: also find me on Radio dot com, I Heart Radio,

472
00:27:01,920 --> 00:27:08,640
Speaker 1: and Spotify. We talk artificial intelligence and contact tracing coming

473
00:27:08,720 --> 00:27:24,720
Speaker 1: up next on Bloomberg NINEO Night On. You're listening to

474
00:27:24,840 --> 00:27:29,480
Speaker 1: Bloomberg Sound On with Kevin Surley on Bloomberg and one

475
00:27:29,480 --> 00:27:34,000
Speaker 1: oh five point seven f M h D two. It's

476
00:27:34,080 --> 00:27:38,119
Speaker 1: Kevin Surley, Chief Washington correspondent for Bloomberg TVM for Bloomberg Radio.

477
00:27:38,240 --> 00:27:41,240
Speaker 1: You know, I've been trying to wrap my head around

478
00:27:41,280 --> 00:27:46,040
Speaker 1: all of these reports of contact tracing and artificial intelligence.

479
00:27:46,119 --> 00:27:48,800
Speaker 1: You know, is it George or relly in or is

480
00:27:48,840 --> 00:27:50,920
Speaker 1: it the future? Is it going to keep us safe?

481
00:27:50,920 --> 00:27:54,160
Speaker 1: How do we balance that with civil liberties and freedoms

482
00:27:54,160 --> 00:27:57,800
Speaker 1: and all of this, you know, especially in democracy. Richard

483
00:27:57,800 --> 00:28:03,439
Speaker 1: Wang's on the line. He's the CEO of Coding Dojo. Uh,

484
00:28:03,480 --> 00:28:07,520
Speaker 1: and you know he's been everywhere and and you know,

485
00:28:07,720 --> 00:28:10,760
Speaker 1: and I have a lot of a lot of questions

486
00:28:10,760 --> 00:28:14,480
Speaker 1: for your Richard wagging. Thanks for thanks for joining us, Thanks,

487
00:28:14,480 --> 00:28:16,000
Speaker 1: thank you so much for having me on the program.

488
00:28:16,320 --> 00:28:19,159
Speaker 1: Excited to be here. Well, first of all, explain to

489
00:28:19,200 --> 00:28:22,439
Speaker 1: our audience before we talk about Coding Dojo. Explain to

490
00:28:22,520 --> 00:28:26,680
Speaker 1: me precisely what contact tracing is and what it isn't

491
00:28:26,680 --> 00:28:28,640
Speaker 1: Because I think a lot of people hear horror stories

492
00:28:28,880 --> 00:28:31,159
Speaker 1: and I want to know what it is, especially if

493
00:28:31,160 --> 00:28:35,879
Speaker 1: it's gonna you know, help us beat COVID nineteen exactly.

494
00:28:35,880 --> 00:28:37,760
Speaker 1: You know, you know how you know? I think we're

495
00:28:37,760 --> 00:28:41,200
Speaker 1: all pretty much aware how COVID nineteen spreads among the people.

496
00:28:41,640 --> 00:28:43,440
Speaker 1: And sometimes you can be in the air of the

497
00:28:43,520 --> 00:28:46,080
Speaker 1: drop leg just by you know, your close contact talking

498
00:28:46,120 --> 00:28:48,560
Speaker 1: to someone and so we esentially contact tracing to the

499
00:28:48,640 --> 00:28:51,920
Speaker 1: essential way. If someone has this virus you started spreading out,

500
00:28:52,280 --> 00:28:54,560
Speaker 1: can we start to find all the people who are

501
00:28:54,600 --> 00:28:56,960
Speaker 1: the source of the individual and all the people that

502
00:28:57,120 --> 00:28:59,640
Speaker 1: the individual have touched so that we can contain the

503
00:28:59,720 --> 00:29:04,640
Speaker 1: virus is within this human chain from spreading even further. Okay,

504
00:29:04,680 --> 00:29:06,640
Speaker 1: So how do you do that though? Because what if

505
00:29:06,680 --> 00:29:08,680
Speaker 1: I came into contact with someone and I don't want

506
00:29:08,680 --> 00:29:10,480
Speaker 1: people to know I came into contact with them. I mean,

507
00:29:10,480 --> 00:29:13,880
Speaker 1: that's my right to privacy, is it not? You know,

508
00:29:13,960 --> 00:29:16,280
Speaker 1: that's a great question. I think this is I think

509
00:29:16,280 --> 00:29:19,040
Speaker 1: this it is more than just a technology challenge we're

510
00:29:19,080 --> 00:29:22,120
Speaker 1: facing with. It's also you know, privacy as well. You

511
00:29:22,120 --> 00:29:24,280
Speaker 1: know that the day and age with living right now,

512
00:29:24,680 --> 00:29:27,160
Speaker 1: you know, just going back to six months months ago,

513
00:29:27,280 --> 00:29:29,440
Speaker 1: we are seeing Facebook and how water is talking about

514
00:29:29,480 --> 00:29:32,240
Speaker 1: privacy telling people's data. So I think there is a

515
00:29:32,280 --> 00:29:37,800
Speaker 1: lot of topic trust issues with you know, privacy, personal data. Okay,

516
00:29:38,040 --> 00:29:41,080
Speaker 1: so when we talk about issues like contact tracing and

517
00:29:41,200 --> 00:29:44,840
Speaker 1: apps that are going to potentially be in in the

518
00:29:46,280 --> 00:29:49,880
Speaker 1: in in the works, how would that work in an

519
00:29:49,920 --> 00:29:54,760
Speaker 1: American legal system? Yeah, I mean that's a great question.

520
00:29:54,880 --> 00:29:57,600
Speaker 1: And at first I think, you know, um, if we

521
00:29:57,600 --> 00:30:00,200
Speaker 1: can use the AI motion learning to help this contact race.

522
00:30:00,320 --> 00:30:03,080
Speaker 1: And the first let me just say what is AI

523
00:30:03,200 --> 00:30:05,160
Speaker 1: Because to a lot of listeners or people, that may

524
00:30:05,200 --> 00:30:07,760
Speaker 1: seem to like a black box. So you know, I

525
00:30:07,800 --> 00:30:12,320
Speaker 1: mean exactly, it is not a robot, right, it is

526
00:30:12,320 --> 00:30:16,040
Speaker 1: not a robot. It's really just computer software. So for example, UM,

527
00:30:16,160 --> 00:30:18,880
Speaker 1: when we think of AI machine learning the broad definition,

528
00:30:19,160 --> 00:30:22,440
Speaker 1: often you will see that you know, it's it's AI

529
00:30:22,440 --> 00:30:25,120
Speaker 1: O machine learning or works by combining large amount of

530
00:30:25,160 --> 00:30:29,080
Speaker 1: data inputs, you know, with computer processing and computer algorithms,

531
00:30:29,360 --> 00:30:32,360
Speaker 1: a lot of solfware to learn automatically, you know, from

532
00:30:32,400 --> 00:30:35,160
Speaker 1: patterns of features in the data, and the outputs will

533
00:30:35,200 --> 00:30:38,760
Speaker 1: help us make better decisions about the outcome of certain things.

534
00:30:38,800 --> 00:30:40,520
Speaker 1: And I think, you know, how do I how do

535
00:30:40,560 --> 00:30:43,320
Speaker 1: I put that into perspectives? I give you a ye. Example,

536
00:30:43,720 --> 00:30:47,240
Speaker 1: So there's a great Boston startup to the bio health

537
00:30:47,920 --> 00:30:50,840
Speaker 1: and bibo health is the AI health is system, the

538
00:30:51,360 --> 00:30:53,800
Speaker 1: health US system talk to people every few seconds and

539
00:30:53,840 --> 00:30:56,600
Speaker 1: the majority of the conversation are with patients within twelve

540
00:30:56,720 --> 00:30:59,440
Speaker 1: hours of having a syntom you know, um even two

541
00:30:59,440 --> 00:31:01,240
Speaker 1: the three days before they even see a doctor or

542
00:31:01,240 --> 00:31:04,360
Speaker 1: get tested. So this data allows the company to see

543
00:31:04,360 --> 00:31:07,080
Speaker 1: the hotspots of the search and that based on the

544
00:31:07,120 --> 00:31:11,080
Speaker 1: conversation text analytics to see the hotspots before it even happen.

545
00:31:11,720 --> 00:31:17,640
Speaker 1: So that's one of the great dempole storm. How would yeah,

546
00:31:17,800 --> 00:31:21,640
Speaker 1: so how would that work if you're able to see

547
00:31:22,200 --> 00:31:24,280
Speaker 1: the hot spots? I mean that would that would be

548
00:31:24,320 --> 00:31:27,360
Speaker 1: an incredible leap forward if there was technology that would

549
00:31:27,400 --> 00:31:30,480
Speaker 1: be able to say, hey, wait a minute, let's let's

550
00:31:30,520 --> 00:31:34,160
Speaker 1: try to see exactly where this hot spot is, because

551
00:31:34,200 --> 00:31:38,680
Speaker 1: then we could start to treat these outbreaks as if

552
00:31:38,720 --> 00:31:41,400
Speaker 1: they were storms, as if it was a weather map,

553
00:31:41,800 --> 00:31:46,480
Speaker 1: as opposed to one blanket shutdown for an entire world.

554
00:31:46,840 --> 00:31:49,840
Speaker 1: Am I wrong or am I missing something? No? I

555
00:31:49,880 --> 00:31:51,640
Speaker 1: think that's a great point is that you know, how

556
00:31:51,680 --> 00:31:55,240
Speaker 1: do we deal with based on gew location by jew location?

557
00:31:55,280 --> 00:31:57,320
Speaker 1: Because a lot of symptoms are based on you know,

558
00:31:57,840 --> 00:32:01,040
Speaker 1: geo bonded of areas, and so I think, you know,

559
00:32:01,200 --> 00:32:03,920
Speaker 1: just in terms of how does this work essentially you know,

560
00:32:04,200 --> 00:32:07,000
Speaker 1: um BioHealth is that kind of helps um you know

561
00:32:07,120 --> 00:32:09,960
Speaker 1: app that people can go on to the to the

562
00:32:09,960 --> 00:32:13,160
Speaker 1: app and talk to this AI assistant and just talk

563
00:32:13,200 --> 00:32:15,360
Speaker 1: about you know, I have this, I have this specific

564
00:32:15,440 --> 00:32:19,040
Speaker 1: symptom and what's the likelihood I would have COVID nineteenland whatnot?

565
00:32:19,120 --> 00:32:22,040
Speaker 1: And so, um it's been able to predict you know,

566
00:32:22,080 --> 00:32:25,200
Speaker 1: based on the search and the volume given to a location.

567
00:32:25,640 --> 00:32:28,360
Speaker 1: And then you maps the CDC uh CVC like you

568
00:32:28,440 --> 00:32:30,640
Speaker 1: know outbreak map, and then I think they have done

569
00:32:30,680 --> 00:32:32,640
Speaker 1: a pretty good job for you accurately amazing to where

570
00:32:32,680 --> 00:32:35,000
Speaker 1: things are happening. So they are able to based on

571
00:32:35,200 --> 00:32:37,720
Speaker 1: this data point and the volume of walk people are

572
00:32:37,760 --> 00:32:40,200
Speaker 1: looking for, they are able to predict where the next

573
00:32:40,200 --> 00:32:43,880
Speaker 1: hospits are. That just surely based on volume yep and

574
00:32:43,960 --> 00:32:46,360
Speaker 1: so and that would be able to to to predict,

575
00:32:46,600 --> 00:32:49,440
Speaker 1: I guess where the flow of a virus or the

576
00:32:49,480 --> 00:32:52,160
Speaker 1: spread of the virus is going at the epicenter, for example,

577
00:32:52,200 --> 00:32:55,120
Speaker 1: is in New York City when it might penetrate into

578
00:32:55,960 --> 00:32:59,960
Speaker 1: another city and that could again be able to predict

579
00:33:00,280 --> 00:33:03,480
Speaker 1: what hospitals would be able to handle, what they would

580
00:33:03,480 --> 00:33:05,160
Speaker 1: not be able to handle. And all of that is

581
00:33:05,200 --> 00:33:07,600
Speaker 1: you're telling me is driven on this idea of artificial

582
00:33:07,640 --> 00:33:11,680
Speaker 1: intelligence and contact tracing? How then does it collect data? Though?

583
00:33:11,720 --> 00:33:13,840
Speaker 1: This is and okay, so I understand how it works now,

584
00:33:13,920 --> 00:33:17,640
Speaker 1: Richard Wayang, but I don't understand how it collects data.

585
00:33:17,720 --> 00:33:22,040
Speaker 1: And explain this as slowly as you can, because it's complex. Yeah,

586
00:33:22,080 --> 00:33:23,960
Speaker 1: I think you know there are a couple of solutions

587
00:33:23,960 --> 00:33:26,680
Speaker 1: to older in terms of data collection for contact tracing.

588
00:33:27,000 --> 00:33:29,160
Speaker 1: For example Google right now or you know, on my

589
00:33:29,280 --> 00:33:31,040
Speaker 1: t right now they are talking about how can we

590
00:33:31,120 --> 00:33:35,040
Speaker 1: can use bluetooth technology to collect data on contact tracing?

591
00:33:35,560 --> 00:33:37,600
Speaker 1: So I would take I would take the Let me

592
00:33:37,600 --> 00:33:40,080
Speaker 1: just take a second to explain what bulletooth technology is.

593
00:33:40,400 --> 00:33:42,920
Speaker 1: You know, bulleto technology is how I listen to my

594
00:33:42,960 --> 00:33:45,440
Speaker 1: headphones when I'm on my run. I get the bluetooth.

595
00:33:45,520 --> 00:33:48,080
Speaker 1: But I want to know hold on because because I

596
00:33:48,080 --> 00:33:50,000
Speaker 1: want opinion, I don't. I want to get an answer

597
00:33:50,040 --> 00:33:53,000
Speaker 1: out of you on this. How how would it work?

598
00:33:53,320 --> 00:33:56,480
Speaker 1: How would you know from my device on my phone

599
00:33:56,520 --> 00:34:00,560
Speaker 1: who I've been in contact with right. So you know,

600
00:34:00,640 --> 00:34:04,400
Speaker 1: Bluetooth technology essentially works by using a short reads wireless

601
00:34:04,440 --> 00:34:08,440
Speaker 1: communication technology to connect to devices together. This the nameless

602
00:34:08,480 --> 00:34:10,719
Speaker 1: the need for cables to wires, as you said. And

603
00:34:10,719 --> 00:34:13,240
Speaker 1: then it works by sending a random stream of numbers

604
00:34:13,960 --> 00:34:17,239
Speaker 1: via there's a low power bluetooth from users smartphone to

605
00:34:17,360 --> 00:34:21,200
Speaker 1: the other nearby devices using the system and create a

606
00:34:21,360 --> 00:34:25,359
Speaker 1: coded nest of smartphones that a given user have been

607
00:34:25,400 --> 00:34:28,120
Speaker 1: close to in the passporting days. And then if the

608
00:34:28,280 --> 00:34:32,240
Speaker 1: users subsequently test positivele COVID key or she can upload

609
00:34:32,920 --> 00:34:35,040
Speaker 1: upload that list of numbers to a database on a

610
00:34:35,040 --> 00:34:38,520
Speaker 1: cloud for example, so that other users can run check

611
00:34:38,560 --> 00:34:42,000
Speaker 1: to determinent whether they might have the whether they might

612
00:34:42,040 --> 00:34:44,759
Speaker 1: have the exploded you're supposed to this virus or not.

613
00:34:45,160 --> 00:34:47,400
Speaker 1: But see you how do you get the way? Because

614
00:34:47,400 --> 00:34:50,440
Speaker 1: that's a little that's are reliant. People can argue that

615
00:34:50,480 --> 00:34:52,759
Speaker 1: that's a reliant Do you have the do does an

616
00:34:52,800 --> 00:34:56,319
Speaker 1: individual have the right to opt in or opt out

617
00:34:56,440 --> 00:34:58,759
Speaker 1: of whether or not they want to share that information?

618
00:35:00,200 --> 00:35:04,560
Speaker 1: I think we better create a opting system otherwise I

619
00:35:04,600 --> 00:35:07,480
Speaker 1: think that that will be a major you know, primacy

620
00:35:07,520 --> 00:35:09,120
Speaker 1: you ssue that they have to deal with. But on

621
00:35:09,160 --> 00:35:11,680
Speaker 1: the other hand, you know, if you only get people opting,

622
00:35:11,760 --> 00:35:14,840
Speaker 1: you may have a self selection biased in the process,

623
00:35:14,840 --> 00:35:17,040
Speaker 1: and so you may not forget as well. So it

624
00:35:17,200 --> 00:35:20,960
Speaker 1: is a you know, a privacy you know, UH paradigm

625
00:35:21,000 --> 00:35:22,960
Speaker 1: that they have to think about. I mean, this is

626
00:35:23,080 --> 00:35:26,040
Speaker 1: more of a uh issue that everybody's dealing with right now.

627
00:35:26,440 --> 00:35:30,359
Speaker 1: It is a fascinating issue. In China. I don't think

628
00:35:30,360 --> 00:35:34,080
Speaker 1: they have that they have that debate, do that. Uh No,

629
00:35:34,200 --> 00:35:38,120
Speaker 1: I mean there's definitely a different system. But I mean,

630
00:35:38,120 --> 00:35:41,320
Speaker 1: but that right there is is fascinating. I mean weighing

631
00:35:41,400 --> 00:35:45,920
Speaker 1: the different privacy issues with uh, with how how that

632
00:35:45,960 --> 00:35:48,960
Speaker 1: fits in in the Western world, how that fits in America.

633
00:35:49,000 --> 00:35:51,200
Speaker 1: I mean, that's literally going to be I think a

634
00:35:51,200 --> 00:35:53,280
Speaker 1: debate that we're having in the in the judicial system

635
00:35:53,360 --> 00:35:57,200
Speaker 1: and the at the election during elections for quite several times.

636
00:35:57,239 --> 00:35:59,560
Speaker 1: To come listen, I really want to thank you because

637
00:36:00,200 --> 00:36:02,839
Speaker 1: this is a very confusing issue and there's so much

638
00:36:03,400 --> 00:36:05,200
Speaker 1: out there on it. But I have a much better

639
00:36:05,280 --> 00:36:08,040
Speaker 1: understanding now of how contact tracing works. It relies on

640
00:36:08,040 --> 00:36:12,080
Speaker 1: bluetooth technology, your phone picking up signals from other phones,

641
00:36:12,120 --> 00:36:14,840
Speaker 1: and this whole debate of privacy, and it's one that

642
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Speaker 1: we're gonna be having for quite a long long time.

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Speaker 1: Richard Whang, CEO of Coding Dojo and an M I

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Speaker 1: T sector practice leader for Future of Work and Education

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Speaker 1: at the Martin Trust Center. UH, talking about opening America

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Speaker 1: back up again through the use of artificial intelligence, contact tracing,

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Speaker 1: and technology that does it for me. I'm Kevin Cirelli,

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Speaker 1: Chief Washington correspondent for Bloomberg Television and for Bloomberg Radio.

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Speaker 1: Have a great rest of your evening. Thanks for listening

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Speaker 1: to Bloomberg and kind of that long