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Speaker 1: Our two.

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Speaker 2: Twin Cities news Talk Am eleven thirty and one oh

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Speaker 2: three five FM.

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Speaker 1: I failed to mention that last hour year.

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Speaker 2: Foes of the Show as we broadcast from the sixty

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Speaker 2: five to one carpet plus next day install studios. Eu

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Speaker 2: Phoes of the Show were brought to you by Dwight Dora.

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Speaker 2: You see, Dwight Dora has an election today. I'm working

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Speaker 2: off of an article from the Minnesota Reformer. Of all

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Speaker 2: places voters will decide today who controls the Minnesota Senates.

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Speaker 2: To get a couple of different races, the most contested

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Speaker 2: one and we'll get to East Metro Wright County and

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Speaker 2: the other elections here in just a moment. But Senate

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Speaker 2: District forty seven you have Representative Amanda Hemingson Dieger running

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Speaker 2: as the DFL candidate. Includes Woodbury, part of Maplewood. This

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Speaker 2: was the seat formally held by the Minnesota Democrat df.

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Speaker 1: Fella Nicole Mitchell.

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Speaker 2: District forty seven leans blue, but it could be competitive

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Speaker 2: in a low turnout special election to replace the disgrace

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Speaker 2: to Democrat and Dwight Dora is the Republican candidate.

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Speaker 1: I say that he is.

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Speaker 2: The Foes of the Show are brought to you by

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Speaker 2: him because typically he listens to the show right around

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Speaker 2: this time and says he especially.

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Speaker 1: Likes it when I call out the foes of the show.

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Speaker 1: So I did that in honor of him.

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Speaker 2: The Republican candidate, Dwight Dora, is an Air Force veteran

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Speaker 2: teacher in the Junior ROTC program at Johnson High School

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Speaker 2: in Saint Paul. Retired colonel served in Afghanistan. We thank

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Speaker 2: him for his service. In twenty twenty two. Dora did

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Speaker 2: lose his bid for District forty seven seat to Mitchell

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Speaker 2: at the time. So if Hemingson Dieger wins the Senate election,

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Speaker 2: Governor Tim Walls will need to call another special election

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Speaker 2: to replace her in the House. So it goes like

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Speaker 2: voters in the East Metro and Wright County will decide

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Speaker 2: who controls the Minnesota Senate. Today, you have two different

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Speaker 2: seats that are up for grabs. You have the GOP

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Speaker 2: Senate Bruce Anderson and Buffalo passing away in July. As

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Speaker 2: I just mentioned Nicole Mitchell's seat. Prior to the two

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Speaker 2: vacancies earlier this year, Democrats controlled the Minnesota Senate thirty

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Speaker 2: four to thirty three. The party endorsed candidates in both

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Speaker 2: the Senate districts also won their August primaries. Now, Senate

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Speaker 2: District twenty nine, wherein you have Michael Holstrom Junior running

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Speaker 2: as the Republican candidate, which includes Buffalo, Monticello, Delano, Annandale.

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Speaker 2: The seat was formably held by Senator Bruce Anderson and

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Speaker 2: as a matter of fact, Michael Holstrom joins us on

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Speaker 2: the show this morning on this election day. Thank you

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Speaker 2: so much for calling in Michael in such short notice.

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Speaker 2: I appreciate it.

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Speaker 1: Good morning, thanks, Shawn.

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Speaker 3: I appreciate you taking the call. It is an exceptional

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Speaker 3: election day here in Minnesota and we are all excited

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Speaker 3: to get out there and turn the state red. Like

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Speaker 3: you said in Senate District forty seven, we have a

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Speaker 3: real tas to take back the Senate, which would be

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Speaker 3: just exceptional.

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Speaker 1: Yeah, what are you hearing?

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Speaker 2: You know your seat, Michael in District twenty nine, you

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Speaker 2: know to safely red district.

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Speaker 1: I know you still have been busy.

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Speaker 2: We shared some audio recently where you were giving your

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Speaker 2: opinion of which I agree with, of where the Democrat

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Speaker 2: Party currently is. We were talking about this earlier in

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Speaker 2: the show. I'm curious though, to get your on the

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Speaker 2: ground perspective. You know, it's one thing for individuals like

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Speaker 2: myself to talk on the radio and you know, use

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Speaker 2: the anecdotes that I see in the news that I

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Speaker 2: covered to give my perception of the Democrat Party as

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Speaker 2: a whole. But what are voters saying to you when

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Speaker 2: you've been out speaking with individuals, whether it's for your

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Speaker 2: race or for this District forty seven race.

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Speaker 3: Yeah, we had close to one thousand doors in Wright

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Speaker 3: County in sen different twenty nine across the whole district

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Speaker 3: this last weekend, and I was shocked to see how

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Speaker 3: many people were not just aware, but we're paying attention

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Speaker 3: and excited for the race. That gives me a lot

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Speaker 3: of hope. I think we have a lot of opportunity

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Speaker 3: to move that momentum into twenty twenty six. People are

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Speaker 3: really excited to get rid of walls. That's number one

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Speaker 3: comment I here is, you know, let's get at a wall.

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Speaker 3: And I have a lot of hope.

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Speaker 4: How much is.

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Speaker 1: Trump and factoring into the conversation.

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Speaker 2: I bring that up because I'm going to cover an

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Speaker 2: editorial and it's an article, but it really is an

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Speaker 2: editorial out of the Star Tribune relating to Lisa Damuth

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Speaker 2: jumping into the race, and they are already trying to

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Speaker 2: tie her to Trump as best they can. She mentioned

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Speaker 2: Trump in her campaign launch piece, and I'll talk about

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Speaker 2: this in a moment, but I'm curious, you know, how

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Speaker 2: much is Trump factoring into the discussion with voters to

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Speaker 2: whom you've spoken with.

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Speaker 3: Not a lot, Honestly. Every now and then you hear

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Speaker 3: a negative comment, you hear a lot more positive comments.

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Speaker 3: People still have the Trump flags out, but people are

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Speaker 3: paying attention to state politics for the first time since

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Speaker 3: I've been paying attention here in Minnesota. So it's it's

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Speaker 3: a good sign.

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Speaker 2: Talking with my Holt from Junior again running Senate District

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Speaker 2: twenty nine. Now again it's a safely red district, but

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Speaker 2: that doesn't mean that people don't need to get out

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Speaker 2: and vote. So I'm going to give you an opportunity

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Speaker 2: to do a last minute plug and encourage people to

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Speaker 2: get out to and vote.

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Speaker 5: Today.

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Speaker 3: Well, today's the day everyone senat District twenty nine. Sen

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Speaker 3: the District forty seven. If you live there, Wright County,

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Speaker 3: Meeker County, and Western Hennithan County, we need your vote.

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Speaker 3: It is a safe red district on a normal years,

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Speaker 3: but we have a special election and anything can happen,

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Speaker 3: So make sure you get out there, Call your friends,

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Speaker 3: call your neighbors. Do you have questions for us, Mike

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Speaker 3: Fremansenate dot com. I'm happy to answer them. Other than that,

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Speaker 3: we really appreciate your time this morning, and we really

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Speaker 3: look forward to serving this district.

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Speaker 2: What are your voting plans today? I'm sorry to say,

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Speaker 2: what are your voting plans?

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Speaker 1: How are you going to be spending your day?

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Speaker 3: Oh? Well, I'm actually at the polls right now. I'm

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Speaker 3: about to go vote, and then we're going to be

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Speaker 3: knocking on doors this morning and then moving to phone

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Speaker 3: banking the rest of the day until seven thirty. Well,

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Speaker 3: so if you are in Wright County, reach out to us.

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Speaker 3: We'd love to have your help.

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Speaker 1: Say hi to everybody as you go and vote.

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Speaker 2: And thank you again for calling in this morning, Michael Holster,

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Speaker 2: I greatly appreciate it.

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Speaker 3: Thanks Sean.

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Speaker 2: All right, let's get back to a few of your

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Speaker 2: talk backs from the iHeartRadio app brought to you by Lindahl, Realty.

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Speaker 6: One and John Listening to Democrats lecture Republicans about the

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Speaker 6: constitutions about astifying as listening to atheist lecture Christians about

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Speaker 6: the Bible. They just don't understand what they're reading, or

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Speaker 6: I have never read it, or misusing it. Have a

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Speaker 6: great day.

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Speaker 4: A defining feature of today's Democratic Party is a belief

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Speaker 4: in the exact opposite of every bit of wisdom that

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Speaker 4: has ever come out of the Western world. Just go

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Speaker 4: ahead and look at the seven Deadly sins. The Democratic

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Speaker 4: Party celebrates every single one of them. They start with

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Speaker 4: parades for pride, and now they have Helena Monte handoff

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Speaker 4: candidates who are openly calling for Hey, go ahead and

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Speaker 4: have all the wrath you want.

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Speaker 2: Yeah, yeah, it really is. It's a scary situation. It's

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Speaker 2: a scary situation. And what concerns me more about today

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Speaker 2: is really tomorrow, and not from a policy standpoint, necessarily,

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Speaker 2: but more from a narrative commentary standpoint, because if Democrats

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Speaker 2: do get the victories that they expect today, we'll talk

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Speaker 2: about the mayoral race. The conventional wisdom is that Mayor

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Speaker 2: Jacob Fry should probably win reelection, but you just don't

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Speaker 2: know when it comes to ranked choice voting. But if

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Speaker 2: Democrats end up having a lot of victories today, the

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Speaker 2: commentary tomorrow is going to continue to be what it

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Speaker 2: is we've been talking about this morning. The Democrats will

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Speaker 2: continue to double down on what they're doing. And while

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Speaker 2: I have an expectation that if Trump does release some

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Speaker 2: of this emergency funding relating to SNAP and we get

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Speaker 2: past the election day today, Democrats may decide to go

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Speaker 2: and reopen the government. We played Ted Cruz yesterday on

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Speaker 2: the show. I've offered up similar commentary that Democrats have

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Speaker 2: been waiting since they were able to push the shut

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Speaker 2: down this long. They're waiting until after today before they

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Speaker 2: reopen the government.

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Speaker 1: But if they feel like they're making.

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Speaker 2: Headway by fomenting the anger on the left, then maybe,

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Speaker 2: you know, those predictions of their reopening the government don't

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Speaker 2: end up happening.

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Speaker 5: I just don't know.

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Speaker 2: But I'm more concerned about the narrative and the Democrats

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Speaker 2: continuing to go down the path that we are on

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Speaker 2: because unfortunately, and I know it sounds over the top,

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Speaker 2: but more people are going to die. That is what

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Speaker 2: is going to happen. I mean, we now live in

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Speaker 2: this assassination culture, and for the individual that can be

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Speaker 2: brave on a voicemail like that, Hell in the City

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Speaker 2: Commission candidate. You know there are other individuals out there

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Speaker 2: who listen to the words of Nancy Pelosi that we

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Speaker 2: paid this morning. The most vile creature on the planet

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Speaker 2: is Donald Trump. I mean, I won't bore you with

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Speaker 2: the comments from Walls, but you know what he said.

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Speaker 2: When you have individuals convinced that they're very livelihood democracy

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Speaker 2: and their lives are at stake, and you have individuals

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Speaker 2: out there not facing any sort of accountability for their

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Speaker 2: over the top rhetoric, then yeah, there will be people inspired,

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Speaker 2: just like we've already seen, to go and commit horrible,

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Speaker 2: heinous acts of violence. Coming up Rachelle Olson's back, Damuth

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Speaker 2: brings Trump into the governor's race, leaning into mega outrage.

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Speaker 2: So I suppose we know now who the Strip believes

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Speaker 2: as the front runner in the governor's race. We'll sure

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Speaker 2: some details on that. I'll also get you up to

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Speaker 2: speed with the latest regarding the Michigan terror suspects who

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Speaker 2: plotted to target bars nightclubs during Halloween celebrations.

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Speaker 1: And then we'll talk with d V Gartenstein Ross.

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Speaker 2: We'll get into some artificial intelligence questions, a bit of

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Speaker 2: Q and A with DVD, including as we talk about

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Speaker 2: the school board races, AI allowing more time for students

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Speaker 2: being a positive in the classroom. It's all coming up

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Speaker 2: on Twin City's News Talk Am eleven thirty and one

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Speaker 2: to three five FM.

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Speaker 1: Twin City's News Tom from the six to five one

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Speaker 1: Carpet Next Day Install Studios. My name is John Justice.

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Speaker 2: David Gartzenstein Ross joining us in about ten minutes. Got

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Speaker 2: a number of issues we'll talk about with Dav'd almost

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Speaker 2: nine to ten say foreign governments will likely use AI

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Speaker 2: to attack the US. Speaking of attacks on the US,

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Speaker 2: we'll update you on the Michigan the Michigan terrorist suspects

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Speaker 2: plotting to target bars and nightclubs during their Halloween celebrations.

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Speaker 2: But first, let's go here. Rochelle Olson Minnesota Star Tribune

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Speaker 2: has a new piece up relating to Lisa Damouth's announcement

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Speaker 2: to run for governor. Rochelle Raschon. While her capital colleagues

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Speaker 2: generally avoid invoking the president's name, the House Speaker's first

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Speaker 2: move as a statewide candidate was to angle for Trump's endorsement. Yes,

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Speaker 2: the media marching orders have been released to tie Damouth

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Speaker 2: to Trump. We now know who the Strip believes as

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Speaker 2: the front runner for the governor's race on the GOP

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Speaker 2: side of things. At a Capital news conference and in

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Speaker 2: an online video, writes Rachelle Olson in The Star Tribune,

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Speaker 2: Damus said she wants to help Minnesotans afford their lives,

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Speaker 2: although she was fussy on details about how she would

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Speaker 2: deliver funny unless I miss, I don't recall this level

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Speaker 2: of scrutiny over Governor Tim Walls and his ad campaign

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Speaker 2: launch just out of curiosity.

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Speaker 7: I've been to every corner of Minnesota and there's nothing

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Speaker 7: like it.

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Speaker 6: Red and blue, and there's all that red across there.

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Speaker 7: Democrats go into depression over it. It's mostly rocks and

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Speaker 7: cows that are in that red area.

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Speaker 1: What was clear is that she was on the move

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Speaker 1: against Walls.

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Speaker 2: Well, yeah, it's the Democrat governor running for reelection, Okay.

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Speaker 2: She goes on to describe the details of the video

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Speaker 2: that Damuth released, then writing damos voiceover returns to saying

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Speaker 2: that Walls is more interested in attacking Trump than fixing Minnesota.

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Speaker 2: Those are the only two sides to Damouth's debut video,

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Speaker 2: Trump versus Walls. It's like a self fulfilling prophecy listen

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Speaker 2: Damuth knows what Rasselle Olson knows, and that Trump is

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Speaker 2: the only thing that Walls can use against his opponents.

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Speaker 2: He can't tout anything that he's done here beyond his

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Speaker 2: free meals for students. Right now, he's plagued with the

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Speaker 2: fraud that has happened underneath his watch, and so of

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Speaker 2: course he's gonna have to go and use Trump to

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Speaker 2: go after her, and damonth is being smart and being

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Speaker 2: upfront about that. Raschelle goes on to say it wasn't

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Speaker 2: wholly surprising, but a little disappointing.

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Speaker 1: Oh, Rachelle was disappointed.

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Speaker 2: Rachelle raschon As if Rochelle Olson was ever going to

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Speaker 2: go and vote for Damuth or any of the GOP candidates,

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Speaker 2: Damuth could have hewed. Her could have hewed closer to

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Speaker 2: her capital persona, which is an even keeled and deliberate

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Speaker 2: Midwestern warmth, not Maga ferocity and outrage. Maybe this is

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Speaker 2: merely foreshadowing of what's to come. Oh, it's my favorite.

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Speaker 2: My favorite is when a leftist is saying how a

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Speaker 2: conservative should go and get elected. Her alignment with Trump

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Speaker 2: is an entirely new says Michelle. She was on stage

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Speaker 2: briefly with him when he was in Saint Cloud for

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Speaker 2: a capital rally in July of twenty twenty four.

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Speaker 1: She was there standing next to him. I saw it.

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Speaker 2: Guilt from a lack of social distancing. Damuth is going

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Speaker 2: to face many more questions about when and if she

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Speaker 2: will side with Trump and the extent of her agreement

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Speaker 2: with his policy. She's need to provide to those clear

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Speaker 2: answers on Trump and much more, including her own positions.

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Speaker 2: For example, she described in her launch video as Minnesota

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Speaker 2: being overtaxed, then was unwilling or perhaps unprepared, to detail

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Speaker 2: what taxes or policy she wants to roll back. Did

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Speaker 2: the Walls campaign did they write this?

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Speaker 7: By the way, I've seen how we help each other

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Speaker 7: through the hard times. But I've not been perfect, and

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Speaker 7: I'm a knucklehead at times. But it's in these moments

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Speaker 7: we have to come together. I called Donald Trump, I

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Speaker 7: wanna be dictator. You bully the shot of him, and

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Speaker 7: I'll never stop fighting to protect us from the chaos,

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Speaker 7: corruption and cruelty coming out of Washington. Well maybe it's

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Speaker 7: time for us to be a little meaner.

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Speaker 2: You want to talk about a lack of substance, I

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Speaker 2: give you that ad. Given the Damuth is clearly courting Trump,

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Speaker 2: she should delineate her agreements and divergence with the President,

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Speaker 2: as well as how she as governor would accommodate him

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Speaker 2: in Minnesota. Welcome to the race. As she wraps up, Speaker, Damuth,

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Speaker 2: you've major splash. Now, let's get beyond Trump and Walls

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Speaker 2: and hear about your plans. Now, Damoth or whoever the

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Speaker 2: nominee is for the governor's race, all they need to

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Speaker 2: do is rally the base, so the base can rally

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Speaker 2: the casuals to increase the voter turnout. That's it. It's

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Speaker 2: as equally hard as it is simple. But that's all

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Speaker 2: that needs to go and take place because there is

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Speaker 2: no debating with Walls, there is no debating.

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Speaker 1: With Democrats right now.

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Speaker 2: It's going to be all about who shows up on

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Speaker 2: election day to vote, all right. Briefly ahead of my

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Speaker 2: conversation with David Gartenstein, Ross Ai Na, let's answering your

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Speaker 2: questions this morning. You can get those into the iHeartRadio app.

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Speaker 2: You know, yesterday we covered the Michigan terror suspects applauding

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Speaker 2: to target bars and nightclubs during Halloween celebrations.

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Speaker 1: Newsweek.

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Speaker 2: Other outlets completely downplayed this threat, focusing on the lawyers

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Speaker 2: defending the suspects, saying that there was no truth behind it.

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Speaker 2: Now we find out in the seventy three page complaint

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Speaker 2: that you have Mohmed Ali, Majid mah Mood, and a

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Speaker 2: juvenile suspect, along with five co conspirators. They've been charged

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Speaker 2: with seeking to carry out a terrorist attack for ISIS,

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Speaker 2: hoping to copy the twenty fifteen Paris terrorist attack that

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Speaker 2: killed more than one hundred and thirty people. They code

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Speaker 2: named the attack Day Pumpkin, led investigators to believe the

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Speaker 2: planned attack would be carried out out on Halloween, when

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Speaker 2: bars and nightclubs would be full of party years. The suspects,

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Speaker 2: who were all under twenty one, allegedly sought guidance from

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Speaker 2: the father of a local Islamic extremist idea logue on

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Speaker 2: when to conduct their attack. Ali lives in Dearborn, Michigan.

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Speaker 2: The criminal complaint states that all Lead and Mahmud met

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Speaker 2: multiple times at night in parks in Dearborn. Alid and

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Speaker 2: Mahmoud also shared ISIS related materials through encrypted messaging and

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Speaker 2: social media apps. They scoped out the sites of potential

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Speaker 2: targets for their attack. In September, they drove past numerous

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Speaker 2: bars and clubs in the region, also checking out a

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Speaker 2: place that was a known go to party spot for

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Speaker 2: gay people. The FBI also said the suspect practice shooting firearms,

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Speaker 2: including AR fifteen style rifles, at a gun range in

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Speaker 2: September and October. The federal authorities served search warrants at

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Speaker 2: all Leeds and mop Moons homes in October October thirty first,

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Speaker 2: where they recovered three AR fifteen style rifles, two shotguns,

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Speaker 2: four handguns, and more than sixteen hundred rounds of ammunition

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Speaker 2: capable or excuse me, compatible with the three AR fifteen

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Speaker 2: style rifles, optical sites, two go pro cameras, a flash suppressor,

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Speaker 2: tactical vets, and other related firearms parts and accessories. And

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Speaker 2: this is being buried by the mainstream media for all

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Speaker 2: the reasons that you know. It's being buried by the

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Speaker 2: mainstream media and the articles when they were released yesterday,

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Speaker 2: of which there's been no follow up. Again, we're focused

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Speaker 2: on one lawyer working on behalf of one of the

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Speaker 2: suspects saying none of this is real. That was it,

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Speaker 2: and now you know the truth of what actually could

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Speaker 2: have happened if it hadn't been for the good work

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Speaker 2: by the FBI, Cash.

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Speaker 1: Hotel and those others working with the FBI.

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Speaker 2: Eighty seven percent of US adults said it is somewhat

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Speaker 2: or very likely that AI technology will be used to

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Speaker 2: target the country. According to a poll, exactly how would

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Speaker 2: that happen? We'll talk with our AI analyst and expert,

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Speaker 2: Divide Gartenstein Ross. So also I answer your questions from

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Speaker 2: the iHeartRadio app Talkbacks next here on Twin Cities News

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Speaker 2: Talk Am eleven thirty and one oh three five FM.

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Speaker 2: And now I started off the show today talking about

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Speaker 2: how with it being election day and also the passing

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Speaker 2: of former Vice President Dick Cheney, you can expect that

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Speaker 2: social media is just going to be a cesspool of

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Speaker 2: horrible commentary. I was first off correct on that front.

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Speaker 2: That was an easy prediction to make. But apparently this

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Speaker 2: is also spilling in to polling sites. There was news

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Speaker 2: that just broke that a handful of bomb threats have

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Speaker 2: been called into multiple polling the locations in New Jersey

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Speaker 2: with the governor's race there, and so many of those

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Speaker 2: polling locations had to close, forcing election day voters out

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Speaker 2: of at least to two of the several locations where

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Speaker 2: these were called in. So we'll continue to update you here,

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Speaker 2: especially on the top of the hour news on Twin

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Speaker 2: Cities News Talk, and we'll talk further about threats coming

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Speaker 2: up in just a moment with our guest AI analyst

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Speaker 2: and expert CEO at the Expert Theory, David Gartenstein or

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Speaker 2: OSCOD Morning Devid.

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Speaker 5: Good morning, John, great to join you.

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Speaker 2: Let's start here for a couple of listeners that had

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Speaker 2: rowed in and those that are familiar with you from

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Speaker 2: the times that we have talked throughout the years, working

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Speaker 2: off of your expertise and counter terrorism, but now talking

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Speaker 2: with artificial intelligence. They were curious what your specific background

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Speaker 2: was in artificial intelligence and the change over, you know,

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Speaker 2: from when we used to talk about counter terrorism and

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Speaker 2: now we're focused on AI.

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Speaker 5: That's an awesome question. So, uh, early on in my life,

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Speaker 5: I was an adopter of a couple of things I

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Speaker 5: do now. I you know, when I was very young,

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Speaker 5: got into coding and did a lot of that several

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Speaker 5: computer languages ago. But it gave me a relatively good

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Speaker 5: understanding of the internal processes that computers use. Even though

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Speaker 5: the languages that I code in are not current. The

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Speaker 5: other thing is, as a kid, I was really big

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Speaker 5: into games, you know, role playing games, Dungeons and Dragons

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Speaker 5: and the like. I didn't think either of these things

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Speaker 5: would end up being very relevant for me until, you know,

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Speaker 5: probably about five years ago. I'd been using AI for years.

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Speaker 5: Artificial intelligence and a couple of my big lines of

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Speaker 5: effort at Valence Global, both in building games and also

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Speaker 5: looking at them to predict the path of terrorist attacks,

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Speaker 5: and actually built an early AI platform around twenty seventeen

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Speaker 5: that could predict terrorist attacks and also other threat So

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Speaker 5: it's a skill set that I had used to use

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Speaker 5: in service of my substantive work in counter terrorism, and

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Speaker 5: eventually my interest in both artificial intelligence and also in

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Speaker 5: games as a method of better understanding the world eclipsed

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Speaker 5: my interest in some of the underlying substantive questions that

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Speaker 5: I asked as an analyst, you know, specifics of what's

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Speaker 5: going on inside terrorist groups and their relationships with one

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Speaker 5: another and the threats that they pose. So my current

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Speaker 5: work very much was an outgrowth of my last professional work. Interestingly,

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Speaker 5: it's in line with kind of what I encourage people

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Speaker 5: to do in a world of AI, which is to

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Speaker 5: develop multiple interlocking sets of skills and to be able

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Speaker 5: to lean into other skills as they become more relevant

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Speaker 5: or more valuable. I think that's the path that I took,

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Speaker 5: and especially given what a weird and wonderful frontier AI is,

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Speaker 5: I'm really glad that my career developed in that way.

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Speaker 2: We just shared the details a moment ago of the

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Speaker 2: Michigan terrorst aspects plotting the target bars and nightclubs during

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Speaker 2: Halloween celebrations. FBI made these arrests heading into the weekend.

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Speaker 2: I've been sitting on this one for a while to

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Speaker 2: v This was a Gallup poll from a few weeks back.

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Speaker 2: Eighty seven percent of adults said it was somewhat are

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Speaker 2: very likely that AI technology will be used to target

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Speaker 2: the country. Americans have mixed views on what AI means

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Speaker 2: for national security, with forty one percent saying the technology

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Speaker 2: will leave the country worse than thirty seven percent believing

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Speaker 2: it will be better for national security. We have a

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Speaker 2: couple of questions along these lines, the sort of baseline

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Speaker 2: AI questions, but when it comes to terrorism, foreign governments

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Speaker 2: using AI to attack the US, how would they go about?

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Speaker 2: How would AI be utilized for our adversaries to move

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Speaker 2: against us.

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Speaker 5: One of the interesting and frightening questions is that I

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Speaker 5: would flip it and just say, how will it not belied.

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Speaker 5: A lot of my last job, as we just put

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Speaker 5: our finger on, was spent figuring out how bad people

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Speaker 5: will do bad things with new technologies that people are

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Speaker 5: optimistic about. And we've been able to clearly see that

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Speaker 5: with social media. Right, you and I have been talking

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Speaker 5: long enough that we remember this wave of massive optimism

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Speaker 5: people had about social media with the Arab Spring revolutions

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Speaker 5: of twenty eleven, and how this was supposed to bring

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Speaker 5: democracy to the Arab world and beyond, and things did

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Speaker 5: not quite work out that way, to put it mildly,

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Speaker 5: So let's just go over a few things we talked about,

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Speaker 5: the jihadist terrorist plot in Michigan, the Halloween plot. AI

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Speaker 5: can be used by foreign governments to help to encourage

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Speaker 5: people to carry out attacks. They can create personas for handlers,

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Speaker 5: or they can take create online buzz or simply use

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Speaker 5: AI to supercharge attempts to build partisan splits or to

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Speaker 5: target different figures. If you look at some of the

438
00:25:00,040 --> 00:25:02,800
Speaker 5: ronment that we have in the country things that led to,

439
00:25:02,840 --> 00:25:07,320
Speaker 5: for example, the assassination of Charlie Kirk or Melissa Hortman.

440
00:25:08,840 --> 00:25:12,520
Speaker 5: I don't want to over emphasize what foreign governments have done,

441
00:25:12,880 --> 00:25:17,719
Speaker 5: but they certainly have been attempting to ratchet up the tension.

442
00:25:18,160 --> 00:25:22,199
Speaker 5: AI can be used in attacks on electrical facilities or

443
00:25:22,240 --> 00:25:26,160
Speaker 5: water infrastructure. We already know that PRC, the People's Republic

444
00:25:26,200 --> 00:25:29,840
Speaker 5: of China, has been able to breach a large number

445
00:25:29,880 --> 00:25:33,440
Speaker 5: of critical utilities across the country. AI can be used

446
00:25:33,440 --> 00:25:36,600
Speaker 5: to supercharge those attacks. AI can be used in hacking,

447
00:25:36,680 --> 00:25:42,600
Speaker 5: to take out, for example, military airplanes civilian aircraft, to

448
00:25:43,080 --> 00:25:47,200
Speaker 5: attack battle carriers that the US has. I'll just add

449
00:25:47,240 --> 00:25:48,840
Speaker 5: one final thing because you get the sense of why

450
00:25:48,840 --> 00:25:51,359
Speaker 5: ie flip the question around, But if you look at

451
00:25:51,440 --> 00:25:54,159
Speaker 5: broader US interests, one thing that we're talking about a

452
00:25:54,160 --> 00:25:58,840
Speaker 5: lot these days is China invading Taiwan. If and when

453
00:25:58,880 --> 00:26:02,200
Speaker 5: that happens, one of the very first things China will

454
00:26:02,240 --> 00:26:08,320
Speaker 5: do upon successfully seizing Taiwan is use AI to round

455
00:26:08,400 --> 00:26:12,840
Speaker 5: up Taiwanese who've been involved in resilience or resistance efforts.

456
00:26:12,840 --> 00:26:16,040
Speaker 5: Getting ready for a PRC occupation. They'll use AI to

457
00:26:16,080 --> 00:26:18,640
Speaker 5: try to round up as many people as possible who

458
00:26:18,640 --> 00:26:21,680
Speaker 5: could pose a threat to their conquest of Taiwan. These

459
00:26:21,680 --> 00:26:24,280
Speaker 5: are just a few of the ways foreign adversaries will

460
00:26:24,359 --> 00:26:27,520
Speaker 5: use AI for sure to attack us. Obviously we'll use

461
00:26:27,560 --> 00:26:30,879
Speaker 5: AI to defend ourselves. But it's a ballgame that I

462
00:26:30,920 --> 00:26:35,120
Speaker 5: don't think anybody has fully mapped out or understood yet.

463
00:26:35,720 --> 00:26:40,080
Speaker 2: Real again, real basic question here. It comes from Morris

464
00:26:40,200 --> 00:26:43,720
Speaker 2: under m N underscore Morris Morris on X can you

465
00:26:43,760 --> 00:26:48,200
Speaker 2: please ask Davide how the heck Sora does what it does?

466
00:26:48,520 --> 00:26:48,680
Speaker 1: Yeah?

467
00:26:48,720 --> 00:26:51,680
Speaker 2: How does Sora go and create those videos? Just off

468
00:26:51,680 --> 00:26:53,080
Speaker 2: of simple basic prompts?

469
00:26:54,640 --> 00:26:57,040
Speaker 5: All right, this is going to be a little technical

470
00:26:57,119 --> 00:26:59,840
Speaker 5: because I want to actually honor his response. I'll try

471
00:26:59,880 --> 00:27:02,679
Speaker 5: to make it boring so as I think your listeners know,

472
00:27:03,040 --> 00:27:08,040
Speaker 5: Sora is a text to video generative AI model. That is,

473
00:27:08,040 --> 00:27:10,959
Speaker 5: you give it a prompt and it generates a short

474
00:27:11,119 --> 00:27:14,840
Speaker 5: video clip that will match the prompt. And so what

475
00:27:14,880 --> 00:27:18,480
Speaker 5: it does is people who are familiar with DOLLI, dolli

476
00:27:18,600 --> 00:27:22,239
Speaker 5: is also part of chat GPT. It's you type in

477
00:27:22,280 --> 00:27:24,480
Speaker 5: what you want for an image and it will generate

478
00:27:24,680 --> 00:27:27,639
Speaker 5: a really good image for you. Everyone has seen obviously

479
00:27:27,720 --> 00:27:31,840
Speaker 5: AI cartoons or AI pictures, so what it does is

480
00:27:31,880 --> 00:27:36,160
Speaker 5: it starts with noise and it gradually produces an image

481
00:27:36,600 --> 00:27:40,480
Speaker 5: based on that noise. So what Sora does is it

482
00:27:40,560 --> 00:27:44,000
Speaker 5: uses the same model as Dolli Generative AI for image,

483
00:27:44,480 --> 00:27:47,880
Speaker 5: but it uses something called video diffusion. So this adds

484
00:27:48,000 --> 00:27:50,720
Speaker 5: a key dimension to the image, the image of time.

485
00:27:51,520 --> 00:27:55,320
Speaker 5: So it needs to keep frames consistent across motion, across

486
00:27:55,400 --> 00:28:00,520
Speaker 5: changing scenes, across changing objects, and it combines a diffusion

487
00:28:00,600 --> 00:28:04,840
Speaker 5: model with a transformer model in order to create this

488
00:28:04,960 --> 00:28:07,520
Speaker 5: temporal dimension to it. That's as technical as I'm going

489
00:28:07,560 --> 00:28:09,520
Speaker 5: to get, but we could we could nerd out a

490
00:28:09,520 --> 00:28:13,199
Speaker 5: little bit more. But basically, it's the same model as DOLLI,

491
00:28:13,880 --> 00:28:16,960
Speaker 5: but matched into a third dimension, the dimension of time,

492
00:28:17,600 --> 00:28:20,119
Speaker 5: which is what allows it to function as video and

493
00:28:20,240 --> 00:28:21,760
Speaker 5: not just as still image.

494
00:28:22,119 --> 00:28:30,320
Speaker 2: If I ask an an AI video generator to create

495
00:28:31,320 --> 00:28:35,199
Speaker 2: a version of John Justice as a Star Wars X

496
00:28:35,240 --> 00:28:39,200
Speaker 2: Wing pilot, I think we've talked about this before. Is

497
00:28:39,240 --> 00:28:44,000
Speaker 2: it akin to what Napster used to do with, you know,

498
00:28:44,080 --> 00:28:47,480
Speaker 2: searching for a particular song. Napster would reach out to

499
00:28:47,840 --> 00:28:51,600
Speaker 2: other computers that were attached to the platform and basically

500
00:28:51,680 --> 00:28:55,440
Speaker 2: piece it together to create the song. In total, does

501
00:28:55,480 --> 00:28:58,120
Speaker 2: AI does the same thing. Is it reaching out across

502
00:28:58,200 --> 00:29:01,959
Speaker 2: what is available to it and grabbing the relevant information

503
00:29:02,120 --> 00:29:04,360
Speaker 2: of what a next wing fighter pilot would look like

504
00:29:04,400 --> 00:29:06,640
Speaker 2: and what I look like, and then create the image

505
00:29:06,680 --> 00:29:07,920
Speaker 2: or video based off that.

506
00:29:09,360 --> 00:29:14,960
Speaker 5: Yes, with a one minor exception, which is that it's

507
00:29:15,000 --> 00:29:18,600
Speaker 5: already been trained on that, right, So sometimes it does,

508
00:29:19,080 --> 00:29:22,280
Speaker 5: you know, it does web searches for you, but it's

509
00:29:22,320 --> 00:29:24,960
Speaker 5: been trained on large amounts of information, so it already

510
00:29:25,000 --> 00:29:28,040
Speaker 5: has an understanding long before you type in the query

511
00:29:28,480 --> 00:29:31,080
Speaker 5: of who John Justice is, what an X wing fighter

512
00:29:31,080 --> 00:29:33,880
Speaker 5: pilot looks like, and the like, in order to put

513
00:29:33,920 --> 00:29:38,360
Speaker 5: them together based on what it knows about the world. Essentially,

514
00:29:38,760 --> 00:29:41,920
Speaker 5: as I think people understand, you know, large language models

515
00:29:42,320 --> 00:29:46,000
Speaker 5: like chat GPT have been trained on as much of

516
00:29:46,040 --> 00:29:50,680
Speaker 5: the human corpus of writing as possible. Essentially, they've a

517
00:29:50,760 --> 00:29:55,440
Speaker 5: large language model suctions in basically everything written that it

518
00:29:55,480 --> 00:29:56,600
Speaker 5: can possibly find.

519
00:29:57,240 --> 00:29:58,960
Speaker 2: We're gonna be talking a bit about the school board

520
00:29:59,040 --> 00:30:01,760
Speaker 2: races today. It's election day, of course across the country.

521
00:30:01,760 --> 00:30:03,479
Speaker 2: We'll get into that just after eight o'clock, and we're

522
00:30:03,520 --> 00:30:06,080
Speaker 2: going to talk briefly before the end of our conversation

523
00:30:06,200 --> 00:30:09,440
Speaker 2: this morning speaking with David Gartenstein, Ross or AI expert

524
00:30:09,520 --> 00:30:10,760
Speaker 2: on AI.

525
00:30:10,640 --> 00:30:11,560
Speaker 1: In the classroom.

526
00:30:11,600 --> 00:30:13,840
Speaker 2: Before we get to that, let's go to the iHeartRadio

527
00:30:13,880 --> 00:30:16,719
Speaker 2: app Talkbacks brought to you by Lindahl Realty for a

528
00:30:16,920 --> 00:30:17,680
Speaker 2: question for David.

529
00:30:19,200 --> 00:30:23,760
Speaker 8: David, I use AI quite a lot, both personally and professionally,

530
00:30:23,920 --> 00:30:27,920
Speaker 8: and I'm still astounded at the very simple mistakes that

531
00:30:28,000 --> 00:30:32,440
Speaker 8: it makes. So, for example, it will tell me on

532
00:30:32,520 --> 00:30:36,280
Speaker 8: a personal note, hey today on Thursday when you do

533
00:30:36,360 --> 00:30:41,040
Speaker 8: your gym workout, and I'm like, it's Tuesday.

534
00:30:41,920 --> 00:30:42,560
Speaker 4: Why is that?

535
00:30:43,360 --> 00:30:43,840
Speaker 1: Why is that?

536
00:30:43,960 --> 00:30:48,280
Speaker 5: David? Yeah, it makes a ton of mistakes, including it

537
00:30:48,880 --> 00:30:52,400
Speaker 5: makes mistakes most frequently about what the date is, what

538
00:30:52,520 --> 00:30:55,760
Speaker 5: day it is, et cetera. It seems like most lms

539
00:30:55,800 --> 00:30:59,320
Speaker 5: are just not trained on understanding where they are in time.

540
00:30:59,760 --> 00:31:03,400
Speaker 5: But leave that aside. Yeah, that's right. They make a

541
00:31:03,440 --> 00:31:07,000
Speaker 5: lot of errors. To step back, what I think is

542
00:31:07,040 --> 00:31:11,680
Speaker 5: amazing about them is just how much they get right right.

543
00:31:11,760 --> 00:31:18,440
Speaker 5: Prior to the massive leap forward in AI, we would

544
00:31:18,520 --> 00:31:22,800
Speaker 5: not have thought that a computer could talk as much

545
00:31:22,880 --> 00:31:26,080
Speaker 5: like a person or have or talk as quickly with

546
00:31:26,360 --> 00:31:30,240
Speaker 5: answers that are as detailed and well structured as what

547
00:31:30,320 --> 00:31:33,360
Speaker 5: it gives you. But there's still a lot of errors.

548
00:31:33,760 --> 00:31:35,800
Speaker 5: And this is one of the reasons why to make

549
00:31:35,880 --> 00:31:41,280
Speaker 5: most of AI you really need to be active and

550
00:31:41,360 --> 00:31:43,680
Speaker 5: not just blindly defer to it, because there's a lot

551
00:31:43,680 --> 00:31:45,960
Speaker 5: of things AI doesn't do well. It makes a lot

552
00:31:45,960 --> 00:31:47,960
Speaker 5: of mistakes and the like. And I also want to

553
00:31:49,600 --> 00:31:52,360
Speaker 5: offer my apologies to M. N. Morris, who seems a

554
00:31:52,400 --> 00:31:54,720
Speaker 5: little bit confused by my answer. He had a great

555
00:31:54,800 --> 00:31:58,040
Speaker 5: gift of saying huh, but I'm happy to go in later.

556
00:31:58,120 --> 00:32:02,680
Speaker 5: But bottom line, for you know, video generation is there's

557
00:32:02,720 --> 00:32:04,840
Speaker 5: complex things going on under the surface. I was trying

558
00:32:04,840 --> 00:32:07,320
Speaker 5: to lift things up a little bit, and at least

559
00:32:07,320 --> 00:32:08,880
Speaker 5: for him, perhaps it didn't quite work.

560
00:32:09,640 --> 00:32:13,640
Speaker 2: Before we before we talk a bit about education, and again,

561
00:32:14,040 --> 00:32:15,480
Speaker 2: you know, this kind of goes back to the early

562
00:32:15,520 --> 00:32:18,680
Speaker 2: conversations that you and I had and your outlook of

563
00:32:18,680 --> 00:32:23,240
Speaker 2: AI and education. We continue to see evidence of your

564
00:32:23,360 --> 00:32:26,160
Speaker 2: your thoughts and feeling towards it being reflected in actual

565
00:32:26,760 --> 00:32:30,560
Speaker 2: in actual classrooms. Just quickly, though, I have an article

566
00:32:30,600 --> 00:32:32,880
Speaker 2: here from the BBC and it says the number one

567
00:32:32,920 --> 00:32:35,680
Speaker 2: sign that you're watching AI video. They post you a

568
00:32:35,680 --> 00:32:38,400
Speaker 2: couple of it. They comment on a couple of things here.

569
00:32:38,760 --> 00:32:42,880
Speaker 2: They talk about resolution, quality and length of video. They

570
00:32:42,880 --> 00:32:46,480
Speaker 2: get into a lot of specificity regarding the resolution and

571
00:32:46,560 --> 00:32:49,880
Speaker 2: quality pixel images. I want to add something to this

572
00:32:49,920 --> 00:32:52,200
Speaker 2: and then get your thoughts on and ask the question

573
00:32:52,280 --> 00:32:54,240
Speaker 2: of what you think the easiest way is to spot

574
00:32:54,600 --> 00:32:59,160
Speaker 2: an AI video and just say that AI still, in

575
00:32:59,240 --> 00:33:03,240
Speaker 2: my opinions, still has that uncanny valley aspect of it

576
00:33:03,280 --> 00:33:07,880
Speaker 2: where you can you can with fair with fairly good accuracy,

577
00:33:08,000 --> 00:33:10,920
Speaker 2: say that's an AI video and not just based off

578
00:33:10,960 --> 00:33:13,160
Speaker 2: the content in and of it in and of itself

579
00:33:13,280 --> 00:33:17,160
Speaker 2: beyond the resolution, quality and length. But I'm curious what

580
00:33:17,200 --> 00:33:20,400
Speaker 2: do you think are the easiest ways to spot an

581
00:33:20,480 --> 00:33:21,160
Speaker 2: AI video?

582
00:33:21,800 --> 00:33:25,480
Speaker 5: But even those that they're giving I think are not accurate. John, Like,

583
00:33:25,560 --> 00:33:29,440
Speaker 5: think back to the video that you posted of Trump

584
00:33:29,720 --> 00:33:33,880
Speaker 5: talking about how terodactyls would be would be at the border, right,

585
00:33:34,080 --> 00:33:36,880
Speaker 5: Like that image quality was very good, Right, it looked

586
00:33:36,880 --> 00:33:39,680
Speaker 5: like a press a Trump press conference, Like you could

587
00:33:39,680 --> 00:33:41,760
Speaker 5: watch right up until he started talking about how he's

588
00:33:41,760 --> 00:33:45,040
Speaker 5: going to use terodactyls for border control, right up until

589
00:33:45,040 --> 00:33:46,600
Speaker 5: that you can watch it and think that it was

590
00:33:46,640 --> 00:33:50,080
Speaker 5: a real Trump press conference. Secondly, the length was it

591
00:33:50,120 --> 00:33:52,880
Speaker 5: was a long video. Yeah, it was not a short video.

592
00:33:53,280 --> 00:33:56,560
Speaker 5: So like I both agree with that analysis, but it

593
00:33:56,600 --> 00:34:00,320
Speaker 5: doesn't hold up in every situation. So look, what we

594
00:34:00,360 --> 00:34:04,600
Speaker 5: are getting into is a world in which we just

595
00:34:04,760 --> 00:34:07,960
Speaker 5: can't believe our eyes and the tells are less than

596
00:34:07,960 --> 00:34:09,759
Speaker 5: we would like. Right. You and I have talked a

597
00:34:09,760 --> 00:34:12,640
Speaker 5: lot about different aspects of deep deep fakes and AI

598
00:34:12,760 --> 00:34:16,160
Speaker 5: videos that are tells, And one thing I've always emphasized,

599
00:34:16,160 --> 00:34:18,719
Speaker 5: which is always born out, is that whatever we look

600
00:34:18,719 --> 00:34:21,960
Speaker 5: at as to tell, it goes away like quickly.

601
00:34:22,400 --> 00:34:22,560
Speaker 3: Right.

602
00:34:22,600 --> 00:34:24,680
Speaker 5: If you look at at what the tell was ten

603
00:34:24,800 --> 00:34:28,680
Speaker 5: years ago, it was that in AI videos people's eyes

604
00:34:28,719 --> 00:34:31,799
Speaker 5: don't blink. That is no longer the case, right. One

605
00:34:31,880 --> 00:34:36,239
Speaker 5: AI tell about six months ago is that AI does

606
00:34:36,320 --> 00:34:40,000
Speaker 5: not form realistic hans. Now you can be the judge

607
00:34:40,000 --> 00:34:42,359
Speaker 5: of whether it's forming realistic hans now. I think it's

608
00:34:42,360 --> 00:34:45,960
Speaker 5: a little bit inconsistent, but it can form realistic hans

609
00:34:46,320 --> 00:34:48,800
Speaker 5: a decent percentage of the time depending on what platform

610
00:34:48,800 --> 00:34:51,840
Speaker 5: you're using. So that tell isn't fully there. So this

611
00:34:51,920 --> 00:34:55,680
Speaker 5: is where we get into one big, big idea. We're

612
00:34:55,719 --> 00:34:58,799
Speaker 5: moving into a future where not only is a lot

613
00:34:58,800 --> 00:35:01,840
Speaker 5: of the content we're going to look at online AI generated,

614
00:35:02,400 --> 00:35:07,120
Speaker 5: but also a lot of the code is AI generated. Right,

615
00:35:07,200 --> 00:35:09,759
Speaker 5: there will be AI agents who are coding in platforms

616
00:35:09,760 --> 00:35:13,040
Speaker 5: that we don't know what they're doing or why, and

617
00:35:13,120 --> 00:35:15,759
Speaker 5: this poses a massive risk. When you look at your

618
00:35:16,000 --> 00:35:20,319
Speaker 5: earlier question, our foreign adversaries or other malign actors going

619
00:35:20,360 --> 00:35:22,320
Speaker 5: to attack in the US are going to try to attack,

620
00:35:22,680 --> 00:35:28,000
Speaker 5: you know, our private data or the like. So I mean,

621
00:35:28,000 --> 00:35:31,200
Speaker 5: there's a solution to all of this. But if you

622
00:35:31,239 --> 00:35:33,880
Speaker 5: look at what you know some of the ideas behind

623
00:35:33,920 --> 00:35:38,480
Speaker 5: cryptocurrency blockchains, one of the big ideas people need to

624
00:35:38,520 --> 00:35:41,799
Speaker 5: get used to is attestation, and what that means in

625
00:35:41,800 --> 00:35:45,279
Speaker 5: the AI context is how do we know that what

626
00:35:45,360 --> 00:35:48,879
Speaker 5: we're looking at is authentic? What is its history, where

627
00:35:48,880 --> 00:35:52,000
Speaker 5: does it come from, what is it doing? And those

628
00:35:52,040 --> 00:35:56,040
Speaker 5: are not going to be basic questions, and I believe

629
00:35:56,080 --> 00:35:59,239
Speaker 5: that we need to look to technology to start to

630
00:35:59,320 --> 00:36:03,120
Speaker 5: rebuild and safeguard this idea of trust, which could be

631
00:36:03,239 --> 00:36:06,760
Speaker 5: utterly eroded by some of those factors that we're talking

632
00:36:06,760 --> 00:36:07,360
Speaker 5: about today.

633
00:36:07,840 --> 00:36:10,160
Speaker 2: There's a lengthy piece and we'll wrap on this as

634
00:36:10,200 --> 00:36:12,799
Speaker 2: we turn our attention coming up in hour three of

635
00:36:12,840 --> 00:36:15,840
Speaker 2: the show to the school board races and the amount

636
00:36:15,840 --> 00:36:18,040
Speaker 2: of money that's being spent on these school board races.

637
00:36:18,040 --> 00:36:20,040
Speaker 2: Coming up but there's a lengthy piece out of the

638
00:36:20,080 --> 00:36:23,960
Speaker 2: North Dakota monitor. AI allows more time for students, according

639
00:36:23,960 --> 00:36:27,120
Speaker 2: to North Dakota educators. The state has provided guidance as

640
00:36:27,160 --> 00:36:30,920
Speaker 2: well on artificial intelligence. One English teacher says the benefit

641
00:36:30,920 --> 00:36:33,920
Speaker 2: of using AI for class preparation is saving time so

642
00:36:34,280 --> 00:36:37,480
Speaker 2: he can instead focus on more critical tasks such as

643
00:36:37,760 --> 00:36:41,040
Speaker 2: student to engagement. And they cover the gamment relating to

644
00:36:41,080 --> 00:36:44,160
Speaker 2: the concerns relating to two AI. I just want to

645
00:36:44,160 --> 00:36:46,120
Speaker 2: ask you this simple question, David, what do you think

646
00:36:46,200 --> 00:36:50,960
Speaker 2: the biggest advancement in the classroom will be with the

647
00:36:51,040 --> 00:36:53,800
Speaker 2: AI technology?

648
00:36:54,520 --> 00:36:58,719
Speaker 5: Great question. It continues your tradition of I know, I

649
00:36:58,719 --> 00:36:59,800
Speaker 5: think with a big question.

650
00:37:00,239 --> 00:37:01,080
Speaker 1: Let me do time.

651
00:37:02,120 --> 00:37:04,520
Speaker 5: But I love it right, it always ends on me

652
00:37:04,719 --> 00:37:08,000
Speaker 5: not getting a satisfactory answer to your big question. So

653
00:37:08,080 --> 00:37:10,920
Speaker 5: let me just kind of footstomp what the North Dakota

654
00:37:11,840 --> 00:37:15,640
Speaker 5: newspaper is saying. Sure, it's absolutely correct that AI will

655
00:37:15,680 --> 00:37:19,640
Speaker 5: free up time for teachers, because AI is like the

656
00:37:19,719 --> 00:37:22,600
Speaker 5: ultimate research assistant. When we talked before, and I answer

657
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Speaker 5: that listener's question about how AI gets stuff wrong, my

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00:37:25,560 --> 00:37:28,320
Speaker 5: point is like, yeah, it does, and we need to

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Speaker 5: be active users and we need to not blindly defer

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Speaker 5: to it, but it's amazing how much it gets right.

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Speaker 5: AI to me is like a really good research assistant

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Speaker 5: that doesn't sleep, and it allows you to do those

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Speaker 5: things that are easy for someone else to do, and

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Speaker 5: do them well and do them cheaply. And when you

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Speaker 5: think about the large range of medial tasks that teachers

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Speaker 5: have to do to prepare, having AI really fills freeze

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Speaker 5: up a good deal of time for more important tasks

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Speaker 5: that really only the teacher can do or that the

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Speaker 5: teacher will be best at doing so. An increasing the

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Speaker 5: amount of time in the teaching context, I think is

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Speaker 5: a wonderful, wonderful thing.

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Speaker 1: See.

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Speaker 5: I only do that DVD because I know you can

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Speaker 5: handle it.

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Speaker 1: At least that's going to be my excuse.

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Speaker 5: Oh John, I fully agree I can handle it, and

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Speaker 5: I like to use you anyway.

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Speaker 2: I know you're used to it fine now after all

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Speaker 2: these years to Vid Gartenstein Ross, CEO at Expert Theory,

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Speaker 2: as always, thank you so much for the time this morning.

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Speaker 1: My friend was great speaking with.

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Speaker 5: You, absolutely a pleasure.

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Speaker 3: John.

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Speaker 2: Coming up, we have school board races. We have highly

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Speaker 2: contested school board races in Prior Lake. We have a

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Speaker 2: Noka Hannepin School District areas three, four six as well.

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Speaker 2: We'll also be talking with a candidate running for school

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Speaker 2: board an isd AS six twenty two coming up next

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Speaker 2: to Justin Midall will be joining us and we'll get

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Speaker 2: in to all the money that's been rolling in to

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Speaker 2: these school board races and why so much money has

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Speaker 2: been rolling into these school board races races on election day.

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Speaker 2: It's coming up next on Twin Cities News Talk at

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Speaker 2: AM eleven thirty and one h three five FM