WEBVTT - Science funding cuts choke tech talent pipeline

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<v Speaker 1>Hey, it's been here at the top, letting you know.

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<v Speaker 1>Peter and I talk a bit about the share market

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<v Speaker 1>in this episode, but neither of us are financial advisors,

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<v Speaker 1>so please don't take what we say and run with it.

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<v Speaker 1>Go and get proper financial advice before you make any

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<v Speaker 1>investment decisions. Now onto the episode.

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<v Speaker 2>This week on the Business of Tech, powered by Two

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<v Speaker 2>Degrees Business, we catch up with one of the countries

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<v Speaker 2>leading science communicators on the state of STEM education, the

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<v Speaker 2>personal toll that speaking out on controversial topics can have,

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<v Speaker 2>and the need to demystify AI.

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<v Speaker 1>If you haven't taken your kids to a Nano Girl

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<v Speaker 1>show or seeing doctor Michelle Dickinson hosting international stars like

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<v Speaker 1>Neil deGrasse Tyson on stage, you've probably seen her on

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<v Speaker 1>TV talking about emerging technology, stem education, or a few

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<v Speaker 1>years ago aspects of the big science related issue of

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<v Speaker 1>the moment, the COVID pandemic.

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<v Speaker 2>Yeah, Michelle has had incredible cut through with thousands of

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<v Speaker 2>kids in newscas and engaging them with science, tech, engineering

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<v Speaker 2>and maths related topics and nurturing the next generation of technologists.

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<v Speaker 2>But as Nanogirl points out in this week's featured guest,

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<v Speaker 2>interview Steam Education and our TAIROA is in crisis.

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<v Speaker 3>Sadly during this government psycho, we have cut existing programs

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<v Speaker 3>that we're doing great things. It's like the whole system's

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<v Speaker 3>been shut off. And the consequences, I mean, it's easy

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<v Speaker 3>to see what the consequences up for that nobody's going

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<v Speaker 3>to come to New Zealand for our high talent pipeline,

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<v Speaker 3>and nobody's going to be trained here for the jobs

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<v Speaker 3>that need to.

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<v Speaker 1>Be trained here. Much more on that and Nano Girl's

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<v Speaker 1>latest AI related project coming up shortly, but first a

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<v Speaker 1>brief dive into the big tech stories of the week.

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<v Speaker 1>And we're starting this week with the turmoil and the

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<v Speaker 1>US markets and what it says about the valuations of

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<v Speaker 1>the big tech companies that dominate those markets.

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<v Speaker 2>Yeah, as we record this on Tuesday, being we've seen

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<v Speaker 2>relatively big drops in the magnificent seven, those big tech stocks,

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<v Speaker 2>which now include Nvidia, Tesla's in there, and then the

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<v Speaker 2>other usual suspects like Alphabet, Microsoft, Meta, and they have

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<v Speaker 2>taken by a large five to ten percent cuts in

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<v Speaker 2>their market capitalization, which is significant. But you know, these

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<v Speaker 2>companies have been on a tear, you know, on a

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<v Speaker 2>real bull run since twenty twenty or so, So really

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<v Speaker 2>is it that much of a problem. People in the US,

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<v Speaker 2>in particular are worried because some of the signals out

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<v Speaker 2>of the US economy are looking a little bit worrying.

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<v Speaker 2>And that's the job data and also last week the

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<v Speaker 2>manufacturing data, and we had some of these big tech

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<v Speaker 2>companies report their earnings and their revenue in late July,

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<v Speaker 2>and that sort of has spooked some analysts and Americans

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<v Speaker 2>in general who are looking at it going wow, you know,

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<v Speaker 2>are these running out of momentum the great run of

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<v Speaker 2>growth that they've had. Then we had Warren Buffett sell

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<v Speaker 2>down a massive stake in Apple, seventy odd billion dollars

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<v Speaker 2>worth of Apple stock. So I guess that's not a

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<v Speaker 2>great sign for a trendsetter like a Warren Buffett in

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<v Speaker 2>his mid nineties now sort of saying I want out

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<v Speaker 2>of Apple it's running out of growth. Not that he's

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<v Speaker 2>actually said that, but there's clearly a reason why he

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<v Speaker 2>is liquidating a big chunk of Apple stock still has

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<v Speaker 2>a lot but once out. At this point, he is

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<v Speaker 2>a guy who is notorious for picking the market very accurately.

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<v Speaker 2>A lot of people are just saying something's not right here,

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<v Speaker 2>what is coming?

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<v Speaker 1>I think you would be remiss if you didn't consider

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<v Speaker 1>the fact that every time a sector of stocks goes

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<v Speaker 1>up and up, eventually it has to go down as well.

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<v Speaker 1>What goes up must come down, right, That's the old

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<v Speaker 1>adagets is true I think in the share market, and

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<v Speaker 1>it may not always go down by as much as

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<v Speaker 1>it's gone up, but the market correction is something that

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<v Speaker 1>is spoken about all the time, and we've just seen,

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<v Speaker 1>like with in Nvidia, for example, that stock went out

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<v Speaker 1>of control. It it went way higher than I think

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<v Speaker 1>it probably should have, and we saw that it returned.

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<v Speaker 1>I think an interesting one is probably Intel. That we

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<v Speaker 1>saw a massive drop in the share price of Intel

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<v Speaker 1>after they announced a bunch of layoffs and some tightening,

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<v Speaker 1>and they're clearly really struggling in this world of arm

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<v Speaker 1>processors and GPUs to try and keep up with the

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<v Speaker 1>new technology. So I think that you can look at

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<v Speaker 1>as an example of where there has been a real

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<v Speaker 1>downturn for a stock. But I think overall, I probably

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<v Speaker 1>wouldn't say this is, you know, the end of tech

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<v Speaker 1>stocks as we know it. It's just that they are

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<v Speaker 1>reaching their new normal and mediating out a little bit, maybe.

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<v Speaker 2>Year fifteen thousand jobs going globally. At Intel, which has

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<v Speaker 2>sort of been in crisis mode really since the rise

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<v Speaker 2>of Invidia and its dominant in AI related chips. It

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<v Speaker 2>supplies eighty nine twenty percent of the market for the

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<v Speaker 2>chips that go into data centers to process workloads, large

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<v Speaker 2>language model training and the like. Now and Nvidia is

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<v Speaker 2>actually facing US Department of Justice action and investigation into

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<v Speaker 2>complaints from its competitors that it may have abused its

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<v Speaker 2>market dominance and selling those chips that power artificial intelligence.

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<v Speaker 2>So we're seeing this on a number of fronts. When

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<v Speaker 2>we're about to talk about the big one this week,

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<v Speaker 2>which is Google after four years of Department of Justice litigation,

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<v Speaker 2>the Department of Justice basically saying, Yep, you're a monopolist

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<v Speaker 2>in the search game and we have to do something

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<v Speaker 2>about it. So it seems between the unease about whether

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<v Speaker 2>the US, which it's sort of done well in the

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<v Speaker 2>last couple of years, is starting to face the same

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<v Speaker 2>sort of hard landing that we did coming out out

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<v Speaker 2>of COVID and we're paying the price of that now.

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<v Speaker 2>Has the US just been pushing that down the road

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<v Speaker 2>through injecting money into the economy through the Inflation Reduction Act,

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<v Speaker 2>all that money that has gone into things like semiconductors

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<v Speaker 2>and manufacturing, pumping out all this money for infrastructure that

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<v Speaker 2>Biden's been doing. Is it just a delayed reaction now?

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<v Speaker 2>And are we going to see a few hard years

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<v Speaker 2>for the US? So? I guess there's that, But also

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<v Speaker 2>people looking at the Stella run in tech and going

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<v Speaker 2>are we ready for that sort of correction we saw

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<v Speaker 2>in the late nineties and two thousand with the bubble bursting.

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<v Speaker 2>I don't think it's going to be that, but clearly

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<v Speaker 2>between regulation and the hollowness of AI at the moment

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<v Speaker 2>where the revenue isn't coming, but the expenses there from

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<v Speaker 2>the likes of Microsoft and NVIDI and all that, a

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<v Speaker 2>lot of people are going, we knew this already there

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<v Speaker 2>overinflated in priced, but we're going to take some money

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<v Speaker 2>off the table now.

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<v Speaker 1>Yeah, the shine is wearing off. I saw our Business

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<v Speaker 1>Insider piece early last week and talking about a pharmaceutical

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<v Speaker 1>company that had five hundred seats I think it was,

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<v Speaker 1>and upgraded them all to co pilot for another one

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<v Speaker 1>hundred and eighty thousand dollars a year and then just

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<v Speaker 1>said it just wasn't worth it for them.

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<v Speaker 2>We'll linked to that Business Insider piece. It was really

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<v Speaker 2>good because it was quite refreshing to see your company

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<v Speaker 2>sort of say, yeah, look we in good faith, we

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<v Speaker 2>implemented it across the business, and we're pulling the plug

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<v Speaker 2>because we're just not seeing the returns. So yeah, it's

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<v Speaker 2>good to see that. You talk to Microsoft and it's

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<v Speaker 2>going gangbusters. Everyone's seeing mental productivity gains and frankly some

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<v Speaker 2>of the analysts are sort of saying that as well.

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<v Speaker 2>But actually getting that tangible, independent feedback is great.

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<v Speaker 1>It was just the evidence that it's about specificity, not

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<v Speaker 1>on mass application, isn't it. And I think that's what's

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<v Speaker 1>maybe causing a little bit of downward turn in these

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<v Speaker 1>tech stocks as well, that there was a lot of

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<v Speaker 1>excitement and that was reflected in those prices for a while.

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<v Speaker 2>Yeah, let's have a look at this Google case that's

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<v Speaker 2>been running for over four years now with the Department

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<v Speaker 2>of Justice. So they just ruled this week turner it.

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<v Speaker 2>In seventy seven page ruling, Judge Ammett Metta basically said

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<v Speaker 2>that Google has made these massive payments to Apple and

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<v Speaker 2>Mozilla to make the Google Search Engine the default on

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<v Speaker 2>new devices, and including that they did this with Samsung

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<v Speaker 2>and others as well, paid billions of dollars to other

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<v Speaker 2>companies to ensure that the first thing you see when

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<v Speaker 2>you boot up a new device is the Google Search Engine.

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<v Speaker 2>So they basically said that after having carefully considered and

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<v Speaker 2>weighed the witness, testimony and evidence, the court reaches the

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<v Speaker 2>following conclusion. Google is a monopolist and it has acted

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<v Speaker 2>as one to maintain its monopoly. The consequences of that

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<v Speaker 2>is that it's charged advertisers higher prices than they would

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<v Speaker 2>have in a more competitive market. And that's why we

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<v Speaker 2>see Google with ninety percent of the search market and

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<v Speaker 2>being and others scrambling for the crumbs off the table.

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<v Speaker 2>That has a tangible impact on how much a business

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<v Speaker 2>pays to advertise on the Google search engine.

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<v Speaker 1>Yeah, by keeping the Google Search engine as the main

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<v Speaker 1>search engine that ninety eight plus percent of people are using,

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<v Speaker 1>that means that they can continue to sell ads on

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<v Speaker 1>that search engine. They know everybody's going to go there,

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<v Speaker 1>and they can put the prices up on those ads.

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<v Speaker 1>And I don't know if you've ever spoken to a

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<v Speaker 1>small business person in New Zealand. Talk to them about

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<v Speaker 1>advertising on Google. They always have that same thing. There's

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<v Speaker 1>just nowhere else I can go. It doesn't matter. I

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<v Speaker 1>have to pay if I want to get those leads

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<v Speaker 1>through Google. And you know we're not talking small change,

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<v Speaker 1>it says in the article Apple got an estimated twenty

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<v Speaker 1>billion dollars from Google in twenty twenty two. It's in

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<v Speaker 1>one year just to make the search engine the default

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<v Speaker 1>on Apple devices. Why would Apple need a twenty billion

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<v Speaker 1>dollar incentive to have that? If everyone want to Google anyway,

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<v Speaker 1>That's a really big and interesting question, and I think

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<v Speaker 1>why the courts have decided the way that they have.

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<v Speaker 2>Yeah, the question is what happens now. And a lot

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<v Speaker 2>of the commentary on this is that it will literally

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<v Speaker 2>take five years to sort this out, minimum because Kent Walker,

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<v Speaker 2>the company's president of global affairs, has come out today

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<v Speaker 2>and said, we are going to appeal this. It's great

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<v Speaker 2>that you think our search engine is so fantastic, thanks guys,

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<v Speaker 2>but we don't like the monopolist aspect of it as

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<v Speaker 2>well that you're accusing us of being. So we are

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<v Speaker 2>going to appeal this. So it we'll go through court.

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<v Speaker 2>It will move into a new phase where they will continue.

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<v Speaker 2>They will start hearing arguments now in court about what

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<v Speaker 2>remedy should be implemented to address this monopoly that the

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<v Speaker 2>court has decided is monopoly. So nothing's going to happen

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<v Speaker 2>in the immediate future. But some of the things that

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<v Speaker 2>could potentially happen is what has happened in Europe where

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<v Speaker 2>they've the EU Court action near decided a similar thing,

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<v Speaker 2>which Google has monopolistic properties there, and sort of what

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<v Speaker 2>they've done there is this what they call a ballot screen.

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<v Speaker 2>So when you boot up a new device there, you

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<v Speaker 2>get to choose what search engine you want, say a

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<v Speaker 2>new Android phone, it will give you a list of them,

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<v Speaker 2>including the Google search engine. But apparently it's had negligible

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<v Speaker 2>effect on the company's market share in Europe, so people

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<v Speaker 2>are still in that mindset of Google is the best,

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<v Speaker 2>Google is the default. So what will actually make a difference.

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<v Speaker 2>Will it have to go to structural separation where they

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<v Speaker 2>sort of break up Google, And how do you even

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<v Speaker 2>do that without killing the effectiveness of its search engine.

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<v Speaker 2>It is renowned for being very good, so how they

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<v Speaker 2>actually fix this problem will create another sort of headache.

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<v Speaker 2>They're going to have to work through.

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<v Speaker 1>Yeah, I mean, there is a lot of rumbling, slow movement.

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<v Speaker 1>I would say in some certain places online about complaints

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<v Speaker 1>around the Google search engine. And I've read articles saying

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<v Speaker 1>that the Google search engines saying there are one hundred

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<v Speaker 1>thousand results is a lie and you can't actually get

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<v Speaker 1>if you keep clicking through it's not those are not

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<v Speaker 1>actually there, and that it will only ever display those

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<v Speaker 1>has a very strong recency bias, and all of these

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<v Speaker 1>kinds of criticisms of the Google search engine that are

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<v Speaker 1>slowly growing. So maybe that movement, in conjunction with the

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<v Speaker 1>ability to select, with new search engines potentially coming out

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<v Speaker 1>with new technologies underpinning them, we don't know, you know,

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<v Speaker 1>there could be a step change, a shift in consumer

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<v Speaker 1>mindset around the corner when it comes to search. It's

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<v Speaker 1>hard to see because Google is so all consuming it

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<v Speaker 1>is a verb at this point, but perhaps we will

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<v Speaker 1>start to see a shift, if you know. I mean,

0:12:52.800 --> 0:12:55.040
<v Speaker 1>all empires fall at the end of the day, don't they.

0:12:55.240 --> 0:12:57.040
<v Speaker 1>I don't think digital ones are any different.

0:12:57.240 --> 0:13:00.959
<v Speaker 2>Yeah, they did well twenty five years and it would

0:13:00.960 --> 0:13:03.440
<v Speaker 2>be great to see three or four players with twenty

0:13:03.480 --> 0:13:07.440
<v Speaker 2>percent market share between them, so they're still profitable. They

0:13:07.480 --> 0:13:09.720
<v Speaker 2>still have a lot of money to invest in search,

0:13:09.880 --> 0:13:12.640
<v Speaker 2>and as you said, you know these new technologies like

0:13:13.559 --> 0:13:18.240
<v Speaker 2>AI generated search results and conversational AI could change the

0:13:18.280 --> 0:13:21.480
<v Speaker 2>game and give new entrants more of an opportunity. So

0:13:22.080 --> 0:13:24.200
<v Speaker 2>we'll see how this play out next week. We do

0:13:24.280 --> 0:13:27.760
<v Speaker 2>have an expert on search advertising, paid advertising and that

0:13:28.040 --> 0:13:31.720
<v Speaker 2>and how some of these changes are affecting what businesses

0:13:31.760 --> 0:13:34.000
<v Speaker 2>will need to do when it comes to trying to

0:13:34.040 --> 0:13:37.600
<v Speaker 2>find an audience. That's Ryan McMillan from Atlas Digital. So

0:13:37.640 --> 0:13:41.840
<v Speaker 2>that's on next week's episode. But just finally on news

0:13:42.120 --> 0:13:46.960
<v Speaker 2>this week, being some interesting commentary about Spotify, and I'm

0:13:46.960 --> 0:13:49.320
<v Speaker 2>no longer a Spotify user. I bailed out of Spotify

0:13:49.480 --> 0:13:51.480
<v Speaker 2>a long time ago just because it was a better

0:13:51.520 --> 0:13:55.240
<v Speaker 2>deal to do YouTube music, because I get bundled in

0:13:55.280 --> 0:13:59.240
<v Speaker 2>the ad free experience on YouTube, which as a super

0:13:59.320 --> 0:14:03.480
<v Speaker 2>user of YouTube, I really appreciate. And there are real

0:14:03.840 --> 0:14:07.839
<v Speaker 2>fanatical loyalists to Spotify, which I remember being a bit

0:14:07.840 --> 0:14:10.560
<v Speaker 2>sad to leave it because it was a great discovery

0:14:10.600 --> 0:14:14.800
<v Speaker 2>machine for new music. But increasingly we're seeing commentary a

0:14:14.840 --> 0:14:16.600
<v Speaker 2>big piece in the New Yorker that's got a lot

0:14:16.600 --> 0:14:20.400
<v Speaker 2>of attention. Another one in the Guardian, people going what

0:14:20.520 --> 0:14:23.600
<v Speaker 2>is up with Spotify? It's not showing the music I

0:14:23.680 --> 0:14:27.960
<v Speaker 2>want to discover anymore. It seems to be recycling all

0:14:28.040 --> 0:14:31.320
<v Speaker 2>the same big name artists. To me, are they paying

0:14:31.360 --> 0:14:34.640
<v Speaker 2>behind the scenes to have this stuff featured? And it

0:14:34.680 --> 0:14:38.080
<v Speaker 2>turns out it's not as simple as that. But what

0:14:38.240 --> 0:14:43.360
<v Speaker 2>is going on is this new discovery mode, which effectively

0:14:43.440 --> 0:14:48.160
<v Speaker 2>allows an artist to forego some royalties to be featured

0:14:48.720 --> 0:14:52.400
<v Speaker 2>prominently in parts of the Spotify app, which effectively gives

0:14:52.440 --> 0:14:56.600
<v Speaker 2>them more exposure to people, encourages people to follow them

0:14:56.680 --> 0:15:00.240
<v Speaker 2>and start listening to their music. So the argument is

0:15:00.480 --> 0:15:05.360
<v Speaker 2>that by manipulating that discovery mode, they're favoring some artists

0:15:05.800 --> 0:15:08.000
<v Speaker 2>and it's why people like you've been are seeing more

0:15:08.040 --> 0:15:08.320
<v Speaker 2>of them.

0:15:09.240 --> 0:15:12.520
<v Speaker 1>Yeah, yeah, I still am a Spotify user, and I

0:15:12.560 --> 0:15:15.400
<v Speaker 1>think it's mainly I did try to bail out into

0:15:15.400 --> 0:15:17.680
<v Speaker 1>Apple Music not long ago, but I just couldn't figure

0:15:17.680 --> 0:15:20.080
<v Speaker 1>out how to get my playlists over, which is just

0:15:20.120 --> 0:15:21.880
<v Speaker 1>a huge thing, like I don't want to lose all

0:15:21.880 --> 0:15:24.560
<v Speaker 1>of the work that I've put into following those particular

0:15:24.920 --> 0:15:27.480
<v Speaker 1>songs that you know that I have over the years.

0:15:28.320 --> 0:15:31.000
<v Speaker 1>That also is an interesting area to look at for

0:15:31.160 --> 0:15:34.560
<v Speaker 1>monopoly and consumer data right kind of approach there in

0:15:34.720 --> 0:15:39.480
<v Speaker 1>terms of who owns the data around my preferences. But yeah,

0:15:39.640 --> 0:15:43.840
<v Speaker 1>I definitely have noticed over the years that Spotify stops

0:15:44.000 --> 0:15:47.880
<v Speaker 1>serving up unexpected everything I hear. Now it kind of

0:15:47.880 --> 0:15:51.760
<v Speaker 1>fits within these kind of expected realm of music that

0:15:51.800 --> 0:15:55.960
<v Speaker 1>it keeps serving to me. And I have fairly broad tastes,

0:15:56.040 --> 0:15:58.560
<v Speaker 1>so it's nice to just hear some new random stuff

0:15:58.560 --> 0:16:00.720
<v Speaker 1>every now and again. That could be completely terrible, but

0:16:01.600 --> 0:16:04.240
<v Speaker 1>when you're actively looking for new music, it's okay to

0:16:04.280 --> 0:16:06.560
<v Speaker 1>have terrible stuff, well, stuff that you think is terrible

0:16:06.560 --> 0:16:08.400
<v Speaker 1>put in front of you, because it's kind of part

0:16:08.400 --> 0:16:09.000
<v Speaker 1>of the fun to.

0:16:08.960 --> 0:16:10.840
<v Speaker 2>Go, oh, what's this crap? Turn that off?

0:16:11.120 --> 0:16:13.840
<v Speaker 1>You know, oh this is quite interesting. It's all part

0:16:13.920 --> 0:16:15.520
<v Speaker 1>of the joy of it, rather than just aiming for

0:16:15.560 --> 0:16:20.480
<v Speaker 1>homogeny and just having bland. But where you have an algorithm,

0:16:20.560 --> 0:16:23.000
<v Speaker 1>you will have gaming of algorithms at the end of

0:16:23.040 --> 0:16:26.080
<v Speaker 1>the day. I think that's the reality of it. And

0:16:26.480 --> 0:16:28.760
<v Speaker 1>now Spotify, with all of its podcasts and all of

0:16:28.800 --> 0:16:31.480
<v Speaker 1>its kind of pretty terrible approach to audio books, to

0:16:31.520 --> 0:16:35.960
<v Speaker 1>be honest, there's a whole new level of kind of

0:16:36.040 --> 0:16:38.760
<v Speaker 1>trying to get through the user experience, and the New

0:16:38.840 --> 0:16:40.360
<v Speaker 1>York A piece talks about how hard it is to

0:16:40.400 --> 0:16:42.560
<v Speaker 1>find stuff that you're looking for, and it's absolutely right,

0:16:42.640 --> 0:16:46.040
<v Speaker 1>like trying to find a playlist, and yeah, so it

0:16:46.120 --> 0:16:49.000
<v Speaker 1>feels like it should be split into a few different

0:16:49.560 --> 0:16:53.840
<v Speaker 1>apps Spotify podcasts, Spotify audiobooks, Spotify Music, and then you

0:16:53.920 --> 0:16:56.320
<v Speaker 1>can kind of go where you want to. But by

0:16:56.320 --> 0:16:58.840
<v Speaker 1>trying to shove what they want in your face, it

0:16:58.960 --> 0:17:02.040
<v Speaker 1>speaks to that kind of inification trope. And if you

0:17:02.200 --> 0:17:05.439
<v Speaker 1>have successfully moved from Spotify to Apple Music, let me

0:17:05.520 --> 0:17:08.600
<v Speaker 1>know how you did it. Until all your playlists with you,

0:17:08.720 --> 0:17:09.639
<v Speaker 1>that would be great. Thank you.

0:17:16.800 --> 0:17:20.040
<v Speaker 2>Now. Our guest this week is an engineer, entrepreneur, and

0:17:20.200 --> 0:17:25.280
<v Speaker 2>former academic, Michelle Dickinson aka Nanogirl. Michelle grew up in

0:17:25.320 --> 0:17:29.280
<v Speaker 2>Hong Kong, the USA, the United Kingdom, did a PhD

0:17:29.480 --> 0:17:34.200
<v Speaker 2>in Biomedical materials engineering at Rutgers University in New Jersey,

0:17:34.720 --> 0:17:37.520
<v Speaker 2>worked in the tech industry, and eventually found a way

0:17:37.640 --> 0:17:40.520
<v Speaker 2>to Auckland, New Zealand, where she set up the country's

0:17:40.560 --> 0:17:42.800
<v Speaker 2>first nanotechnology testing lab.

0:17:42.840 --> 0:17:45.320
<v Speaker 1>And so that's where she gets the nano and nanogirl

0:17:45.720 --> 0:17:48.439
<v Speaker 1>and Michelle is fascinated with the science of small stuff,

0:17:48.560 --> 0:17:52.800
<v Speaker 1>manipulating individual atoms and molecules to come up with cool

0:17:52.960 --> 0:17:55.040
<v Speaker 1>new materials and technologies.

0:17:55.359 --> 0:17:58.080
<v Speaker 2>But she's also got her teeth into some big issues

0:17:58.119 --> 0:18:01.040
<v Speaker 2>over the last decade or so, including the skill shortage

0:18:01.080 --> 0:18:04.600
<v Speaker 2>in the so called STEM subjects as science, tech, engineering,

0:18:04.720 --> 0:18:09.119
<v Speaker 2>and maths. She co founded OMG Tech to address that issue,

0:18:09.160 --> 0:18:12.119
<v Speaker 2>and later Nanogirl Labs, which is her vehicle for bringing

0:18:12.119 --> 0:18:14.399
<v Speaker 2>STEM to kids here and around the world.

0:18:14.520 --> 0:18:17.400
<v Speaker 1>She really is a science communication dynamo, which we really

0:18:17.480 --> 0:18:20.199
<v Speaker 1>need as a country. But it hasn't been smooth sailing

0:18:20.520 --> 0:18:24.159
<v Speaker 1>in recent years for Michelle or other high profile science

0:18:24.160 --> 0:18:26.280
<v Speaker 1>communicators like Susie Wiles.

0:18:26.520 --> 0:18:30.320
<v Speaker 2>Yeah, COVID wasn't just bad for business for Nanogirl Labs,

0:18:30.320 --> 0:18:32.399
<v Speaker 2>at least for a while. It unleashed a lot of

0:18:32.520 --> 0:18:37.160
<v Speaker 2>toxic sentiment towards scientists, which Michelle had to deal with.

0:18:37.240 --> 0:18:40.960
<v Speaker 2>So here's Nanogirl on all of that and her take

0:18:41.000 --> 0:18:43.760
<v Speaker 2>on artificial intelligence and what it means to the next

0:18:43.800 --> 0:18:51.200
<v Speaker 2>generation of STEM graduates and the workforce in general. Michelle,

0:18:51.359 --> 0:18:53.880
<v Speaker 2>thanks so much for being on the business of tech.

0:18:54.000 --> 0:18:57.040
<v Speaker 2>So good to see you again. It's been quite a while,

0:18:57.080 --> 0:18:59.439
<v Speaker 2>haven't caught up with you recently, but I think our

0:18:59.480 --> 0:19:02.639
<v Speaker 2>relationship goes back over a decade. Related to the Science

0:19:02.720 --> 0:19:08.200
<v Speaker 2>Media Center. We were working together on the Cydeblogs platform.

0:19:08.280 --> 0:19:10.800
<v Speaker 2>You were a big contributor at the time to the

0:19:10.880 --> 0:19:14.320
<v Speaker 2>commetary that we were putting out to the media. At

0:19:14.320 --> 0:19:16.840
<v Speaker 2>the Science Media Center, you went through our Science Media

0:19:16.880 --> 0:19:21.280
<v Speaker 2>Savvy course, and it's just been incredible watching your science

0:19:21.320 --> 0:19:24.680
<v Speaker 2>communication journey, going from being an academic that didn't do

0:19:24.720 --> 0:19:27.800
<v Speaker 2>a lot of communication to being on stage with Neil

0:19:27.800 --> 0:19:30.280
<v Speaker 2>de grasse Tyson doing a Q and A with him

0:19:30.320 --> 0:19:33.679
<v Speaker 2>at spark Areen in front of tens of thousands of people.

0:19:34.440 --> 0:19:37.720
<v Speaker 2>What's that been like? What was the key really to you?

0:19:37.760 --> 0:19:40.400
<v Speaker 2>Sort of coming out of your shell and really building

0:19:40.480 --> 0:19:42.040
<v Speaker 2>communication into your career?

0:19:43.280 --> 0:19:45.679
<v Speaker 3>You were the key, Peter. I always say people go,

0:19:45.720 --> 0:19:46.920
<v Speaker 3>how did you get air? And I was like, there's

0:19:46.920 --> 0:19:49.679
<v Speaker 3>a man called Peter Griffin that I met, Not the

0:19:49.680 --> 0:19:53.320
<v Speaker 3>family guy, the family guy you, I mean, you really

0:19:53.400 --> 0:19:55.400
<v Speaker 3>are in the Science Media Center that you were running

0:19:55.440 --> 0:19:57.840
<v Speaker 3>at the time. Is the reason why I'm here. It

0:19:57.880 --> 0:20:00.000
<v Speaker 3>opened my eyes to something that I didn't know exists

0:20:00.080 --> 0:20:04.760
<v Speaker 3>did I was a nerdy, socially awkward academic doing nanotech

0:20:04.840 --> 0:20:08.320
<v Speaker 3>in my lab and frustrated that a lot of the

0:20:09.320 --> 0:20:11.600
<v Speaker 3>false and the misinformation I was seeing at the time

0:20:11.680 --> 0:20:15.080
<v Speaker 3>around the field I was in wasn't being corrected. And

0:20:15.119 --> 0:20:17.560
<v Speaker 3>then saw a course and managed to get the scholarship

0:20:17.600 --> 0:20:20.159
<v Speaker 3>to go on the course, and then was like, hold on,

0:20:20.400 --> 0:20:22.800
<v Speaker 3>I could be the person who talks about this and

0:20:22.840 --> 0:20:24.560
<v Speaker 3>I had no skills in it, right, I was painfully

0:20:24.600 --> 0:20:27.680
<v Speaker 3>shy and it was awful. But the Science Media Center

0:20:27.720 --> 0:20:29.439
<v Speaker 3>and the media Savvy course I went on that you

0:20:29.560 --> 0:20:32.879
<v Speaker 3>led showed me that there are different ways to communicate,

0:20:33.200 --> 0:20:36.080
<v Speaker 3>and there are different platforms, and actually it's really important

0:20:36.119 --> 0:20:40.120
<v Speaker 3>for scientists to have a voice when it's about things

0:20:40.200 --> 0:20:42.239
<v Speaker 3>that you know, the public just don't know where to

0:20:42.240 --> 0:20:45.840
<v Speaker 3>get good, solid, evidence based information on. Then I've also

0:20:45.880 --> 0:20:48.440
<v Speaker 3>seen a need for it as I've got deeper into

0:20:48.440 --> 0:20:52.000
<v Speaker 3>science communication around you know, different pockets of the community

0:20:52.040 --> 0:20:54.440
<v Speaker 3>that really don't get this. So yeah, you you, Peter,

0:20:54.600 --> 0:20:55.400
<v Speaker 3>you where I am here?

0:20:55.600 --> 0:20:57.480
<v Speaker 2>Well, that was a stepping off point, but then you

0:20:57.560 --> 0:21:02.440
<v Speaker 2>did so much more to take that to great heights.

0:21:02.560 --> 0:21:04.840
<v Speaker 2>What process did you go through to get to the

0:21:04.880 --> 0:21:06.520
<v Speaker 2>point where that's sick and nature to you?

0:21:08.440 --> 0:21:10.560
<v Speaker 3>I would never say that I don't have nerves even today.

0:21:10.640 --> 0:21:14.760
<v Speaker 3>I think all good people who should be nervous. It's

0:21:14.760 --> 0:21:16.760
<v Speaker 3>a good feeling to have. It means you're doing something serious.

0:21:17.359 --> 0:21:20.200
<v Speaker 3>And I don't think people realize how much preparation goes

0:21:20.240 --> 0:21:24.120
<v Speaker 3>into even a two minute interview live on TV. I've

0:21:24.160 --> 0:21:26.960
<v Speaker 3>met extroverted communicators who can really, nearly on the fly,

0:21:27.160 --> 0:21:30.000
<v Speaker 3>just come up with something that's not me. So the

0:21:30.040 --> 0:21:32.440
<v Speaker 3>amount of work that I will do behind the scenes,

0:21:32.520 --> 0:21:36.640
<v Speaker 3>the research, the memorizing soundbites, the things to make myself

0:21:36.680 --> 0:21:40.720
<v Speaker 3>confident is massive, and maybe people don't appreciate how much

0:21:40.760 --> 0:21:42.280
<v Speaker 3>work happens behind there.

0:21:42.840 --> 0:21:46.199
<v Speaker 2>Yeah, and at short notice when a major issue is

0:21:46.280 --> 0:21:49.440
<v Speaker 2>going down, you know that takes dedication and carving out

0:21:49.440 --> 0:21:51.199
<v Speaker 2>the time to do that preparation.

0:21:52.080 --> 0:21:54.400
<v Speaker 3>And yeah, all night usually if there's a breaking news.

0:21:54.440 --> 0:21:57.080
<v Speaker 3>And usually you'll get the call from the media the

0:21:57.200 --> 0:21:58.800
<v Speaker 3>night before at eight pm and they'll be like, can

0:21:58.840 --> 0:22:01.080
<v Speaker 3>you be on at six thirty eight. I won't sleep

0:22:01.119 --> 0:22:03.119
<v Speaker 3>that night. I'll have read around the subject. I'll make

0:22:03.160 --> 0:22:04.879
<v Speaker 3>sure that I've got my soundbites. I write them on

0:22:04.920 --> 0:22:07.760
<v Speaker 3>post it notes, I'll start memorizing them. Often you'll see

0:22:07.800 --> 0:22:09.760
<v Speaker 3>I've written on my hand before I've gone into the

0:22:09.760 --> 0:22:12.280
<v Speaker 3>studio right before we're live, I've just chucked my hand.

0:22:12.359 --> 0:22:14.720
<v Speaker 3>So it's in my brain like there's lots of little

0:22:14.720 --> 0:22:17.119
<v Speaker 3>things that I do at least to make sure I'm prepped.

0:22:17.800 --> 0:22:21.000
<v Speaker 2>And it's great. We saw this cohort that really around

0:22:21.000 --> 0:22:24.280
<v Speaker 2>the same time as you were building your science communication skills,

0:22:24.760 --> 0:22:28.360
<v Speaker 2>others were doing it as well. Richard Easter, Sean Hendy,

0:22:28.640 --> 0:22:30.639
<v Speaker 2>Michael Plank, all these people, and a lot of them

0:22:30.680 --> 0:22:34.960
<v Speaker 2>became very prominent during the COVID pandemic, most notably I

0:22:34.960 --> 0:22:38.679
<v Speaker 2>think Susie Wiles, who went through hell really with her

0:22:38.680 --> 0:22:43.280
<v Speaker 2>own institution and recently won that employment court case against

0:22:43.280 --> 0:22:46.800
<v Speaker 2>the University of Auckland, was a great communicator for the

0:22:46.920 --> 0:22:50.920
<v Speaker 2>university and in her own right didn't get to support

0:22:51.240 --> 0:22:54.560
<v Speaker 2>that she needed. For you. You were at the University

0:22:54.560 --> 0:22:56.640
<v Speaker 2>of Auckland. I think you said you've sort of had

0:22:56.680 --> 0:22:58.360
<v Speaker 2>to put up with that as well then going out

0:22:58.400 --> 0:23:00.760
<v Speaker 2>on your own. I guess the freedom that gave you,

0:23:00.800 --> 0:23:04.240
<v Speaker 2>but also no safety in it, no institutional support at all.

0:23:04.760 --> 0:23:07.520
<v Speaker 3>Look, academia is a really interesting place. It was a

0:23:07.520 --> 0:23:10.359
<v Speaker 3>place that I learned, you know, early on, but I

0:23:10.359 --> 0:23:13.120
<v Speaker 3>didn't quit it early enough that I didn't really fit

0:23:13.240 --> 0:23:15.800
<v Speaker 3>for that. There's lots of people there who are a

0:23:15.920 --> 0:23:19.040
<v Speaker 3>type personalities, who believe, and they often are the best

0:23:19.160 --> 0:23:21.800
<v Speaker 3>in their field at what they do academically. And so

0:23:21.880 --> 0:23:23.840
<v Speaker 3>when you've got what I call lots of egos in

0:23:23.880 --> 0:23:26.280
<v Speaker 3>a room, you can feel like there are lots of

0:23:26.320 --> 0:23:29.879
<v Speaker 3>fifdoms everywhere. And so when communicators like myself and like

0:23:29.920 --> 0:23:32.520
<v Speaker 3>Susie come along, where our craft is not just our

0:23:32.560 --> 0:23:37.399
<v Speaker 3>academic knowledge, but our ability to get information out to

0:23:37.760 --> 0:23:41.359
<v Speaker 3>the layperson, to the public quickly. It's a really a skill,

0:23:41.400 --> 0:23:43.800
<v Speaker 3>and I think people think they could do it but

0:23:43.840 --> 0:23:46.800
<v Speaker 3>don't understand that actually it's a skill that has to

0:23:46.880 --> 0:23:49.840
<v Speaker 3>have work. So yeah, there was a few more, probably

0:23:49.840 --> 0:23:51.840
<v Speaker 3>more times that I want to admit that I was

0:23:51.880 --> 0:23:54.679
<v Speaker 3>told that my communication was a waste of time. I

0:23:54.720 --> 0:23:58.399
<v Speaker 3>remember winning the Prime Minister's Science Communication Prize and I

0:23:58.480 --> 0:24:00.720
<v Speaker 3>literally got off the plane and I went straight to work,

0:24:01.119 --> 0:24:04.240
<v Speaker 3>went to my office, put the it was this massive trophy,

0:24:04.280 --> 0:24:06.399
<v Speaker 3>it was amazing, it was so heavy, put it on

0:24:06.440 --> 0:24:08.280
<v Speaker 3>my shelf and I was so proud. And within three

0:24:08.320 --> 0:24:11.840
<v Speaker 3>minutes an academic in my department walked into it, picked

0:24:11.840 --> 0:24:13.720
<v Speaker 3>it up, looked at me and said, well, it's not

0:24:13.720 --> 0:24:15.639
<v Speaker 3>like it's a real reward, is it. And then walked

0:24:15.640 --> 0:24:18.080
<v Speaker 3>out and I just went, why would you take that

0:24:18.320 --> 0:24:22.600
<v Speaker 3>from me to elevate yourself Like it's crazy. But that's academia, right.

0:24:22.640 --> 0:24:25.160
<v Speaker 3>It's just filled with lots of quirky people. And that's

0:24:25.200 --> 0:24:27.560
<v Speaker 3>the amazing thing about academia. And that's when I realized

0:24:27.560 --> 0:24:30.639
<v Speaker 3>that great, that it's not a space that I probably

0:24:30.720 --> 0:24:33.160
<v Speaker 3>want to stay in. But I've come from other places,

0:24:33.160 --> 0:24:35.000
<v Speaker 3>so I sort of had to think to compare it

0:24:35.040 --> 0:24:38.240
<v Speaker 3>to But during that time became great friends with Richard

0:24:38.280 --> 0:24:40.720
<v Speaker 3>Easter and shown Hendy and Susie and sort of became

0:24:40.760 --> 0:24:43.760
<v Speaker 3>this amazing communication cohort where we could bounce ideas off

0:24:43.800 --> 0:24:46.879
<v Speaker 3>each other and talk about what we were doing. And

0:24:46.920 --> 0:24:51.040
<v Speaker 3>then COVID and so I had left the university by

0:24:51.040 --> 0:24:52.760
<v Speaker 3>that point, and I had my own business, and so

0:24:53.200 --> 0:24:56.040
<v Speaker 3>I was also asked by lots of people, including the government,

0:24:56.040 --> 0:24:58.760
<v Speaker 3>to help communicate things around COVID, and I think the

0:24:58.840 --> 0:25:01.480
<v Speaker 3>difference is when you run your own business and you

0:25:01.520 --> 0:25:06.320
<v Speaker 3>don't have academic freedom to protect you. I made choices

0:25:06.359 --> 0:25:08.959
<v Speaker 3>about what I went into or one I didn't, and

0:25:09.000 --> 0:25:11.200
<v Speaker 3>what I said and what I didn't. So as a communicator.

0:25:11.640 --> 0:25:14.159
<v Speaker 3>I turned down lots of lots of media when they

0:25:14.160 --> 0:25:15.480
<v Speaker 3>said can you do this? And I was like, do

0:25:15.480 --> 0:25:18.000
<v Speaker 3>you know what, No, I feel like it's too high risk,

0:25:18.119 --> 0:25:20.600
<v Speaker 3>especially things that are aligned with telling people what they

0:25:20.640 --> 0:25:22.560
<v Speaker 3>should do. I never once said you should do this.

0:25:22.640 --> 0:25:24.720
<v Speaker 3>I said, hey, here's the evidence that we know right now.

0:25:25.480 --> 0:25:27.760
<v Speaker 3>This might change tomorrow because it's coming in thick and first,

0:25:27.840 --> 0:25:29.919
<v Speaker 3>I'm not going to tell you what to do, but

0:25:30.000 --> 0:25:32.600
<v Speaker 3>this is what the evidence says. And I never aligned

0:25:32.640 --> 0:25:36.760
<v Speaker 3>myself with any sort of political party. Labor was obviously

0:25:36.800 --> 0:25:39.199
<v Speaker 3>in at the time, so I went, hey, you know,

0:25:39.240 --> 0:25:41.600
<v Speaker 3>these are the people who are in. This is what

0:25:41.640 --> 0:25:43.680
<v Speaker 3>they're saying, this is what the evidence says. But I

0:25:44.040 --> 0:25:47.440
<v Speaker 3>had to be really careful because I have stuff, and

0:25:47.480 --> 0:25:49.600
<v Speaker 3>if it all goes horribly wrong, it doesn't just go

0:25:49.640 --> 0:25:52.280
<v Speaker 3>horribly wrong for me. It's the livelihood of all of

0:25:52.280 --> 0:25:54.399
<v Speaker 3>the stuff that they have, who have mortgages, you know,

0:25:54.440 --> 0:25:57.639
<v Speaker 3>that depend on me bringing an income in to the organization.

0:25:57.800 --> 0:26:00.080
<v Speaker 3>So I had to think about those people. And I

0:26:00.119 --> 0:26:02.119
<v Speaker 3>think if I was an academic, I maybe would have

0:26:02.800 --> 0:26:05.560
<v Speaker 3>taken on more things, hoping that academic freedom would have

0:26:05.600 --> 0:26:08.560
<v Speaker 3>protected me. And I saw that, you know, Susie was

0:26:08.600 --> 0:26:10.560
<v Speaker 3>able to do that. Sean Hendy was able to take

0:26:10.560 --> 0:26:14.120
<v Speaker 3>on more things, or at least they thought they could. Yeah,

0:26:14.280 --> 0:26:17.080
<v Speaker 3>and obviously it went pretty horribly wrong for them. And

0:26:17.119 --> 0:26:19.640
<v Speaker 3>I'm not saying that I didn't have issues too. So

0:26:19.960 --> 0:26:23.760
<v Speaker 3>my home address, photos of my home were taken, pictures

0:26:24.000 --> 0:26:26.080
<v Speaker 3>places that you could shoot me from the easiest as

0:26:26.080 --> 0:26:28.640
<v Speaker 3>a gas station across my old house. I moved, actually,

0:26:28.880 --> 0:26:30.360
<v Speaker 3>but it did the same with Susie, you know, taking

0:26:30.400 --> 0:26:33.440
<v Speaker 3>picture of a cat outside a house, posting her address, saying, well,

0:26:33.440 --> 0:26:35.159
<v Speaker 3>do what you want, this is where she lives. And

0:26:35.520 --> 0:26:38.359
<v Speaker 3>it was a really awful, frightening time. And then she

0:26:38.440 --> 0:26:41.360
<v Speaker 3>had a public workplace right that people could and they

0:26:41.400 --> 0:26:44.760
<v Speaker 3>did go to and confront and I think it was

0:26:44.800 --> 0:26:47.000
<v Speaker 3>a really scary time because people were just a little

0:26:47.000 --> 0:26:50.320
<v Speaker 3>bit unhinged. I think everybody was super stressed and you

0:26:50.600 --> 0:26:53.399
<v Speaker 3>just never knew. And the challenge with being in the

0:26:53.440 --> 0:26:56.080
<v Speaker 3>media spotlight is people know who you are and you

0:26:56.119 --> 0:26:59.960
<v Speaker 3>don't know who they are. And being recognized in part

0:27:00.400 --> 0:27:02.720
<v Speaker 3>is a double edged sword for sure, because if they're

0:27:02.720 --> 0:27:05.040
<v Speaker 3>a friendly, it's great, But if they're a foe, let

0:27:05.080 --> 0:27:07.000
<v Speaker 3>me tell you, they'll come up to you personally and

0:27:07.480 --> 0:27:11.320
<v Speaker 3>tell you what for. So watching what happened with Susie,

0:27:11.359 --> 0:27:14.679
<v Speaker 3>I mean, she's so brave for taking on the university

0:27:14.720 --> 0:27:18.639
<v Speaker 3>and luckily being awarded the win. And I think it's

0:27:19.200 --> 0:27:21.480
<v Speaker 3>I hope it's better for academics to be able to

0:27:21.480 --> 0:27:24.239
<v Speaker 3>come out and talk about things that might be a

0:27:24.240 --> 0:27:28.439
<v Speaker 3>bit hairy. But in the meantime, we've lost I'm an

0:27:28.480 --> 0:27:31.639
<v Speaker 3>amazing communicator. She's, you know, a shell of herself. She

0:27:31.640 --> 0:27:34.560
<v Speaker 3>doesn't come out anymore to talk about the things and

0:27:34.960 --> 0:27:37.679
<v Speaker 3>she was at the top of her game around communication,

0:27:37.800 --> 0:27:40.639
<v Speaker 3>and it's been really distressing to see that. So you

0:27:41.040 --> 0:27:44.040
<v Speaker 3>do take more risk as a communicator. I do it

0:27:44.080 --> 0:27:47.400
<v Speaker 3>because I really see I really feel the benefit of

0:27:47.640 --> 0:27:49.639
<v Speaker 3>the work that I do, because I do get people

0:27:49.680 --> 0:27:52.440
<v Speaker 3>saying thank you for that. I just didn't know. It

0:27:52.480 --> 0:27:55.440
<v Speaker 3>really helped me navigate choices in my life, and those

0:27:55.480 --> 0:27:58.479
<v Speaker 3>can be choices, big choices that people you know are

0:27:58.480 --> 0:28:00.960
<v Speaker 3>trying to make because they don't have great science literacy.

0:28:01.000 --> 0:28:05.400
<v Speaker 3>And that's the challenge. Our population has terrible science literacy

0:28:05.520 --> 0:28:08.000
<v Speaker 3>in general. And so where do you go when you're

0:28:08.000 --> 0:28:10.040
<v Speaker 3>an adult and you're trying to make a good informed

0:28:10.040 --> 0:28:13.400
<v Speaker 3>decision about something When Google says anything you wanted to say.

0:28:13.680 --> 0:28:17.160
<v Speaker 2>Yeah, and you still do a lot of that sort

0:28:17.200 --> 0:28:21.320
<v Speaker 2>of communication aimed at the population in general on often

0:28:21.359 --> 0:28:25.159
<v Speaker 2>contentious issues. But your real focus in recent news has

0:28:25.160 --> 0:28:29.000
<v Speaker 2>been nanogurl Labs. It's an online platform, but it's live events.

0:28:29.040 --> 0:28:32.320
<v Speaker 2>You go to schools, you do big shows, lots of

0:28:32.440 --> 0:28:35.920
<v Speaker 2>special effects and that to get people engaged. And it's

0:28:35.960 --> 0:28:39.560
<v Speaker 2>what's that journey been like? Leaving academia, setting up on

0:28:39.760 --> 0:28:42.360
<v Speaker 2>your own steam and having to navigate some hard years

0:28:42.440 --> 0:28:44.920
<v Speaker 2>when you couldn't do live events because of COVID.

0:28:46.600 --> 0:28:48.960
<v Speaker 3>Yeah, I mean I you know, anybody who owns a

0:28:49.000 --> 0:28:52.680
<v Speaker 3>business knows that you don't get it in it because

0:28:52.720 --> 0:28:54.440
<v Speaker 3>you want to sleep more or you want to make

0:28:54.480 --> 0:28:56.760
<v Speaker 3>more money. You do it because you see a problem

0:28:56.760 --> 0:28:58.760
<v Speaker 3>that you think you might be able to help, at

0:28:58.840 --> 0:29:01.200
<v Speaker 3>least not solve, but go in the right direction and

0:29:01.280 --> 0:29:03.360
<v Speaker 3>be part of a cohort. So those who don't know

0:29:03.400 --> 0:29:07.360
<v Speaker 3>my background, I was not great at school. I didn't

0:29:07.360 --> 0:29:09.160
<v Speaker 3>grow up with much money. I didn't grow up with

0:29:09.280 --> 0:29:12.280
<v Speaker 3>educated parents, so even going to university was never something

0:29:12.280 --> 0:29:15.600
<v Speaker 3>that was on my radar. I think, you know, having

0:29:16.000 --> 0:29:20.040
<v Speaker 3>fallen into lots of lucky situations and lots of grown

0:29:20.120 --> 0:29:23.240
<v Speaker 3>ups at the time who helped me becoming an engineer

0:29:23.280 --> 0:29:26.120
<v Speaker 3>in the end, and then having an academic career and

0:29:26.160 --> 0:29:29.080
<v Speaker 3>having a career in tech in the US. I just

0:29:29.160 --> 0:29:32.320
<v Speaker 3>I always, every day felt so grateful that I was here,

0:29:32.560 --> 0:29:34.320
<v Speaker 3>especially when I look back at the kids I went

0:29:34.360 --> 0:29:37.280
<v Speaker 3>to school with. Granville Harvey I went to school with

0:29:37.520 --> 0:29:40.520
<v Speaker 3>is in prison for attempted murder, no surprise, but he's

0:29:40.560 --> 0:29:42.680
<v Speaker 3>the guy I shared my textbooks with. You know, we

0:29:42.680 --> 0:29:46.360
<v Speaker 3>were rough kids, And I go, well, it was only

0:29:46.600 --> 0:29:49.520
<v Speaker 3>a hot for me not following in his footsteps. Right,

0:29:49.680 --> 0:29:51.720
<v Speaker 3>So how am I not in jail? How do I

0:29:51.760 --> 0:29:53.960
<v Speaker 3>have this amazing career? And how do I make sure

0:29:54.000 --> 0:29:56.800
<v Speaker 3>that kids like me, who through no fault of our own,

0:29:56.960 --> 0:29:59.280
<v Speaker 3>just not living in areas with lots of tech, not

0:29:59.560 --> 0:30:04.440
<v Speaker 3>having those ecosystems where academia is promoted, how do those

0:30:04.520 --> 0:30:08.080
<v Speaker 3>kids get to do this? And so I always had

0:30:08.080 --> 0:30:10.560
<v Speaker 3>this inner fire to go how do I get that

0:30:10.560 --> 0:30:13.000
<v Speaker 3>to happen? And when I worked at the university, and

0:30:13.040 --> 0:30:15.640
<v Speaker 3>even when I worked in sort of the tech space

0:30:15.640 --> 0:30:17.320
<v Speaker 3>in the US, it became very clear to me that

0:30:17.360 --> 0:30:19.120
<v Speaker 3>the people I was working with and the students we

0:30:19.120 --> 0:30:22.960
<v Speaker 3>were bringing in our privileged students. That's privilege through education.

0:30:23.160 --> 0:30:27.040
<v Speaker 3>That's privileged through Often parents are academic or would push

0:30:27.040 --> 0:30:29.120
<v Speaker 3>them into that system. And the kids who weren't making

0:30:29.160 --> 0:30:31.600
<v Speaker 3>it through are those kids you expect not to write,

0:30:31.640 --> 0:30:34.240
<v Speaker 3>those growing up in poverty, those growing up in rural

0:30:34.400 --> 0:30:37.480
<v Speaker 3>those growing up with parents who aren't in this sector

0:30:37.520 --> 0:30:39.400
<v Speaker 3>and don't know it exists. I said, well, how do

0:30:39.480 --> 0:30:44.280
<v Speaker 3>we because diversity is so important in tech, especially because

0:30:44.280 --> 0:30:46.600
<v Speaker 3>otherwise all we have is a bunch of Caucasian Silicon

0:30:46.680 --> 0:30:49.960
<v Speaker 3>Valley nerds inventing tech for us, and that doesn't represent

0:30:50.000 --> 0:30:54.000
<v Speaker 3>our problems. And it became very clear to me that

0:30:54.280 --> 0:30:57.560
<v Speaker 3>even our academic system shuts off so many students based

0:30:57.600 --> 0:31:01.320
<v Speaker 3>on grades, and the grades these kids getting might not

0:31:01.440 --> 0:31:04.160
<v Speaker 3>be the top because their school doesn't have a physics teacher,

0:31:04.200 --> 0:31:06.880
<v Speaker 3>because there's so many things that affect our young people

0:31:06.920 --> 0:31:11.000
<v Speaker 3>because of their postcode. And so I'm still on this

0:31:11.120 --> 0:31:13.480
<v Speaker 3>mission to go, how do we help more young people

0:31:13.480 --> 0:31:16.760
<v Speaker 3>who come from diverse backgrounds to realize that STEM is

0:31:16.800 --> 0:31:19.440
<v Speaker 3>a place that they should be, They should be welcomed,

0:31:19.480 --> 0:31:21.080
<v Speaker 3>and we have to figure out how we get them

0:31:21.120 --> 0:31:24.600
<v Speaker 3>into it when so many doors are closed because the

0:31:24.640 --> 0:31:27.520
<v Speaker 3>system's been the system for a long time, and then

0:31:27.600 --> 0:31:30.479
<v Speaker 3>how do we then keep them in the system and

0:31:30.600 --> 0:31:33.840
<v Speaker 3>help them to think through problems that nobody else in

0:31:33.880 --> 0:31:36.160
<v Speaker 3>the field is really thinking about. And we've just rewritten

0:31:36.160 --> 0:31:38.760
<v Speaker 3>the high school curriculum for four Pacific island nations, which

0:31:38.760 --> 0:31:42.280
<v Speaker 3>has been such an honor, and we've shown that those

0:31:42.440 --> 0:31:45.920
<v Speaker 3>students who now study It was a year ten program

0:31:46.040 --> 0:31:48.120
<v Speaker 3>and now fifty percent of them are now staying on

0:31:48.160 --> 0:31:52.880
<v Speaker 3>to study science at year eleven because we did localized context.

0:31:53.760 --> 0:31:56.040
<v Speaker 3>Right now, they're being taught by a non science teacher

0:31:56.080 --> 0:31:58.440
<v Speaker 3>and they're being given a free New Zealand or Australian

0:31:58.440 --> 0:32:00.800
<v Speaker 3>textbook to read from right, And that's just how we've

0:32:00.840 --> 0:32:04.160
<v Speaker 3>dealt with the Pacific And so we wrote this amazing

0:32:04.240 --> 0:32:07.600
<v Speaker 3>program that was I mean, it was amazing that you know,

0:32:07.600 --> 0:32:09.440
<v Speaker 3>they could look out of the window and suddenly see

0:32:09.480 --> 0:32:12.000
<v Speaker 3>the context of what they were doing. The examples were

0:32:12.040 --> 0:32:15.040
<v Speaker 3>local to them, and it's I mean, it's not brain science,

0:32:15.120 --> 0:32:17.640
<v Speaker 3>like it's not rocket science. You just go, hey, yeah,

0:32:17.880 --> 0:32:21.600
<v Speaker 3>make kids understand why we're doing this'll stick with it.

0:32:22.600 --> 0:32:26.320
<v Speaker 3>So for me, yeah, I have this inner burning desire

0:32:26.400 --> 0:32:28.520
<v Speaker 3>to help increase diversity in STEM and that's been a

0:32:28.520 --> 0:32:32.040
<v Speaker 3>big part of what we do, and it's been a

0:32:32.200 --> 0:32:36.800
<v Speaker 3>rollercoaster because funding keeps getting cut. So covid obviously happens

0:32:36.800 --> 0:32:38.680
<v Speaker 3>our in person stuff. We were about to do a

0:32:38.680 --> 0:32:42.000
<v Speaker 3>big global tour. We had just opened our California office

0:32:42.040 --> 0:32:45.080
<v Speaker 3>in February twenty twenty. We shut it in March twenty twenty,

0:32:45.120 --> 0:32:48.880
<v Speaker 3>I think, with the shortest New Zealand company ever see

0:32:50.200 --> 0:32:52.040
<v Speaker 3>having built up all of that stuff setting up a

0:32:52.120 --> 0:32:53.920
<v Speaker 3>Delawes c or like all of the work that goes

0:32:53.920 --> 0:32:57.160
<v Speaker 3>into setting up your American office and then hiring a

0:32:57.240 --> 0:32:59.160
<v Speaker 3>GM there, only to have to let them go, like

0:32:59.200 --> 0:33:01.640
<v Speaker 3>it's a huge spence and it's a huge learning curve.

0:33:01.680 --> 0:33:04.480
<v Speaker 3>So it's been rookie. But what I've loved is being

0:33:04.520 --> 0:33:06.560
<v Speaker 3>able to build all these communicators. So we currently have

0:33:06.600 --> 0:33:10.240
<v Speaker 3>thirty five science communicators in New Zealand. They're all students,

0:33:10.320 --> 0:33:14.160
<v Speaker 3>usually graduate students doing their musters who also are Nana girls.

0:33:14.400 --> 0:33:16.680
<v Speaker 3>They all have their own superhero names and they're local

0:33:16.720 --> 0:33:20.200
<v Speaker 3>to their communities and they go out and they do schools, parties,

0:33:20.440 --> 0:33:25.040
<v Speaker 3>mall shows, public performances under the Nanogol brand. And I go, well,

0:33:25.040 --> 0:33:26.760
<v Speaker 3>this is also how we get to sort of create

0:33:26.840 --> 0:33:30.520
<v Speaker 3>the next generation of science communicators and show young people

0:33:30.840 --> 0:33:35.320
<v Speaker 3>that there's an amazing young female scientists in their neighborhood

0:33:35.320 --> 0:33:37.160
<v Speaker 3>and this is what they're doing. And we've got everything

0:33:37.160 --> 0:33:41.480
<v Speaker 3>from jumping spider experts to music physicists. I mean, it's

0:33:41.560 --> 0:33:42.240
<v Speaker 3>just incredible.

0:33:42.640 --> 0:33:48.400
<v Speaker 2>Yeah, And it's such a compelling proposition the STEM subjects,

0:33:48.520 --> 0:33:50.680
<v Speaker 2>I mean, the careers that people can have, the salaries

0:33:50.680 --> 0:33:53.760
<v Speaker 2>that people can earn from Maria and Pacifico who are

0:33:53.840 --> 0:34:00.200
<v Speaker 2>underrepresented in the STEM related industries. It's really tough for

0:34:00.320 --> 0:34:03.719
<v Speaker 2>STEM organizations at the moment. Funding has been cut. In

0:34:03.760 --> 0:34:06.960
<v Speaker 2>real terms, a lot of them are barely holding on.

0:34:07.040 --> 0:34:10.480
<v Speaker 2>It's ironic, isn't it that as any government that is

0:34:10.560 --> 0:34:13.080
<v Speaker 2>in power at the moment is all about we need

0:34:13.120 --> 0:34:18.160
<v Speaker 2>to diversify our economy using engineering, science and technology. But

0:34:18.239 --> 0:34:20.239
<v Speaker 2>we're not backing it up with that commitment at the

0:34:20.239 --> 0:34:21.000
<v Speaker 2>early stages.

0:34:21.800 --> 0:34:24.640
<v Speaker 3>I think worse in that. I think sadly during this

0:34:25.120 --> 0:34:27.319
<v Speaker 3>government cycle, not only way not backing up, we have

0:34:27.520 --> 0:34:31.799
<v Speaker 3>cut existing programs that we're doing great things. I'm going

0:34:31.800 --> 0:34:33.080
<v Speaker 3>to give you a list because I've been writing it

0:34:33.080 --> 0:34:35.440
<v Speaker 3>down because it's been depressing. So OMD Tech obviously that

0:34:35.480 --> 0:34:37.879
<v Speaker 3>I co founded with Born rosel from then back ten

0:34:37.960 --> 0:34:41.640
<v Speaker 3>years ago, they were the main national digital technologies education

0:34:41.800 --> 0:34:46.319
<v Speaker 3>provider if you wanted to learn anything about coding robotics,

0:34:46.960 --> 0:34:50.399
<v Speaker 3>and they had a massive MADI and PACIFICA Group two

0:34:50.760 --> 0:34:53.640
<v Speaker 3>making sure that they were doing it bilingually and trilingually.

0:34:53.680 --> 0:34:56.040
<v Speaker 3>It was amazing. So they have just closed down. So

0:34:56.080 --> 0:34:57.759
<v Speaker 3>that means it's going to be really hard now if

0:34:57.760 --> 0:35:01.319
<v Speaker 3>you're a teacher to do PD development, to learn or

0:35:01.400 --> 0:35:04.319
<v Speaker 3>upskill in tech. But that's just one of them. So

0:35:05.160 --> 0:35:08.719
<v Speaker 3>we lost the Curious Minds funding now that's one point

0:35:08.760 --> 0:35:12.480
<v Speaker 3>six million dollars a year. That has a significant effect

0:35:12.600 --> 0:35:15.680
<v Speaker 3>not only on cool projects that spun out of it,

0:35:16.120 --> 0:35:19.720
<v Speaker 3>but also it was where Comet, which is the big

0:35:19.800 --> 0:35:24.000
<v Speaker 3>South Auckland STEM group got all their funding from. Now

0:35:24.040 --> 0:35:26.600
<v Speaker 3>they're independent and I think it's going to be really

0:35:26.640 --> 0:35:29.200
<v Speaker 3>hard for them to do what they used to do

0:35:29.320 --> 0:35:31.600
<v Speaker 3>with that. So they are obviously downsizing and trying to

0:35:31.600 --> 0:35:37.240
<v Speaker 3>figure out who they are. Otago Museum, who do amazing outreach.

0:35:37.600 --> 0:35:41.120
<v Speaker 3>Curious Minds funded all of their communicators to go up

0:35:41.120 --> 0:35:43.560
<v Speaker 3>to schools and do those programs. They have cut all

0:35:43.560 --> 0:35:47.440
<v Speaker 3>of those programs now because they've lost that funding. The

0:35:47.520 --> 0:35:51.000
<v Speaker 3>Wonder project, which is an incredible program by Engineering New

0:35:51.080 --> 0:35:54.200
<v Speaker 3>Zealand where they would go into schools and so my

0:35:54.800 --> 0:35:57.000
<v Speaker 3>finger dab into that is I helped to build that program.

0:35:57.080 --> 0:35:58.799
<v Speaker 3>And what I wanted to build was a long term

0:35:58.840 --> 0:36:02.640
<v Speaker 3>relationship with engineers and scientists with school so they would

0:36:02.640 --> 0:36:05.120
<v Speaker 3>go in for nine to twelve weeks every week and

0:36:05.360 --> 0:36:07.240
<v Speaker 3>help kids build a rocket. And they had a project

0:36:07.239 --> 0:36:11.120
<v Speaker 3>from start to finish. They've lost a million dollars a

0:36:11.200 --> 0:36:14.759
<v Speaker 3>year of Callahan funding, which is basically their big breadwinners.

0:36:14.800 --> 0:36:18.399
<v Speaker 3>So who knows what's going to happen to them. House

0:36:18.440 --> 0:36:21.319
<v Speaker 3>of Sciences. You may have seen City and Upper Hut

0:36:21.320 --> 0:36:25.040
<v Speaker 3>Council stopped their funding. That was access for fifteen thousand students.

0:36:25.360 --> 0:36:28.200
<v Speaker 3>Now Chris luckily has managed to get enough because she's

0:36:28.280 --> 0:36:31.800
<v Speaker 3>worked hard on raising some funds till twenty twenty five.

0:36:31.880 --> 0:36:35.759
<v Speaker 3>But then what and I just go, oh onn this

0:36:35.840 --> 0:36:38.120
<v Speaker 3>is nuts. This is on top of all of the

0:36:38.640 --> 0:36:41.319
<v Speaker 3>academic jobs that have been cut and the knee were

0:36:41.320 --> 0:36:45.319
<v Speaker 3>in the CRI jobs and so the jobs have gone,

0:36:45.560 --> 0:36:47.880
<v Speaker 3>and the training and the funding has gone, and teachers

0:36:47.880 --> 0:36:50.320
<v Speaker 3>now don't have anywhere to go to learn this stuff.

0:36:50.840 --> 0:36:53.400
<v Speaker 3>It's like the whole system's been shut off and the

0:36:53.440 --> 0:36:55.719
<v Speaker 3>consequences are I mean, it's easy to see what the

0:36:55.719 --> 0:36:57.840
<v Speaker 3>consequences are for that. Nobody's going to come to New

0:36:57.960 --> 0:37:00.960
<v Speaker 3>Zealand for our high talent line and nobody's going to

0:37:01.000 --> 0:37:02.440
<v Speaker 3>be trained here for the jobs that need to be

0:37:02.480 --> 0:37:02.880
<v Speaker 3>trained in.

0:37:03.080 --> 0:37:06.400
<v Speaker 2>Yeah, we've got our Science Minister are out there championing

0:37:06.400 --> 0:37:09.680
<v Speaker 2>the space sick difference. It's our first Minister of Space,

0:37:09.719 --> 0:37:12.120
<v Speaker 2>which is all well and good, but where's the pipeline

0:37:12.160 --> 0:37:15.719
<v Speaker 2>of future space engineers that are going to feed this industry.

0:37:16.280 --> 0:37:19.919
<v Speaker 2>If we don't nurture them at those early stages, we're

0:37:19.920 --> 0:37:22.040
<v Speaker 2>going to be relying on people coming to this country

0:37:22.080 --> 0:37:23.120
<v Speaker 2>to fill those positions.

0:37:23.280 --> 0:37:25.520
<v Speaker 3>Hundred percent. It's got to be immigration. That has to

0:37:25.520 --> 0:37:28.640
<v Speaker 3>be the solution, because we are not building that talent

0:37:28.760 --> 0:37:32.440
<v Speaker 3>pipeline right now, and that talent pipeline is a long

0:37:32.560 --> 0:37:35.359
<v Speaker 3>lead pipeline. You can't go oh, when they've picked their

0:37:35.440 --> 0:37:37.560
<v Speaker 3>unique subjects. That's when we're going to do it. Because

0:37:37.560 --> 0:37:40.080
<v Speaker 3>what we've seen around innovation, So David diet Downs and

0:37:40.120 --> 0:37:42.279
<v Speaker 3>I wrote a book called Number eight Recharged where we

0:37:42.719 --> 0:37:47.120
<v Speaker 3>studied our top big companies, including Rocket Lab and Peter Beckham.

0:37:47.160 --> 0:37:50.839
<v Speaker 3>What those journeys are of those top people, and it's

0:37:50.840 --> 0:37:55.640
<v Speaker 3>not academics. It's experience, it's trying things, it's being hanging

0:37:55.680 --> 0:37:57.560
<v Speaker 3>out with people who are diverse to you to solve

0:37:57.600 --> 0:38:00.640
<v Speaker 3>those problems. And if those people aren't getting into the

0:38:00.719 --> 0:38:03.520
<v Speaker 3>system and being able to test some things out, we're

0:38:03.520 --> 0:38:06.440
<v Speaker 3>not going to build the next whatever it is. Rocket

0:38:06.480 --> 0:38:09.480
<v Speaker 3>Lab is a great example, and we seem to go, oh, well,

0:38:09.520 --> 0:38:11.560
<v Speaker 3>once you've got your degree dot dot dot, you can

0:38:11.600 --> 0:38:14.400
<v Speaker 3>do this, but the evidence shows you that the degree

0:38:14.480 --> 0:38:17.840
<v Speaker 3>has very little to do with it. It's those types

0:38:17.880 --> 0:38:21.000
<v Speaker 3>of personalities having good systems around them where they can

0:38:21.040 --> 0:38:23.719
<v Speaker 3>access funding, where they can access information, where they can

0:38:23.840 --> 0:38:27.480
<v Speaker 3>just try something, fail and try again, and with that

0:38:27.520 --> 0:38:30.439
<v Speaker 3>comes confidence and with that comes your ability to when

0:38:30.480 --> 0:38:32.680
<v Speaker 3>you I mean, if you talk to Peter Beck, he's

0:38:32.719 --> 0:38:35.239
<v Speaker 3>a rocket scientist because when he was eleven and Invercargo,

0:38:35.360 --> 0:38:37.680
<v Speaker 3>he was building rockets in his shed with his dad,

0:38:37.840 --> 0:38:41.400
<v Speaker 3>like that sort of stuff. Having kids building things in schools,

0:38:41.440 --> 0:38:45.440
<v Speaker 3>trying robots, trying coding to build that confidence young is

0:38:45.560 --> 0:38:47.280
<v Speaker 3>how they make it through the system.

0:38:47.640 --> 0:38:50.359
<v Speaker 2>Yeah, so we do have a real problem to address here,

0:38:50.480 --> 0:38:52.719
<v Speaker 2>and it can't just be philanthropic money. We don't have

0:38:52.840 --> 0:38:55.320
<v Speaker 2>enough of it. It can't just be TICH companies because

0:38:55.320 --> 0:38:58.120
<v Speaker 2>they have their own spin on the technology stack. They

0:38:58.120 --> 0:39:01.520
<v Speaker 2>want you to invest your time, so it does need

0:39:01.560 --> 0:39:10.600
<v Speaker 2>to be government funding. Another thing I really admire you

0:39:10.640 --> 0:39:13.640
<v Speaker 2>for is how well you engage with the business community

0:39:14.360 --> 0:39:18.959
<v Speaker 2>around technology and working with companies to encourage them to

0:39:19.040 --> 0:39:23.200
<v Speaker 2>explore new technology. The technology of the moment is generative AI,

0:39:23.960 --> 0:39:27.920
<v Speaker 2>which you have been scoping out and are heavily involved

0:39:27.920 --> 0:39:30.320
<v Speaker 2>in as well. Just last week, you spoke at Gartner

0:39:30.840 --> 0:39:33.920
<v Speaker 2>and Sydney at their big annual conference. Rewiring for the

0:39:34.000 --> 0:39:36.600
<v Speaker 2>Future was the theme of your talk, So you've obviously

0:39:36.680 --> 0:39:39.799
<v Speaker 2>been looking at this technology. What's the message that you

0:39:39.800 --> 0:39:43.280
<v Speaker 2>were giving to people who went to the Gartner conference

0:39:43.440 --> 0:39:47.600
<v Speaker 2>about what this technology means for the workplace, about skills

0:39:47.600 --> 0:39:49.759
<v Speaker 2>and what they need to do to make the most

0:39:49.760 --> 0:39:51.799
<v Speaker 2>of it. Yeah.

0:39:51.920 --> 0:39:54.520
<v Speaker 3>As a science communicator, and I guess as a tech communicator,

0:39:54.760 --> 0:39:57.920
<v Speaker 3>my goal is to help demystify some of the jargon

0:39:58.040 --> 0:40:02.720
<v Speaker 3>that's involved around highly technical or fields, to help democratize tech,

0:40:03.239 --> 0:40:05.359
<v Speaker 3>to help people to make good decisions for them. That's

0:40:05.400 --> 0:40:07.600
<v Speaker 3>always what I've done as a communicator. I don't tell

0:40:07.600 --> 0:40:09.399
<v Speaker 3>you what you should do or what you shouldn't do,

0:40:09.760 --> 0:40:12.400
<v Speaker 3>But I will help you understand what is probably hype

0:40:13.239 --> 0:40:16.239
<v Speaker 3>and what is probably going to be very expensive. And

0:40:16.280 --> 0:40:19.680
<v Speaker 3>with businesses, it's all about return on investment and AI actually,

0:40:19.680 --> 0:40:21.480
<v Speaker 3>if you're going to build your own system in house,

0:40:21.719 --> 0:40:26.600
<v Speaker 3>is a lot of financial commitment, and so businesses are

0:40:26.640 --> 0:40:30.120
<v Speaker 3>feeling the pressure to throw all this money into something

0:40:30.160 --> 0:40:32.799
<v Speaker 3>that they really feel like is a black box right now.

0:40:33.160 --> 0:40:35.520
<v Speaker 3>So my goal is to help people understand, Hey, what's

0:40:35.560 --> 0:40:37.880
<v Speaker 3>already out there? What does it mean. There's all of

0:40:37.920 --> 0:40:42.360
<v Speaker 3>these terms, you know, like large language models, neural networks,

0:40:42.400 --> 0:40:46.399
<v Speaker 3>and they all sound so insanely technical, and I actually go, hey,

0:40:46.520 --> 0:40:48.439
<v Speaker 3>here's what it is like. This is what it does,

0:40:48.480 --> 0:40:49.880
<v Speaker 3>this is what it can do, this is what it

0:40:49.920 --> 0:40:53.880
<v Speaker 3>can't do. And my philosophy, whatever age you are, has

0:40:53.920 --> 0:40:57.520
<v Speaker 3>always been come play, because when you play with whatever

0:40:57.600 --> 0:40:59.560
<v Speaker 3>it is, you learn, whether I'm giving you a self

0:40:59.640 --> 0:41:01.480
<v Speaker 3>driving robot and you're learning how to code it to

0:41:01.520 --> 0:41:04.400
<v Speaker 3>go around in circles, or I'm giving you some AI

0:41:04.480 --> 0:41:07.760
<v Speaker 3>tools to play with that are fun, that are silly.

0:41:08.040 --> 0:41:11.680
<v Speaker 3>My favorite one is there's a website called bored humans

0:41:11.719 --> 0:41:14.160
<v Speaker 3>dot com and in there is a marriage simulator and

0:41:14.280 --> 0:41:17.400
<v Speaker 3>you can get your virtual AI husband or wife and

0:41:17.440 --> 0:41:20.840
<v Speaker 3>you can argue with them. And I love that because

0:41:20.960 --> 0:41:22.880
<v Speaker 3>suddenly you went you out of your work environment and

0:41:22.880 --> 0:41:26.279
<v Speaker 3>you're playing with an AI system and you're arguing with it.

0:41:26.360 --> 0:41:29.640
<v Speaker 3>You'll realize that humans are way better at insarting than AI. Right,

0:41:29.680 --> 0:41:32.920
<v Speaker 3>So it just takes that intimidation out. And I've had

0:41:32.960 --> 0:41:35.520
<v Speaker 3>lots of people go, I don't know where to get started,

0:41:35.640 --> 0:41:39.440
<v Speaker 3>and so credit a YouTube series to help people not

0:41:39.520 --> 0:41:42.440
<v Speaker 3>only demystify the jargon. So in three minutes unless you'll

0:41:42.520 --> 0:41:45.960
<v Speaker 3>learn about whatever the jargon is, hallucination or the difference

0:41:45.960 --> 0:41:49.640
<v Speaker 3>between traditional AI and generative AI, that's easy. But then

0:41:49.760 --> 0:41:52.239
<v Speaker 3>Joe Crib came to me and said, can you just

0:41:52.320 --> 0:41:55.239
<v Speaker 3>help me actually get started practically? I don't know where

0:41:55.239 --> 0:41:58.720
<v Speaker 3>to use this, and so I'm building a YouTube series

0:41:59.040 --> 0:42:01.760
<v Speaker 3>basically use AI to heck your life that she's following

0:42:01.800 --> 0:42:04.600
<v Speaker 3>and writing up and in the Sunday Star Times every Sunday,

0:42:04.600 --> 0:42:07.160
<v Speaker 3>but actually is free for everybody to go. Hey, So

0:42:07.200 --> 0:42:10.520
<v Speaker 3>the one that's this week is how do you use

0:42:10.640 --> 0:42:14.280
<v Speaker 3>AI to help you take the mental load off figuring

0:42:14.280 --> 0:42:17.640
<v Speaker 3>out what's for dinner every day? So we have a

0:42:17.640 --> 0:42:20.440
<v Speaker 3>simple one which is recipes by AI. Just look in

0:42:20.480 --> 0:42:22.239
<v Speaker 3>your fridge, type in what you've got and it'll give

0:42:22.239 --> 0:42:25.239
<v Speaker 3>you dinner for tonight. But the longer version is you

0:42:25.280 --> 0:42:27.640
<v Speaker 3>can actually take that meal planning away. So I'll give

0:42:27.680 --> 0:42:30.120
<v Speaker 3>you some prompts and jet GBT and just explaining that

0:42:30.160 --> 0:42:32.680
<v Speaker 3>prompts are instructions, and I have a way that I

0:42:32.719 --> 0:42:35.360
<v Speaker 3>write my prompts a really simple formula that gets a

0:42:35.400 --> 0:42:38.400
<v Speaker 3>good result out and then you literally go, hey, this

0:42:38.520 --> 0:42:40.480
<v Speaker 3>is what my family looks like. It's winter in New

0:42:40.560 --> 0:42:43.320
<v Speaker 3>Zealand and we're budget conscious, so only you seasonal things.

0:42:44.200 --> 0:42:46.799
<v Speaker 3>My kids don't eat, bean, speech, treat, whatever it is.

0:42:47.000 --> 0:42:48.680
<v Speaker 3>Give me a meal plan for the week, and also

0:42:48.800 --> 0:42:51.399
<v Speaker 3>write me a grocery list with everything in order that's

0:42:51.440 --> 0:42:53.880
<v Speaker 3>in the grocery. I also, I'm not having to find everything,

0:42:54.360 --> 0:42:56.080
<v Speaker 3>and then you can just print it out and go

0:42:56.239 --> 0:42:59.160
<v Speaker 3>and you've suddenly taken away all of that mental load

0:42:59.360 --> 0:43:01.200
<v Speaker 3>of what's for dinner? What are I need to get

0:43:01.200 --> 0:43:03.759
<v Speaker 3>from the sharps, blah blah blah. And the goal is

0:43:03.800 --> 0:43:06.040
<v Speaker 3>just to give people time back in their life, in

0:43:06.080 --> 0:43:09.360
<v Speaker 3>their personal life. And what I've seen in AI is

0:43:09.400 --> 0:43:11.600
<v Speaker 3>the big hype, especially around the media, is it's going

0:43:11.640 --> 0:43:14.000
<v Speaker 3>to take all of our jobs, and everybody's petroviied, and

0:43:14.040 --> 0:43:16.480
<v Speaker 3>I just try and sort of show people how you

0:43:16.480 --> 0:43:18.600
<v Speaker 3>can really push it to its limits in ways that

0:43:18.640 --> 0:43:21.239
<v Speaker 3>you're not afraid of, like doing your grocery shopping or

0:43:21.239 --> 0:43:24.400
<v Speaker 3>picking what's for dinner, and then see what it's greater

0:43:24.560 --> 0:43:27.400
<v Speaker 3>and what it's terrible at, and learn when it lies

0:43:27.480 --> 0:43:30.279
<v Speaker 3>to your faith through hallucinations like how many hours are

0:43:30.280 --> 0:43:32.720
<v Speaker 3>in the word strawberry, and how it tries to convince

0:43:32.719 --> 0:43:35.280
<v Speaker 3>you that you're wrong as a human and that's okay

0:43:35.440 --> 0:43:38.319
<v Speaker 3>because that's just genera to AI. That's what it does.

0:43:38.600 --> 0:43:42.640
<v Speaker 2>Yeah, Gartner has its infamous hype cycle, and at the

0:43:42.680 --> 0:43:46.920
<v Speaker 2>moment appears GENAI is sort of on the trough of disillusionment.

0:43:47.360 --> 0:43:49.840
<v Speaker 2>And I think that's really that it was hyped up.

0:43:49.840 --> 0:43:52.040
<v Speaker 2>A lot. A lot of money has gone into the industry,

0:43:52.080 --> 0:43:55.520
<v Speaker 2>and the initial adopters of this, who maybe gave copilot

0:43:55.600 --> 0:43:57.919
<v Speaker 2>to everyone in the organization, are going and paying thirty

0:43:58.000 --> 0:44:01.359
<v Speaker 2>dollars extra a month. I'm not getting the the productivity

0:44:01.400 --> 0:44:03.239
<v Speaker 2>boost that I was promised to you. So we still

0:44:03.280 --> 0:44:05.200
<v Speaker 2>have a bit of work to do, don't we Until

0:44:05.480 --> 0:44:09.360
<v Speaker 2>we do see productivity efficiency, But also new product generation,

0:44:09.480 --> 0:44:13.320
<v Speaker 2>new ideas coming through in businesses that these tools are enabling.

0:44:14.040 --> 0:44:16.680
<v Speaker 3>Yeah, and there's so much happening so quickly, like every day,

0:44:16.800 --> 0:44:18.759
<v Speaker 3>you know, like now matters coming out with that, Like

0:44:19.000 --> 0:44:21.040
<v Speaker 3>everybody's trying to launch the next new and big thing.

0:44:21.080 --> 0:44:23.000
<v Speaker 3>And I think it could be really confusing as to

0:44:23.440 --> 0:44:25.960
<v Speaker 3>what should you use and what's the best and how

0:44:26.000 --> 0:44:28.440
<v Speaker 3>do you find it? And I think what happens is

0:44:28.640 --> 0:44:31.960
<v Speaker 3>businesses productize the system, so you just have to wait

0:44:32.000 --> 0:44:34.640
<v Speaker 3>a little bit and somebody will find a good solution

0:44:34.800 --> 0:44:37.600
<v Speaker 3>for you that will be great for solving your problem.

0:44:37.880 --> 0:44:39.920
<v Speaker 3>And AI has been around for a long time, obviously,

0:44:39.960 --> 0:44:42.719
<v Speaker 3>I think it's just the jargon of saying, Hey, what

0:44:42.760 --> 0:44:45.319
<v Speaker 3>people are talk about is generative AI. That's great, this

0:44:45.400 --> 0:44:47.320
<v Speaker 3>is what it can do. This is where it gets stuck.

0:44:47.560 --> 0:44:50.200
<v Speaker 3>You've been using AI on your Spotify or on Netflix

0:44:50.239 --> 0:44:52.400
<v Speaker 3>for a long time. You don't even think about it.

0:44:52.440 --> 0:44:55.759
<v Speaker 3>So let's not stress about the big scary words that

0:44:55.800 --> 0:44:57.839
<v Speaker 3>are being thrown down. If you want to understand them,

0:44:57.880 --> 0:45:01.239
<v Speaker 3>here are some videos just be a way and rewaring

0:45:01.360 --> 0:45:03.759
<v Speaker 3>the brain. The talk that I give is about, hey,

0:45:03.800 --> 0:45:05.920
<v Speaker 3>you don't have to be an expert in everything, but

0:45:06.080 --> 0:45:09.360
<v Speaker 3>just be open to. If you hear something new, just

0:45:09.520 --> 0:45:12.239
<v Speaker 3>dabble in. What is it? And do you think that's

0:45:12.239 --> 0:45:14.520
<v Speaker 3>going to be the next big thing? And the easiest

0:45:14.520 --> 0:45:18.280
<v Speaker 3>way to tell is ROI like, does it have huge

0:45:18.280 --> 0:45:21.880
<v Speaker 3>economic potential? If the answer is yes, great, it's going

0:45:21.920 --> 0:45:24.240
<v Speaker 3>to be big. But we've been through the cycle through

0:45:24.640 --> 0:45:27.120
<v Speaker 3>you know, blockchain and NFTs, like I feel like there's

0:45:27.160 --> 0:45:30.680
<v Speaker 3>always something on the cards and what succeeds is the

0:45:30.719 --> 0:45:34.399
<v Speaker 3>thing that has huge economic potential. So just go can

0:45:34.520 --> 0:45:36.600
<v Speaker 3>somebody make lots of money out of this? If the

0:45:36.640 --> 0:45:39.120
<v Speaker 3>answer is yes, keep an eye on it. If the

0:45:39.160 --> 0:45:41.440
<v Speaker 3>answer is no, keep an eye on it too. But

0:45:41.560 --> 0:45:45.160
<v Speaker 3>don't start trying to move your whole business to incorporating

0:45:45.239 --> 0:45:48.680
<v Speaker 3>something early. And we all know that early adopters are

0:45:48.719 --> 0:45:52.640
<v Speaker 3>never the ones that actually succeed. I think it's good

0:45:52.640 --> 0:45:54.920
<v Speaker 3>that New Zealand's a little bit behind sometimes because we

0:45:55.080 --> 0:45:57.479
<v Speaker 3>just get to sit and watch everybody else throw money

0:45:57.520 --> 0:45:59.719
<v Speaker 3>into something and then we go cool that one would

0:45:59.800 --> 0:46:00.760
<v Speaker 3>let's go with that one?

0:46:01.040 --> 0:46:03.880
<v Speaker 2>Yeah, And I really love that message of experimentation. And

0:46:03.920 --> 0:46:07.000
<v Speaker 2>you can do that safely without putting all your company

0:46:07.040 --> 0:46:10.200
<v Speaker 2>information into the large language model, so you know, have

0:46:10.280 --> 0:46:12.319
<v Speaker 2>some governance around that, and there's some great tools out

0:46:12.320 --> 0:46:14.680
<v Speaker 2>there now from the AI Forum and others around how

0:46:14.719 --> 0:46:17.919
<v Speaker 2>to do it safely, but experimentation just finishing up back

0:46:17.960 --> 0:46:21.959
<v Speaker 2>on in the classroom in the STEM environments. For years,

0:46:21.960 --> 0:46:24.080
<v Speaker 2>the mantra was we've got to get more kids coding

0:46:24.080 --> 0:46:28.520
<v Speaker 2>in that. What do you think the implications of AI

0:46:28.920 --> 0:46:34.239
<v Speaker 2>are for coding? We've got GitHub Copilot, we've got increasingly

0:46:34.360 --> 0:46:38.479
<v Speaker 2>automation off the coding process. Are you still recommending kids

0:46:38.920 --> 0:46:40.080
<v Speaker 2>go and learn how to code?

0:46:40.440 --> 0:46:43.040
<v Speaker 3>Yeah, one hundred percent. And there is a being is

0:46:43.120 --> 0:46:47.440
<v Speaker 3>that you still need human checks and look, I have

0:46:47.560 --> 0:46:50.600
<v Speaker 3>loved generative AI for coding, like it helps me to

0:46:50.640 --> 0:46:52.880
<v Speaker 3>be a better coder. I think if you're going to

0:46:52.920 --> 0:46:56.080
<v Speaker 3>learn anything, if you understand data and you understand Python

0:46:56.239 --> 0:46:59.680
<v Speaker 3>right now, you are probably the most sought after person

0:46:59.800 --> 0:47:03.280
<v Speaker 3>in industry because that's sort of what the AI field

0:47:03.360 --> 0:47:06.120
<v Speaker 3>is looking for. The thing about learning coding is it's

0:47:06.160 --> 0:47:08.719
<v Speaker 3>like learning any language. I don't care what language you

0:47:08.760 --> 0:47:11.120
<v Speaker 3>actually learn to code in. What you're understanding is the

0:47:11.160 --> 0:47:15.560
<v Speaker 3>process of how do these systems work? And that I

0:47:15.560 --> 0:47:18.000
<v Speaker 3>think is the most important thing. It gives you confidence

0:47:18.040 --> 0:47:21.399
<v Speaker 3>around tech. It allows you to turn something that wasn't

0:47:21.480 --> 0:47:24.960
<v Speaker 3>moving into something that does something. And I think having

0:47:25.160 --> 0:47:29.200
<v Speaker 3>digital literacy is really important. So if you're learning to

0:47:29.239 --> 0:47:30.960
<v Speaker 3>code at the age of eleven, like, it's not going

0:47:31.000 --> 0:47:34.200
<v Speaker 3>to harm you. You're learning about language, you're learning about

0:47:34.320 --> 0:47:38.520
<v Speaker 3>order and structure. And also if your AI coding system

0:47:38.640 --> 0:47:41.880
<v Speaker 3>has a bug, you can see where it is, and

0:47:41.920 --> 0:47:45.120
<v Speaker 3>that's the most important human side. AI is not going

0:47:45.120 --> 0:47:47.760
<v Speaker 3>to replace us. What you need is a good human

0:47:47.800 --> 0:47:50.160
<v Speaker 3>to overview the AI to know where the bugs might be.

0:47:50.600 --> 0:47:52.520
<v Speaker 3>And to do that you have to be proficient in

0:47:52.560 --> 0:47:56.080
<v Speaker 3>the language that it's speaking. And so that's code, that's

0:47:56.160 --> 0:47:59.399
<v Speaker 3>understanding how things work in sequence, that's understanding brackets, that's

0:47:59.440 --> 0:48:01.960
<v Speaker 3>all of the nerdy stuff. And I think if you

0:48:02.000 --> 0:48:05.239
<v Speaker 3>do that young, you just have a confidence throughout that

0:48:05.280 --> 0:48:08.000
<v Speaker 3>you can, even if you don't know the language that's in,

0:48:08.080 --> 0:48:10.799
<v Speaker 3>you know the process of that language, and then you

0:48:10.840 --> 0:48:13.520
<v Speaker 3>can sort of debug it. So I'm still an advocate

0:48:13.600 --> 0:48:16.120
<v Speaker 3>because I don't see any harm in it in having

0:48:16.120 --> 0:48:18.840
<v Speaker 3>our kids learn how to Even if you're just coding

0:48:18.880 --> 0:48:21.080
<v Speaker 3>a self driving robot that drives from A to B,

0:48:21.719 --> 0:48:24.760
<v Speaker 3>go through that sequence and you'll never lose that skill.

0:48:25.239 --> 0:48:28.880
<v Speaker 2>Yeah, and you look at the Titan New Zealand at

0:48:28.880 --> 0:48:31.360
<v Speaker 2>the moment. But the bit's paying jobs is still paying

0:48:31.480 --> 0:48:35.600
<v Speaker 2>great money for coding all those sort of languages like

0:48:35.640 --> 0:48:38.680
<v Speaker 2>Python you were talking about, still a great career to

0:48:38.719 --> 0:48:38.960
<v Speaker 2>be in.

0:48:39.840 --> 0:48:42.000
<v Speaker 3>Yeah, and a career where you can work remotely now

0:48:42.360 --> 0:48:44.720
<v Speaker 3>and be working if there's no money in New Zealand,

0:48:44.760 --> 0:48:47.600
<v Speaker 3>working for an American or as Singaporean company and still

0:48:47.800 --> 0:48:50.759
<v Speaker 3>being a kei we I mean, it's flexibility. It's best

0:48:50.800 --> 0:48:53.520
<v Speaker 3>with an amazing paycheck. And you know, if we can

0:48:53.560 --> 0:48:57.400
<v Speaker 3>help New Zealanders to get on a road to a

0:48:57.560 --> 0:49:00.960
<v Speaker 3>job that actually gives the security and finance, security and

0:49:01.000 --> 0:49:03.480
<v Speaker 3>housing security, why wouldn't we want to build that?

0:49:03.560 --> 0:49:03.759
<v Speaker 2>Here?

0:49:08.440 --> 0:49:11.799
<v Speaker 1>Lots covered there, lots of really fascinating stuff. I think

0:49:11.800 --> 0:49:15.040
<v Speaker 1>the thing that stuck out to me most was when

0:49:15.040 --> 0:49:17.680
<v Speaker 1>she was talking about the needless their education and reaching

0:49:17.719 --> 0:49:22.400
<v Speaker 1>people who were not reaching, and she made the point

0:49:22.480 --> 0:49:25.400
<v Speaker 1>that what we need is more of these people who

0:49:25.640 --> 0:49:29.520
<v Speaker 1>are super passionate and excited and will just take something

0:49:29.600 --> 0:49:32.239
<v Speaker 1>and run with it like you're Peter Beck. That was

0:49:32.560 --> 0:49:34.759
<v Speaker 1>one of her examples, but I think Peter Jackson is

0:49:34.800 --> 0:49:38.960
<v Speaker 1>another example, Edmund Hillary and Kate Shepherd. But the thing

0:49:39.000 --> 0:49:41.680
<v Speaker 1>about those people and a lot of people is that

0:49:41.719 --> 0:49:47.080
<v Speaker 1>they are generally from families that have the privilege of

0:49:47.160 --> 0:49:49.680
<v Speaker 1>kind of giving them space to be able to do

0:49:49.840 --> 0:49:54.440
<v Speaker 1>what they want. And you know, she talks about the

0:49:55.560 --> 0:49:58.279
<v Speaker 1>creating a new curriculum for PACIFICA students and putting it

0:49:58.320 --> 0:50:01.960
<v Speaker 1>in a context that they understand or not they understand

0:50:01.960 --> 0:50:05.960
<v Speaker 1>that suits them, I should say, And it's always going

0:50:06.000 --> 0:50:07.400
<v Speaker 1>to be the case that if you have kids who

0:50:07.440 --> 0:50:12.040
<v Speaker 1>are coming to something and they are having to understand

0:50:12.440 --> 0:50:15.440
<v Speaker 1>a new context for it as well as the new content,

0:50:15.800 --> 0:50:19.000
<v Speaker 1>they're going to be doing double the mental workload. So

0:50:19.520 --> 0:50:22.319
<v Speaker 1>being able to make it more accessible is not just

0:50:22.400 --> 0:50:25.359
<v Speaker 1>about taking the same curriculum and putting it in front

0:50:25.400 --> 0:50:28.239
<v Speaker 1>of new kids. It's about finding new ways of engaging

0:50:28.239 --> 0:50:32.120
<v Speaker 1>them and then giving them wrap around support so that

0:50:32.200 --> 0:50:34.799
<v Speaker 1>they can try and fail and explore and create and

0:50:34.840 --> 0:50:36.920
<v Speaker 1>build in all of those kinds of things as well,

0:50:36.960 --> 0:50:41.120
<v Speaker 1>Like just restructuring the school curriculum in minor ways is

0:50:41.160 --> 0:50:43.799
<v Speaker 1>not actually going to make the major shift that we

0:50:43.920 --> 0:50:44.479
<v Speaker 1>might need.

0:50:44.960 --> 0:50:47.760
<v Speaker 2>No, And I was just blown away. I knew about

0:50:47.960 --> 0:50:52.000
<v Speaker 2>OMG tech winding up, but when Michelle was sort of

0:50:52.520 --> 0:50:57.360
<v Speaker 2>listing off all of those other organizations that have wound

0:50:57.480 --> 0:51:01.640
<v Speaker 2>up or have had massive budget cuts. It's really worrying

0:51:01.760 --> 0:51:04.920
<v Speaker 2>if we want to build this high tech workforce, all

0:51:04.920 --> 0:51:08.240
<v Speaker 2>of these opportunities, whether they be with Mari and Pacifica

0:51:08.400 --> 0:51:11.960
<v Speaker 2>or just in general in schools, a lot of that

0:51:12.000 --> 0:51:14.399
<v Speaker 2>stuff is not going to exist anymore. It's the same

0:51:14.440 --> 0:51:18.520
<v Speaker 2>with digital equity stuff around subsidizing broadband for poorer households.

0:51:18.560 --> 0:51:21.080
<v Speaker 2>A lot of that stuff is getting cut as well.

0:51:21.200 --> 0:51:25.279
<v Speaker 2>So I think we're at risk, and times are tough

0:51:25.360 --> 0:51:28.359
<v Speaker 2>across the economy, but we're at risk of really taking

0:51:28.400 --> 0:51:33.279
<v Speaker 2>a step backwards in terms of having those opportunities for

0:51:33.320 --> 0:51:36.400
<v Speaker 2>people to really get exposed to STEM subjects and therefore

0:51:36.480 --> 0:51:39.200
<v Speaker 2>want to pursue a career in those topics. But great

0:51:39.239 --> 0:51:42.879
<v Speaker 2>to see what Michelle's doing and nanogirl Labs, and we'll

0:51:42.880 --> 0:51:44.960
<v Speaker 2>be seeing a lot more of her, including on our

0:51:45.320 --> 0:51:48.840
<v Speaker 2>YouTube channel around artificial intelligence as well.

0:51:49.080 --> 0:51:51.840
<v Speaker 1>Yeah, it's great to have people like that. It's a

0:51:51.880 --> 0:51:54.840
<v Speaker 1>pity to see all those cuts and to see less spaces.

0:51:54.960 --> 0:51:58.120
<v Speaker 1>A central city library has this awesome maker space, but

0:51:58.160 --> 0:52:00.319
<v Speaker 1>a lot of the suburban libraries don't have those kinds

0:52:00.360 --> 0:52:02.279
<v Speaker 1>of things, or if they do, they're not really that

0:52:02.520 --> 0:52:05.719
<v Speaker 1>well known. We could be doing so much more as

0:52:05.800 --> 0:52:10.920
<v Speaker 1>a society to provide these amazing spaces in communal areas

0:52:10.960 --> 0:52:14.520
<v Speaker 1>that don't require huge expense for people to just go

0:52:14.640 --> 0:52:16.120
<v Speaker 1>and try and be well.

0:52:16.200 --> 0:52:18.880
<v Speaker 2>We could be our Central Library in Wellington's a shell

0:52:19.080 --> 0:52:20.880
<v Speaker 2>at the moment, it's going to cost hundreds of millions

0:52:20.920 --> 0:52:24.880
<v Speaker 2>of dollars, so there's no getting away from experience there unfortunately.

0:52:25.400 --> 0:52:28.520
<v Speaker 1>Yeah, no, that's true. Well, that's it for the Business

0:52:28.560 --> 0:52:30.879
<v Speaker 1>of Tech this week. Thanks so much to Nano Girl

0:52:30.920 --> 0:52:33.840
<v Speaker 1>Michelle Dickinson for coming on the show. We've put links

0:52:33.840 --> 0:52:37.800
<v Speaker 1>to her various ventures, including her Ai Life Hacks YouTube

0:52:37.880 --> 0:52:39.280
<v Speaker 1>series in the show notes.

0:52:39.440 --> 0:52:42.719
<v Speaker 2>The Business off Tech is on all major podcast platforms

0:52:42.760 --> 0:52:45.760
<v Speaker 2>as well as iHeartRadio, where you can stream every episode.

0:52:45.880 --> 0:52:48.080
<v Speaker 2>Show notes are in the Tech section on the Business

0:52:48.160 --> 0:52:50.839
<v Speaker 2>Desk website. Leave us a review and share it with

0:52:50.880 --> 0:52:51.960
<v Speaker 2>your friends and colleagues.

0:52:52.120 --> 0:52:55.360
<v Speaker 1>Get in touch with your feedback, ideas, topic and guest suggestions.

0:52:55.360 --> 0:52:57.719
<v Speaker 1>You can email me ben at business test dot com

0:52:57.800 --> 0:53:00.600
<v Speaker 1>dot ben Z. We'll find both of us on LinkedIn

0:53:00.719 --> 0:53:01.799
<v Speaker 1>and x and.

0:53:01.800 --> 0:53:04.200
<v Speaker 2>You'll find the next episode of the Business of Tech

0:53:04.280 --> 0:53:07.080
<v Speaker 2>in your podcast app bright and early next Thursday.

0:53:07.239 --> 0:53:11.000
<v Speaker 1>Until then, have a great week.