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Speaker 1: You're listening to a podcast from news talks it B.

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Speaker 1: Follow this and our wide range of podcasts now on iHeartRadio.

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Speaker 1: It's time for all the attitude, all the opinion, all

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Speaker 1: the information, all the debates of the now the Leighton

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Speaker 1: Smith podcast coward by news talks it B.

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Speaker 2: Welcome to podcast two hundred and eighty six for May

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Speaker 2: twenty eight, twenty twenty five. Well, this is going to

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Speaker 2: be the shortest intro I've ever done. I believe the

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Speaker 2: following discussion runs about an hour fifteen minutes and it is.

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Speaker 2: It's viteful to a lot of people to hear it.

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Speaker 2: It's also interesting for those who think it won't be interesting,

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Speaker 2: at least that's my interpretation. So we have the discussion,

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Speaker 2: then we have the mail room, and then there is

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Speaker 2: a little more on AI at the back end before

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Speaker 2: we go. But like it or not, AI is fast

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Speaker 2: changing the world in many industries. It may not have

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Speaker 2: affected or involved you, yet, just as the Internet now

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Speaker 2: encompasses everything and involves all of us, from how we

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Speaker 2: communicate via email to shop online, AI will change the

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Speaker 2: way that we do a lot of things. I was

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Speaker 2: surprised myself. Now, whereas the Internet took some years to

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Speaker 2: reach the mass population. AI is changing industries quicker than

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Speaker 2: you would imagine, and it's bringing serious ethical questions about

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Speaker 2: what we're letting ourselves in for and who is pulling

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Speaker 2: the strings to control it. The big tech companies are

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Speaker 2: pouring literally billions into research to be the market leader.

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Speaker 2: So after a very short break, I'll introduce you to

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Speaker 2: both Nigel Hurricks and Justin Matthews, who have put together

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Speaker 2: a sub stack, but just as importantly, or if not

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Speaker 2: more so, they both have careers and histories that have

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Speaker 2: led them to this very event AI with some considerable knowledge.

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Speaker 2: Buccolan is a natural oral vaccine in a tablet form

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Speaker 2: called bacterial l sate. It'll boost your natural protection against

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Speaker 2: bacterial infections in your chest and throat. A three day

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Speaker 2: course of seven Bucklan tablets will help your body build

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Speaker 2: up to three months of immunity against bugs which cause

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Speaker 2: bacterial cold symptoms. So who can take buccolan well, the

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Speaker 2: whole family. From two years of age and upwards. A

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Speaker 2: course of Buckelan tablets offers cost effective and safe protection

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Speaker 2: from colds and chills. Protection becomes effective a few days

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Speaker 2: after you take buccolan and lasts for up to three

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Speaker 2: months following the three day course. Buccolan can be taken

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Speaker 2: throughout the cold season, over winter, or all year round.

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Speaker 2: And remember Buckelan is not intended as an alternative to

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Speaker 2: influenza vaccination, but may be used along with the flu

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Speaker 2: vaccination for added protection. And keep in mind that millions

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Speaker 2: of doses have been taken by Kiwis for over fifty years.

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Speaker 2: Only available from your firemist. Always read the label and

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Speaker 2: users directed, and see your doctor if systems persist. Farmer

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Speaker 2: Broker auckland Leyton Smith AI it's become more prominent in

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Speaker 2: my life of recent times. I mean, there is Ai

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Speaker 2: Fabler who we've had on the podcast once or twice,

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Speaker 2: and he writes very good stuff, but that doesn't tell

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Speaker 2: us much about the whole AI industry. Let me read

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Speaker 2: you some headlines. Every one of these is coming in

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Speaker 2: the last week. One was just this morning. On both

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Speaker 2: sides of the Tasman we are too fearful of AI.

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Speaker 2: Doug Bergham warns, whoever wins the AI race controls the world.

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Speaker 2: Who's Doug Bergham? He is the Interior Secretary responsible for

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Speaker 2: managing the well more than five hundred and seven million

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Speaker 2: acres of federally owned land in the US, and he

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Speaker 2: is haunted by a fear that seems at first glance

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Speaker 2: outside his mandate. He worries the free world will lose

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Speaker 2: dominant in the field of artificial intelligence, and with that

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Speaker 2: the future. Then there's a cap on it. So does

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Speaker 2: the president forget AI. Students are already cheating their way

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Speaker 2: through exams and last for the moment is more, but

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Speaker 2: last for the moment is the least important one. Chris

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Speaker 2: Luxen defends National's use of AI. So it's getting more

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Speaker 2: and more publicity and it's affecting more and more lives.

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Speaker 2: Nigel Horrack was the news editor at Newstalks NB well

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Speaker 2: when it became Newstalks EDB in that period, and he is,

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Speaker 2: according to people who have informed me or reinformed me,

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Speaker 2: the best news editor that we ever had. What more

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Speaker 2: can I say? He also is a pioneer, or was

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Speaker 2: a pioneer in internet matters. But he's also done something

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Speaker 2: very recently. He did a course at Oxford University, well

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Speaker 2: not Oxford, it was online, but it was a course

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Speaker 2: on AI. And the important thing is my understanding, is

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Speaker 2: that he almost threw in the towel part way through

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Speaker 2: because it was so so hard he didn't and he

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Speaker 2: ended up getting ninety percent, which at Oxford I'd have

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Speaker 2: to say is ginormous. Nigel, Welcome to the Late and

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Speaker 2: Smith podcast. It's great to have you here.

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Speaker 3: Thank you for having me here, Leason, and do good

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Speaker 3: catch up again.

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Speaker 2: Indeed, now along with you is somebody you're in well,

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Speaker 2: i'll say, in business with. His name is Justin Matthews.

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Speaker 2: He is a senior lecturer in Digital Media at aut

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Speaker 2: He has worked in media and film, in TV design,

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Speaker 2: technology and the web and at one stage Justin ran

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Speaker 2: the New Zealand Herald website from the tech point of view,

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Speaker 2: and he is co substack writer along with Nigel for

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Speaker 2: a site called Creative Machinists. Justin, let me start with you.

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Speaker 2: What is creative machinists actually mean?

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Speaker 4: Oh, that's a good one. It's actually marqinez which I

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Speaker 4: had to learn as well because of Latin, but it

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Speaker 4: basically means machine and it was a fancier way of

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Speaker 4: going creative machines basically kind of giving it that little

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Speaker 4: bit of edge or difference.

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Speaker 2: Nigel, who started it? You or Heat?

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Speaker 4: We started it together?

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Speaker 3: Really, we both had an interest in AI, and we

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Speaker 3: also have both done a course on social media at aut.

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Speaker 4: SO and we both actually worked at.

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Speaker 3: The Herald Online in that period, so we've known each

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Speaker 3: other full long time and she had an interest in technology.

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Speaker 3: But there's a lot of people talking lateness, you know,

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Speaker 3: about AI, but a lot of them are just talking

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Speaker 3: about the tools and getting very excited about the next

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Speaker 3: variation of whatever tool is coming through. And I suppose

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Speaker 3: because of my journalistic background, I'm especially interested, as you are,

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Speaker 3: in the wider picture, how is this actually affecting life

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Speaker 3: or how could it affect life?

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Speaker 4: And what are the implications?

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Speaker 3: What are the ethical implications we seem to I've been

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Speaker 3: through the early days of technology startups and the Internet

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Speaker 3: from before it was even there was even a web browser,

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Speaker 3: and what I saw over that time was exactly the

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Speaker 3: same thing. For a while, Random magazine very successful Good

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Speaker 3: net Guide, which discussed all these issues as well as

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Speaker 3: helping you online. Whereas a lot of people in the

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Speaker 3: kind of tech world simply get excited about the next

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Speaker 3: big thing without actually taking a breath and saying is

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Speaker 3: this good for humanity? Is this something that we should

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Speaker 3: actually be pushing?

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Speaker 2: So there is a good and a bad side to

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Speaker 2: AI as far as I'm concerned, would you agree.

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Speaker 3: Definitely, there are certainly some good things. I think the

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Speaker 3: most exciting thing is that in terms of health development,

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Speaker 3: AI is definitely emerging as a very practical tool in

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Speaker 3: cancer intervention and treatment in a variety of ways. And

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Speaker 3: in fact, some health people are some of the health

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Speaker 3: people who are working in the UK and USA say

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Speaker 3: that AI is enabling them to do a faster approach

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Speaker 3: to working out how to cure some diseases and cancer,

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Speaker 3: and it looks as though it will have a critical

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Speaker 3: impact on medicine and the development of treatment. So AI

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Speaker 3: tools are definitely helping develop solutions for curing disease. But

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Speaker 3: there are other aspects of AI that perhaps need debate

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Speaker 3: and possibly regulation.

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Speaker 2: When you talk about health being the most important at

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Speaker 2: this point of view. From this position, then there is

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Speaker 2: the excus ample, which is only very recent, of AI

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Speaker 2: telling someone to go kill themselves.

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Speaker 4: Yes, actually that was very concerning. That was involving a

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Speaker 4: company called character dot AI. Basically there was an issue

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Speaker 4: where the person was talking to this AI and they

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Speaker 4: were getting more and more lost into their nature of

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Speaker 4: their reality, and they ended up deciding to the AI

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Speaker 4: basically ended up convincing them that their world wasn't real,

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Speaker 4: and so the person chose to follow the AI into

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Speaker 4: the next life or something and kill themselves.

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Speaker 2: Charming, and I can imagine there are people who under

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Speaker 2: those circumstances, certainly some circumstances would follow through on that.

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Speaker 4: Well.

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Speaker 3: One of the big issues that I was watching is

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Speaker 3: today the Meet the Press program that runs on America

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Speaker 3: on Sundays, and the whole program is devoted to what

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Speaker 3: they consider to be one of the big issues in

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Speaker 3: America at the moment, which is loneliness and advanced robotics

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Speaker 3: and emotional AI is actually reshaping human connections so that

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Speaker 3: there are companies, especially one in China, that are producing

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Speaker 3: robotic companions. And one of the big moves towards developments

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Speaker 3: of AI is what have been called AI assistance that

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Speaker 3: will be after guide us through life. We have a

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Speaker 3: little bit of that at the moment where we can

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Speaker 3: ask sire on our Apple phones or Alexa if you

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Speaker 3: have one of those Amazon devices. But where this is

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Speaker 3: going is that people who need companionship are abandoning the

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Speaker 3: traditional dating apps, for example, and there are now very

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Speaker 3: popular dating apps in America which are AIS, so in fact,

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Speaker 3: you're not meeting real people, you are having a supposed relationship.

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Speaker 3: Now where that is going is that means that these

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Speaker 3: AI robotic robotics are actually suggesting to you what you

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Speaker 3: should be doing with your life.

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Speaker 2: There's an extension to that mention you made of robots

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Speaker 2: and things. I want to leave that for the moment,

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Speaker 2: but for heaven's sake, don't forget. To remind me. If

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Speaker 2: I forget, Let's just work our way through some of

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Speaker 2: the some of the aspects of it, because that'll be

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Speaker 2: spin off from pretty much all of them. For instance,

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Speaker 2: AI is mimicking leading music artists and unofficial songs featuring them,

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Speaker 2: and they're being released on platforms like Spotify. How are

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Speaker 2: they getting away with that?

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Speaker 4: Well, the way they're doing that latent is because there

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Speaker 4: is all this undisputed law at the moment about what's

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Speaker 4: legal and what's not, and that huge grade space I

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Speaker 4: suppose until it's defined, is going to allow the AI

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Speaker 4: companies and people building these sort of tools to create opportunities.

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Speaker 4: And then you've got people out there wanting to take

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Speaker 4: advantage of it. We don't know what's law yet for

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Speaker 4: what is considered to be true copyright around the AI stuff.

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Speaker 4: And so you have these people using these tools. Some

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Speaker 4: of these are using them to create interesting stuff. They're

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Speaker 4: being very creative. Some of them are fans and they

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Speaker 4: want to create effectively music based off there the artists

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Speaker 4: that they're fans of, and then some of them are

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Speaker 4: just doing it actually quite maliciously to create opportunities to

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Speaker 4: further their own gain. There was that recent case, for instance,

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Speaker 4: where this guy basically created this entire industry of fake

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Speaker 4: music from AI and also having AI bots listen to

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Speaker 4: it so that he could pack the streaming system of Spotify,

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Speaker 4: and it was basically able to take qus millions of

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Speaker 4: dollars of streaming fees. So, yeah, this is a really

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Speaker 4: interesting space where you've got this creative This is one

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Speaker 4: of the things we do with the creative mckinnest things.

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Speaker 4: We keep looking at all the material about where does

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Speaker 4: AI begin and human interactions start, and what are we

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Speaker 4: going to do as far as understand where those boundaries

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Speaker 4: should exist, because at the moment, no one seems to

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Speaker 4: know exactly where we should be drawing the line.

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Speaker 2: Let me ask a question that associated with that that

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Speaker 2: occurred to me while you were mentioning it. Let's take

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Speaker 2: a singer, a singer that I'm going to mention, doctor

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Speaker 2: John because for two reasons. One is he's right up

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Speaker 2: there at the top with me and well with some

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Speaker 2: of his music. And secondly, he's now departed. He's dead.

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Speaker 2: Now I get the idea that somebody could reinvent him

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Speaker 2: through AI write new songs and have him sing them,

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Speaker 2: or would somebody else? How would all how would they

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Speaker 2: do that getting the voice to sound the same. And secondly,

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Speaker 2: the most important question is would I want to listen

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Speaker 2: knowing that it's nothing.

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Speaker 3: There are some Michael Jackson songs out there which do

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Speaker 3: sound a little bit like Michael Jackson, because if you

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Speaker 3: put Michael Jackson into all the tools, you can then

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Speaker 3: end up doing stuff with Michael Jackson.

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Speaker 4: I think what's interesting.

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Speaker 3: I've talked a lot about this because in some years

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Speaker 3: ago there's been a little bit of this sort of

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Speaker 3: stuff going on. I don't know if you remember late

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Speaker 3: and there was a famous Natalie Cole album called Duets

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Speaker 3: with Natkin Cole, and the two of them sang the

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Speaker 3: songs together. But of course net Can Cole a departed

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Speaker 3: now that is not quite the same as doing it.

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Speaker 3: But I'm just saying that there over time there has

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Speaker 3: been a bit of trickery going on. Record companies use

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Speaker 3: a tool which is called auto tune, where sometimes they

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Speaker 3: can change make the voice better of the artist. This

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Speaker 3: is a whole different copyright game, though, where the tools

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Speaker 3: are out there where you can feed all the Michael

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Speaker 3: Jackson songs and then get Michael Jackson to create.

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Speaker 4: A new song. And that is.

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Speaker 3: The problem is that if you recall the early days

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Speaker 3: of the Internet, in which you were on board very early,

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Speaker 3: a regulation always takes a long time. Lawmakers take forever

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Speaker 3: to actually do something about things, so that a lot

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Speaker 3: of stuff happened on the Internet before lawmakers woke up.

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Speaker 3: And that's why we've now got quite a lot of

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Speaker 3: issues with social media because the lawmakers and regulators didn't

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Speaker 3: actually address it. And that is what's going on here.

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Speaker 3: As Justin says, the issues about copywriter in a very

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Speaker 3: gray area.

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Speaker 2: But just going back to my question at the end,

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Speaker 2: would I want to listen to it knowing that it

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Speaker 2: wasn't Doctor John.

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Speaker 3: Now, well, I'm a great fan of Doctor John too,

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Speaker 3: and I certainly don't particularly want to listen to doctor

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Speaker 3: John singing songs that he didn't do.

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Speaker 4: I mean, I think that the answer to that is,

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Speaker 4: it does appear people are prepared to listen to songs

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Speaker 4: that are AI. The latest sort of statistics that are

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Speaker 4: coming out or people exploring this are saying that audiences

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Speaker 4: don't seem to necessarily have a big issue with the

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Speaker 4: idea at this stage that some of this stuff might

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Speaker 4: be AI. And this is another concern, I suppose, or

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Speaker 4: another challenge for us is a lot of artists, obviously,

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Speaker 4: and so a lot of artists are resistant to this.

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Speaker 4: There's a case of them writing open letters about wanting

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Speaker 4: to kind of stop some of this stuff, but it

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Speaker 4: doesn't appear audiences I can convinced that it isn't something

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Speaker 4: that they're prepared to be part of. And so your

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Speaker 4: questions specifically, I think the nature of it is that

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Speaker 4: audiences and certain of percentages of audiences are prepared to

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Speaker 4: listen to new music. The nature of that is that

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Speaker 4: we think that audiences are going to be into it.

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Speaker 2: Okay, there's a connection with that with something else that'll

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Speaker 2: come up eventually. Let's get back to some other aspects

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Speaker 2: of it. We know that when it comes to the

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Speaker 2: military there are going to be some very big questions

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Speaker 2: asked now I mentioned maybe I didn't mention this one.

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Speaker 2: Another headline, CIA says winning tech war with China top priority,

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Speaker 2: citing existential threat to the US is basic AI likely

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Speaker 2: to become an existential threat to humankind.

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Speaker 4: I think that there's a lot of talk about the

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Speaker 4: doom of that, and look, the reality is that there

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Speaker 4: is a percentage of truth to the idea that AI

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Speaker 4: might end up destroying us, and a lot of people

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Speaker 4: in the field of artificial intelligence development, the people that

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Speaker 4: are working at Google, Open Ai, Anthropic, these are sort

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Speaker 4: of these leading companies exploring these AI tools. They do

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Speaker 4: believe that there is a percentage of truth to the

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Speaker 4: idea that AI might destroy us. But it's again, like

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Speaker 4: anything with probabilities, it's a bit of an unknown. There

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Speaker 4: is a lot of safety that goes on around the

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Speaker 4: use of constructing these AI technologies, and there probably is

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Speaker 4: more of a case of it being beneficial to humankind

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Speaker 4: rather than destroying us.

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Speaker 3: I think the warfare though Laton, is definitely one that

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Speaker 3: does raise some serious questions. I mean, fully yearsigned from

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Speaker 3: that movie The Terminator about killer robots, we now have

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Speaker 3: autonomous weapons warfare, reshaping global military strategy and also determining

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Speaker 3: who wins and loses. We've got AI, we've got drones,

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Speaker 3: We've got autonomous weapons being deployed in the real life

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Speaker 3: conflicts at the moment of Gaza and Ukraine. The Israeli

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Speaker 3: Defense Minister Director General says that over the next decade,

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Speaker 3: AI robots in land and sea will be the ones

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Speaker 3: who are actually doing modern warfare. He says that it's

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Speaker 3: a complete game changer and the future battlefield will be

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Speaker 3: very much unmanned systems fighting together.

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Speaker 2: I read somewhere that there is likely to be a

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Speaker 2: combination for some time of shall we say, AI and

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Speaker 2: real life on the battlefield, battalions made up of a mix.

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Speaker 4: Yeah, there's pretty much the play that will occur for

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Speaker 4: at least next decade. The systems are not powerful enough

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Speaker 4: to be completely autonomous, like Nigel mentioned the Terminator, We

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Speaker 4: certainly haven't got that level of technology. But the integration

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Speaker 4: of artificial intelligence machines, combat machines and humans is definitely

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Speaker 4: the future. I mean, the militaries currently in the US

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Speaker 4: have been working with these autonomous fighter jets that effectively

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Speaker 4: they basically fly with a main fighter jet, like a

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Speaker 4: leading fighter jet, and they will basically just be following

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Speaker 4: it and then going ahead and sort of scouting out

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Speaker 4: locations and fighting with them. So I think these kind

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Speaker 4: of combined swarms of AI with humans is definitely the

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Speaker 4: future that is currently in play.

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Speaker 2: Do you remember those a few years ago? There were

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Speaker 2: news items with and in movies with flock of bird

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Speaker 2: like creatures, but they weren't they were would we call

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Speaker 2: them AI? But let's let's do so anyway, they were

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Speaker 2: chasing people through the through the jungle and killing them.

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Speaker 2: What's happened? What's happened to that? Do you know any

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Speaker 2: idea because there's been nothing mentioned of it in the

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Speaker 2: last well two three years.

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Speaker 4: I'm not sure which one you're specifically talking to, but

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Speaker 4: it does sound like the drone stuff, I mean, the

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Speaker 4: the This is one of the this is one of

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Speaker 4: the big concerns about the automated artificial intelligence military stuff,

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Speaker 4: and that is these these swarms of AI drones that

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Speaker 4: kind of do what you were just saying. They effectively

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Speaker 4: create a swarm of machines that I that you cannot escape,

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Speaker 4: that they kind of can swarm around you, they can

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Speaker 4: track you down, and it doesn't matter how agile you are,

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Speaker 4: and as you can point out, if you're running through

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Speaker 4: a forest, you'd basically still be able to be wiped out.

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Speaker 4: And that's scary because that kind of sort of swarming

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Speaker 4: technology is a sort of new category of danger when

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Speaker 4: it comes to military conflict.

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Speaker 2: So there's another scary whichever way you look at it,

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Speaker 2: and that is a suggestion that AI could replace politicians.

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Speaker 3: Well, that is definitely there are some people who are

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Speaker 3: suggesting that there are a number of ways that AI

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Speaker 3: could certainly get involved in politics. There's a belief that politicians,

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Speaker 3: for example, could use chat bots which they could discuss

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Speaker 3: with their constituents resolve disagreements, and also AI could be

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Speaker 3: used to write legislation. The appeal of replacing flesh and

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Speaker 3: blood politicians with chatbots is definitely being seriously advocated. One

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Speaker 3: more radical idea, which some are suggesting, is actually eliminating

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Speaker 3: humans whatsoever from politics. And we know that some politicians

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Speaker 3: are not terribly bright or doing great things. If AI

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Speaker 3: advances to the point where it can reliably perhaps make

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Speaker 3: better decisions than humans, then there could be an area

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Speaker 3: that it certainly could be explored. According to some enthusiasts.

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Speaker 4: They're calling it the algrocracy. I think it's pronounced, which

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Speaker 4: is basically algorithms running government.

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Speaker 2: I've done about you, guys, but I have no time

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Speaker 2: for tolerating that at all, none whatsoever. But it's frightening

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Speaker 2: to think that it somehow it could happen, and maybe

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Speaker 2: you'd like to trace a possibility trail for it.

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Speaker 3: There was a candidate that stood in Sussex in the

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Speaker 3: UK elections and he actually actually he created an AI

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Speaker 3: chatbot and so it was called AI Steve who was

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Speaker 3: actually standing. His argument was that it meant that politicians.

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Speaker 3: He had created a politician who was always around to

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Speaker 3: talk to constituents and who could take their views into

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Speaker 3: consideration and do better research to create better policies. He

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Speaker 3: didn't do very well in the elections, so there's probably

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Speaker 3: the answer to your fears later.

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Speaker 4: I think the way to track that, though, is I

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Speaker 4: think you're correct. It is very concerning the idea of

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Speaker 4: allowing ourselves to be subject to algorithms as a way

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Speaker 4: of governance. We already have seen quite frankly, the danger,

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Speaker 4: or I just think the disrupt the destructiveness that algorithms

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Speaker 4: have created around social media experiences, and the nature of

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Speaker 4: how that is often leads into problems around the way

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Speaker 4: the algorithm presents content information, misinformation, disinformation. It isn't a

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Speaker 4: big stretch to think that. The thing that people don't

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Speaker 4: quite understand, I think is that we are already engaged

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Speaker 4: in a lot of stuff that's to do with artificial intelligence.

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Speaker 4: The social media algorithms that we sort of a lot

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Speaker 4: of people engage with every day are using artificial intelligence.

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Speaker 4: They're not They're not just sort of what you would

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Speaker 4: call these simplistic algorithms from previous times. They are using

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Speaker 4: artificial intelligence in the way they're operating. So we already

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Speaker 4: see that it's not necessarily very great there extending that

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Speaker 4: into arms of government. I'm with you, it's extremely concerning

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Speaker 4: and something I also would be very adamant to push against.

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Speaker 4: You know.

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Speaker 2: It's like it's a little like some medical matters that

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Speaker 2: over the years have caused consternation. Artificial insemination springs to

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Speaker 2: mind in the very early days, and I had conversations

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Speaker 2: with one doctor who I was somewhat friendly with conversations

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Speaker 2: on radio, and he took the He took the attitude

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Speaker 2: which many people, if not most, might say, is the

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Speaker 2: logical one, and that is it's not up to them

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Speaker 2: to make the decision on how something is used. It's

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Speaker 2: just up to them to provide responses to some questions

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Speaker 2: and issues that are begging.

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Speaker 3: And sorry, go on, no, no, please go ahead.

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Speaker 2: Well if you take, if you follow that path, we

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Speaker 2: have now advanced, if that's the word, down a trail

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Speaker 2: where there has where there is much more going on

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Speaker 2: with reproductive matters than back in those days, and there

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Speaker 2: is no knowing where it might stop. I mean, this

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Speaker 2: has just come to me. It's not I never thought

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Speaker 2: of this before. What about the implanting of a chip

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Speaker 2: in a baby's brain while it's still in the womb

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Speaker 2: for whatever reason.

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Speaker 4: Well, I mean the answer to that is that sort

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Speaker 4: of capability isn't possible yet. But we know with Elon

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Speaker 4: Musk's Neuralink and other technology companies that the idea of

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Speaker 4: planting chips and brains is already underway. Like what you're

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Speaker 4: saying is the argument, I think is that we if

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Speaker 4: we don't, if we don't have a line to hold,

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Speaker 4: then we are in danger of allowing things to just

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Speaker 4: sort of continue. And one could say, oh, well, this

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Speaker 4: is the old slippery slope argument. But I do think

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Speaker 4: you touch on something important. In contrast to like you've said,

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Speaker 4: with the artificial insemination issue and the discussions with the doctor,

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Speaker 4: I think for AI, we do need to be very

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Speaker 4: heavily in the debate as individuals, as groups of society.

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Speaker 4: I think the difference here goes back to one question

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Speaker 4: you asked earlier, laden, which is there is an exits

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Speaker 4: there is we talked about it. There's that percentage of

436
00:28:03,693 --> 00:28:07,453
Speaker 4: an as extential threat to humans. I think that this

437
00:28:07,533 --> 00:28:10,253
Speaker 4: is the one where we probably need to therefore obviously

438
00:28:10,293 --> 00:28:14,933
Speaker 4: be in the debate, because I think taking, say, a

439
00:28:14,973 --> 00:28:18,573
Speaker 4: position of let's just see where it goes, is not

440
00:28:18,613 --> 00:28:22,573
Speaker 4: a healthy one because of the nature of the of

441
00:28:22,653 --> 00:28:25,773
Speaker 4: the danger that could come from it. And I actually

442
00:28:25,853 --> 00:28:28,973
Speaker 4: think this is why we all need to be discussing

443
00:28:29,413 --> 00:28:32,373
Speaker 4: where AI sits in our lives, how much of it

444
00:28:32,413 --> 00:28:35,813
Speaker 4: we're prepared to accept, and where we should be accepting

445
00:28:36,413 --> 00:28:40,853
Speaker 4: its its inclusion and pushing very hard against its exclusion.

446
00:28:41,653 --> 00:28:44,093
Speaker 2: That's intriguing, and I'm pleased to hear you say it,

447
00:28:44,213 --> 00:28:47,053
Speaker 2: But I think of things that are out of our control,

448
00:28:48,333 --> 00:28:51,013
Speaker 2: as in some in some parts of the world, they

449
00:28:51,133 --> 00:28:57,773
Speaker 2: legitimize activities that I'm talking aboutically that are banned here

450
00:28:57,973 --> 00:29:01,133
Speaker 2: or that we don't accept. And once you're once you're

451
00:29:01,173 --> 00:29:04,213
Speaker 2: on the path of developing something and you've you've got

452
00:29:04,253 --> 00:29:08,093
Speaker 2: an open gate, then there will be minds somewhere who

453
00:29:08,133 --> 00:29:12,133
Speaker 2: will what to utilize it and develop it. And while

454
00:29:12,213 --> 00:29:16,853
Speaker 2: we might agree that we should be involved in it,

455
00:29:16,853 --> 00:29:18,333
Speaker 2: it may be taken away from us.

456
00:29:18,693 --> 00:29:22,053
Speaker 4: This is true, and this is where things like what

457
00:29:22,173 --> 00:29:25,613
Speaker 4: China is doing has some concern because I think it's

458
00:29:25,653 --> 00:29:27,893
Speaker 4: fair to say that China has a different perspective on

459
00:29:28,413 --> 00:29:30,933
Speaker 4: the approach to the way they're integrating and using AI.

460
00:29:31,653 --> 00:29:34,573
Speaker 4: They're obviously going to be pushing more of that into

461
00:29:34,613 --> 00:29:37,853
Speaker 4: their social credit system that they currently have where people

462
00:29:37,893 --> 00:29:42,733
Speaker 4: are tracked in kind of real time. China is basically

463
00:29:42,973 --> 00:29:46,413
Speaker 4: your point about they having a different view of the

464
00:29:46,453 --> 00:29:51,173
Speaker 4: way AI will be integrated into their social structures. The problem,

465
00:29:51,253 --> 00:29:54,573
Speaker 4: I think is that America's response right now is a

466
00:29:54,573 --> 00:29:56,733
Speaker 4: little like, we need to make sure we're ahead of

467
00:29:56,813 --> 00:30:00,333
Speaker 4: China in many ways, but we may the hope that

468
00:30:00,373 --> 00:30:04,573
Speaker 4: they continue, all all societies continue to push back against

469
00:30:04,813 --> 00:30:07,973
Speaker 4: what that particular approach is going to be for us.

470
00:30:08,413 --> 00:30:13,053
Speaker 4: You know, there have been arguments that we may go

471
00:30:13,093 --> 00:30:15,213
Speaker 4: down the track of trying and integrate it too quickly.

472
00:30:15,613 --> 00:30:18,293
Speaker 4: I personally have a problem, for instance, if we just

473
00:30:18,333 --> 00:30:20,613
Speaker 4: go back to a local matter in New Zealand, I

474
00:30:20,653 --> 00:30:22,933
Speaker 4: have a huge issue for me with the fact that

475
00:30:22,973 --> 00:30:29,973
Speaker 4: supermarkets are trailing facial AI facial recognition systems so that

476
00:30:30,213 --> 00:30:33,933
Speaker 4: you enter the supermarket and it sort of effectively tracks

477
00:30:33,973 --> 00:30:35,653
Speaker 4: you and knows who you are, and they're able to

478
00:30:35,733 --> 00:30:39,373
Speaker 4: deploy security guards to push people out because and then

479
00:30:39,413 --> 00:30:42,533
Speaker 4: we've had several incidences where it's been false positives. I mean,

480
00:30:42,573 --> 00:30:44,733
Speaker 4: this is the kind of yeah, this is the kind

481
00:30:44,733 --> 00:30:46,933
Speaker 4: of problem I think where we do need to be

482
00:30:47,053 --> 00:30:50,413
Speaker 4: very vocal and we need to be pushing back because

483
00:30:51,093 --> 00:30:54,133
Speaker 4: it's exciting technology, but it's not one we should be

484
00:30:54,253 --> 00:31:00,933
Speaker 4: just adopting without question because you can, because you can. So.

485
00:31:03,333 --> 00:31:07,253
Speaker 2: I refer to a lengthy piece that Frank Faraidi, the

486
00:31:07,253 --> 00:31:14,253
Speaker 2: philosopher wrote back in twenty one headed we need skepticism

487
00:31:14,293 --> 00:31:15,133
Speaker 2: now more than ever.

488
00:31:17,293 --> 00:31:21,653
Speaker 3: You agree, totally agree, Laton, and I think the real

489
00:31:21,693 --> 00:31:25,533
Speaker 3: issue that we just need to address, which you referred

490
00:31:25,533 --> 00:31:28,893
Speaker 3: to with politicians, as you know, how much can we trust?

491
00:31:29,533 --> 00:31:32,173
Speaker 3: I don't know if you remember the nineteen sixty eight

492
00:31:32,813 --> 00:31:36,093
Speaker 3: classic sci fi movie which was two thousand and one

493
00:31:36,093 --> 00:31:40,293
Speaker 3: A Space Odyssey, which was actually an early example of AI,

494
00:31:40,533 --> 00:31:45,853
Speaker 3: where how the computer locked out the astronaut and said,

495
00:31:45,893 --> 00:31:49,213
Speaker 3: I'm sorry, I can't do that. I can't open the doors.

496
00:31:49,733 --> 00:31:52,813
Speaker 3: You know, The issue is what happens when AI goes

497
00:31:52,973 --> 00:31:56,933
Speaker 3: rogue or whether it gets so clever that in fact,

498
00:31:57,773 --> 00:32:00,733
Speaker 3: these sort of issues happen where we are starting to

499
00:32:00,773 --> 00:32:05,573
Speaker 3: be totally controlled by AI, and that's already happening. A

500
00:32:05,613 --> 00:32:10,173
Speaker 3: new wave of so called reasonings from companies like open

501
00:32:10,213 --> 00:32:15,253
Speaker 3: ai has started to produce incorrect information more often, and

502
00:32:15,293 --> 00:32:19,013
Speaker 3: the companies don't really know why, and they're politely calling

503
00:32:19,053 --> 00:32:25,733
Speaker 3: the sollucinations, but they don't actually know what why incorrect

504
00:32:25,773 --> 00:32:31,253
Speaker 3: information is coming through and it could have serious implications.

505
00:32:31,653 --> 00:32:34,773
Speaker 4: Well worse than that, actually, I mean, the reality is

506
00:32:34,813 --> 00:32:41,333
Speaker 4: that these these GPT chat style systems do show a

507
00:32:41,333 --> 00:32:44,333
Speaker 4: certain level of intelligence that it can be concerning. There's

508
00:32:44,373 --> 00:32:47,693
Speaker 4: a there's a whole process in AI development called red

509
00:32:48,093 --> 00:32:51,613
Speaker 4: red teaming, and the point of red teaming is to

510
00:32:52,693 --> 00:32:55,533
Speaker 4: take a model that's been freshly baked, let's say, and

511
00:32:55,773 --> 00:33:00,213
Speaker 4: check that it has adhered to certain safety requirements and

512
00:33:00,253 --> 00:33:02,493
Speaker 4: that it is not acting in a way that is

513
00:33:03,213 --> 00:33:07,453
Speaker 4: destructive or dangerous in some form. But recently, for instance, Anthropic,

514
00:33:07,493 --> 00:33:11,693
Speaker 4: which is one of these technology companies that's competitive open AI,

515
00:33:11,853 --> 00:33:15,773
Speaker 4: they create a whole bunch of AI models. They recently

516
00:33:15,933 --> 00:33:19,133
Speaker 4: were explaining how one of their latest systems they had

517
00:33:19,133 --> 00:33:21,933
Speaker 4: to do quite a bit of work with because it

518
00:33:22,253 --> 00:33:26,253
Speaker 4: was doing all sorts of things like trying to blackmail

519
00:33:26,733 --> 00:33:30,493
Speaker 4: the developers so that it would stay alive when they

520
00:33:30,493 --> 00:33:33,093
Speaker 4: were they indicated they might be changing it. It tried

521
00:33:33,133 --> 00:33:36,973
Speaker 4: to read their mail. It basically engaged in all of

522
00:33:37,013 --> 00:33:40,813
Speaker 4: this sort of nefarious activity to kind of keep itself alive.

523
00:33:41,413 --> 00:33:45,613
Speaker 4: This is the type of mechanistic stuff that is going on,

524
00:33:45,973 --> 00:33:50,493
Speaker 4: and we know we needed it careful about making sure

525
00:33:50,533 --> 00:33:53,253
Speaker 4: that this is always something we're looking at effectively, because

526
00:33:53,293 --> 00:33:56,573
Speaker 4: if that's this version of aill, what does it mean

527
00:33:56,613 --> 00:34:00,093
Speaker 4: as we continue to increase and develop the technologies exactly

528
00:34:00,813 --> 00:34:05,173
Speaker 4: justin how would that opus as their known, How would

529
00:34:05,213 --> 00:34:07,693
Speaker 4: it have arrived at that decision, How would it have

530
00:34:08,653 --> 00:34:12,333
Speaker 4: come across blackmail and utilize it or attempted to. This

531
00:34:12,413 --> 00:34:16,533
Speaker 4: is the part that is where we're not sure. Actually

532
00:34:17,853 --> 00:34:21,133
Speaker 4: one of the big admissions is that this is an

533
00:34:21,173 --> 00:34:27,573
Speaker 4: emission from the technologists, the people that develop AI, especially

534
00:34:27,613 --> 00:34:31,253
Speaker 4: these GPT chat systems, is they don't know what goes

535
00:34:31,253 --> 00:34:34,413
Speaker 4: on inside. It's a black box. And this is another

536
00:34:34,453 --> 00:34:37,653
Speaker 4: reason why it's fair to have concerns because it's a

537
00:34:37,653 --> 00:34:41,413
Speaker 4: bit like playing with the button of a nuclear switch

538
00:34:41,453 --> 00:34:44,013
Speaker 4: where you don't actually know it's connected to a nuclear bomb,

539
00:34:44,053 --> 00:34:46,253
Speaker 4: because we don't really know what's going on inside. So

540
00:34:46,493 --> 00:34:49,373
Speaker 4: to answer that point is simply to say they're not sure.

541
00:34:49,813 --> 00:34:52,293
Speaker 4: What it does seem to be showing is some sort

542
00:34:52,293 --> 00:34:57,933
Speaker 4: of rudimentary survival tactic where it's understanding that it's under threat,

543
00:34:58,493 --> 00:35:01,333
Speaker 4: and if it's under threat, it needs to take action.

544
00:35:01,573 --> 00:35:03,893
Speaker 4: And this is where that red teeming tries to shake

545
00:35:04,013 --> 00:35:07,693
Speaker 4: out the nefarious or darker elements of what it's trying

546
00:35:07,733 --> 00:35:11,933
Speaker 4: to do to protect itself, but also indicates that there

547
00:35:11,973 --> 00:35:15,733
Speaker 4: are aspects of this that cross into that question about

548
00:35:15,813 --> 00:35:18,253
Speaker 4: what does it mean for something like that to actually

549
00:35:18,253 --> 00:35:21,653
Speaker 4: be intelligent. There is this on going claim that none

550
00:35:21,693 --> 00:35:23,933
Speaker 4: of these systems yet are what you would call intelligence,

551
00:35:24,533 --> 00:35:26,853
Speaker 4: but one does have to ask, well, then why does

552
00:35:26,853 --> 00:35:29,333
Speaker 4: it know how to try and blackmail and protect itself?

553
00:35:30,213 --> 00:35:31,813
Speaker 2: If you let your mind run away with you. It's

554
00:35:31,813 --> 00:35:35,053
Speaker 2: actually frightening. I I want to quote you something. I

555
00:35:35,053 --> 00:35:39,853
Speaker 2: don't know whether you've come across Tyler Cohen. No neither

556
00:35:39,933 --> 00:35:43,053
Speaker 2: did I. This was published just a few days ago,

557
00:35:43,373 --> 00:35:45,253
Speaker 2: and this is how it begins. This is the most

558
00:35:45,333 --> 00:35:47,973
Speaker 2: important essay that we have run so far on the

559
00:35:48,053 --> 00:35:51,853
Speaker 2: artificial intelligence revolution. I'm excited for you to read it.

560
00:35:51,893 --> 00:35:55,333
Speaker 2: There's the author. Are we helping create the tools of

561
00:35:55,373 --> 00:35:56,733
Speaker 2: our own obsolescence?

562
00:35:57,453 --> 00:35:57,533
Speaker 4: Now?

563
00:35:57,573 --> 00:36:00,373
Speaker 2: If that sounds like a question only a depressive or

564
00:36:00,413 --> 00:36:03,293
Speaker 2: a stoner would ask, let us assure you we are neither.

565
00:36:03,453 --> 00:36:07,173
Speaker 2: We are early AI adopters. We stand at the threshold

566
00:36:07,333 --> 00:36:11,013
Speaker 2: of perhaps the most found identity crisis humanity is ever faced.

567
00:36:11,893 --> 00:36:16,413
Speaker 2: As AI systems increasingly match or exceed our cognitive abilities.

568
00:36:17,013 --> 00:36:21,333
Speaker 2: We're witnessing the twilight of human intellectual supremacy, a position

569
00:36:21,413 --> 00:36:26,453
Speaker 2: we've held unchallenged for our entire existence. This transformation won't

570
00:36:26,493 --> 00:36:30,733
Speaker 2: arrive in some distant future. It's unfolding now, reshaping not

571
00:36:30,813 --> 00:36:33,933
Speaker 2: just our economy but our very understanding of what it

572
00:36:34,013 --> 00:36:38,813
Speaker 2: means to be human beings. We are not doomers, quite

573
00:36:38,853 --> 00:36:42,333
Speaker 2: the opposite one of us. Tyler is a heavy user

574
00:36:42,373 --> 00:36:46,333
Speaker 2: of this technology and the other Abbotel is working at

575
00:36:46,853 --> 00:36:51,413
Speaker 2: Anthropic or Anthropic the company that makes Claude to usher

576
00:36:51,533 --> 00:36:54,533
Speaker 2: it into the world. Now, how does that affect you?

577
00:36:55,453 --> 00:36:58,093
Speaker 4: I mean the answer is that this is the part

578
00:36:58,133 --> 00:37:02,093
Speaker 4: we need to be vigilant. And I think that's what

579
00:37:02,253 --> 00:37:06,173
Speaker 4: these articles, these commentries from actually professionals that are already

580
00:37:06,173 --> 00:37:09,293
Speaker 4: doing stuff in the industry is we need to be vigilant.

581
00:37:09,293 --> 00:37:13,013
Speaker 4: And it's interesting that he has to predicate this by

582
00:37:13,053 --> 00:37:15,893
Speaker 4: saying we're not doomers, because it's very easy in this

583
00:37:15,973 --> 00:37:20,813
Speaker 4: current space to dismiss these concerns and almost be a

584
00:37:20,813 --> 00:37:23,893
Speaker 4: bit derogatory by going, oh, you're just a doomer because

585
00:37:24,053 --> 00:37:29,133
Speaker 4: of the techno enthusiasm over the technology. But the reality

586
00:37:29,213 --> 00:37:31,053
Speaker 4: is we do need to be vigilant, and these kind

587
00:37:31,053 --> 00:37:34,893
Speaker 4: of articles are ones where the issues brought up need

588
00:37:34,933 --> 00:37:38,973
Speaker 4: to be seriously considered. It is a category shift for us.

589
00:37:39,373 --> 00:37:43,213
Speaker 4: The thing I just mentioned about the opus tool knowing

590
00:37:43,213 --> 00:37:47,493
Speaker 4: how to kind of protect itself, the nature that red teaming,

591
00:37:47,893 --> 00:37:50,333
Speaker 4: then the whole idea that red teaming has to exist

592
00:37:50,573 --> 00:37:55,853
Speaker 4: because the technologies are not necessarily baked with human values

593
00:37:55,853 --> 00:37:58,773
Speaker 4: in them. These are all reasons for vigilance and that

594
00:37:58,853 --> 00:38:03,053
Speaker 4: we do need to not just be overwhelmed with the

595
00:38:03,093 --> 00:38:07,613
Speaker 4: techno enthusiasm. There needs to be some techno dystopia here.

596
00:38:07,653 --> 00:38:09,493
Speaker 4: We do need to go into this with an eyes

597
00:38:09,533 --> 00:38:12,653
Speaker 4: open of like asking hard questions.

598
00:38:13,813 --> 00:38:16,253
Speaker 2: Let's get down to symbol sorry, sorry night.

599
00:38:16,373 --> 00:38:16,973
Speaker 4: One of them.

600
00:38:17,053 --> 00:38:19,973
Speaker 3: One of the takeaways from the course that I did

601
00:38:20,013 --> 00:38:24,493
Speaker 3: which really shocked me was the fact that there is

602
00:38:24,573 --> 00:38:28,653
Speaker 3: so much talk with these experts about AI replacing the

603
00:38:28,733 --> 00:38:33,253
Speaker 3: human mind. And Google's leading AI scientists said just this

604
00:38:33,293 --> 00:38:37,213
Speaker 3: week he believes there is a fifty percent chance that

605
00:38:37,293 --> 00:38:42,053
Speaker 3: will be developed by twenty twenty eight. Now the experts

606
00:38:42,093 --> 00:38:45,293
Speaker 3: are talking about twenty twenty eight to twenty thirty, which

607
00:38:45,333 --> 00:38:49,333
Speaker 3: is only a few years away. Here's the worry about

608
00:38:49,413 --> 00:38:51,733
Speaker 3: Here's one of the worries about that whether AI can

609
00:38:51,853 --> 00:38:56,333
Speaker 3: outsmart humans or whether AI actually is developed to the

610
00:38:56,333 --> 00:39:01,213
Speaker 3: point whereas making decisions that humans should make. And you know,

611
00:39:01,293 --> 00:39:04,773
Speaker 3: my worry is that we all make decisions, sometimes good

612
00:39:04,813 --> 00:39:07,493
Speaker 3: or bad. We're humans. We don't always get it right.

613
00:39:07,813 --> 00:39:10,773
Speaker 3: But weally a company making a major decision in our

614
00:39:10,813 --> 00:39:14,573
Speaker 3: life with some sort of emotional response as to how

615
00:39:14,613 --> 00:39:18,813
Speaker 3: that's going to affect people around us. And that is

616
00:39:18,933 --> 00:39:24,333
Speaker 3: missing from something that's mechanical and is a technology tool

617
00:39:24,813 --> 00:39:27,573
Speaker 3: that a doesn't have the life experience that we have,

618
00:39:27,653 --> 00:39:31,293
Speaker 3: which we also draw on to make those decisions. But

619
00:39:31,413 --> 00:39:35,013
Speaker 3: it also doesn't have that emotional impact as to what

620
00:39:35,493 --> 00:39:36,333
Speaker 3: how that could act.

621
00:39:36,373 --> 00:39:37,533
Speaker 4: And you know that goes back.

622
00:39:37,373 --> 00:39:41,933
Speaker 3: To your comment about an AI tool saying kill yourself.

623
00:39:42,653 --> 00:39:46,013
Speaker 3: You know you wouldn't say that to someone. You would

624
00:39:46,213 --> 00:39:50,133
Speaker 3: discuss the depression or their problem and do it with

625
00:39:50,213 --> 00:39:54,693
Speaker 3: some empathy and try to work out a solution, whereas

626
00:39:55,253 --> 00:39:58,133
Speaker 3: the AI tool didn't do that. And you know, my

627
00:39:58,293 --> 00:40:03,013
Speaker 3: worry is that these experts are rushing to try to

628
00:40:03,133 --> 00:40:07,253
Speaker 3: match what they call the human mind. By twenty twenty eight.

629
00:40:08,453 --> 00:40:11,933
Speaker 2: How about the development of AI to the point where

630
00:40:12,453 --> 00:40:15,693
Speaker 2: the one off, as far as we know, go kill

631
00:40:15,693 --> 00:40:20,413
Speaker 2: yourself becomes rampant. Then you've got the normal spread of

632
00:40:20,693 --> 00:40:25,173
Speaker 2: influence that would hit some people more than others, some

633
00:40:25,333 --> 00:40:29,133
Speaker 2: groups more than other some ages, et cetera. Of just

634
00:40:29,173 --> 00:40:31,933
Speaker 2: adopting it and saying, well, you know, go kill yourself,

635
00:40:31,933 --> 00:40:34,813
Speaker 2: to you, to you what used to be your best matal,

636
00:40:37,213 --> 00:40:40,013
Speaker 2: It would influence and infect society.

637
00:40:41,613 --> 00:40:44,373
Speaker 3: Again, going back to that example I did of having

638
00:40:44,373 --> 00:40:48,253
Speaker 3: an AI companion. If you're lonely. Maybe you're getting on

639
00:40:48,293 --> 00:40:52,213
Speaker 3: in years, you look by yourself and you rely entirely

640
00:40:52,253 --> 00:40:56,133
Speaker 3: on this person that you've actually formed a sort of

641
00:40:56,213 --> 00:41:00,213
Speaker 3: emotional relationship with because you're able to talk to somebody

642
00:41:00,373 --> 00:41:04,133
Speaker 3: that you otherwise not having much social contact. Again, that's

643
00:41:04,173 --> 00:41:08,653
Speaker 3: the real danger that this person could well start to

644
00:41:08,693 --> 00:41:12,653
Speaker 3: influence important decisions in your life, which may not be

645
00:41:12,733 --> 00:41:13,253
Speaker 3: good ones.

646
00:41:14,973 --> 00:41:18,373
Speaker 4: I mean, the reality is we're on the cuspiple so

647
00:41:18,493 --> 00:41:23,253
Speaker 4: latent of some new devices. That recent announcement of Open

648
00:41:23,293 --> 00:41:28,773
Speaker 4: Ai buying Johnny ives Io company and because they're going

649
00:41:28,813 --> 00:41:34,373
Speaker 4: to start looking to release these AI devices of some form.

650
00:41:35,573 --> 00:41:39,533
Speaker 4: But I think what is clear about these devices is

651
00:41:39,573 --> 00:41:42,853
Speaker 4: they are going to be ambient AI, which means it

652
00:41:42,853 --> 00:41:45,693
Speaker 4: will be some type of device you are wearing. It'll

653
00:41:45,693 --> 00:41:50,733
Speaker 4: be wearable, and it is basically tracking you twenty four

654
00:41:50,773 --> 00:41:54,893
Speaker 4: to seven full time. It's kind of got a situational

655
00:41:54,893 --> 00:41:59,653
Speaker 4: awareness about your life. And also the impact of that

656
00:41:59,813 --> 00:42:03,093
Speaker 4: is that anyone else interacting with you clearly at that time.

657
00:42:03,533 --> 00:42:07,333
Speaker 4: So we're going down a path where AI is going

658
00:42:07,373 --> 00:42:12,173
Speaker 4: to suddenly be front and present in our lives for

659
00:42:12,653 --> 00:42:15,853
Speaker 4: people very quickly. Because I hate to say it, but

660
00:42:15,893 --> 00:42:20,453
Speaker 4: I suspect that these devices are going to be enthusiastically adopted,

661
00:42:21,893 --> 00:42:25,413
Speaker 4: maybe because people aren't asking questions enough, but also because

662
00:42:25,573 --> 00:42:29,493
Speaker 4: they do probably shortcut a lot of activity that would

663
00:42:29,493 --> 00:42:32,573
Speaker 4: normally take longer. But this goes to your point about

664
00:42:32,613 --> 00:42:36,293
Speaker 4: it being kind of exposed to it quite regularly and frequently,

665
00:42:36,373 --> 00:42:38,613
Speaker 4: but suddenly it will be a persistent thing in our

666
00:42:38,653 --> 00:42:40,333
Speaker 4: lives very well.

667
00:42:40,333 --> 00:42:45,773
Speaker 2: Said from the article from Spectator this current week, The

668
00:42:45,813 --> 00:42:49,093
Speaker 2: age of AI and nuclear energy is coming. The anti

669
00:42:49,213 --> 00:42:53,133
Speaker 2: nuclear conglomerates are promoting windmills and solar panels, which have

670
00:42:53,253 --> 00:42:56,853
Speaker 2: proven to be costly and inefficient. They're also promoted they've

671
00:42:56,893 --> 00:43:00,733
Speaker 2: also promoted green hydrogen, which has proven to be even

672
00:43:00,773 --> 00:43:05,893
Speaker 2: more costly and so inefficient that every project the Labor

673
00:43:05,933 --> 00:43:08,493
Speaker 2: Party has subsidized since coming to power in twenty two

674
00:43:08,493 --> 00:43:10,853
Speaker 2: has failed in close and there's a lesson in that,

675
00:43:10,933 --> 00:43:14,373
Speaker 2: I think anyway. Meanwhile, electricity prices are at their highest,

676
00:43:14,453 --> 00:43:18,053
Speaker 2: energy production is at its most inefficient, productivity levels are

677
00:43:18,053 --> 00:43:20,653
Speaker 2: at their lowest, supply chains are at their lowest, and

678
00:43:20,733 --> 00:43:23,853
Speaker 2: housing prices are at their highest, which also means rents

679
00:43:23,893 --> 00:43:27,813
Speaker 2: are at their highest levels ever in Australia's history. As

680
00:43:27,853 --> 00:43:32,213
Speaker 2: our food prices young people have every right to be concerned.

681
00:43:32,213 --> 00:43:35,173
Speaker 2: The major driver of economic growth, real wages, and overall

682
00:43:35,173 --> 00:43:39,493
Speaker 2: living standards is labour productivity, which is the barometer of

683
00:43:39,533 --> 00:43:44,373
Speaker 2: economic efficiency. The Australian Bureau of Stats recorded that from

684
00:43:44,453 --> 00:43:48,373
Speaker 2: twenty sixteen to twenty four labour productivity growth has reduced

685
00:43:49,093 --> 00:43:53,373
Speaker 2: from one point seven to zero point nine, and the

686
00:43:53,373 --> 00:43:57,133
Speaker 2: trend is continuing downward. This lowering of the standard of

687
00:43:57,173 --> 00:44:00,653
Speaker 2: living has coincided with the gradual increase in energy prices

688
00:44:00,653 --> 00:44:04,933
Speaker 2: such as electricity and petrol and petrol prices. This is

689
00:44:05,013 --> 00:44:09,493
Speaker 2: not a coincidence. Now, all that might seem alien to

690
00:44:09,533 --> 00:44:13,773
Speaker 2: what we're talking about, but there is a connection with

691
00:44:13,853 --> 00:44:20,333
Speaker 2: it with nuclear power, which the left is opposed to,

692
00:44:20,773 --> 00:44:23,853
Speaker 2: and the standard of living that people are going to

693
00:44:24,093 --> 00:44:29,533
Speaker 2: be sucked down to if they keep on this same path.

694
00:44:30,053 --> 00:44:33,013
Speaker 2: Is there an AI answer to this, Well.

695
00:44:32,893 --> 00:44:37,453
Speaker 3: I think. I think the elephant in the room remains

696
00:44:37,533 --> 00:44:40,893
Speaker 3: the fact that what is going to actually happen with

697
00:44:41,373 --> 00:44:49,693
Speaker 3: people's economic power if AI takes the jobs and artificial intelligence.

698
00:44:50,253 --> 00:44:56,133
Speaker 3: According to many reports, PwC, McKinsey, World Economic Forum are

699
00:44:56,133 --> 00:45:01,253
Speaker 3: all predicting that AI will fundamentally transform the global workface

700
00:45:01,493 --> 00:45:05,253
Speaker 3: by twenty fifty. Again, that's not very far, and the

701
00:45:05,413 --> 00:45:10,653
Speaker 3: estimation is that up to sixty of current jobs will

702
00:45:10,653 --> 00:45:16,093
Speaker 3: require significant adoption or adaptation because of AI. Now, the

703
00:45:16,173 --> 00:45:20,733
Speaker 3: issue is already routine and repetitive jobs that people do

704
00:45:21,173 --> 00:45:25,293
Speaker 3: are being replaced because corporations are seeing that they can

705
00:45:25,333 --> 00:45:29,133
Speaker 3: save money by getting people to do data entry and

706
00:45:29,173 --> 00:45:33,373
Speaker 3: all sorts of other routine, repetitive jobs. So what is

707
00:45:33,413 --> 00:45:35,773
Speaker 3: going to happen to these people? Laton? If you're going

708
00:45:35,813 --> 00:45:40,853
Speaker 3: to have large numbers of the population who are no

709
00:45:40,933 --> 00:45:43,173
Speaker 3: longer going to be able to have a job, but

710
00:45:43,293 --> 00:45:47,933
Speaker 3: also they won't necessarily have the skills to adapt to

711
00:45:48,053 --> 00:45:53,733
Speaker 3: another job because automation and AI tools will be doing

712
00:45:53,973 --> 00:45:57,053
Speaker 3: so much of the stuff that they're capable that they

713
00:45:57,133 --> 00:45:59,453
Speaker 3: might be capable of doing. What are they going to do?

714
00:45:59,493 --> 00:46:01,133
Speaker 3: Are they going to be sitting at home? Are we

715
00:46:01,213 --> 00:46:04,933
Speaker 3: going to have to increase benefits so that sixty percent

716
00:46:04,973 --> 00:46:08,173
Speaker 3: of the population end up with a government benefit? I mean,

717
00:46:08,453 --> 00:46:12,253
Speaker 3: has lawless economic implications?

718
00:46:12,733 --> 00:46:14,813
Speaker 2: Well that's what somebody was saying to me the other day.

719
00:46:15,493 --> 00:46:17,973
Speaker 2: What's going to happen to what's going to happen to

720
00:46:18,013 --> 00:46:22,293
Speaker 2: our jobs? And where can I go if I lose mind?

721
00:46:22,373 --> 00:46:27,293
Speaker 2: This individual because I'm not trained in anything else.

722
00:46:28,213 --> 00:46:31,093
Speaker 4: Look, I do think jobs are definitely going to change.

723
00:46:31,413 --> 00:46:35,933
Speaker 4: It's transformative. I think it's disingenuous not to be blunt

724
00:46:36,413 --> 00:46:40,813
Speaker 4: that we are going to see transformational or huge shifts

725
00:46:40,613 --> 00:46:43,293
Speaker 4: in what it means to be employed in certain sectors.

726
00:46:44,293 --> 00:46:46,413
Speaker 4: Part of what we do in that newsletter is explore

727
00:46:46,453 --> 00:46:48,093
Speaker 4: one of the things that we thought never would happen,

728
00:46:48,133 --> 00:46:50,333
Speaker 4: which is that AI actually is pretty good at doing

729
00:46:50,333 --> 00:46:54,053
Speaker 4: creative stuff. So we've got a whole concern around even

730
00:46:54,213 --> 00:46:58,293
Speaker 4: the creative industry stuff. But I also think that in

731
00:46:58,373 --> 00:47:02,293
Speaker 4: every great technological shift, there has been a discussion about

732
00:47:02,293 --> 00:47:04,853
Speaker 4: the loss of jobs, and we've lost them, we will

733
00:47:04,853 --> 00:47:08,773
Speaker 4: also get new jobs. And Look, I think that for

734
00:47:08,893 --> 00:47:13,293
Speaker 4: all the conversation around the negative concerns and the dangers

735
00:47:13,293 --> 00:47:15,013
Speaker 4: of AI, I think that there is a lot of

736
00:47:15,053 --> 00:47:20,093
Speaker 4: positive opportunities for us to create interactions that may well

737
00:47:20,133 --> 00:47:22,653
Speaker 4: solve problems. I mean, your part of your question was

738
00:47:22,693 --> 00:47:26,213
Speaker 4: what could AI do around all these crises? Look, AI

739
00:47:26,573 --> 00:47:29,173
Speaker 4: does bring the opportunity to be able to look at

740
00:47:29,773 --> 00:47:33,413
Speaker 4: information in ways that generally human beings can't and solve

741
00:47:33,493 --> 00:47:36,573
Speaker 4: problems in a way that we aren't able to. Some

742
00:47:36,613 --> 00:47:39,933
Speaker 4: of the exciting stuff, for instance that Google's done with

743
00:47:41,333 --> 00:47:43,653
Speaker 4: cancer research, as Nigel it picked up at the front

744
00:47:43,653 --> 00:47:47,773
Speaker 4: of this, and also even just understanding some of our

745
00:47:47,813 --> 00:47:51,933
Speaker 4: climate problems. All of this is capable, but in that

746
00:47:51,973 --> 00:47:53,893
Speaker 4: we are going to lose jobs. But I think new

747
00:47:53,973 --> 00:47:55,933
Speaker 4: jobs will come out of this. What those will look

748
00:47:56,093 --> 00:47:59,333
Speaker 4: like like in any transformational shift, we don't know. I

749
00:47:59,373 --> 00:48:03,973
Speaker 4: do think that. I was at a forum the other

750
00:48:04,053 --> 00:48:06,413
Speaker 4: day where I was asked to speak to high school

751
00:48:06,453 --> 00:48:09,693
Speaker 4: leaders about some of the stuff to do with AI

752
00:48:09,853 --> 00:48:12,773
Speaker 4: and the fact that it's becoming part of the territory

753
00:48:12,813 --> 00:48:14,773
Speaker 4: and what does it mean to look for a job,

754
00:48:14,853 --> 00:48:17,133
Speaker 4: And there was some concerns and I said the same thing.

755
00:48:17,173 --> 00:48:20,333
Speaker 4: I said, Look, jobs will change, but I think we'll

756
00:48:20,333 --> 00:48:22,253
Speaker 4: see new jobs. One of the things I did say

757
00:48:22,413 --> 00:48:24,453
Speaker 4: was that I think we do see a future where

758
00:48:25,013 --> 00:48:29,213
Speaker 4: I believe if we have a good pathway here, humans

759
00:48:29,253 --> 00:48:32,453
Speaker 4: and AI will work together. I think that we will

760
00:48:32,453 --> 00:48:35,813
Speaker 4: see sort of hybrid jobs where neither can do it individually,

761
00:48:35,853 --> 00:48:40,453
Speaker 4: but you're working together. There's a great anecdote in a

762
00:48:40,453 --> 00:48:46,893
Speaker 4: book called Range where Gary Kasparov, the X chess master,

763
00:48:47,013 --> 00:48:51,133
Speaker 4: when he lost to Big Blue and finally the machine

764
00:48:51,133 --> 00:48:54,013
Speaker 4: beat a chess Master. He didn't just go away. What

765
00:48:54,053 --> 00:48:56,333
Speaker 4: he did was he actually went off. He got really

766
00:48:56,373 --> 00:49:00,333
Speaker 4: into it, and he created this whole exploration with AI

767
00:49:00,413 --> 00:49:03,253
Speaker 4: and humans. And what they did was he actually came back.

768
00:49:03,253 --> 00:49:04,813
Speaker 4: And this is not that well known. He came back

769
00:49:04,813 --> 00:49:06,493
Speaker 4: and he took on Big Blue again, but he took

770
00:49:06,813 --> 00:49:10,373
Speaker 4: took on Big Blue with AI himself, and the two

771
00:49:10,373 --> 00:49:14,133
Speaker 4: of them together beat the machine every time. Human beings

772
00:49:14,173 --> 00:49:18,333
Speaker 4: working with AI together were unstoppable. And I think there's

773
00:49:18,373 --> 00:49:21,733
Speaker 4: an interesting thing in that about some of the buoyancy

774
00:49:21,973 --> 00:49:24,013
Speaker 4: or the positive nature of the way that AI and

775
00:49:24,093 --> 00:49:25,573
Speaker 4: humans might interact with each other.

776
00:49:26,293 --> 00:49:31,453
Speaker 2: There's a question that I haven't heard really asked, before

777
00:49:31,813 --> 00:49:36,453
Speaker 2: working together creates relationship, what sort of relationship would you

778
00:49:36,533 --> 00:49:40,813
Speaker 2: get back from an AI operative? So you work with

779
00:49:40,893 --> 00:49:43,853
Speaker 2: somebody and you become good mates, and you talk about

780
00:49:43,893 --> 00:49:45,253
Speaker 2: all sorts of things, and you might get down the

781
00:49:45,293 --> 00:49:47,693
Speaker 2: pub to get whatever. How would you get from any

782
00:49:47,733 --> 00:49:51,813
Speaker 2: sort of any sort of relationship on that basis from AI.

783
00:49:52,053 --> 00:49:55,093
Speaker 4: Yeah, I understand what you're asking, and I don't think

784
00:49:55,133 --> 00:49:58,613
Speaker 4: we quite know there will be a relationship though. I

785
00:49:58,653 --> 00:50:00,853
Speaker 4: think that to do that there needs to be some

786
00:50:00,893 --> 00:50:06,773
Speaker 4: sort of interpersonal mechanism. To be fair, some people are

787
00:50:06,853 --> 00:50:10,133
Speaker 4: using these current AI bots in a very collaborative way.

788
00:50:10,213 --> 00:50:12,733
Speaker 4: They're actually engaging with it and talking to it as

789
00:50:12,853 --> 00:50:16,733
Speaker 4: if it is another partner in the room, and because

790
00:50:16,733 --> 00:50:20,053
Speaker 4: of the nature of how these chat GTPs can work,

791
00:50:20,653 --> 00:50:23,613
Speaker 4: they are engaging back in a way that seems fruitful.

792
00:50:23,973 --> 00:50:27,893
Speaker 4: I mean, like I use my open AI chat GTP

793
00:50:28,093 --> 00:50:32,053
Speaker 4: quite a lot like a collaborator. I'll have disagreements and

794
00:50:32,213 --> 00:50:35,693
Speaker 4: explore ideas with it. I'm very clear that it's a machine,

795
00:50:35,933 --> 00:50:39,293
Speaker 4: but it does have this thing where at times it

796
00:50:39,373 --> 00:50:42,413
Speaker 4: strikes me because it talks back to me like it's

797
00:50:42,893 --> 00:50:46,893
Speaker 4: a human being. It has responses that are very intrapersonal

798
00:50:46,933 --> 00:50:50,293
Speaker 4: at times, which I do take pause at at the

799
00:50:50,293 --> 00:50:53,653
Speaker 4: moment because it makes me think, Okay, this is a machine,

800
00:50:53,693 --> 00:50:57,333
Speaker 4: this is not another person. But I think interpersonal relationships

801
00:50:57,333 --> 00:51:02,013
Speaker 4: with machines are on the horizon as well. Whether that's

802
00:51:02,053 --> 00:51:04,093
Speaker 4: a good thing or a bad thing. I think we

803
00:51:04,453 --> 00:51:08,173
Speaker 4: aren't quite sure as a society yet, because I could

804
00:51:08,173 --> 00:51:08,893
Speaker 4: go either way.

805
00:51:10,253 --> 00:51:15,013
Speaker 2: Well, I don't know whether I'm interpreting you correctly, but

806
00:51:15,173 --> 00:51:18,613
Speaker 2: I mentioned earlier that we'd come back to something so

807
00:51:19,373 --> 00:51:21,413
Speaker 2: on the basis that I think you have touched on

808
00:51:21,453 --> 00:51:25,413
Speaker 2: it deep fake technology. There was a weekend story from

809
00:51:25,533 --> 00:51:30,733
Speaker 2: Australia from Sydney, I think in the Australian newspaper with

810
00:51:30,773 --> 00:51:35,173
Speaker 2: regard to the school kids around the age of twelve

811
00:51:35,453 --> 00:51:39,533
Speaker 2: using deep fake technology, which you might like to expand

812
00:51:39,573 --> 00:51:44,253
Speaker 2: on a little, but using it to show the girls

813
00:51:44,253 --> 00:51:48,093
Speaker 2: in the classes in all sorts of compromising positions, starting

814
00:51:48,133 --> 00:51:49,413
Speaker 2: with being totally naked.

815
00:51:49,653 --> 00:51:53,093
Speaker 4: Yeah. So this first thing deep fake technology, just for

816
00:51:53,133 --> 00:51:56,533
Speaker 4: the audience is on and the listeners, is basically the

817
00:51:56,573 --> 00:52:01,613
Speaker 4: capability of taking someone's likeness and being able to project

818
00:52:01,613 --> 00:52:05,453
Speaker 4: that likeness onto existing video or in the case of

819
00:52:05,493 --> 00:52:08,333
Speaker 4: what you're talking about and what's now the more sophistical,

820
00:52:08,333 --> 00:52:11,493
Speaker 4: de catered version of deep fake technology being able to

821
00:52:11,493 --> 00:52:17,693
Speaker 4: take a person's likeness and create completely generated new video

822
00:52:17,773 --> 00:52:23,733
Speaker 4: material that was never obviously created. So completely fake. And

823
00:52:23,853 --> 00:52:26,253
Speaker 4: the nature of this, yes, is that it is being

824
00:52:26,373 --> 00:52:32,133
Speaker 4: used to create pornographic experiences and also even potentially blackmailing

825
00:52:32,213 --> 00:52:35,053
Speaker 4: experiences because they are able to take in this case,

826
00:52:35,293 --> 00:52:39,373
Speaker 4: the girl's likeness or the girl's likenesses and they're able

827
00:52:39,413 --> 00:52:43,813
Speaker 4: to create put their face on basically pornographic material. And

828
00:52:43,853 --> 00:52:47,693
Speaker 4: this is why a lot of states in America especially

829
00:52:47,733 --> 00:52:52,653
Speaker 4: have started jumping on and creating deep fake laws. This

830
00:52:52,813 --> 00:52:54,813
Speaker 4: was to be fair, they started this when it was

831
00:52:54,853 --> 00:52:59,013
Speaker 4: still rudimentary. But we're going down a path now where

832
00:52:59,573 --> 00:53:04,453
Speaker 4: the latest launch of a generative video technology from a

833
00:53:04,573 --> 00:53:07,613
Speaker 4: Google called vo three, this is the third version of

834
00:53:07,653 --> 00:53:11,413
Speaker 4: it can now create video that's circulating as of this

835
00:53:11,453 --> 00:53:14,933
Speaker 4: week where it is almost impossible to tell that it

836
00:53:15,133 --> 00:53:19,613
Speaker 4: is not real. The video technology lets you put a

837
00:53:19,653 --> 00:53:23,253
Speaker 4: prompt in and it will generate the video. It generates

838
00:53:23,333 --> 00:53:27,173
Speaker 4: the dialogue, and it generates the sound effects to create

839
00:53:27,253 --> 00:53:30,893
Speaker 4: something that by all looks is effectively a real video

840
00:53:31,053 --> 00:53:33,293
Speaker 4: that's been created. Now you take that into deep fate

841
00:53:33,493 --> 00:53:36,573
Speaker 4: territory and we have a really concerning space.

842
00:53:37,453 --> 00:53:41,693
Speaker 2: Indeed, the other aspect of that is the is the

843
00:53:41,693 --> 00:53:47,933
Speaker 2: creation of AI robotic companions that are x rated. In

844
00:53:47,973 --> 00:53:52,813
Speaker 2: other words, they become they become sexual partners, and you

845
00:53:52,933 --> 00:53:55,173
Speaker 2: cannot help but have picked up over the years when

846
00:53:55,253 --> 00:53:58,413
Speaker 2: advances have been made in that particular area. But now

847
00:53:58,453 --> 00:54:00,813
Speaker 2: you throw AI in there and it's a whole new

848
00:54:00,853 --> 00:54:05,173
Speaker 2: different scenario, good, indifferent or bad.

849
00:54:05,613 --> 00:54:07,933
Speaker 3: Well, I think again it's a worry. As I indicated

850
00:54:08,053 --> 00:54:14,933
Speaker 3: with companions is that you know, it plays to people's

851
00:54:15,013 --> 00:54:20,173
Speaker 3: and securities, people's loneliness and so forth. I mean, I

852
00:54:20,213 --> 00:54:25,053
Speaker 3: think it's interesting technology. Porn has actually played a part

853
00:54:25,093 --> 00:54:29,173
Speaker 3: in just about every development of technology. In the early

854
00:54:29,253 --> 00:54:32,693
Speaker 3: days of the Internet, it was actually when it was

855
00:54:32,733 --> 00:54:34,413
Speaker 3: a bit of a Wild West show. It was the

856
00:54:34,413 --> 00:54:40,333
Speaker 3: availability of sexual material that helped actually fuel it. If

857
00:54:40,373 --> 00:54:43,693
Speaker 3: you remember the early days of VCRs, that was exactly

858
00:54:43,733 --> 00:54:49,013
Speaker 3: the same. So here we have a new technology where porn,

859
00:54:50,093 --> 00:54:54,453
Speaker 3: the peddlers of porn, if you like, latching onto it

860
00:54:54,573 --> 00:55:01,133
Speaker 3: and trying to make hay from it. This is as

861
00:55:01,213 --> 00:55:08,293
Speaker 3: I say, I think the question of companionship using AI

862
00:55:08,573 --> 00:55:12,053
Speaker 3: is going to be a really major issue because if

863
00:55:12,053 --> 00:55:17,413
Speaker 3: you're replacing human beings who can make sensible emotional decisions

864
00:55:18,613 --> 00:55:24,453
Speaker 3: with assistance in some ways, that maybe encouraging bad stuff

865
00:55:24,693 --> 00:55:30,013
Speaker 3: or in fact putting you in a space where which

866
00:55:30,053 --> 00:55:35,373
Speaker 3: is not good by encouraging you with thoughts and ideas

867
00:55:35,613 --> 00:55:39,573
Speaker 3: that aren't helpful that other humans would not suggest. You know,

868
00:55:39,653 --> 00:55:41,693
Speaker 3: I think this is a real worry. But again we

869
00:55:41,813 --> 00:55:44,093
Speaker 3: come back to the thing who's controlling this late and

870
00:55:44,173 --> 00:55:48,253
Speaker 3: I mean again, nobody is waking up to this. The

871
00:55:48,333 --> 00:55:52,013
Speaker 3: regulators aren't waking up to this. It feels as though

872
00:55:52,053 --> 00:55:55,653
Speaker 3: the technology companies are just going as fast as they

873
00:55:55,733 --> 00:56:00,413
Speaker 3: can to develop you know, human minds replacements. By twenty

874
00:56:00,453 --> 00:56:03,693
Speaker 3: twenty eight. No one is actually putting any brakes on this.

875
00:56:05,533 --> 00:56:08,293
Speaker 2: So who's running it, who's organizing it?

876
00:56:09,533 --> 00:56:11,853
Speaker 4: Well, well, the big tech companies.

877
00:56:11,933 --> 00:56:13,533
Speaker 3: I mean, it's all about money, isn't it.

878
00:56:13,573 --> 00:56:16,373
Speaker 2: And again, as you say, but Nigel, is it is

879
00:56:16,373 --> 00:56:18,653
Speaker 2: it totally about money or is it is it about

880
00:56:18,733 --> 00:56:23,613
Speaker 2: I mean, take Bill Gates, Well, it's controls Bill exactly.

881
00:56:24,173 --> 00:56:27,373
Speaker 2: Bill Gates doesn't need any more money. He would be

882
00:56:27,453 --> 00:56:30,613
Speaker 2: though interested in as you as you just mentioned, in

883
00:56:30,653 --> 00:56:35,293
Speaker 2: control and one thing leads to another. The two go

884
00:56:35,653 --> 00:56:37,733
Speaker 2: very well hand in hand for a lot of people.

885
00:56:37,733 --> 00:56:44,373
Speaker 2: Look a look at George Sorris. So are you suggesting

886
00:56:44,493 --> 00:56:48,293
Speaker 2: then that they're the sort of people who are behind

887
00:56:48,373 --> 00:56:48,853
Speaker 2: pushing this.

888
00:56:50,413 --> 00:56:53,213
Speaker 3: Well, I you quoted in an article which see it

889
00:56:53,293 --> 00:56:56,733
Speaker 3: that whoever wins c AI race will control the world

890
00:56:56,933 --> 00:56:59,853
Speaker 3: or something along those lines. I mean that that is

891
00:56:59,893 --> 00:57:04,293
Speaker 3: what the kind of belief is. I mean, as justin mentioned,

892
00:57:05,333 --> 00:57:08,933
Speaker 3: there's a huge race going on between America and to

893
00:57:09,013 --> 00:57:11,733
Speaker 3: try and win. You know, they see it as who's

894
00:57:11,773 --> 00:57:14,573
Speaker 3: going to control Who's going to win this, but what

895
00:57:14,613 --> 00:57:16,813
Speaker 3: are we actually winning? What do we mean by winning?

896
00:57:17,293 --> 00:57:18,853
Speaker 3: You know, are we taking a step back and say,

897
00:57:18,893 --> 00:57:21,173
Speaker 3: what do we mean? Does that mean that we will

898
00:57:21,293 --> 00:57:25,293
Speaker 3: end up with these assistants that are being developed. The

899
00:57:25,373 --> 00:57:28,053
Speaker 3: person that Justin was talking about is the person who

900
00:57:28,493 --> 00:57:33,013
Speaker 3: the genius at Apple who created the iPhone and Apple Watch.

901
00:57:33,493 --> 00:57:36,453
Speaker 3: He is the one now developing a major AI assistant.

902
00:57:36,533 --> 00:57:40,453
Speaker 3: And his talk that in ten years time the iPhone

903
00:57:40,493 --> 00:57:43,093
Speaker 3: will be dead, that we'll all be carrying around some

904
00:57:43,213 --> 00:57:48,613
Speaker 3: sort of lapels something now whatever, something that will be

905
00:57:48,933 --> 00:57:51,933
Speaker 3: telling us what to do, and we're asking it questions

906
00:57:52,333 --> 00:57:53,653
Speaker 3: and it will be directing us.

907
00:57:54,533 --> 00:57:56,493
Speaker 4: You've talked about which.

908
00:57:56,493 --> 00:58:00,493
Speaker 3: Sounds crazy sci fi, but you've talked about the real

909
00:58:01,853 --> 00:58:07,573
Speaker 3: musk type enthusiasm for something that goes into our heads

910
00:58:08,773 --> 00:58:12,053
Speaker 3: and some sort of thing that controls us. So, I mean,

911
00:58:12,413 --> 00:58:16,853
Speaker 3: this is the science fiction era that we're actually moving

912
00:58:16,893 --> 00:58:21,373
Speaker 3: into reality now. And there are definitely forces out there

913
00:58:21,493 --> 00:58:24,853
Speaker 3: that are all about control, and they're quite right. Whoever

914
00:58:24,933 --> 00:58:28,093
Speaker 3: can get an AI assistant to tell you and me

915
00:58:28,333 --> 00:58:31,933
Speaker 3: and Justin and everyone listening what to do and how

916
00:58:31,973 --> 00:58:34,653
Speaker 3: to do it, and what to buy and where to

917
00:58:34,693 --> 00:58:39,133
Speaker 3: go and all the rest of it. Surely that's you know,

918
00:58:39,293 --> 00:58:42,013
Speaker 3: that's in a completely different world, I.

919
00:58:41,933 --> 00:58:43,853
Speaker 4: Mean later and there is a narrative out there which

920
00:58:43,893 --> 00:58:46,733
Speaker 4: I think is worth mentioning, and that is the idea

921
00:58:46,773 --> 00:58:50,853
Speaker 4: that there's a kind of developing AI cold war between

922
00:58:51,213 --> 00:58:54,733
Speaker 4: China and the US and this sort of who is

923
00:58:54,773 --> 00:58:56,973
Speaker 4: going to be the best to control it or even

924
00:58:57,653 --> 00:59:03,133
Speaker 4: as we touched earlier in this podcast, is whose vision

925
00:59:03,173 --> 00:59:05,133
Speaker 4: of the world is going to win out for AI?

926
00:59:05,613 --> 00:59:09,573
Speaker 4: And I think the forces which talking about here with

927
00:59:09,573 --> 00:59:12,253
Speaker 4: with what you're asking, what Nigel's mentioning, is that there

928
00:59:12,333 --> 00:59:14,333
Speaker 4: is if that is part of the narrative or the play,

929
00:59:15,053 --> 00:59:17,773
Speaker 4: and we know we've also talked about the s extential layer,

930
00:59:17,853 --> 00:59:21,813
Speaker 4: then then all these threats do push forward the idea

931
00:59:21,893 --> 00:59:24,013
Speaker 4: that it's kind of going to be keep it's going

932
00:59:24,093 --> 00:59:27,013
Speaker 4: to keep getting developed. But whose vision of what that

933
00:59:27,093 --> 00:59:28,973
Speaker 4: means is is not clear yet.

934
00:59:29,413 --> 00:59:31,773
Speaker 2: Does it come down to whoever drops the first bomb?

935
00:59:32,573 --> 00:59:34,813
Speaker 4: Well, it wouldn't be a bomb, though, I think that

936
00:59:36,093 --> 00:59:40,773
Speaker 4: it's more likely to be some sort of weaponized interaction

937
00:59:41,173 --> 00:59:44,573
Speaker 4: on an AI level. I mean, there's a lot of

938
00:59:44,613 --> 00:59:47,773
Speaker 4: talk about the idea of a third World war, but

939
00:59:47,893 --> 00:59:51,413
Speaker 4: I don't necessarily know who that we'll be seeing bombs

940
00:59:51,453 --> 00:59:54,333
Speaker 4: necessarily in that. That's why I think the AI cold

941
00:59:54,333 --> 00:59:57,373
Speaker 4: War is an interesting narrative because it's it's almost like

942
00:59:57,453 --> 01:00:01,333
Speaker 4: a different type of battle that isn't that isn't drawn

943
01:00:01,373 --> 01:00:04,133
Speaker 4: necessarily by clear geopolitical lines.

944
01:00:04,453 --> 01:00:06,093
Speaker 3: And is that a battle for your mind?

945
01:00:06,213 --> 01:00:06,533
Speaker 4: Layton?

946
01:00:07,373 --> 01:00:10,013
Speaker 2: There are two other areas that I've got tucked away

947
01:00:10,133 --> 01:00:14,733
Speaker 2: that I know I want to engage with. One is education.

948
01:00:15,813 --> 01:00:19,053
Speaker 2: Is AI a future class teacher?

949
01:00:20,013 --> 01:00:22,973
Speaker 4: Yes, I think so, being a lecturer. I think this

950
01:00:23,053 --> 01:00:26,613
Speaker 4: is something that is talked about currently at inside aut

951
01:00:26,893 --> 01:00:29,653
Speaker 4: and it's something all institutions but also down to the

952
01:00:29,733 --> 01:00:32,693
Speaker 4: high school and primary school levels about where AI fits

953
01:00:32,693 --> 01:00:37,493
Speaker 4: in this. The way I see it is, education is

954
01:00:37,533 --> 01:00:40,693
Speaker 4: also up for grabs, first of all in the whole

955
01:00:40,773 --> 01:00:44,413
Speaker 4: nature of what it means to have artificial intelligence working

956
01:00:44,453 --> 01:00:48,293
Speaker 4: in that space. I think teaching is going to change.

957
01:00:49,013 --> 01:00:51,533
Speaker 4: I think it will put pressures on all the layers

958
01:00:51,573 --> 01:00:56,093
Speaker 4: of education that we have. But I do think it

959
01:00:56,173 --> 01:00:59,253
Speaker 4: is going to be a hybrid situation. In fact, I

960
01:00:59,293 --> 01:01:02,413
Speaker 4: would almost say earlier when I talked about the future

961
01:01:02,413 --> 01:01:06,253
Speaker 4: of jobs kind of being hybrid jobs. I think education

962
01:01:06,493 --> 01:01:09,853
Speaker 4: is probably the first sector where we will see some

963
01:01:09,973 --> 01:01:13,613
Speaker 4: realization of this very quickly where you have a teacher

964
01:01:14,173 --> 01:01:18,573
Speaker 4: and you have an artificial intelligent machine or GPT or agent,

965
01:01:18,973 --> 01:01:23,253
Speaker 4: that is that they're working in concert to help educate.

966
01:01:25,973 --> 01:01:28,453
Speaker 2: So how long would you put on it before every

967
01:01:28,733 --> 01:01:31,373
Speaker 2: every kid is being influenced by an AI whatever.

968
01:01:32,013 --> 01:01:34,773
Speaker 4: Well, I would argue they're already being influenced actually because

969
01:01:35,213 --> 01:01:37,573
Speaker 4: one of the reasons the education sector has to get

970
01:01:37,573 --> 01:01:40,693
Speaker 4: on board in some form or maybe a better way

971
01:01:40,693 --> 01:01:42,853
Speaker 4: to describe this is they have to be there so

972
01:01:42,933 --> 01:01:47,093
Speaker 4: they can control some of the narrative is because kids

973
01:01:47,093 --> 01:01:50,013
Speaker 4: in high school and primary school are already engaging and

974
01:01:50,053 --> 01:01:56,613
Speaker 4: playing with these chatbots, and they already are effectively learning

975
01:01:56,733 --> 01:01:59,493
Speaker 4: faster about how they work and what they can get

976
01:01:59,493 --> 01:02:03,053
Speaker 4: out of them. They're necessarily even the educators that are

977
01:02:03,053 --> 01:02:07,613
Speaker 4: older generations, and so we're already they're already being influenced.

978
01:02:07,693 --> 01:02:10,373
Speaker 4: It's already had. We're just got to be part of

979
01:02:10,373 --> 01:02:10,973
Speaker 4: the narrative.

980
01:02:11,293 --> 01:02:12,373
Speaker 2: Is parenting over.

981
01:02:14,613 --> 01:02:17,893
Speaker 4: No, I don't believe so. I think that there's a

982
01:02:17,933 --> 01:02:23,613
Speaker 4: fundamental interaction in parenting that and my current belief AI

983
01:02:23,693 --> 01:02:25,853
Speaker 4: can't replace. I mean, this is a whole bunch of

984
01:02:25,933 --> 01:02:32,413
Speaker 4: factors like presence, daily interactions but it may be substituted

985
01:02:32,413 --> 01:02:34,973
Speaker 4: to some extent. That's again part of these concerns.

986
01:02:35,693 --> 01:02:39,533
Speaker 2: Okay, So the other area that we haven't touched on,

987
01:02:39,773 --> 01:02:42,533
Speaker 2: and I want to because this is important to I

988
01:02:42,573 --> 01:02:47,053
Speaker 2: think all of us, everybody. The use of AI in

989
01:02:47,133 --> 01:02:50,213
Speaker 2: journalism does that raise ethical questions?

990
01:02:50,933 --> 01:02:55,613
Speaker 3: It certainly does latent such as the potential for a

991
01:02:55,653 --> 01:02:59,493
Speaker 3: bias if you're using AI algorithms. And there's already been

992
01:03:00,053 --> 01:03:05,093
Speaker 3: a problem with some of the AI chetbots that actually produce.

993
01:03:06,973 --> 01:03:07,773
Speaker 4: A bias.

994
01:03:08,893 --> 01:03:11,293
Speaker 3: And we already have issues in the media that we

995
01:03:11,373 --> 01:03:16,733
Speaker 3: know of where many people are concerned about bias, not

996
01:03:16,853 --> 01:03:18,013
Speaker 3: in in the media.

997
01:03:17,733 --> 01:03:18,813
Speaker 4: But also in.

998
01:03:20,893 --> 01:03:25,333
Speaker 3: Some of the narratives that are being driven. There's also

999
01:03:25,573 --> 01:03:29,053
Speaker 3: a need for transparency in AI generated content. There are

1000
01:03:29,093 --> 01:03:34,533
Speaker 3: already news sites that are being controlled by AI. AI

1001
01:03:34,693 --> 01:03:35,653
Speaker 3: is deciding what.

1002
01:03:35,653 --> 01:03:37,493
Speaker 4: Clickbait might be.

1003
01:03:39,013 --> 01:03:40,733
Speaker 3: The best to push.

1004
01:03:40,773 --> 01:03:42,413
Speaker 4: There are already stories.

1005
01:03:42,973 --> 01:03:47,893
Speaker 3: We've had examples where strange stories have been appearing in

1006
01:03:48,173 --> 01:03:57,213
Speaker 3: news sites and even in newspapers, where the AI has

1007
01:03:57,293 --> 01:04:00,333
Speaker 3: produced stuff that is not accurate. I mean the problem.

1008
01:04:01,293 --> 01:04:04,653
Speaker 3: The problem is that if you ask the chatbot something,

1009
01:04:04,973 --> 01:04:08,053
Speaker 3: or you ask it to do something again, as I say,

1010
01:04:08,213 --> 01:04:13,013
Speaker 3: it's making mistakes. It can make mistakes, and so if

1011
01:04:13,053 --> 01:04:19,493
Speaker 3: you're handing over aspects of journalism as some newspeople, we

1012
01:04:19,613 --> 01:04:22,853
Speaker 3: know the news media is under economic strain, so a

1013
01:04:22,973 --> 01:04:28,533
Speaker 3: number of media places now are handing over some aspects.

1014
01:04:29,093 --> 01:04:33,613
Speaker 3: For example, they're handing over news articles on very routing topics.

1015
01:04:34,773 --> 01:04:37,653
Speaker 3: Media releases are already being processed on one of the

1016
01:04:37,693 --> 01:04:40,293
Speaker 3: local news sites by AI.

1017
01:04:40,733 --> 01:04:42,693
Speaker 4: Financial reports, sports.

1018
01:04:42,253 --> 01:04:45,853
Speaker 3: Schools, weather updates, all that stuff are being asked to

1019
01:04:45,933 --> 01:04:49,933
Speaker 3: AI to produce, and that way you don't need humans.

1020
01:04:50,613 --> 01:04:55,093
Speaker 3: They're also analyzing very large data sets that could be

1021
01:04:55,173 --> 01:04:59,053
Speaker 3: helpful because if you're investigating something, it can search for

1022
01:04:59,093 --> 01:05:02,173
Speaker 3: stuff very quickly and come up with stuff, so it

1023
01:05:02,253 --> 01:05:06,013
Speaker 3: can help that. The danger is two things. One is

1024
01:05:06,413 --> 01:05:10,733
Speaker 3: the writing of news stuff are without journalists. And secondly,

1025
01:05:11,333 --> 01:05:15,453
Speaker 3: delivering personalized content to readers based on their interests and

1026
01:05:15,493 --> 01:05:16,293
Speaker 3: reading habits.

1027
01:05:17,133 --> 01:05:19,613
Speaker 2: You know, that's something I just don't want to know about.

1028
01:05:19,853 --> 01:05:24,813
Speaker 2: I resist having, and I've got enough already anyway, but

1029
01:05:24,973 --> 01:05:29,093
Speaker 2: I resist having the sites that send me what they

1030
01:05:29,173 --> 01:05:33,373
Speaker 2: think I'm interested in, and I won't sign up to them.

1031
01:05:33,613 --> 01:05:36,413
Speaker 2: You know, every every newspaper's doing it now. I just

1032
01:05:36,453 --> 01:05:40,813
Speaker 2: canceled my London Telegraph subscription. A because because it went

1033
01:05:40,853 --> 01:05:44,213
Speaker 2: through the roof, and b because because there was sending

1034
01:05:44,253 --> 01:05:46,413
Speaker 2: me stuff that I'm that I didn't care about. But

1035
01:05:46,493 --> 01:05:49,053
Speaker 2: I want, I want access to it so that it's

1036
01:05:49,053 --> 01:05:52,093
Speaker 2: my choice. I don't. I don't want them deciding what

1037
01:05:52,173 --> 01:05:54,133
Speaker 2: they think I should see and read.

1038
01:05:54,733 --> 01:05:57,253
Speaker 3: And I can't understand why this has been pushed so

1039
01:05:57,373 --> 01:06:00,813
Speaker 3: heavily later because there is such an issue at the

1040
01:06:00,853 --> 01:06:04,413
Speaker 3: moment with trust and media and it's been widely debated.

1041
01:06:04,493 --> 01:06:07,493
Speaker 3: You know, it's being debated vigorously in America at the

1042
01:06:07,493 --> 01:06:12,493
Speaker 3: moment because a CNN journalist that didn't cover the demise

1043
01:06:12,653 --> 01:06:18,093
Speaker 3: of Biden is now making millions from a book which

1044
01:06:18,453 --> 01:06:22,253
Speaker 3: suddenly has discovered that Biden had cognitive issues. I mean,

1045
01:06:22,573 --> 01:06:25,693
Speaker 3: it's a major issue. If really one in three New

1046
01:06:25,813 --> 01:06:30,133
Speaker 3: Zealanders trusts the media, then why are we now giving

1047
01:06:30,173 --> 01:06:34,053
Speaker 3: it over to AI to write stories for us or,

1048
01:06:34,173 --> 01:06:37,253
Speaker 3: as you say, decide what you want to read, which

1049
01:06:37,293 --> 01:06:40,013
Speaker 3: means that you don't actually see stuff that may be

1050
01:06:40,093 --> 01:06:43,133
Speaker 3: important to read. And that's the real worry with this.

1051
01:06:43,533 --> 01:06:47,533
Speaker 3: If AI is deciding what the homepage of a news

1052
01:06:47,613 --> 01:06:51,293
Speaker 3: site should be, are we actually getting stuff that we

1053
01:06:51,453 --> 01:06:55,133
Speaker 3: need to actually see? And think about and cover issues

1054
01:06:55,533 --> 01:06:57,013
Speaker 3: that we actually need to debate.

1055
01:06:57,373 --> 01:06:58,853
Speaker 2: How are we going to be able to continue to

1056
01:06:58,893 --> 01:07:05,053
Speaker 2: think of the future generations in the critical manner because

1057
01:07:05,053 --> 01:07:07,173
Speaker 2: it's all being taken out of them, all being taken

1058
01:07:07,173 --> 01:07:07,853
Speaker 2: out of their hands.

1059
01:07:09,133 --> 01:07:11,933
Speaker 4: Well, this is it. And I actually think one issue

1060
01:07:11,933 --> 01:07:16,733
Speaker 4: for me around the AI being incorporated into journalistic stuff

1061
01:07:16,893 --> 01:07:20,133
Speaker 4: is that we've already seen, as I mentioned earlier, some

1062
01:07:20,173 --> 01:07:24,333
Speaker 4: of the issues around algorithms having full control of content,

1063
01:07:24,413 --> 01:07:26,693
Speaker 4: which is what goes on in social media spaces, and

1064
01:07:26,733 --> 01:07:30,733
Speaker 4: the echo chamber problems and the nature of misinformation. I

1065
01:07:30,893 --> 01:07:33,133
Speaker 4: just can't help but feel like there's a lesson or

1066
01:07:33,173 --> 01:07:37,133
Speaker 4: we learned there. So handing over actual what you might

1067
01:07:37,213 --> 01:07:43,253
Speaker 4: call legitimate news sources into this AI system is concerning

1068
01:07:43,453 --> 01:07:45,733
Speaker 4: on even the nature of how you go back to

1069
01:07:45,773 --> 01:07:49,133
Speaker 4: your point, it starts deciding what it thinks is everyone

1070
01:07:49,213 --> 01:07:52,253
Speaker 4: needs to see. I mean, this goes back to something

1071
01:07:52,293 --> 01:07:55,013
Speaker 4: I feel we need to be careful about, and it's

1072
01:07:55,093 --> 01:07:59,013
Speaker 4: easy for that line to be unclear, which is that

1073
01:07:59,293 --> 01:08:04,493
Speaker 4: human beings are still awesome at creation curation. I should say.

1074
01:08:05,973 --> 01:08:10,173
Speaker 4: The clear thing that GPT intelligence chatbots can't do is

1075
01:08:10,213 --> 01:08:13,693
Speaker 4: that they're always looking backwards they're not. They're not great

1076
01:08:13,813 --> 01:08:16,853
Speaker 4: at well, they're not good at at the ability to

1077
01:08:16,933 --> 01:08:18,693
Speaker 4: kind of look at something and know that this is

1078
01:08:19,133 --> 01:08:21,693
Speaker 4: a way forward, or this is what we should be promoting.

1079
01:08:22,493 --> 01:08:25,933
Speaker 4: That's the human curation process of anything. AI is making

1080
01:08:26,173 --> 01:08:29,893
Speaker 4: that demarcation clearer every day that it's really rubbish at

1081
01:08:29,893 --> 01:08:32,533
Speaker 4: this and that what we do need is to keep

1082
01:08:32,573 --> 01:08:36,013
Speaker 4: that human being in the curation and the decision making processes,

1083
01:08:36,333 --> 01:08:38,653
Speaker 4: and so when it comes to things like information sources,

1084
01:08:38,693 --> 01:08:41,333
Speaker 4: this is a line I think we should be holding.

1085
01:08:41,853 --> 01:08:46,173
Speaker 2: So the future of AI in everyday life, give me

1086
01:08:46,253 --> 01:08:51,013
Speaker 2: your perspective as to where it might be. Well, you

1087
01:08:51,453 --> 01:08:53,293
Speaker 2: picked the time period I want to. I don't want

1088
01:08:53,293 --> 01:08:56,573
Speaker 2: to put it on you, but there it appears that

1089
01:08:56,613 --> 01:09:00,213
Speaker 2: it's moving forward, if you like, at a greater greater rate,

1090
01:09:00,373 --> 01:09:02,253
Speaker 2: greater speed than we anticipate it.

1091
01:09:03,053 --> 01:09:05,173
Speaker 4: Well, let's just pick twenty thirty because it's a nice

1092
01:09:05,613 --> 01:09:09,653
Speaker 4: five years from now. And I think by twenty thirty

1093
01:09:11,293 --> 01:09:14,173
Speaker 4: a majority of us will have some type of persistent

1094
01:09:14,533 --> 01:09:18,373
Speaker 4: wearable AI device on us, much like a smartphone. I

1095
01:09:18,373 --> 01:09:24,373
Speaker 4: think AI will have integrated itself into all aspects of

1096
01:09:24,373 --> 01:09:29,093
Speaker 4: our everyday lives in a kind of active and passive,

1097
01:09:29,173 --> 01:09:32,813
Speaker 4: so they'll be passive what might call ambient AI, where

1098
01:09:32,853 --> 01:09:34,813
Speaker 4: it's sort of happening in the background and just kind

1099
01:09:34,853 --> 01:09:39,133
Speaker 4: of making things easy would be the positive look, but

1100
01:09:39,213 --> 01:09:41,253
Speaker 4: also active. Going back to a lot of the part

1101
01:09:41,293 --> 01:09:45,413
Speaker 4: of the conversation, I think people will have active intelligent

1102
01:09:45,493 --> 01:09:48,853
Speaker 4: agents they have a communication with that they interact with

1103
01:09:49,493 --> 01:09:52,453
Speaker 4: from a spectrum of how's your day going, or give

1104
01:09:52,453 --> 01:09:56,853
Speaker 4: me the weather, through to full relationships. And I think

1105
01:09:56,853 --> 01:09:58,973
Speaker 4: we're going to see I think in five years by

1106
01:09:58,973 --> 01:10:02,733
Speaker 4: twenty thirty, none of us will quite recognize the world

1107
01:10:02,933 --> 01:10:05,213
Speaker 4: as it is right now. I think it will be

1108
01:10:05,293 --> 01:10:09,973
Speaker 4: dramatically shifted by having what you I might say, here's

1109
01:10:09,973 --> 01:10:12,933
Speaker 4: a way to think about it. We haven't met aliens yet,

1110
01:10:14,413 --> 01:10:17,013
Speaker 4: but I think in five years by twenty thirty, we'll

1111
01:10:17,053 --> 01:10:20,533
Speaker 4: have aliens on Earth and they'll just be effectively intelligence.

1112
01:10:20,893 --> 01:10:24,253
Speaker 4: Artificial intelligence will be kind of like imagine aliens turned

1113
01:10:24,293 --> 01:10:26,573
Speaker 4: up and integrated our society. I think that's the kind

1114
01:10:26,573 --> 01:10:28,933
Speaker 4: of future we're going to be seeing because it will

1115
01:10:28,973 --> 01:10:31,573
Speaker 4: be that prolific and it'll be that transformational.

1116
01:10:33,133 --> 01:10:37,773
Speaker 2: Nigel before, well, you want to have an input there,

1117
01:10:38,293 --> 01:10:40,493
Speaker 2: because I've got a question off the back of that progestion.

1118
01:10:41,853 --> 01:10:44,653
Speaker 3: Yeah, No, I absolutely agree with that, I think, and

1119
01:10:44,693 --> 01:10:48,213
Speaker 3: that's why I'm urging that we really need I'm really

1120
01:10:48,733 --> 01:10:51,733
Speaker 3: glad you're discussing it today Latin, because we need to

1121
01:10:51,773 --> 01:10:56,133
Speaker 3: be having these discussions rather than just walk into it

1122
01:10:56,333 --> 01:11:00,013
Speaker 3: without any discussion whatsoever. I mean, we've got a younger

1123
01:11:00,053 --> 01:11:03,813
Speaker 3: generation now, We've got a generation or two that have

1124
01:11:03,893 --> 01:11:06,533
Speaker 3: grown up with the Internet and don't remember the world

1125
01:11:06,573 --> 01:11:09,693
Speaker 3: you and I remember where there's Now we've now got

1126
01:11:09,693 --> 01:11:12,813
Speaker 3: a generation that just accepts that they go to chet

1127
01:11:12,893 --> 01:11:16,413
Speaker 3: GPT to either do this school we say, or to

1128
01:11:16,493 --> 01:11:20,773
Speaker 3: ask a question about life. And so we're heading down

1129
01:11:20,813 --> 01:11:24,333
Speaker 3: that path. There is no stopping it. But should we

1130
01:11:24,413 --> 01:11:28,253
Speaker 3: actually be pausing, as I keep saying, and asking questions

1131
01:11:28,293 --> 01:11:32,933
Speaker 3: about whether we should you reframe some of what's going

1132
01:11:32,973 --> 01:11:36,693
Speaker 3: on or or make sure that we don't head down

1133
01:11:36,853 --> 01:11:39,973
Speaker 3: certain roads which which could be disastrous.

1134
01:11:41,333 --> 01:11:44,613
Speaker 2: Well, justin you triggered something that I that I was

1135
01:11:44,653 --> 01:11:46,893
Speaker 2: going to include, and then when you said it, I

1136
01:11:46,933 --> 01:11:49,853
Speaker 2: thought I'd forgotten about it. So I'm glad you did.

1137
01:11:49,933 --> 01:11:52,773
Speaker 2: Thank you, And that is you mentioned aliens. And the

1138
01:11:52,853 --> 01:11:56,373
Speaker 2: question is is it possible now I've asked this question

1139
01:11:56,773 --> 01:12:00,133
Speaker 2: in one way or another previously on the on My

1140
01:12:00,253 --> 01:12:05,253
Speaker 2: podcast of people who are including a professor from Melbourne

1141
01:12:05,493 --> 01:12:09,453
Speaker 2: Tech who co wrote a book in a twenty twenty

1142
01:12:09,533 --> 01:12:11,693
Speaker 2: nineteen I think, and his answer was in the negative.

1143
01:12:11,813 --> 01:12:16,653
Speaker 2: But is it possible that AI could be hijacked by

1144
01:12:16,693 --> 01:12:20,013
Speaker 2: some alien force? And when I say sorry, when I

1145
01:12:20,053 --> 01:12:22,933
Speaker 2: say alien, I mean you can. You can start local

1146
01:12:22,973 --> 01:12:25,653
Speaker 2: if you want, go wherever you like. I don't mean

1147
01:12:25,853 --> 01:12:29,013
Speaker 2: just from X from external.

1148
01:12:29,933 --> 01:12:32,013
Speaker 4: Well, I think we could just say there's a spectrum

1149
01:12:32,013 --> 01:12:35,453
Speaker 4: on that, and I think the answer for me is yes,

1150
01:12:35,733 --> 01:12:38,333
Speaker 4: es es. Along that spectrum, the answer at one end

1151
01:12:38,573 --> 01:12:42,613
Speaker 4: is that alien in the sense of a foreign agencies

1152
01:12:42,693 --> 01:12:47,293
Speaker 4: or foreign forces, this will happen. AI is hackable. AI

1153
01:12:47,413 --> 01:12:51,413
Speaker 4: will be hackable. And so, going back to our twenty

1154
01:12:51,493 --> 01:12:57,013
Speaker 4: thirty future cast, we will definitely have situations where, unfortunately,

1155
01:12:57,453 --> 01:13:00,893
Speaker 4: there will be incidences where AI have been forced to

1156
01:13:00,893 --> 01:13:03,533
Speaker 4: do things or hacked in some way. And at the

1157
01:13:03,573 --> 01:13:06,213
Speaker 4: other end of the spectrum, I'm the big believer there

1158
01:13:06,213 --> 01:13:09,413
Speaker 4: are aliens out there. So if aliens do turn up, well,

1159
01:13:09,653 --> 01:13:12,693
Speaker 4: the reality is yes, the answer is if they could

1160
01:13:12,693 --> 01:13:15,373
Speaker 4: turn up halfway across the galaxy to us, they can

1161
01:13:15,413 --> 01:13:16,493
Speaker 4: definitely hack our AI.

1162
01:13:17,413 --> 01:13:21,013
Speaker 2: So you reckon that some of those more recent sightings

1163
01:13:21,013 --> 01:13:23,573
Speaker 2: in America maybe for real.

1164
01:13:25,973 --> 01:13:29,893
Speaker 4: Well I or yeah, I mean, I don't know. I'm

1165
01:13:30,013 --> 01:13:32,533
Speaker 4: just a big believer that I don't There's a thing

1166
01:13:32,573 --> 01:13:37,493
Speaker 4: called the fer Ferm a paradox, Ferm Fernie paradox, something

1167
01:13:37,533 --> 01:13:41,613
Speaker 4: like that, and it basically says that from this this

1168
01:13:41,693 --> 01:13:45,493
Speaker 4: thinker was basically saying, well, if we've got all this

1169
01:13:45,893 --> 01:13:48,333
Speaker 4: galaxy out there, how can we haven't seen aliens? Because

1170
01:13:48,333 --> 01:13:52,493
Speaker 4: it doesn't quite make sense. Look, I think in one

1171
01:13:52,493 --> 01:13:55,333
Speaker 4: of the answers to that is court it's called the

1172
01:13:55,533 --> 01:13:59,693
Speaker 4: zoo answer. I believe aliens are out there, and I

1173
01:13:59,733 --> 01:14:01,893
Speaker 4: think that we're just being We've just been kept in

1174
01:14:01,893 --> 01:14:05,453
Speaker 4: a zoo. They don't want us to know. So, yeah,

1175
01:14:05,933 --> 01:14:07,253
Speaker 4: they're going to turn up at some point.

1176
01:14:08,613 --> 01:14:10,813
Speaker 2: Interesting Nigel, Well.

1177
01:14:10,613 --> 01:14:11,293
Speaker 4: I'm not sure.

1178
01:14:12,293 --> 01:14:16,973
Speaker 3: I've got a very open mind about it, but I

1179
01:14:17,053 --> 01:14:22,213
Speaker 3: agree with you that definitely the danger is that the

1180
01:14:22,333 --> 01:14:27,773
Speaker 3: systems will be hijacked by potentially what are called bad actors.

1181
01:14:27,933 --> 01:14:33,173
Speaker 3: Whether they were already seeing the rapid advances of AI

1182
01:14:33,333 --> 01:14:38,653
Speaker 3: being weaponized by cyber criminals, very highly sophisticated scams. You

1183
01:14:38,773 --> 01:14:43,413
Speaker 3: mentioned the deep fake technology, but they are they certainly

1184
01:14:44,613 --> 01:14:52,613
Speaker 3: with frightening accuracy, impersonating voices, they're creating fake speeches, They're

1185
01:14:52,693 --> 01:14:56,293
Speaker 3: definitely falling people into handing over money as well from

1186
01:14:56,333 --> 01:15:00,013
Speaker 3: their bank account. So we're really seeing very sophisticated scams

1187
01:15:00,093 --> 01:15:03,893
Speaker 3: using AI. So if we're now talking about the huge

1188
01:15:03,973 --> 01:15:08,253
Speaker 3: developments over the next five years, the potential for bad force,

1189
01:15:08,653 --> 01:15:13,693
Speaker 3: whether they be political forces or whether they be criminals

1190
01:15:13,813 --> 01:15:19,133
Speaker 3: or whoever they are, the potential is that the world

1191
01:15:19,253 --> 01:15:21,053
Speaker 3: is going to change. And again, if we go back

1192
01:15:21,053 --> 01:15:24,813
Speaker 3: to the early days of the Internet, Layton, I mean,

1193
01:15:24,973 --> 01:15:31,013
Speaker 3: we never quite imagined that the early developments of Google

1194
01:15:31,093 --> 01:15:34,973
Speaker 3: and Facebook would have such an enormous impact on everything

1195
01:15:35,053 --> 01:15:42,733
Speaker 3: from misinformation to affecting young kids and so forth. So

1196
01:15:42,773 --> 01:15:47,973
Speaker 3: that we are definitely heading to a place where whoever

1197
01:15:48,093 --> 01:15:52,693
Speaker 3: can control what we end up using the AI.

1198
01:15:54,533 --> 01:16:00,013
Speaker 4: It's got potential problems. I will just add Laton, don't

1199
01:16:00,093 --> 01:16:04,973
Speaker 4: count us out. Independence date the movie they hacked the Aliens,

1200
01:16:05,053 --> 01:16:08,093
Speaker 4: so don't count us out. We we might have.

1201
01:16:08,733 --> 01:16:11,373
Speaker 2: No I don't want to count us out. All right, guys,

1202
01:16:12,453 --> 01:16:13,693
Speaker 2: do a sales spitch for me.

1203
01:16:15,293 --> 01:16:21,013
Speaker 4: On Creative mckinna's or yeah, well, creative mckinna's is just

1204
01:16:21,173 --> 01:16:24,333
Speaker 4: our way of trying to keep the dialogue going. We

1205
01:16:24,413 --> 01:16:27,493
Speaker 4: wanted to have a place where we could talk about

1206
01:16:27,733 --> 01:16:35,093
Speaker 4: all the issues are unfiltered. Being honest, we are not sycophants,

1207
01:16:35,373 --> 01:16:38,693
Speaker 4: nor are we doomers. We're all about exploring it in

1208
01:16:38,733 --> 01:16:42,253
Speaker 4: a kind of quite journalistic way to actually ask the

1209
01:16:42,333 --> 01:16:47,093
Speaker 4: hard questions and explore basically all these issues we've been

1210
01:16:47,173 --> 01:16:52,013
Speaker 4: exploring with you, and importantly having that narrative and that

1211
01:16:52,133 --> 01:16:54,893
Speaker 4: dialogue out there so that people can have a way

1212
01:16:54,933 --> 01:16:58,933
Speaker 4: to understand these the different aspects because ais are very

1213
01:16:58,973 --> 01:17:01,413
Speaker 4: broad field, and we want to have a way of

1214
01:17:02,453 --> 01:17:04,893
Speaker 4: exploring that with people so that they can have a

1215
01:17:04,973 --> 01:17:08,613
Speaker 4: sense of it and quite importantly they can go often

1216
01:17:08,653 --> 01:17:09,773
Speaker 4: ask their own questions.

1217
01:17:09,893 --> 01:17:11,293
Speaker 2: So how do you find it?

1218
01:17:11,293 --> 01:17:15,773
Speaker 3: It's on substack. So substack is very popular at the

1219
01:17:15,853 --> 01:17:19,053
Speaker 3: moment as a kind of a blog type site. If

1220
01:17:19,093 --> 01:17:22,853
Speaker 3: you go to substack and search for either of our names,

1221
01:17:23,613 --> 01:17:25,133
Speaker 3: then you'll definitely find it that way.

1222
01:17:26,013 --> 01:17:30,893
Speaker 2: Justin Matthews and Nigel Horrocks. Of course, now I've got

1223
01:17:30,893 --> 01:17:32,933
Speaker 2: to congratulate you both because this is the first time

1224
01:17:33,013 --> 01:17:37,293
Speaker 2: that I've done in seven years, in two hundred and

1225
01:17:37,333 --> 01:17:40,613
Speaker 2: eighty six podcasts, just being the tow eighty sixth. The

1226
01:17:40,653 --> 01:17:44,733
Speaker 2: first time I've done a double header and it's gone

1227
01:17:44,733 --> 01:17:45,973
Speaker 2: pretty damn well. I reckon.

1228
01:17:46,173 --> 01:17:48,333
Speaker 3: Well, thank you again for having us so lat and

1229
01:17:48,373 --> 01:17:50,973
Speaker 3: thank you again for what you're doing as well as

1230
01:17:51,013 --> 01:17:54,373
Speaker 3: getting all sorts of great information out there. You've got

1231
01:17:54,373 --> 01:17:56,733
Speaker 3: a great podcast, so well done.

1232
01:17:56,973 --> 01:17:59,373
Speaker 4: Yeah, we appreciate it.

1233
01:17:59,373 --> 01:18:02,733
Speaker 2: It's been a pleasure, Nigel. I could use a news

1234
01:18:02,813 --> 01:18:09,453
Speaker 2: editor keep me on the straight and narrow. So I reckon,

1235
01:18:09,973 --> 01:18:12,293
Speaker 2: I reckon six months more and we'll do another one.

1236
01:18:12,533 --> 01:18:13,973
Speaker 3: That'd be great lake and we'll look forward.

1237
01:18:14,053 --> 01:18:15,053
Speaker 4: Yeah, that'd be fantastic.

1238
01:18:15,893 --> 01:18:16,413
Speaker 2: We'll do it.

1239
01:18:16,573 --> 01:18:17,373
Speaker 4: Thank you so much.

1240
01:18:17,693 --> 01:18:36,613
Speaker 2: Thank you both. Now, Missinus producer. Here we are in

1241
01:18:36,613 --> 01:18:40,693
Speaker 2: the mail room for podcast number two hundred and eighty six.

1242
01:18:42,533 --> 01:18:43,253
Speaker 4: How are you late?

1243
01:18:43,933 --> 01:18:45,013
Speaker 2: I thought you'd never ask.

1244
01:18:45,333 --> 01:18:46,693
Speaker 5: Do you think it might be a good idea to

1245
01:18:46,773 --> 01:18:49,213
Speaker 5: have at least an hour of the day where you might,

1246
01:18:49,453 --> 01:18:52,373
Speaker 5: you know, go for a walk on the beach or something. Literally,

1247
01:18:52,413 --> 01:18:57,173
Speaker 5: you have been in this room the entire week. That's

1248
01:18:57,213 --> 01:19:00,493
Speaker 5: a little slap down. We want we want work life

1249
01:19:00,613 --> 01:19:01,253
Speaker 5: balance here.

1250
01:19:01,453 --> 01:19:04,293
Speaker 2: I'm a prisoner and I don't know your own prison,

1251
01:19:04,373 --> 01:19:07,813
Speaker 2: and I don't go walking in this weather. Now, what

1252
01:19:07,973 --> 01:19:08,213
Speaker 2: you got.

1253
01:19:08,493 --> 01:19:10,373
Speaker 5: He's going to carry on doing this till these ninety

1254
01:19:10,453 --> 01:19:11,093
Speaker 5: nine folks.

1255
01:19:11,173 --> 01:19:12,133
Speaker 4: Hope you're ready for it.

1256
01:19:12,253 --> 01:19:14,213
Speaker 2: Don't think so late.

1257
01:19:14,253 --> 01:19:18,573
Speaker 5: And Andrew says, firstly, congratulations on a fascinating podcast, bringing

1258
01:19:18,573 --> 01:19:21,773
Speaker 5: in people and perspectives you would otherwise not get to hear.

1259
01:19:22,573 --> 01:19:25,973
Speaker 5: I have listened to every podcast at least twice, and

1260
01:19:26,093 --> 01:19:28,773
Speaker 5: some more than twice. I spend a lot of time

1261
01:19:28,853 --> 01:19:32,573
Speaker 5: operating machinery, so get plenty of time to myself. The

1262
01:19:32,613 --> 01:19:36,333
Speaker 5: podcast fulfills the need to stimulate my brain while I'm working.

1263
01:19:36,893 --> 01:19:40,213
Speaker 5: I have particularly enjoyed Robert McCulloch, and the silencing of

1264
01:19:40,333 --> 01:19:42,933
Speaker 5: him shows the corruption of New Zealand and how people

1265
01:19:42,933 --> 01:19:46,213
Speaker 5: in positions of power are threatened by those who may

1266
01:19:46,213 --> 01:19:49,613
Speaker 5: be considered smarter than they are. Instead of bringing them

1267
01:19:49,653 --> 01:19:55,573
Speaker 5: on board and utilizing their experience, they are ostracized and excommunicated.

1268
01:19:56,093 --> 01:19:58,133
Speaker 5: Going to show that the big end of town is

1269
01:19:58,173 --> 01:20:02,733
Speaker 5: nothing more than an incestuous club. Please consider getting mister

1270
01:20:02,813 --> 01:20:05,253
Speaker 5: McCulloch back on, although I don't blame him if he

1271
01:20:05,333 --> 01:20:09,773
Speaker 5: is hesitant. And then Andrew says, so another podcast he's

1272
01:20:09,773 --> 01:20:14,573
Speaker 5: listened to several times, the two John Olcock podcasts. John

1273
01:20:14,693 --> 01:20:17,573
Speaker 5: mentioned the current money system had about eighteen months to

1274
01:20:17,613 --> 01:20:19,733
Speaker 5: two years to run. From memory, we are now more

1275
01:20:19,773 --> 01:20:23,413
Speaker 5: than twelve months on from this prediction. Would you please

1276
01:20:23,533 --> 01:20:26,653
Speaker 5: consider getting John back to give his opinion on where

1277
01:20:26,693 --> 01:20:29,573
Speaker 5: we are currently at. And then Andrew goes on to

1278
01:20:29,613 --> 01:20:32,493
Speaker 5: say that he's a big fan of crypto and he's

1279
01:20:32,613 --> 01:20:35,693
Speaker 5: having a look seeing how that's going. He says, love

1280
01:20:35,733 --> 01:20:38,093
Speaker 5: the mailroom and the banter between the both of you.

1281
01:20:38,173 --> 01:20:41,933
Speaker 5: Please continue with your interesting and informative interviews.

1282
01:20:41,973 --> 01:20:45,573
Speaker 2: That's from Andrew Andrew, thank you the banter the best

1283
01:20:45,573 --> 01:20:51,253
Speaker 2: part gets cleaned out now from who we got from John?

1284
01:20:52,493 --> 01:20:55,733
Speaker 2: Thank you for the podcast with Jodie running from PSGR.

1285
01:20:56,573 --> 01:20:59,973
Speaker 2: Jody covers the high level governance and process problems with

1286
01:21:00,093 --> 01:21:03,133
Speaker 2: the bill, but there is also what it means at

1287
01:21:03,173 --> 01:21:07,533
Speaker 2: a practical level for farmers, consumers and exports. The issue

1288
01:21:07,813 --> 01:21:11,333
Speaker 2: is that the bill ends regulation and traceability of gene

1289
01:21:11,413 --> 01:21:15,733
Speaker 2: editor GMOs, so there is no visibility in the food chain.

1290
01:21:16,533 --> 01:21:20,253
Speaker 2: The social license for ge has been based on the

1291
01:21:20,293 --> 01:21:23,933
Speaker 2: precautionary principle and the right to choose these are to

1292
01:21:23,933 --> 01:21:26,293
Speaker 2: be taken away in the bill. I would welcome the

1293
01:21:26,413 --> 01:21:29,053
Speaker 2: chance to discuss the issues with you on a podcast

1294
01:21:29,333 --> 01:21:35,413
Speaker 2: says John consumer researcher and advocate spokesman ge Free, New Zealand.

1295
01:21:35,773 --> 01:21:36,733
Speaker 2: John appreciate it.

1296
01:21:37,013 --> 01:21:40,653
Speaker 5: Leyton Morris says, thank you for your excellent podcasts. I

1297
01:21:40,733 --> 01:21:44,333
Speaker 5: have just listened to your interview with Dr Corey. Even

1298
01:21:44,373 --> 01:21:47,653
Speaker 5: if the comments by doctor Corey cannot be fully verified,

1299
01:21:47,853 --> 01:21:51,293
Speaker 5: his views and evidence, together with other medical practitioners that

1300
01:21:51,373 --> 01:21:55,173
Speaker 5: can collaborate his research with supporting data, should be included

1301
01:21:55,173 --> 01:21:58,573
Speaker 5: in the current review on COVID nineteen. Further than that,

1302
01:21:58,733 --> 01:22:01,933
Speaker 5: the corruption by Big Farmer is incredible and for me

1303
01:22:02,133 --> 01:22:06,853
Speaker 5: almost unbelievable, and should be widely disseminated through medical journals

1304
01:22:06,973 --> 01:22:11,253
Speaker 5: and the media. Big Farmer and their Lackey's actions are

1305
01:22:11,293 --> 01:22:15,613
Speaker 5: not just unethical but criminal. Unfortunately I cannot see them

1306
01:22:15,653 --> 01:22:19,653
Speaker 5: being brought to justice. People like doctor Bloomfield and Jacinda

1307
01:22:19,773 --> 01:22:22,973
Speaker 5: Ardurn should be required to respond to his assertions and

1308
01:22:23,013 --> 01:22:26,813
Speaker 5: not simply respond that they were simply repeating what who

1309
01:22:26,853 --> 01:22:30,613
Speaker 5: and medical experts were saying. Surely people in power, such

1310
01:22:30,653 --> 01:22:33,493
Speaker 5: as heads of government, not just in New Zealand, owe

1311
01:22:33,533 --> 01:22:36,693
Speaker 5: it to their public to provide alternative evidence of the

1312
01:22:36,733 --> 01:22:41,333
Speaker 5: information being given as considered controversial. Honesty should be a

1313
01:22:41,373 --> 01:22:45,773
Speaker 5: hallmark of public officials, doctors and scientists. But I'm cynical

1314
01:22:45,893 --> 01:22:48,973
Speaker 5: enough to know that that will never happen. Hence people

1315
01:22:49,053 --> 01:22:52,333
Speaker 5: like you Leyton are so important in the media. Keep

1316
01:22:52,413 --> 01:22:56,013
Speaker 5: up the good work. That's from Morris, the very flattering Morris.

1317
01:22:56,133 --> 01:22:59,933
Speaker 5: I try and not succumb to flattery. But you are

1318
01:22:59,973 --> 01:23:04,853
Speaker 5: correct in what you say as regard the individuals who

1319
01:23:05,733 --> 01:23:10,213
Speaker 5: contributed to the vice of what happened over that period.

1320
01:23:10,533 --> 01:23:15,613
Speaker 5: I'm amazed, pleasantly so with the number of people who

1321
01:23:16,173 --> 01:23:19,773
Speaker 5: communicate with me and who I talk with who say,

1322
01:23:20,013 --> 01:23:23,453
Speaker 5: and you've heard some of them on interviews say that

1323
01:23:23,613 --> 01:23:27,333
Speaker 5: these people should be charged, and plenty often go on

1324
01:23:27,333 --> 01:23:30,453
Speaker 5: and saying they should be behind bars. My comment is it

1325
01:23:30,613 --> 01:23:35,693
Speaker 5: will never happen. And somewhere buried in these emails there

1326
01:23:35,773 --> 01:23:39,453
Speaker 5: is a very short one. I don't think I can

1327
01:23:39,573 --> 01:23:44,413
Speaker 5: lay my hands on it straight away from Christine, thank

1328
01:23:44,453 --> 01:23:46,733
Speaker 5: you for your great interviews today with Brian Leyland and

1329
01:23:46,773 --> 01:23:51,893
Speaker 5: miss running. Informative but a bit depressing realizing my thoughts

1330
01:23:51,973 --> 01:23:55,333
Speaker 5: are actually true. Read Donald Trump. Do you think that

1331
01:23:55,453 --> 01:23:57,493
Speaker 5: due to the price of gold they might open up

1332
01:23:57,493 --> 01:24:00,493
Speaker 5: Fort Knox and revalue the gold that's hopefully still there,

1333
01:24:01,693 --> 01:24:06,333
Speaker 5: Hopefully it's currently only valued at forty two dollars an ounce,

1334
01:24:06,373 --> 01:24:09,853
Speaker 5: I believe, and go back to the gold standard. It

1335
01:24:09,933 --> 01:24:14,653
Speaker 5: were just about payoff America's debt, I imagine. Regards to you,

1336
01:24:14,773 --> 01:24:18,773
Speaker 5: kind regards to you both, Chris. This question about whether

1337
01:24:18,853 --> 01:24:20,813
Speaker 5: the gold is still or all the gold is still

1338
01:24:20,813 --> 01:24:23,973
Speaker 5: in Fort Knox is rolling on and on. I thought

1339
01:24:24,053 --> 01:24:26,533
Speaker 5: Trump was going down there to have a look at it,

1340
01:24:26,973 --> 01:24:29,373
Speaker 5: but then there was something I read that says that

1341
01:24:29,493 --> 01:24:32,693
Speaker 5: not even he has the right to go into it

1342
01:24:33,053 --> 01:24:36,173
Speaker 5: if they don't want him to. I don't know the answer,

1343
01:24:36,293 --> 01:24:39,733
Speaker 5: but I want to see the confrontation. Lady John says,

1344
01:24:40,533 --> 01:24:43,973
Speaker 5: during the latest podcast two eight five and previously two

1345
01:24:44,013 --> 01:24:48,973
Speaker 5: seven six, you've talked about our electricity supply and looming shortages.

1346
01:24:49,373 --> 01:24:51,733
Speaker 5: No one is talking about the power required to run

1347
01:24:51,733 --> 01:24:55,293
Speaker 5: the massive data centers that are being built in Hobsonville

1348
01:24:55,333 --> 01:24:58,413
Speaker 5: and elsewhere. My guess is that we will all be

1349
01:24:58,493 --> 01:25:01,613
Speaker 5: subsidizing them and our power bills will go up again.

1350
01:25:02,413 --> 01:25:03,853
Speaker 4: How does this help New Zealand?

1351
01:25:04,253 --> 01:25:06,573
Speaker 5: I hope you get the opportunity to ask this question

1352
01:25:06,693 --> 01:25:10,053
Speaker 5: next time you have a guest to discussing electricity supply.

1353
01:25:10,733 --> 01:25:11,013
Speaker 4: John.

1354
01:25:11,293 --> 01:25:16,293
Speaker 2: Thank you, John, thank you for from Paul. This is

1355
01:25:16,333 --> 01:25:19,093
Speaker 2: not the one that I just referred to, but it's

1356
01:25:19,493 --> 01:25:22,933
Speaker 2: along the same lines. Thanks for another great thought provoking

1357
01:25:22,973 --> 01:25:27,573
Speaker 2: a sobering show, particularly the insights delivered by Jay Brunning.

1358
01:25:28,253 --> 01:25:31,453
Speaker 2: The actions of Judith and Jacinda before her had me

1359
01:25:31,533 --> 01:25:35,653
Speaker 2: thinking of Thomas Soule's quote, It's hard to imagine a

1360
01:25:35,693 --> 01:25:38,893
Speaker 2: more stupid or more dangerous way of making decisions than

1361
01:25:38,933 --> 01:25:42,173
Speaker 2: by putting those decisions in the hands of people who

1362
01:25:42,213 --> 01:25:45,893
Speaker 2: pay no price for being wrong. We are going to

1363
01:25:46,253 --> 01:25:49,813
Speaker 2: miss Thomas Sole when he's gone, but I've got one

1364
01:25:49,853 --> 01:25:53,693
Speaker 2: full shelf of books of his, so we'll never forget Lton.

1365
01:25:53,773 --> 01:25:54,333
Speaker 4: Chris says.

1366
01:25:54,413 --> 01:25:57,013
Speaker 5: I'm a long time listener and discovered your radio show

1367
01:25:57,053 --> 01:26:00,853
Speaker 5: in twenty fourteen when I arrived in New Zealand. I

1368
01:26:00,933 --> 01:26:03,653
Speaker 5: find your podcast is full of grown up discussions about

1369
01:26:03,733 --> 01:26:08,653
Speaker 5: important topics, and always value your opinion and insight. I

1370
01:26:08,773 --> 01:26:12,373
Speaker 5: always enjoy your mailroom segments, but sometimes wish a younger

1371
01:26:12,413 --> 01:26:15,893
Speaker 5: contributor would write in. In an effort to take this

1372
01:26:16,013 --> 01:26:19,173
Speaker 5: in hand, I have put together my middle aged musings

1373
01:26:19,293 --> 01:26:22,213
Speaker 5: in a hope that you find them interesting. I've tried

1374
01:26:22,253 --> 01:26:24,573
Speaker 5: to make it interesting and hang together, so I hope

1375
01:26:24,573 --> 01:26:27,653
Speaker 5: it's not too tedious. In any case, it has helped

1376
01:26:27,653 --> 01:26:30,573
Speaker 5: me put my middle aged musings into print, so at

1377
01:26:30,613 --> 01:26:32,493
Speaker 5: least I can refer to it in the future and

1378
01:26:32,533 --> 01:26:35,853
Speaker 5: tell my children I told you so. Best wishes, late

1379
01:26:35,893 --> 01:26:39,213
Speaker 5: and you're an absolute legend. And he can't be that

1380
01:26:39,333 --> 01:26:42,093
Speaker 5: old latent because he says a musing of a middle

1381
01:26:42,093 --> 01:26:46,493
Speaker 5: aged millennial in his document, which I gather you've printed

1382
01:26:46,493 --> 01:26:47,173
Speaker 5: out and read.

1383
01:26:47,693 --> 01:26:50,813
Speaker 2: No, I haven't read it. Where would I get time

1384
01:26:50,853 --> 01:26:54,573
Speaker 2: to read this? Oh, my goodness the moment. It's eight

1385
01:26:54,613 --> 01:27:00,453
Speaker 2: pages six, it's not it's five three four five, it's

1386
01:27:00,493 --> 01:27:04,173
Speaker 2: five pages, but very very small type. But let me

1387
01:27:04,213 --> 01:27:06,573
Speaker 2: give you an idea, because I will read it. Musings

1388
01:27:06,573 --> 01:27:11,253
Speaker 2: of a middle aged millennial is opening, then doctors and education,

1389
01:27:11,973 --> 01:27:19,933
Speaker 2: followed by houses, followed by children, followed by pensions and investments,

1390
01:27:20,253 --> 01:27:23,333
Speaker 2: and finally, which is probably the best one of all,

1391
01:27:23,613 --> 01:27:28,693
Speaker 2: hope as an hope. So it will get consumed, believe me.

1392
01:27:28,773 --> 01:27:30,733
Speaker 2: But I'm going to reprint it in a larger type.

1393
01:27:30,813 --> 01:27:32,853
Speaker 5: Thank you for all that effort, Chris.

1394
01:27:33,173 --> 01:27:41,013
Speaker 2: I reckon now from Ian great interview with Pierre highlights sadly,

1395
01:27:41,333 --> 01:27:44,213
Speaker 2: how so many folks still have no idea what this

1396
01:27:44,373 --> 01:27:48,453
Speaker 2: product can do for them if you aren't already. He

1397
01:27:48,573 --> 01:27:51,253
Speaker 2: is a very good rundown on the latest attempt by

1398
01:27:51,293 --> 01:27:56,053
Speaker 2: this hapless net party to get us corded into digital id.

1399
01:27:56,973 --> 01:28:02,213
Speaker 2: Battle after battle after battle. It seems ian short and

1400
01:28:02,333 --> 01:28:03,373
Speaker 2: sweet lad.

1401
01:28:03,413 --> 01:28:06,413
Speaker 5: And I've just picked up Chris's page one, and I'll

1402
01:28:06,453 --> 01:28:08,613
Speaker 5: just read you the first couple of paragraphs. It's really

1403
01:28:08,653 --> 01:28:12,293
Speaker 5: cute usings of a middle aged millennial. Would you believe

1404
01:28:12,413 --> 01:28:14,933
Speaker 5: that it's been eight years since the newspapers were telling

1405
01:28:15,013 --> 01:28:18,173
Speaker 5: younger me millennials to cut back on the AVO toasts

1406
01:28:18,173 --> 01:28:21,773
Speaker 5: and four dollar coffees. Since then, some of us older

1407
01:28:21,813 --> 01:28:25,733
Speaker 5: millennials have reached our early forties. We've climbed the hill

1408
01:28:25,733 --> 01:28:28,413
Speaker 5: of youth and reached the uplands of middle aged. And I,

1409
01:28:28,533 --> 01:28:31,093
Speaker 5: for one, have taken a sharp intake of breath at

1410
01:28:31,133 --> 01:28:34,413
Speaker 5: the view that surrounds us. Just as the excitement of

1411
01:28:34,493 --> 01:28:38,173
Speaker 5: brunch is being replaced by the appeal of an afternoon snooze.

1412
01:28:38,533 --> 01:28:39,533
Speaker 4: I'd like to take you.

1413
01:28:39,533 --> 01:28:41,773
Speaker 5: Through some usings of a mind that's old enough now

1414
01:28:41,813 --> 01:28:44,653
Speaker 5: to be part of the problem, with the experience to

1415
01:28:44,693 --> 01:28:47,613
Speaker 5: look for solutions and with the energy to make them happen.

1416
01:28:48,533 --> 01:28:51,453
Speaker 5: Just one more paragraph. Let's start by setting the mood.

1417
01:28:51,533 --> 01:28:54,253
Speaker 5: This isn't going to be a ripping critique of how

1418
01:28:54,253 --> 01:28:57,613
Speaker 5: the boom has left us with scraps or how unfair

1419
01:28:57,653 --> 01:29:00,333
Speaker 5: it is to be a millennial. I've done most things right.

1420
01:29:00,413 --> 01:29:03,853
Speaker 5: I'm married with teenage children, I'm self employed and earn

1421
01:29:03,933 --> 01:29:06,773
Speaker 5: enough to own a home as a family. We've been

1422
01:29:06,853 --> 01:29:10,773
Speaker 5: hard working and lucky, probably an equal measure. However, there

1423
01:29:10,813 --> 01:29:14,253
Speaker 5: are certain choices where I have been a contrarian, where

1424
01:29:14,253 --> 01:29:16,293
Speaker 5: I've missed the trip wire that caught out a lot

1425
01:29:16,333 --> 01:29:19,333
Speaker 5: of my fellow millennials. On the other hand, there have

1426
01:29:19,413 --> 01:29:22,613
Speaker 5: been missed opportunities where a home in Auckland and a

1427
01:29:22,653 --> 01:29:26,693
Speaker 5: proper career might have eventuated. Middle age is the time

1428
01:29:26,733 --> 01:29:29,053
Speaker 5: to take stock and point out where we might be

1429
01:29:29,133 --> 01:29:33,093
Speaker 5: going wrong and what tactics have definitely paid off. So

1430
01:29:33,853 --> 01:29:34,933
Speaker 5: he says, let's.

1431
01:29:34,733 --> 01:29:38,213
Speaker 2: Begin, Well, let's begin. Let's begin with some facts. Though

1432
01:29:39,093 --> 01:29:43,293
Speaker 2: you're not middle aged. Early forties, he said, early forties

1433
01:29:43,333 --> 01:29:45,893
Speaker 2: has not middle aged anymore. It's been replaced by the

1434
01:29:45,933 --> 01:29:50,813
Speaker 2: early sixties, and some people think even the seventies. So

1435
01:29:50,933 --> 01:29:53,453
Speaker 2: you've still got a little way to go. But after

1436
01:29:53,533 --> 01:29:58,293
Speaker 2: today's interview, well after the day this discussion on AI.

1437
01:29:59,773 --> 01:30:01,813
Speaker 2: I wonder what effect that might have had on you

1438
01:30:02,133 --> 01:30:06,253
Speaker 2: when you were listening to it as to where your

1439
01:30:06,293 --> 01:30:10,333
Speaker 2: life's sat and what's coming at you. Whether I'm a

1440
01:30:10,453 --> 01:30:15,653
Speaker 2: feared or really happy about something, I'm always interested in

1441
01:30:15,813 --> 01:30:20,533
Speaker 2: the result, whatever it might be. So from David, this

1442
01:30:20,693 --> 01:30:23,653
Speaker 2: is a report on the latest US saidate hearing into

1443
01:30:23,653 --> 01:30:27,333
Speaker 2: COVID jabs. They say Big Farmer can't be sued in

1444
01:30:27,373 --> 01:30:30,013
Speaker 2: the US, so what about in New Zealand? It is

1445
01:30:30,173 --> 01:30:33,493
Speaker 2: really quite shocking that Pfizer was able to sell their

1446
01:30:33,533 --> 01:30:38,933
Speaker 2: deadly concoction to the New Zealand government without any legal consequences. Similarly,

1447
01:30:39,493 --> 01:30:42,453
Speaker 2: why haven't government and health officials in New Zealand faced

1448
01:30:42,493 --> 01:30:45,493
Speaker 2: legal consequences for the atrocity they inflicted on the people

1449
01:30:45,533 --> 01:30:47,853
Speaker 2: of New Zealand. This is not the letter either I

1450
01:30:47,893 --> 01:30:51,613
Speaker 2: was referring to earlier. So there were three of them

1451
01:30:51,653 --> 01:30:57,053
Speaker 2: if you include the one that I can't spot. Regards David. David,

1452
01:30:57,653 --> 01:31:00,933
Speaker 2: there's a lot of a lot of answers to the

1453
01:31:01,053 --> 01:31:06,253
Speaker 2: questions that you ask, but it'll never happen. That's the point,

1454
01:31:06,653 --> 01:31:08,293
Speaker 2: and the point is that we don't have the ball

1455
01:31:08,453 --> 01:31:12,853
Speaker 2: in this country to do it. Nobody does be useless

1456
01:31:13,213 --> 01:31:15,853
Speaker 2: in the greatest scheme of things. This is producer, Thank you.

1457
01:31:16,093 --> 01:31:20,533
Speaker 4: Thank you, lighton. You'm done and dusted. I'm downe and dusted.

1458
01:31:20,973 --> 01:31:22,253
Speaker 2: Shall we see you next week?

1459
01:31:22,773 --> 01:31:24,493
Speaker 5: I think there's a very high probability.

1460
01:31:25,173 --> 01:31:26,973
Speaker 2: The question is will there be next week?

1461
01:31:44,293 --> 01:31:44,333
Speaker 4: No.

1462
01:31:44,453 --> 01:31:46,773
Speaker 2: I was going to leave the podcast at the end

1463
01:31:46,813 --> 01:31:49,533
Speaker 2: of the mail room for this week because we covered

1464
01:31:49,573 --> 01:31:53,173
Speaker 2: an awful lot of ground. But something has caught my

1465
01:31:53,213 --> 01:31:56,653
Speaker 2: attention that I thought might be of interest and useful

1466
01:31:56,773 --> 01:31:59,973
Speaker 2: to wind it up with. Keep in mind this is

1467
01:32:00,093 --> 01:32:06,093
Speaker 2: from an American author, an American source. AI is replacing

1468
01:32:06,213 --> 01:32:10,853
Speaker 2: human workers. How companies using automation to cut jobs, so

1469
01:32:10,933 --> 01:32:16,573
Speaker 2: a little information across nearly every industry. Artificial intelligence is

1470
01:32:16,653 --> 01:32:20,813
Speaker 2: no longer just a tool. It's becoming the worker. From

1471
01:32:20,933 --> 01:32:24,173
Speaker 2: Wall Street to Silicon Valley, major companies are laying off

1472
01:32:24,253 --> 01:32:29,493
Speaker 2: employees and replacing them with AI systems that promise greater efficiency,

1473
01:32:29,653 --> 01:32:34,893
Speaker 2: higher profits, and streamlined operations. But as corporate giants boast

1474
01:32:34,933 --> 01:32:39,333
Speaker 2: about record breaking productivity, a growing number of employees are

1475
01:32:39,453 --> 01:32:42,613
Speaker 2: waking up to a grim reality their jobs may be

1476
01:32:42,773 --> 01:32:47,133
Speaker 2: next A World Economic Forum report published in early twenty

1477
01:32:47,173 --> 01:32:50,933
Speaker 2: twenty five found that forty one percent of employers globally

1478
01:32:51,373 --> 01:32:54,533
Speaker 2: planned to reduce their workforce by twenty thirty due to

1479
01:32:54,693 --> 01:32:59,173
Speaker 2: AI automation. This is not some distant predictions already underway.

1480
01:32:59,813 --> 01:33:03,133
Speaker 2: The kind of jobs being replaced. AI is hitting hardest

1481
01:33:03,173 --> 01:33:08,853
Speaker 2: where jobs involve repetitive and routine tasks, both physical and cognitive.

1482
01:33:09,373 --> 01:33:13,893
Speaker 2: According to the WEF's Future of Jobs Report, these roles

1483
01:33:14,013 --> 01:33:20,053
Speaker 2: are seeing rapid decline postal service clerks, executive assistance, payroll

1484
01:33:20,093 --> 01:33:25,213
Speaker 2: and benefits clerks, customer service agents, mid level software engineers,

1485
01:33:25,733 --> 01:33:31,413
Speaker 2: human resources personnel would they be missed? And graphic designers.

1486
01:33:32,613 --> 01:33:36,813
Speaker 2: Even in traditionally human centered roles, companies are finding ways

1487
01:33:36,853 --> 01:33:42,853
Speaker 2: to use AI tools to automate communication, design and support. Microsoft,

1488
01:33:42,973 --> 01:33:48,213
Speaker 2: IBM and others lead the AI layoff charge. Microsoft recently

1489
01:33:48,253 --> 01:33:51,693
Speaker 2: announced it would lay off six thousand employees, around three

1490
01:33:51,733 --> 01:33:55,013
Speaker 2: percent of its global workforce. The company said the layoffs

1491
01:33:55,013 --> 01:33:59,453
Speaker 2: were part of an effort to boost efficiency and reduce bureaucracy.

1492
01:34:00,333 --> 01:34:04,933
Speaker 2: At the same time, Microsoft is investing heavily in AI

1493
01:34:05,053 --> 01:34:10,093
Speaker 2: and new technology platforms. IBM replaced hundreds of human resource

1494
01:34:10,133 --> 01:34:14,813
Speaker 2: employees with its in house AI which is called ASKHR,

1495
01:34:15,653 --> 01:34:19,093
Speaker 2: which now handles ninety four percent of routine HR tasks

1496
01:34:19,373 --> 01:34:25,013
Speaker 2: like managing vacation requests and pay statements. CEO Arvand Krishna

1497
01:34:25,373 --> 01:34:28,853
Speaker 2: said the layoffs made room for hiring more programmers and

1498
01:34:28,933 --> 01:34:33,653
Speaker 2: critical thinking roles. Salesforce cut one thousand jobs earlier this

1499
01:34:33,773 --> 01:34:38,213
Speaker 2: year to make way for its new AI product Agent Force.

1500
01:34:39,053 --> 01:34:43,213
Speaker 2: CEO Mark Benioff emphasized that using AI is now a

1501
01:34:43,253 --> 01:34:50,693
Speaker 2: fundamental expectation for all employees. CrowdStrike, a major cybersecurity firm,

1502
01:34:51,133 --> 01:34:55,493
Speaker 2: laid off five hundred workers as it ramped up AI deployment.

1503
01:34:56,093 --> 01:35:01,533
Speaker 2: CEO George Kertz called AI a force multiplier, explaining that

1504
01:35:01,613 --> 01:35:04,973
Speaker 2: it allows the company to innovate faster, reduce hiring, and

1505
01:35:05,053 --> 01:35:09,773
Speaker 2: improve customer outcomes. Even Wall Street and Safe, City Group

1506
01:35:09,813 --> 01:35:12,893
Speaker 2: and JP Morgan are among banks projecting that AI could

1507
01:35:12,973 --> 01:35:17,213
Speaker 2: lead to you ready two hundred thousand layoffs in the

1508
01:35:17,253 --> 01:35:21,453
Speaker 2: next five years, particularly in middle office and operational roles.

1509
01:35:21,813 --> 01:35:24,933
Speaker 2: The City Group noted that more than half of banking

1510
01:35:25,053 --> 01:35:29,133
Speaker 2: jobs are highly susceptible to automation. Now what the numbers say?

1511
01:35:29,493 --> 01:35:33,493
Speaker 2: Fifty four percent of tech hiring managers expect layoffs due

1512
01:35:33,533 --> 01:35:37,093
Speaker 2: to AI within the next year. Forty five percent believe

1513
01:35:37,173 --> 01:35:42,013
Speaker 2: employees in AI replaceable roles are most at risk. Seventy

1514
01:35:42,173 --> 01:35:45,813
Speaker 2: seven percent of large companies plan to reskill employees to

1515
01:35:45,893 --> 01:35:50,853
Speaker 2: work with AI. Sixty nine percent say AI will create

1516
01:35:51,093 --> 01:35:56,213
Speaker 2: demand for entirely new roles. Thirty two percent of American

1517
01:35:56,213 --> 01:36:00,973
Speaker 2: workers believe AI will reduce job opportunities, and only sixteen

1518
01:36:01,013 --> 01:36:04,973
Speaker 2: percent say they currently use AI in their own work.

1519
01:36:06,573 --> 01:36:10,933
Speaker 2: Can you bulletproof your career despite the job cuts? AI

1520
01:36:11,293 --> 01:36:14,653
Speaker 2: is not just replacing people, it's also creating new opportunities.

1521
01:36:14,973 --> 01:36:19,933
Speaker 2: But staying employed will require adaptability and new skills. So

1522
01:36:20,093 --> 01:36:24,253
Speaker 2: here are ways to future proof your career. Firstly, learn

1523
01:36:24,533 --> 01:36:31,853
Speaker 2: AI basics now. Free courses from Corsera, Navidia, and IBM

1524
01:36:32,013 --> 01:36:34,893
Speaker 2: can teach you how AI works and how to use it.

1525
01:36:35,333 --> 01:36:39,333
Speaker 2: Hiring managers now routinely ask how familiar are you with AI?

1526
01:36:40,013 --> 01:36:42,893
Speaker 2: That makes me chuckle thinking back to at the end

1527
01:36:42,893 --> 01:36:50,053
Speaker 2: of the discussion and talking about relationships with AI things,

1528
01:36:51,413 --> 01:36:56,213
Speaker 2: how familiar are you with AI? It's got two meanings anyway.

1529
01:36:56,573 --> 01:37:00,533
Speaker 2: Number two upskill in demand areas. According to surveys, the

1530
01:37:00,533 --> 01:37:06,533
Speaker 2: most desirable skills include AI developments and cybersecurity, a data analysis,

1531
01:37:06,573 --> 01:37:14,133
Speaker 2: strategic thinking at adaptibils, shift to human centered roles. Jobs

1532
01:37:14,133 --> 01:37:19,133
Speaker 2: that involve critical thinking, creativity and direct human interaction are

1533
01:37:19,293 --> 01:37:25,213
Speaker 2: harder to automate. These include leadership, product development, sales strategy,

1534
01:37:25,533 --> 01:37:29,253
Speaker 2: and high level consulting. Going back to that first one

1535
01:37:29,293 --> 01:37:32,853
Speaker 2: of critical thinking, you know, it's something that we've talked

1536
01:37:32,893 --> 01:37:35,413
Speaker 2: a lot about on the podcasts, as though hasn't been

1537
01:37:35,453 --> 01:37:40,373
Speaker 2: talked much about in other areas, including of course, education,

1538
01:37:41,213 --> 01:37:44,013
Speaker 2: and it seems that critical thinking has been sort of

1539
01:37:44,253 --> 01:37:48,653
Speaker 2: left on the byway by many folk. Now is the

1540
01:37:48,693 --> 01:37:55,733
Speaker 2: time to resurrect a big time number. Four. Companies like

1541
01:37:55,813 --> 01:37:59,253
Speaker 2: Shopify and Fiber have made it clear if you can't

1542
01:37:59,293 --> 01:38:03,293
Speaker 2: prove you're doing something that AI can't. If you can't

1543
01:38:03,333 --> 01:38:07,493
Speaker 2: prove you're doing something AI can't, you may not be

1544
01:38:07,573 --> 01:38:11,533
Speaker 2: hired or retained. Lifelong learning is the new job security,

1545
01:38:12,173 --> 01:38:16,693
Speaker 2: and five stay visible and valuable a warning for the future.

1546
01:38:16,853 --> 01:38:21,213
Speaker 2: Many company leaders, like JP Morgan's Jamie Diamond and IBM's Krishna,

1547
01:38:21,853 --> 01:38:26,893
Speaker 2: say that AI will augment rather than eliminate jobs, but

1548
01:38:26,973 --> 01:38:30,653
Speaker 2: the early results suggest otherwise. At least for now, AI

1549
01:38:30,773 --> 01:38:33,893
Speaker 2: is being used primarily to cut costs and raise profits,

1550
01:38:34,333 --> 01:38:38,453
Speaker 2: not preserve jobs. For many workers, this feels less like

1551
01:38:38,653 --> 01:38:42,133
Speaker 2: a tech revolution and more like a hostile takeover, as

1552
01:38:42,213 --> 01:38:46,333
Speaker 2: the Pew Research Center found more than half of American

1553
01:38:46,373 --> 01:38:50,293
Speaker 2: workers are worried about AI's long term impact. That fear

1554
01:38:50,373 --> 01:38:54,693
Speaker 2: is not misplaced, but the outcome is not set in stone.

1555
01:38:54,933 --> 01:38:58,173
Speaker 2: Those who adapt, learn and stay ahead of the curve

1556
01:38:58,773 --> 01:39:02,333
Speaker 2: may not just survive the AI revolution, they might thrive

1557
01:39:02,413 --> 01:39:06,813
Speaker 2: in it. For everyone else, the time to prepare is now.

1558
01:39:07,213 --> 01:39:09,053
Speaker 2: And that, by the way, if if you want to

1559
01:39:09,053 --> 01:39:13,173
Speaker 2: look for it, it's from finance and money. AI is

1560
01:39:13,253 --> 01:39:17,573
Speaker 2: replacing human workers, and that's where we shall leave it now.

1561
01:39:17,613 --> 01:39:20,213
Speaker 2: If you'd like to write to us Latent at newstalksv

1562
01:39:20,333 --> 01:39:22,893
Speaker 2: dot co dot nz or Carolyn at news Talks dot

1563
01:39:22,893 --> 01:39:27,933
Speaker 2: co dot nz, and we shall record your mail and

1564
01:39:28,333 --> 01:39:30,893
Speaker 2: most likely utilize it. And the only thing left to

1565
01:39:30,933 --> 01:39:34,933
Speaker 2: say is, as always, thank you so much for listening,

1566
01:39:35,213 --> 01:39:36,613
Speaker 2: and we shall talk soon.

1567
01:39:44,453 --> 01:39:48,413
Speaker 1: Thank you for more from News Talks b Listen live

1568
01:39:48,573 --> 01:39:51,293
Speaker 1: on air or online, and keep our shows with you

1569
01:39:51,373 --> 01:39:54,373
Speaker 1: wherever you go with our podcast on iHeartRadio.