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Speaker 1: Already and this is the Daily This is the Daily OS.

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Speaker 1: Oh Now it makes sense.

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Speaker 2: Good morning and welcome to the Daily OS. It's Monday,

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Speaker 2: the sixteenth of March. I'm Sam Kazlowski.

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Speaker 1: I'm Billyefit Simon's.

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Speaker 2: Australia's biggest tech companies have cut thousands of jobs in

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Speaker 2: a matter of weeks, and they're all pointing to the

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Speaker 2: same reason, and that's AI. But experts say the picture

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Speaker 2: is slightly more complicated than the headlines, which often invoke

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Speaker 2: fear in most of us across almost any line of work.

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Speaker 2: So today I thought Billy and I would break down

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Speaker 2: all the latest developments.

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Speaker 1: Sam.

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Speaker 3: Before we get into the developments, I want to set

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Speaker 3: up that at the Daily OS you are the go

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Speaker 3: to person when it comes to AI. You obsess over

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Speaker 3: it more than anyone I know, and I'm interested in

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Speaker 3: the intro. You said that it invokes fear in most

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Speaker 3: of us, because you tend to have quite a positive

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Speaker 3: view in terms of what it could do for the

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Speaker 3: Daily Ohs and then also other companies.

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Speaker 2: I think it has a lot of positives even for

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Speaker 2: somebody who wants to get on top of life admin

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Speaker 2: which is everyone. But I have felt over the last

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Speaker 2: kind of twelve months, especially that I'm in the minority here,

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Speaker 2: I do feel like overall, there are more conversations about

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Speaker 2: this as a really scary idea than there are about

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Speaker 2: the opportunities. And I completely understand that. But I think

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Speaker 2: it's a really a really important part of our media

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Speaker 2: news cycle to at least acknowledge and address when we're

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Speaker 2: reading stories like the one we're going to talk about

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Speaker 2: today about job cards. It's really serious, it's about human

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Speaker 2: face to it. But yes, I'm glad you acknowledge my

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Speaker 2: optimism because it is important in the framing of all

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Speaker 2: of this.

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Speaker 3: Yes, and I think where the fear can come from

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Speaker 3: is just the speed at which everything is changing.

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Speaker 2: Totally.

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Speaker 3: Let's talk about the job cuts that major tech companies

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Speaker 3: have announced in Australia but also around the world. I

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Speaker 3: want to start with one of the biggest companies in Australia,

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Speaker 3: at Lassan. They had news last week that they were

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Speaker 3: cutting quite a significant portion of their workforce or about

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Speaker 3: ten percent is that right?

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Speaker 2: Ten percent of the global workforce, one in three of

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Speaker 2: their Australian workforce though, so I mean we're talking here

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Speaker 2: about sixteen hundred people around the world. So Atlasian is

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Speaker 2: headquartered in Sydney. It's a global tech company. The two

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Speaker 2: founders Mike cannon Brooks is Scott Farquha. They're the two

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Speaker 2: wealthiest tech entrepreneurs in Australia, maybe tied neck and neck

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Speaker 2: with the folks at Canva. So this is a massive

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Speaker 2: tech company. It's listed in America. And yeah, they sacked

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Speaker 2: sixteen hundred people, four hundred and eighty jobs in Australia.

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Speaker 2: The CEO, Mike cannon Brooks, he said in the video

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Speaker 2: message to staff, I know there are real consequences for everybody,

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Speaker 2: their families, their career plans, their friendships. But he was

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Speaker 2: very direct about the reason why, and it was the

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Speaker 2: increasing adoption of artificial intelligence across their business.

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Speaker 3: One thing I read his statement and he did seem

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Speaker 3: to have more nuance in the statement in terms of

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Speaker 3: saying that it wasn't that AI was necessarily replacing the

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Speaker 3: jobs and these are his words, ye, but that it

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Speaker 3: was the jobs are changing.

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Speaker 2: Yeah, I mean in the same announcement he also acknowledged

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Speaker 2: that they are putting out about one hundred and sixty

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Speaker 2: new jobs on the market.

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Speaker 1: Oh I missed that.

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Speaker 2: Yeah, so there's this kind of double edged sword here where,

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Speaker 2: and I wanted to kind of kind of thread this

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Speaker 2: throughout that there are opportunities for job creation according to

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Speaker 2: experts as well. Again that might be my optimism coming through.

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Speaker 2: We're going to try and keep this as balance as

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Speaker 2: possible for something so close to all of our lives.

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Speaker 2: But yeah, it's a complicated one. But I mean reading

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Speaker 2: some of the LinkedIn statements from people who had just

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Speaker 2: lost their jobs. We're talking about one work who was

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Speaker 2: two hundred days into their maternity leave. Then we've got

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Speaker 2: another Sydney based software engineer. He had been at Lassian

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Speaker 2: for sixteen years and he got let go via an email.

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Speaker 2: So there was a lot of pain within the Australian

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Speaker 2: tech community and a very human cost.

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Speaker 3: And that human cost of people losing their jobs as

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Speaker 3: the skills required in jobs changes. That's not specific to

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Speaker 3: it lasting that is something that we have seen across

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Speaker 3: different companies across Australia and then also overseas.

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Speaker 2: Yeah, I mean it's definitely not different. But what is

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Speaker 2: different about where we are in the point of time

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Speaker 2: is the frequency of these announcements. I mean, two weeks ago,

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Speaker 2: Wyse Tech Global, which is Australia's largest locally listed tech company,

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Speaker 2: It announced it would cut around two thousand jobs over

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Speaker 2: the next two years. That's more than a quarter of

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Speaker 2: its global workforce. Block, the company that owns after pay,

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Speaker 2: It announced it was cutting nearly half its workforce, also

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Speaker 2: citing AI. But it's not just the tech companies. I

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Speaker 2: mean any company that's using technology, which is pretty every

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Speaker 2: large corporation. They're also kind of looking for in all

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Speaker 2: of their annual reports, they're foreshadowing job losses in the future.

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Speaker 2: A restructured workforce reskilled a lot of those sorts of words.

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Speaker 2: So we're talking about banks, we're talking about medical companies,

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Speaker 2: we're talking about construction companies. Everything is being impacted here.

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Speaker 3: I feel like, just over the past two weeks it

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Speaker 3: has really dawned on me just how much jobs across

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Speaker 3: every industry are changing. And I have an example because

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Speaker 3: someone brought this up with me the other night at

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Speaker 3: the pub, saying that it's changing for models. And they

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Speaker 3: brought up a very popular fashion brand in Australia and

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Speaker 3: they showed me a photo of this beautiful new campaign

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Speaker 3: that they have and they said that model doesn't exist,

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Speaker 3: that model is AI. And you genuinely never would have

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Speaker 3: been able to tell. And when I looked at the comments,

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Speaker 3: it was somehow known that this was a A few

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Speaker 3: people did know, and the fashion brand actually responded to

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Speaker 3: comments saying, yes, this isn't a model that we have

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Speaker 3: produced with an AI artist, And that just goes to

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Speaker 3: show how the job market is completely changing and the

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Speaker 3: skills required for these things, like where once you needed

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Speaker 3: to be a model, we now are an AI artist.

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Speaker 3: That's just one example of one person, but it was

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Speaker 3: so interesting.

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Speaker 2: I cannot think of an industry where I have not

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Speaker 2: personally had a discussion with somebody in that industry who

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Speaker 2: says I'm completely unaffected. Yes, I mean even those like

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Speaker 2: intensely service based industries, people working in hospitals who are

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Speaker 2: hands on with patients in long recoveries, even they are

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Speaker 2: using AI for writing better patient notes or speeding up

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Speaker 2: the admin that they have to do. So you know,

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Speaker 2: no one really can say that they are not at

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Speaker 2: all going to be impacted.

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Speaker 1: By this, And that's the thing that we know.

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Speaker 3: It's going to impact everyone, but there are some people

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Speaker 3: who will be impacted more than others. What do we

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Speaker 3: know about who will be impacted the most?

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Speaker 2: So I think the most compro corehensive analysis of this

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Speaker 2: really big question comes from Jobs and Skills Australia, the

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Speaker 2: Federal Department, and they released a major report on this

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Speaker 2: late last year and it found that about seventy nine

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Speaker 2: percent of Australians so four and five of us, are

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Speaker 2: in jobs with low automation exposure, and that means AI

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Speaker 2: is unlikely to fully replace what they do. But and

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Speaker 2: this is the important bit, around eighty seven percent of

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Speaker 2: workers are in jobs where AI could materially reshape how

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Speaker 2: the work gets done, right, So I think that distinction

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Speaker 2: really matters a lot. So there is a distinction here

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Speaker 2: between AI fully replacing your job and AI changing your job.

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Speaker 2: And the language the agency is using is automation and augmentation.

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Speaker 2: So automation just means the machine is doing the task

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Speaker 2: instead of you, but augmentation means the machine is helping

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Speaker 2: you do your task better and faster. And so their

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Speaker 2: finding is that the augmentation a changing how you work.

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Speaker 2: That's more likely to be felt by everybody rather than

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Speaker 2: I don't have a job tomorrow because AI is here.

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Speaker 3: Today, Although that is something that as we have seen

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Speaker 3: in the past month, is happening.

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Speaker 1: To a lot of people.

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Speaker 2: Millions of workers are going to have to adapt to

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Speaker 2: that scenario for sure.

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Speaker 3: I mean, just to give an example of the automation.

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Speaker 3: I don't know much about coding, but what I do

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Speaker 3: know is that even at the daily ours, we used

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Speaker 3: to have someone who would write all of the code

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Speaker 3: of our website. I now know that there is something

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Speaker 3: called vibe coding, where basically you just tell Ai what

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Speaker 3: you want to create, just a normal plane English, and

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Speaker 3: it does all of the code for you.

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Speaker 2: Yeah, and just to clarify, he left because he got

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Speaker 2: a way better job because of an Oh, yes, you're right.

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Speaker 2: I mean, I'm vibe coding a lot. And just this

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Speaker 2: week I looked at something that is software program that

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Speaker 2: we spend about eight hundred dollars a month on and

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Speaker 2: I built it. I built it myself. And so the

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Speaker 2: questions that remain of what I built, and this is

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Speaker 2: what the technological community would say, is a secure to

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Speaker 2: put our data through. I have no idea about online cybersecurity.

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Speaker 1: Which is why we have not rolled it out exactly.

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Speaker 2: You know, is it sustainable and will it crash in

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Speaker 2: a week? I mean, is are we building kind of eventually,

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Speaker 2: I would say probably yes, And so there is still

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Speaker 2: a long way to go before we just kind of

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Speaker 2: get rid of any sort of software skills. But I'm

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Speaker 2: pretty comfortable with what I've built. So it's a really

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Speaker 2: interesting I mean, I'm a nerd in this space, as

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Speaker 2: we have acknowledged, but it's an interesting change to the workforce.

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Speaker 3: Sam, We've kind of flagged it, but I do want

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Speaker 3: to have a bit more of a conversation about how

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Speaker 3: the Daily Os is approaching this. But first, here is

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Speaker 3: a quick message from today's sponsor.

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Speaker 2: SA.

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Speaker 3: I do want to get to TDA, but first, before

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Speaker 3: we came in here, you mentioned that the Jobs and

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Speaker 3: Skills Australia Report is that the right name. Yeah, Jobs

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Speaker 3: and Skills Australia Report said that there was a difference

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Speaker 3: between genders of.

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Speaker 1: How we will all be impacted. What did it say?

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Speaker 2: So when it went through and identified the careers that

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Speaker 2: are most likely to be first replaced by AI, they

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Speaker 2: were talking about things like keyboard operators, telemarketers, call center workers,

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Speaker 2: accounting clerks, receptionists and because there's an overrepresentation of women

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Speaker 2: in those careers, the report then said that you know,

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Speaker 2: thirty six percent of women in the workforce fall into

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Speaker 2: this disrupted category compared to twenty six percent of men,

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Speaker 2: and so they recommended that policymakers and employers need to

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Speaker 2: pay close attention to this. And I think overlaying some

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Speaker 2: of you know, socioeconomic barriers that are in place, language barriers,

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Speaker 2: ability to access good technology. A good computer means that

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Speaker 2: you're going to be able to build with AI a

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Speaker 2: lot faster than if you have a bad computer, and

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Speaker 2: there's a big difference in price in all of that.

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Speaker 2: So I think overlaying some of those broader factors that

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Speaker 2: exist in society around these findings is really important.

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Speaker 3: Can I just pick up on something you said that

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Speaker 3: you said you need a better computer in order to

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Speaker 3: build with AI? Do you need to build with AI

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Speaker 3: in order to implement AI into your workflow?

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Speaker 2: No, I think build was probably a bad choice of

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Speaker 2: word there for me to use AI at a really

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Speaker 2: large scale. And what I mean by that is, let's

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Speaker 2: say that you're a call center worker and your boss

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Speaker 2: has said we're going to send you a file via

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Speaker 2: some AI program that has the phone numbers of one

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Speaker 2: hundred thousand people that you need to call. Your computer

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Speaker 2: needs to handle a file with one hundred thousand rows

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Speaker 2: in an Excel or Google spreadsheet, that's a big file.

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Speaker 2: And so because you're expected to get through that work faster,

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Speaker 2: and a call center because of some AI aspect to

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Speaker 2: it all, you have to handle larger packages of information.

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Speaker 2: So it's not necessarily building something. But if you're trying

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Speaker 2: to generate an image because your workplace has told you

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Speaker 2: that they're not going to hire, as you said before,

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Speaker 2: or a photographer, then generating an image will take a

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Speaker 2: lot more brain power in your computer. So there's all

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Speaker 2: of those kind of things.

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Speaker 3: So if someone's listening to this yeah, and is thinking

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Speaker 3: about whether or not their job is safe, where do

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Speaker 3: you think this conversation leaves them or leaves all of us?

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Speaker 1: Because that's something that we've all thought about, right.

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Speaker 2: I think we're going to have to keep checking in

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Speaker 2: with each other to see how this conversation evolves. You

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Speaker 2: how fast this is moving. It struck me as well.

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Speaker 2: I mean, things are moving at wild pace. But at

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Speaker 2: the moment, I think there's kind of no core consensus

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Speaker 2: with how safe we all are. There seems to be

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Speaker 2: two big agreed ideas. One is that human skills really matter,

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Speaker 2: and so things like decision making, empathy, communication, the ability

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Speaker 2: to have good conversations in person, those skills are actually

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Speaker 2: going to get more important, and so one thing you

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Speaker 2: can do to try and make sure that you're a

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Speaker 2: worthwhile employee to keep around in the future is invest

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Speaker 2: in those skills and get better at your human connections.

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Speaker 2: And the other really agreed upon core consensus is that

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Speaker 2: those workers who are the most at risk are the

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Speaker 2: ones who are waiting for their jobs to be disrupted

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Speaker 2: and that they're not learning at least or getting exposed

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Speaker 2: to the tools that they're out there. And there was

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Speaker 2: this fantastic line from an Australian innovation expert who said

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Speaker 2: it only takes thirty hours to become a very good

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Speaker 2: AI operator, and that was really reassuring for me because

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Speaker 2: I don't have a coding background at all. I've never

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Speaker 2: written any sort of code. I'm not naturally good at

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Speaker 2: using this sort of software. And this isn't about getting

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Speaker 2: a new university degree. This is about watching some tutorials

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Speaker 2: online and so the barriers to entry are quite low

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Speaker 2: when you think about how you can actually just at

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Speaker 2: least get exposed to these kind of tools. Again, optimists,

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Speaker 2: I'm sorry, and I know that I might get some

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Speaker 2: unpleasant comments from listeners in the way that I'm framing things,

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Speaker 2: but I'm trying to balance all of this out. The

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Speaker 2: truth is that this kind of wave is here.

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Speaker 3: I think one thing that I want to talk about is,

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Speaker 3: you know, we're talking about other workplaces, but we are

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Speaker 3: currently sitting in a workplace, the Daily OS, and these

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Speaker 3: are conversations that we're obviously having not in the podcast

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Speaker 3: studio off mic, about how we approach it. And you know,

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Speaker 3: the lower barrier to entry is one thing, but also

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Speaker 3: the hesitancy around is this ethical to use? And especially

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Speaker 3: for journalism where you know your voice is really important

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Speaker 3: and you know there are very clear processes about what

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Speaker 3: you should do in order to produce quality journalism, and

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Speaker 3: the question of whether or not AI can do that.

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Speaker 3: I think there's two things there, Like it's not just

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Speaker 3: can I do this or can I not? It's also

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Speaker 3: do I want to do this? And do I want

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Speaker 3: my work to go down this path? And I mean,

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Speaker 3: we're talking about difficult conversations that other workplaces are having

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Speaker 3: and other companies are having. But I think it's important

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Speaker 3: to acknowledge that we are also having these conversations internally.

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Speaker 3: We've had many conversations disagreements about what we should do,

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Speaker 3: and I think the clear thing is is that no

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Speaker 3: one knows the answer no.

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Speaker 2: And I mean another aspect that you haven't mentioned is

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Speaker 2: how much we've talked about the environmental impact of this

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Speaker 2: changing strategy of different ways of working. So this is

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Speaker 2: incredibly complex, and I mean many of the lines that

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Speaker 2: you read from workers before the internet was around have

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Speaker 2: a similar sentiment behind them, which is that as humans,

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Speaker 2: we need stability, we need to be able to see

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Speaker 2: what's coming up, and there are these particular moments in

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Speaker 2: time where it's harder to do so than others. And

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Speaker 2: whether that's a pandemic or a technological innovation that we

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Speaker 2: kind of didn't see coming at the pace that it has.

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Speaker 2: I think that it's perfectly reasonable for everybody to be

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Speaker 2: thinking not just how do I get on top of it,

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Speaker 2: but do I actually want this? And do I actually

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Speaker 2: want to have my work changed in this way. It's

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Speaker 2: a difficult one to answer because then you have to

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Speaker 2: overlay the fact that you need to make a buck

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Speaker 2: and you need to stay employed. And if your boss

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Speaker 2: Sam says we'd like you to start using this tool,

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Speaker 2: and it's lucky you.

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Speaker 1: Have a billy to say, well, hold on, guys.

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Speaker 2: And that's what makes this podcast great, hopefully, is that

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Speaker 2: we can have some disagreements about all of this. We're

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Speaker 2: going to make some glorious mistakes, I'm sure, but it's here,

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Speaker 2: and I think at one level I'm quite a realist

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Speaker 2: in that I'm raring to go when I am put

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Speaker 2: in a scenario and said, this is the state of

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Speaker 2: play now.

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Speaker 3: And just to be clear, the Daily Olls is not

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Speaker 3: looking at replacing anyone or anything like that. That has

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Speaker 3: never been our approach, and where a small enough company

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Speaker 3: that is not required. But it's about how, like we

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Speaker 3: have talked about, how do we change our skills set.

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Speaker 1: It's even something as simple as proofreading.

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Speaker 3: Is that something now that you know we don't need

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Speaker 3: the editors to be spending time on and instead they

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Speaker 3: can work with journalists on the best angle and the

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Speaker 3: best way to approach your story. But something like proofreading

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Speaker 3: that doesn't need to happen through a person as much.

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Speaker 2: I know you would never say something like this, but

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Speaker 2: I've been trying to kind of prick my ears up

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Speaker 2: when I hear people talking about things they don't like doing,

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Speaker 2: and I'm trying to work out, Okay, you've said you

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Speaker 2: don't like this particular task. Let me figure out with

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Speaker 2: you a way that perhaps AI could be helpful.

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Speaker 1: There you're saying, I would never say I don't like

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Speaker 1: doing a job.

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Speaker 3: Billy, you love your job, Sam, Thank you for explaining

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Speaker 3: all of that.

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Speaker 1: Thanks really for having such an open conversation, of.

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Speaker 3: Course, and thank you so much for listening to this

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Speaker 3: episode of The Daily Ods.

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Speaker 1: We'll be back later today with.

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Speaker 3: The afternoon headlines, but until then, we hope you have

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Speaker 3: a good day.

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Speaker 2: My name is Lily Maddon and I'm a proud Adunda

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Speaker 2: bunge lung Chalcultin woman from Gadigal Country.

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Speaker 1: The Daily acknowledges that this podcast is recorded on the

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Speaker 1: lands of the Gadigal people and pays respect to all

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Speaker 1: Aboriginal and torrest Rate island and nations. We pay our

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Speaker 1: respects to the first peoples of these countries, both past

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Speaker 1: and present.