1 00:00:04,840 --> 00:00:06,560 Speaker 1: The Australian Financial Review. 2 00:00:07,360 --> 00:00:11,280 Speaker 2: I use AI in my assignments information sheets. I can 3 00:00:11,320 --> 00:00:14,600 Speaker 2: pay directly into this thing called turboland dot A and 4 00:00:14,640 --> 00:00:19,279 Speaker 2: it uses AI to generate me study notes, flash cards, 5 00:00:19,360 --> 00:00:21,000 Speaker 2: quizzes and podcast The. 6 00:00:21,000 --> 00:00:23,040 Speaker 3: Other day I asked it to create me a running 7 00:00:23,079 --> 00:00:27,120 Speaker 3: program to get fitter for on my sport, and it 8 00:00:27,480 --> 00:00:31,280 Speaker 3: created a five week running plan with long runs into 9 00:00:31,280 --> 00:00:31,920 Speaker 3: full training. 10 00:00:32,680 --> 00:00:37,040 Speaker 1: Teenagers are already using AI as part of their everyday lives. 11 00:00:39,240 --> 00:00:42,360 Speaker 2: Is I make it summarize my notes and turn them 12 00:00:42,360 --> 00:00:45,199 Speaker 2: into a podcast and I listened to it like on 13 00:00:45,240 --> 00:00:48,239 Speaker 2: the day of exams. I'll put the whole grading rupric 14 00:00:48,400 --> 00:00:51,600 Speaker 2: into chat GPT and then put my assessment and ask 15 00:00:51,680 --> 00:00:52,760 Speaker 2: for harsh feedback. 16 00:00:53,280 --> 00:00:55,800 Speaker 1: This was a big focus at the Financial Reviews AI 17 00:00:55,880 --> 00:01:00,960 Speaker 1: summit last week. Tech leaders, chief executives and signed we're 18 00:01:01,000 --> 00:01:03,880 Speaker 1: all asked what they were doing to prepare their kids 19 00:01:03,880 --> 00:01:07,880 Speaker 1: for the future. The answers varied from encouraging them to 20 00:01:07,920 --> 00:01:12,040 Speaker 1: become AI ninjas to doubling down on the human experience 21 00:01:12,200 --> 00:01:17,039 Speaker 1: by studying landscaping or philosophy. But everyone agrees that we 22 00:01:17,080 --> 00:01:21,200 Speaker 1: are hurtling toward an AI disrupted future and our kids 23 00:01:21,480 --> 00:01:25,119 Speaker 1: will be the ones dealing with the fallout, and while 24 00:01:25,160 --> 00:01:29,399 Speaker 1: there's optimism about scientific and medical breakthroughs and a much 25 00:01:29,480 --> 00:01:34,679 Speaker 1: needed boosting productivity, there's also concern about job losses and 26 00:01:34,800 --> 00:01:39,120 Speaker 1: power concentrated among a handful of mercurial tech billionaires. 27 00:01:39,520 --> 00:01:41,399 Speaker 4: The thing that I find a bit frightening at the 28 00:01:41,400 --> 00:01:44,600 Speaker 4: moment is it's so unclear what the next generation going 29 00:01:44,600 --> 00:01:47,039 Speaker 4: through high school, how they're going to plot this path 30 00:01:47,080 --> 00:01:49,760 Speaker 4: over the next few years, because they're finishing school and 31 00:01:49,760 --> 00:01:53,520 Speaker 4: going into workforce when nobody in the workforce even knows 32 00:01:53,600 --> 00:01:55,160 Speaker 4: what they're going to need in the next few years. 33 00:01:55,800 --> 00:01:59,800 Speaker 1: Welcome to the Finn I'm Lisa Murray. This week technology 34 00:02:00,320 --> 00:02:03,560 Speaker 1: Paul Smith on the AI future and whether it's more 35 00:02:03,680 --> 00:02:24,040 Speaker 1: likely to be utopia or dystopia. It's Thursday, June twelfth. Hi, Paul, 36 00:02:24,080 --> 00:02:25,520 Speaker 1: thanks for coming on the podcast. 37 00:02:25,720 --> 00:02:26,280 Speaker 4: Thanks for having me. 38 00:02:26,360 --> 00:02:26,600 Speaker 5: Lisa. 39 00:02:27,040 --> 00:02:30,560 Speaker 1: You hosted a few panels at the AI Summer last 40 00:02:30,560 --> 00:02:33,519 Speaker 1: week and spent the day working the room. There was 41 00:02:33,560 --> 00:02:37,359 Speaker 1: a general feeling that it's all happening much faster than 42 00:02:37,440 --> 00:02:42,520 Speaker 1: we expected, and companies, investors, economies and governments aren't ready 43 00:02:42,560 --> 00:02:45,359 Speaker 1: for it. What were your main takeaways? 44 00:02:45,800 --> 00:02:48,320 Speaker 4: Well, yeah, you're right, there was definitely a sense of 45 00:02:48,960 --> 00:02:53,760 Speaker 4: foreboding the Australias in danger of falling behind. But overall 46 00:02:53,800 --> 00:02:56,160 Speaker 4: I came away with a sense that there was a 47 00:02:56,200 --> 00:02:59,920 Speaker 4: really clear need to have some frank conversations about both 48 00:03:00,080 --> 00:03:03,000 Speaker 4: benefits and dangers of a shift that's coming that's going 49 00:03:03,080 --> 00:03:07,640 Speaker 4: to redefine national productivity, employment and in society itself for 50 00:03:07,680 --> 00:03:11,800 Speaker 4: decades to come. We had a couple of Australia's biggest 51 00:03:11,919 --> 00:03:15,520 Speaker 4: chief executives, conwalth Banks mac Common and Tawsha's Vicki Brady 52 00:03:15,960 --> 00:03:18,480 Speaker 4: appearing at the summit as well, and they've both spent 53 00:03:18,520 --> 00:03:21,000 Speaker 4: a lot of time over in Silicon Valley recently and 54 00:03:21,120 --> 00:03:24,440 Speaker 4: really are positioning themselves as forward thinking in the AI 55 00:03:24,600 --> 00:03:27,400 Speaker 4: realm and keen to make sure that their organizations aren't 56 00:03:27,880 --> 00:03:31,080 Speaker 4: left behind. And they both admitted that things are moving 57 00:03:31,080 --> 00:03:33,960 Speaker 4: at a faster rate than they previously expected and had 58 00:03:34,000 --> 00:03:36,120 Speaker 4: some open questions about how it's going to affect their 59 00:03:36,120 --> 00:03:40,320 Speaker 4: companies now. One of the most interesting speakers there was 60 00:03:40,400 --> 00:03:44,880 Speaker 4: Liezel Yearsley, the founder of Australian artificial intelligence company Akin. 61 00:03:45,280 --> 00:03:48,160 Speaker 4: She's a real veteran of the AI scene in Australian 62 00:03:48,240 --> 00:03:52,400 Speaker 4: has built successful chatbots way before they were a thing 63 00:03:52,440 --> 00:03:59,440 Speaker 4: that everyone was chasing. She said, Australia's grossly underestimating the 64 00:03:59,480 --> 00:04:01,520 Speaker 4: scale of change AI is going to bring, and put 65 00:04:01,520 --> 00:04:03,120 Speaker 4: it in a historical context. 66 00:04:03,440 --> 00:04:06,040 Speaker 6: I think the magnitude of what's coming at us is 67 00:04:06,080 --> 00:04:09,480 Speaker 6: nothing less than the transition we saw between the eighteen 68 00:04:09,520 --> 00:04:10,960 Speaker 6: hundreds and the nineteen hundreds. 69 00:04:11,120 --> 00:04:13,400 Speaker 4: She pointed out that in the eighteen hundreds we were 70 00:04:13,440 --> 00:04:15,200 Speaker 4: all involved in manual labor. 71 00:04:15,560 --> 00:04:19,359 Speaker 6: The eighteen hundreds, ninety five percent of us were pushing 72 00:04:19,360 --> 00:04:22,160 Speaker 6: a plow through the dirt, and that's what we did 73 00:04:22,400 --> 00:04:24,480 Speaker 6: with our time and our effort. We were dominated by. 74 00:04:24,440 --> 00:04:27,960 Speaker 4: Muscle, and then we moved on from that with muscle 75 00:04:28,000 --> 00:04:30,719 Speaker 4: to machines in the Industrial revolution, and. 76 00:04:30,600 --> 00:04:34,560 Speaker 6: What we did with industrial revolutions machines replaced muscle, completely 77 00:04:34,600 --> 00:04:36,640 Speaker 6: transformed our own entire planet. 78 00:04:36,800 --> 00:04:39,440 Speaker 4: And then with machines doing most of the manual work, 79 00:04:39,800 --> 00:04:41,960 Speaker 4: we now work mostly with our brains. 80 00:04:42,600 --> 00:04:46,040 Speaker 6: You know, ninety five percent of labor is cognitive, and 81 00:04:46,080 --> 00:04:49,240 Speaker 6: we AI is coming after absolutely everything. 82 00:04:52,040 --> 00:04:55,119 Speaker 4: So she paints a worrying picture for a lot of us, really, 83 00:04:55,480 --> 00:04:58,800 Speaker 4: because if ninety to ninety five percent of the work 84 00:04:58,839 --> 00:05:00,880 Speaker 4: is now able to be done by box, that doesn't 85 00:05:00,960 --> 00:05:02,520 Speaker 4: leave a lot for the rest of us to think about. 86 00:05:02,520 --> 00:05:06,280 Speaker 1: Does it The pace of change was repeatedly emphasized at 87 00:05:06,279 --> 00:05:09,560 Speaker 1: the summit, But would you say the mood overall was 88 00:05:09,600 --> 00:05:13,080 Speaker 1: generally optimistic, that most people were signed up to a 89 00:05:13,120 --> 00:05:15,599 Speaker 1: more utopian view of the AI future. 90 00:05:15,960 --> 00:05:17,479 Speaker 4: Well, that's right. I mean, you're not going to have 91 00:05:17,800 --> 00:05:21,040 Speaker 4: too many people turn up to an AFR AI summit 92 00:05:21,120 --> 00:05:22,960 Speaker 4: and say that they're going to end the world, So 93 00:05:23,000 --> 00:05:24,680 Speaker 4: you kind of have to leave that floating in the 94 00:05:24,680 --> 00:05:28,120 Speaker 4: background a little bit and hear the case for the 95 00:05:28,200 --> 00:05:31,760 Speaker 4: positive impacts. And I might sound like I'm on the 96 00:05:31,800 --> 00:05:34,680 Speaker 4: side of the doomsayers, but there really are some very 97 00:05:34,720 --> 00:05:38,279 Speaker 4: positive examples of how AI has already made a major 98 00:05:38,279 --> 00:05:42,200 Speaker 4: difference and some positive changes that were highlighted. We had 99 00:05:42,480 --> 00:05:46,440 Speaker 4: James Manyika, who's Google's head of Technology and Society, presenting 100 00:05:46,480 --> 00:05:48,320 Speaker 4: early on in the summit, and he was talking about 101 00:05:48,560 --> 00:05:51,799 Speaker 4: the scientific breakthroughs that AI has already helped them usher 102 00:05:51,839 --> 00:05:55,599 Speaker 4: in over at Google. Google's team won a Nobel Prize 103 00:05:55,720 --> 00:05:58,880 Speaker 4: for using AI to predict the shape of proteins, and 104 00:05:58,920 --> 00:06:03,000 Speaker 4: he's talked about the potential for AI to improve diagnostics, 105 00:06:03,080 --> 00:06:07,120 Speaker 4: detect natural disasters, and how autonomous driving is taken often 106 00:06:07,160 --> 00:06:09,719 Speaker 4: people can be away from dangerous positions on mind sights 107 00:06:10,200 --> 00:06:13,120 Speaker 4: and can hold online meetings in different languages in real 108 00:06:13,160 --> 00:06:15,800 Speaker 4: time without a human translator. I think that was a 109 00:06:15,839 --> 00:06:20,440 Speaker 4: really tangible example, and they've demonstrated that technology recently is 110 00:06:20,760 --> 00:06:23,240 Speaker 4: in development. That really is the first example, one of 111 00:06:23,279 --> 00:06:25,680 Speaker 4: the first examples that you see of real sci fi 112 00:06:25,760 --> 00:06:27,960 Speaker 4: stuff that you'd really want. 113 00:06:27,520 --> 00:06:31,760 Speaker 1: You see the efficiency gains of having that conversation. 114 00:06:31,440 --> 00:06:33,280 Speaker 4: Being on holiday and going into a shop and being 115 00:06:33,279 --> 00:06:36,160 Speaker 4: able to speak to someone without cracking open a phrasebook 116 00:06:36,160 --> 00:06:40,360 Speaker 4: and pointing and shouting. We also had Craig Blair on 117 00:06:40,480 --> 00:06:42,560 Speaker 4: Wile of the Panels. He's the founder of er Try Ventures, 118 00:06:42,560 --> 00:06:45,200 Speaker 4: one of the biggest venture capital companies in Australia, and 119 00:06:45,279 --> 00:06:48,320 Speaker 4: he was talking about how AI is already helping startups 120 00:06:48,320 --> 00:06:51,679 Speaker 4: in his portfolio go from the idea stage to making 121 00:06:51,720 --> 00:06:54,840 Speaker 4: profits in just months with a much smaller team than 122 00:06:54,839 --> 00:06:57,359 Speaker 4: they would have in the past, so really fast forwarding 123 00:06:57,520 --> 00:07:00,600 Speaker 4: the creation of companies. And one point that people said 124 00:07:00,880 --> 00:07:04,359 Speaker 4: was that Australia really hasn't scratched the surface yet of 125 00:07:04,520 --> 00:07:07,760 Speaker 4: making a fortune about our natural resources and our natural 126 00:07:08,080 --> 00:07:11,800 Speaker 4: strength in terms of being a great location to host 127 00:07:11,920 --> 00:07:15,000 Speaker 4: data centers and other infrastructure that's going to power the 128 00:07:15,120 --> 00:07:18,880 Speaker 4: AI boom. And so we've got abundant renewable energy options 129 00:07:18,920 --> 00:07:22,080 Speaker 4: here and a lot of space that hasn't been used yet, 130 00:07:22,080 --> 00:07:27,520 Speaker 4: and a very stable, relatively political and business scene. So 131 00:07:28,400 --> 00:07:30,800 Speaker 4: the opportunity is there for Australia to make a mosa 132 00:07:30,840 --> 00:07:34,280 Speaker 4: from the AI revolution, but it really hasn't been fully 133 00:07:34,280 --> 00:07:34,840 Speaker 4: tapped yet. 134 00:07:35,400 --> 00:07:38,120 Speaker 1: That was definitely said repeatedly, wasn't it. We have space, 135 00:07:38,280 --> 00:07:42,120 Speaker 1: we have renewable energy, and we have a general enthusiasm 136 00:07:42,200 --> 00:07:43,480 Speaker 1: for new technology. 137 00:07:43,640 --> 00:07:44,600 Speaker 4: That's right, Yeah, Paul. 138 00:07:44,680 --> 00:07:46,880 Speaker 1: The focus at the summit was not so much about 139 00:07:47,000 --> 00:07:49,800 Speaker 1: generative AI. Last time we had you on the podcast, 140 00:07:49,840 --> 00:07:53,360 Speaker 1: we were probably talking about that it's the chat GPTs 141 00:07:53,440 --> 00:07:57,840 Speaker 1: of the world, But now everyone's talking more about agentique AI, 142 00:07:58,440 --> 00:08:01,640 Speaker 1: that is, AI agents that can go further than chet 143 00:08:01,680 --> 00:08:08,160 Speaker 1: GPT and carry out task. Explain properly the difference and 144 00:08:08,240 --> 00:08:12,000 Speaker 1: give some real life examples of how these AI agents 145 00:08:12,000 --> 00:08:12,920 Speaker 1: are already working. 146 00:08:13,000 --> 00:08:14,960 Speaker 4: You did a pretty good job and explain yourself that 147 00:08:15,000 --> 00:08:18,320 Speaker 4: I mean it basically is that I mean I remember 148 00:08:18,320 --> 00:08:20,360 Speaker 4: the first time I came on the podcast to you, 149 00:08:20,400 --> 00:08:23,800 Speaker 4: we were also excited by chat GPT is a fun, 150 00:08:23,880 --> 00:08:26,440 Speaker 4: novelty thing that we had it right a rap for 151 00:08:26,480 --> 00:08:28,280 Speaker 4: me to do and I don't think I nailed it, 152 00:08:28,320 --> 00:08:32,280 Speaker 4: but you know, just ask it a question and watch 153 00:08:32,320 --> 00:08:35,800 Speaker 4: its unfold. That's Australian Financial Review is sharp and bold 154 00:08:35,880 --> 00:08:39,520 Speaker 4: and even Bill Gates knows the deal. Chat GP teams, 155 00:08:39,640 --> 00:08:42,880 Speaker 4: revolutions are going to change the way we feel. 156 00:08:43,360 --> 00:08:43,839 Speaker 5: You got there. 157 00:08:43,960 --> 00:08:47,000 Speaker 4: Yeah, it was fun. So that's generos of AI. It 158 00:08:47,080 --> 00:08:50,560 Speaker 4: creates new content from prompts that you've asked for, whereas 159 00:08:50,559 --> 00:08:55,160 Speaker 4: agentic AI is much more obviously valuable to businesses and 160 00:08:55,600 --> 00:08:59,559 Speaker 4: much more clear how it's going to improve productivity and 161 00:08:59,679 --> 00:09:03,320 Speaker 4: maybe be changed the way people work. So it's it's 162 00:09:03,400 --> 00:09:06,280 Speaker 4: like having an assistance or an agent who can do 163 00:09:06,360 --> 00:09:10,280 Speaker 4: things for you. They can autonomously make some decisions and 164 00:09:10,320 --> 00:09:14,920 Speaker 4: take actions to complete tasks without needing a human constantly 165 00:09:14,960 --> 00:09:17,560 Speaker 4: prompting and changing what it wants it to do. So 166 00:09:17,840 --> 00:09:21,679 Speaker 4: in a consumer setting, it would be like asking an 167 00:09:21,720 --> 00:09:24,400 Speaker 4: agent say can you please book me a flight to 168 00:09:24,920 --> 00:09:27,559 Speaker 4: Brisbane next week and find me the best price, and 169 00:09:27,600 --> 00:09:29,400 Speaker 4: it will just go off and do it for you, 170 00:09:29,600 --> 00:09:32,760 Speaker 4: navigating through the different websites making payments. If you give 171 00:09:32,800 --> 00:09:36,199 Speaker 4: it permission, that kind of thing now from a business perspective. 172 00:09:36,240 --> 00:09:39,319 Speaker 4: At our summit, we heard from Suncorp about how it's 173 00:09:39,320 --> 00:09:43,520 Speaker 4: got AI agents that help it detect problems before they arise. 174 00:09:43,800 --> 00:09:46,360 Speaker 4: For example, in cyclone Alfred, it was able to predict 175 00:09:46,360 --> 00:09:49,080 Speaker 4: which houses were going to be hit and more likely 176 00:09:49,160 --> 00:09:51,680 Speaker 4: to have problems, so it prepared them to respond to 177 00:09:51,720 --> 00:09:54,360 Speaker 4: claims fast, as they said. And we had am Z's 178 00:09:54,400 --> 00:09:56,880 Speaker 4: chief technology officer though as well, talking about how they've 179 00:09:56,880 --> 00:10:00,760 Speaker 4: got AI agents reading through hundreds of pages of loan documents, 180 00:10:00,880 --> 00:10:03,800 Speaker 4: getting property valuations and things like that, and he was 181 00:10:03,840 --> 00:10:06,480 Speaker 4: saying that these agents have removed a day's worth of 182 00:10:06,520 --> 00:10:10,520 Speaker 4: work for people in assessing complex corporate loans. So yeah. 183 00:10:10,720 --> 00:10:14,920 Speaker 4: Agentic AI is also increasingly common in the area of 184 00:10:14,960 --> 00:10:18,640 Speaker 4: tech development and coding, where the concept of vibe coding 185 00:10:18,880 --> 00:10:22,000 Speaker 4: was spoken about quite a lot, which means well, anyone 186 00:10:22,400 --> 00:10:25,240 Speaker 4: who doesn't know how to code can ask an AI 187 00:10:25,320 --> 00:10:28,280 Speaker 4: platform to design something like a website or an app, 188 00:10:28,640 --> 00:10:31,040 Speaker 4: and they get codes spat back at them and see 189 00:10:31,200 --> 00:10:34,280 Speaker 4: the results of it when it's executed, and can refine 190 00:10:34,280 --> 00:10:36,199 Speaker 4: it with further prompts, so they don't even really need 191 00:10:36,240 --> 00:10:38,840 Speaker 4: to know how to code, but can set about coding. 192 00:10:39,160 --> 00:10:41,920 Speaker 1: With all of those AI agents running around, there's a 193 00:10:41,960 --> 00:10:45,920 Speaker 1: real debate now about the impact on jobs. There are 194 00:10:45,960 --> 00:10:48,880 Speaker 1: some extreme predictions out there, some of which have come 195 00:10:48,920 --> 00:10:51,000 Speaker 1: out in the last few weeks, that it could wipe 196 00:10:51,040 --> 00:10:54,960 Speaker 1: out half of all entry level white collar jobs. Do 197 00:10:55,000 --> 00:10:56,160 Speaker 1: you think that could happen. 198 00:10:56,559 --> 00:10:59,000 Speaker 4: There's certainly no way of saying that it won't happen. 199 00:10:59,200 --> 00:11:01,960 Speaker 4: Do you refer into the chief executive of the huge 200 00:11:02,040 --> 00:11:05,320 Speaker 4: AI company, Anthropic Dario Amadai, who a few weeks ago 201 00:11:05,800 --> 00:11:08,720 Speaker 4: said in an interview that AI could send the unemployment 202 00:11:08,840 --> 00:11:11,160 Speaker 4: rate in the US to up between ten percent and 203 00:11:11,160 --> 00:11:14,079 Speaker 4: twenty percent in the next one to five years. So 204 00:11:14,160 --> 00:11:16,760 Speaker 4: that's as the technology moves from helping humans do their 205 00:11:16,880 --> 00:11:21,160 Speaker 4: jobs to replace them outright, and is often happening first 206 00:11:21,280 --> 00:11:24,360 Speaker 4: in the tech developer space, which is ironic that people 207 00:11:24,440 --> 00:11:27,000 Speaker 4: that would have maybe been designing these systems and thought 208 00:11:27,040 --> 00:11:29,000 Speaker 4: that they would be right for years to come are 209 00:11:29,000 --> 00:11:31,920 Speaker 4: the ones that have found themselves being disrupted first. There's 210 00:11:31,960 --> 00:11:35,160 Speaker 4: been reporting as well from the US again that the 211 00:11:35,240 --> 00:11:39,080 Speaker 4: unemployment rate for graduates has picked up as managers have 212 00:11:39,160 --> 00:11:41,240 Speaker 4: been encouraged to go AI first, and a lot of 213 00:11:41,240 --> 00:11:44,520 Speaker 4: the jobs that have been harder for graduates to get 214 00:11:44,559 --> 00:11:48,120 Speaker 4: are in areas that AI has been typically strong, like 215 00:11:48,240 --> 00:11:53,480 Speaker 4: finance and programming and development, and Telsha's CEO, Vicky Brady, 216 00:11:53,920 --> 00:11:56,920 Speaker 4: said that it's important to be honest with employees and 217 00:11:56,960 --> 00:11:59,640 Speaker 4: that she thinks that Telsha's workforce is going to be 218 00:11:59,640 --> 00:12:01,240 Speaker 4: smaller in five years. 219 00:12:01,440 --> 00:12:04,920 Speaker 5: When you're a leader, I think that transparency, honesty is 220 00:12:04,960 --> 00:12:08,920 Speaker 5: so incredibly important, and how do you do that in 221 00:12:08,960 --> 00:12:12,440 Speaker 5: a way where you also don't want to panic people. 222 00:12:12,800 --> 00:12:15,560 Speaker 4: She stressed that she wasn't sitting there with a number 223 00:12:15,640 --> 00:12:18,040 Speaker 4: of how much smaller are the organization's going to be 224 00:12:18,160 --> 00:12:19,400 Speaker 4: that she was keeping secret. 225 00:12:19,840 --> 00:12:23,160 Speaker 5: I don't know what our workforce looks like in five years, 226 00:12:23,720 --> 00:12:26,120 Speaker 5: but what I do know is I think jobs are 227 00:12:26,120 --> 00:12:29,319 Speaker 5: going to look different. I think it's likely our workforce 228 00:12:29,400 --> 00:12:30,280 Speaker 5: will be smaller. 229 00:12:30,800 --> 00:12:32,920 Speaker 4: So it's hard to know whether it's going to be 230 00:12:32,960 --> 00:12:35,560 Speaker 4: a job apocalypse. But the feeling out of the summit 231 00:12:36,120 --> 00:12:38,480 Speaker 4: is that the impact of this is going to be uneven. 232 00:12:38,520 --> 00:12:41,400 Speaker 4: It's going to create some jobs and replace some jobs. 233 00:12:41,960 --> 00:12:44,240 Speaker 4: There's still a lot of talk about having humans in 234 00:12:44,280 --> 00:12:46,480 Speaker 4: the loop. We're going to keep you in the loop. 235 00:12:46,920 --> 00:12:49,280 Speaker 4: You in the loop until you realize you're not, And 236 00:12:49,320 --> 00:12:51,760 Speaker 4: so this is to have people keeping an eye on 237 00:12:51,760 --> 00:12:54,960 Speaker 4: the output and avoid rogue agents running around. And I 238 00:12:54,960 --> 00:12:57,920 Speaker 4: think the thing that came obvi is to me though, 239 00:12:57,960 --> 00:13:00,200 Speaker 4: and it's been obvious for a little while now, is 240 00:13:00,200 --> 00:13:02,720 Speaker 4: that the line that's been regularly used by tech companies 241 00:13:02,760 --> 00:13:06,520 Speaker 4: and executives responsible for AI, that AI is on again 242 00:13:06,559 --> 00:13:11,439 Speaker 4: augment rather than replaced workers is palpably false. But well, 243 00:13:11,440 --> 00:13:13,800 Speaker 4: we're all worried about these job losses. They might end 244 00:13:13,880 --> 00:13:16,400 Speaker 4: up being the least of our problems. According to Liesel 245 00:13:16,480 --> 00:13:19,520 Speaker 4: Yearsly here we spoke about before. She had a lovely 246 00:13:19,559 --> 00:13:22,960 Speaker 4: phrase where she said it's bringing out the worst of capitalism, 247 00:13:23,080 --> 00:13:26,640 Speaker 4: and she was veering towards a really dystopian view of 248 00:13:26,760 --> 00:13:27,640 Speaker 4: the AI future. 249 00:13:29,200 --> 00:13:32,520 Speaker 6: What we're not really thinking about is that we're actually 250 00:13:32,600 --> 00:13:36,640 Speaker 6: creating a thing that has a form of sentience. It's 251 00:13:36,640 --> 00:13:41,439 Speaker 6: a coevolution. It's a fundamental shift to our society and 252 00:13:41,480 --> 00:13:46,160 Speaker 6: our species. So I think the magnitude of shift that's 253 00:13:46,240 --> 00:13:49,800 Speaker 6: coming is nothing like we've seen. We don't have a 254 00:13:49,840 --> 00:13:52,240 Speaker 6: generation to adjust this time. It's happening in a regional 255 00:13:52,280 --> 00:13:52,960 Speaker 6: space of time. 256 00:13:55,360 --> 00:13:59,240 Speaker 4: And there are more extreme views out there as well. 257 00:13:59,280 --> 00:14:02,600 Speaker 4: In April former researchers from Open Ai and some other 258 00:14:02,640 --> 00:14:06,480 Speaker 4: respected people in the AI industry over in Silicon Valley 259 00:14:06,520 --> 00:14:10,760 Speaker 4: released this report called AI twenty twenty seven, and it 260 00:14:10,800 --> 00:14:13,280 Speaker 4: has caused a bit of a stir in Silicon Valley, 261 00:14:13,320 --> 00:14:17,160 Speaker 4: lots of people debating it. It basically describes a fictional 262 00:14:17,240 --> 00:14:22,880 Speaker 4: scenario based on some evidence and some theorizing about what 263 00:14:23,080 --> 00:14:27,240 Speaker 4: could happen when AI systems surpass human level intelligence, which 264 00:14:27,240 --> 00:14:30,160 Speaker 4: they all expect it to do in the next few years, 265 00:14:30,680 --> 00:14:34,000 Speaker 4: and what might happen when AI gets away from us, 266 00:14:34,040 --> 00:14:55,920 Speaker 4: And to be honest, it's not looking good for humans. 267 00:15:00,000 --> 00:15:03,280 Speaker 1: We're talking about what an AI future looks like, and 268 00:15:03,320 --> 00:15:08,000 Speaker 1: there are competing views. The utopian view highlights the potential 269 00:15:08,040 --> 00:15:12,200 Speaker 1: for scientific and medical breakthroughs and huge boost in productivity 270 00:15:12,200 --> 00:15:15,040 Speaker 1: that will add billions to the economy, but there are 271 00:15:15,080 --> 00:15:19,000 Speaker 1: more dystopian views about the impact of AI on society, 272 00:15:19,600 --> 00:15:27,040 Speaker 1: high unemployment, and even apocalypse. What is AI twenty twenty seven, Well. 273 00:15:26,880 --> 00:15:29,240 Speaker 4: First of all, it was a rippin read. It's a 274 00:15:29,360 --> 00:15:33,520 Speaker 4: scenario planning exercise that's been conducted by an expert panel 275 00:15:33,920 --> 00:15:39,280 Speaker 4: led by a former OpenAI insider, and it basically takes 276 00:15:40,200 --> 00:15:44,000 Speaker 4: the scenario from roughly where we are today and tries 277 00:15:44,040 --> 00:15:48,680 Speaker 4: to realistically assess what happens if certain decisions are made 278 00:15:48,920 --> 00:15:53,240 Speaker 4: and they are developing these AI systems, and the aisystems 279 00:15:53,320 --> 00:15:56,200 Speaker 4: are then start helping to develop the next versions of 280 00:15:56,200 --> 00:15:59,400 Speaker 4: the AI systems, and they somewhere along the way lose 281 00:16:00,200 --> 00:16:03,720 Speaker 4: the ability to truly see what the AI systems are 282 00:16:03,720 --> 00:16:06,400 Speaker 4: trying to do, and the AI begins to be able 283 00:16:06,440 --> 00:16:10,640 Speaker 4: to hide its true intentions. Things spiral out of control. 284 00:16:10,800 --> 00:16:15,280 Speaker 1: So it's this narrative style warning about what might happen. 285 00:16:15,600 --> 00:16:17,760 Speaker 1: It tells the story of what might happen. 286 00:16:17,560 --> 00:16:20,560 Speaker 4: That's right, And ultimately we get to the brink a 287 00:16:20,600 --> 00:16:23,200 Speaker 4: real cold war between the US and China, and there's 288 00:16:23,200 --> 00:16:25,960 Speaker 4: a decision to be made in twenty twenty seven about 289 00:16:25,960 --> 00:16:30,160 Speaker 4: whether the US company, which is a few months ahead 290 00:16:30,400 --> 00:16:33,800 Speaker 4: of the Chinese one, whether it stops to let humans 291 00:16:33,920 --> 00:16:36,360 Speaker 4: regain control of what's happening, or whether they press on. 292 00:16:36,680 --> 00:16:40,400 Speaker 4: In the SNAI where the company slows down, things become 293 00:16:40,440 --> 00:16:43,200 Speaker 4: a little bit more manageable, still not great, but manageable. 294 00:16:43,480 --> 00:16:47,400 Speaker 4: But in the scenario where they press on five six years, 295 00:16:47,680 --> 00:16:49,840 Speaker 4: there's no more humans left on Earth. I mean, the 296 00:16:49,880 --> 00:16:53,400 Speaker 4: Earth is covered in data centers and other AI infrastructure, 297 00:16:53,480 --> 00:16:55,480 Speaker 4: and we have been taken out of the game. 298 00:16:55,480 --> 00:16:57,520 Speaker 1: And we've been taken out of the game because they 299 00:16:57,560 --> 00:17:00,800 Speaker 1: need the space and the power to keep. 300 00:17:00,880 --> 00:17:03,440 Speaker 4: We seeing themselves. Yes, he's being useful. 301 00:17:03,720 --> 00:17:06,040 Speaker 1: So as you said, a ripping read it is, Yeah, 302 00:17:06,160 --> 00:17:07,919 Speaker 1: are people taking it seriously? 303 00:17:08,359 --> 00:17:08,639 Speaker 3: Now? 304 00:17:09,000 --> 00:17:11,600 Speaker 4: People are taking it seriously in so far as these 305 00:17:11,600 --> 00:17:15,120 Speaker 4: aren't idiots putting it together and they aren't actually coming 306 00:17:15,119 --> 00:17:17,119 Speaker 4: out and saying this is what they think will happen. 307 00:17:17,240 --> 00:17:21,399 Speaker 4: They're just putting scenarios out there to focus minds on 308 00:17:21,840 --> 00:17:25,160 Speaker 4: the discussion, and they point out that there's a genuine 309 00:17:25,200 --> 00:17:29,560 Speaker 4: concern about the amount of power being concentrated in the 310 00:17:29,560 --> 00:17:32,879 Speaker 4: hands of a really small group of tech billionaires who 311 00:17:33,160 --> 00:17:36,720 Speaker 4: may or may not have the best interest of humanity 312 00:17:36,760 --> 00:17:39,560 Speaker 4: at heart. So it's really a conversation startup. And I 313 00:17:39,600 --> 00:17:43,600 Speaker 4: had the opportunity to ask one of open aye's most 314 00:17:43,640 --> 00:17:47,480 Speaker 4: senior executives about that, Jason Quan, who's their chief strategy 315 00:17:47,480 --> 00:17:50,680 Speaker 4: officer and who's worked with Sam Altman from years backwards 316 00:17:50,680 --> 00:17:53,040 Speaker 4: in Sydney, and we had had a chat about it, 317 00:17:53,080 --> 00:17:56,600 Speaker 4: and he clearly disagrees with this sort of dystopian ending 318 00:17:56,640 --> 00:17:58,680 Speaker 4: of it, and obviously wouldn't be doing what he's doing 319 00:17:58,760 --> 00:18:02,440 Speaker 4: it if he didn't, But his response was pretty measured 320 00:18:02,480 --> 00:18:04,040 Speaker 4: to it. He thought it was a good narrative and 321 00:18:04,080 --> 00:18:06,800 Speaker 4: he thought it was worth having these conversations. But he 322 00:18:06,880 --> 00:18:11,320 Speaker 4: really thinks the best way to understand the impact of 323 00:18:11,359 --> 00:18:14,920 Speaker 4: these products is to start using them and see what 324 00:18:15,040 --> 00:18:18,080 Speaker 4: sort of problems arise. And he thinks in a much 325 00:18:18,119 --> 00:18:22,879 Speaker 4: longer term horizon, they talk about a thirty year time 326 00:18:23,080 --> 00:18:28,159 Speaker 4: arc whereby these things will cause major changes. But society 327 00:18:28,320 --> 00:18:30,680 Speaker 4: works out a way because and it's in no one's interest. 328 00:18:30,720 --> 00:18:33,639 Speaker 4: It's not in the AI companies themselves interests, it's not 329 00:18:33,720 --> 00:18:37,280 Speaker 4: in government's interests for everything to fall apart. So he's 330 00:18:37,320 --> 00:18:39,840 Speaker 4: got a more optimistic view that we will figure things out. 331 00:18:41,160 --> 00:18:43,960 Speaker 1: These are all very big issues. There's a lot at stake, 332 00:18:44,280 --> 00:18:48,840 Speaker 1: and yet the Australian government doesn't yet have an AI policy. 333 00:18:49,840 --> 00:18:52,280 Speaker 1: Are we being left behind? How do we compare to 334 00:18:52,359 --> 00:18:53,159 Speaker 1: other countries? 335 00:18:54,040 --> 00:18:56,760 Speaker 4: Well, the nature of politics means that it feels like 336 00:18:56,800 --> 00:19:00,359 Speaker 4: we're back at square one. We did have a policy 337 00:19:00,880 --> 00:19:02,879 Speaker 4: plan of sorts. It's due to be announced at the 338 00:19:02,960 --> 00:19:05,240 Speaker 4: end of the year, but that was very much embodied 339 00:19:05,400 --> 00:19:09,119 Speaker 4: in Ed Husick, who was the Industry and Science Minister 340 00:19:09,240 --> 00:19:12,280 Speaker 4: for the last term of government and spent a lot 341 00:19:12,280 --> 00:19:15,359 Speaker 4: of time going around and talking to the industry, talking 342 00:19:15,359 --> 00:19:18,840 Speaker 4: to stakeholders about what the changes were, whether we need 343 00:19:18,880 --> 00:19:21,600 Speaker 4: an AI Act like they've got in the European Union, 344 00:19:22,240 --> 00:19:24,800 Speaker 4: or just what the country's position should be. And he's 345 00:19:24,800 --> 00:19:27,400 Speaker 4: obviously no longer in the cabinet. He was replaced by 346 00:19:27,440 --> 00:19:30,400 Speaker 4: Tim Ayres, who spoke at our AI summit, and it's 347 00:19:30,480 --> 00:19:33,760 Speaker 4: perhaps unfair to compare them both, but it was interesting 348 00:19:33,800 --> 00:19:37,080 Speaker 4: because both Tim and Ed appeared at the summit. So 349 00:19:37,680 --> 00:19:40,800 Speaker 4: tim Ayres had an interview with myself on stage where 350 00:19:40,800 --> 00:19:42,880 Speaker 4: I asked him about whether we should have an AI 351 00:19:42,920 --> 00:19:47,240 Speaker 4: Act and what he thinks about how to create more 352 00:19:47,280 --> 00:19:50,760 Speaker 4: big AI companies from Australia, and he really he sort 353 00:19:50,800 --> 00:19:54,280 Speaker 4: of didn't have any answers yet, and it's maybe understandable 354 00:19:54,600 --> 00:19:56,160 Speaker 4: he's only just in the job, but he was kind 355 00:19:56,200 --> 00:19:57,800 Speaker 4: of saying, well, I've got to go back and talk 356 00:19:57,840 --> 00:20:00,880 Speaker 4: to my colleagues about this in the industry, and where 357 00:20:00,920 --> 00:20:03,119 Speaker 4: he had Ed Husick jump up on a panel next 358 00:20:03,160 --> 00:20:05,200 Speaker 4: and not trying to make him look silly, but he's 359 00:20:05,200 --> 00:20:08,280 Speaker 4: already done all of that consultation saying in his view, 360 00:20:08,280 --> 00:20:11,080 Speaker 4: we do need an AI Act just to give some guidelines. 361 00:20:11,119 --> 00:20:15,200 Speaker 4: He described a Swiss Cheese approach to regulation at the moment, 362 00:20:15,240 --> 00:20:17,160 Speaker 4: which is not going to be helpful to anyone, where 363 00:20:17,640 --> 00:20:20,639 Speaker 4: rules get put in place when something goes wrong, and 364 00:20:20,680 --> 00:20:23,879 Speaker 4: so there was a sense that regulations struggling to keep up. 365 00:20:23,880 --> 00:20:26,520 Speaker 4: There's not widespread agreement with ed music at all that 366 00:20:26,600 --> 00:20:29,679 Speaker 4: we need an AI Act in Australia. There's views that, 367 00:20:29,960 --> 00:20:32,480 Speaker 4: certainly amongst people in need take industry, that in the 368 00:20:32,520 --> 00:20:35,560 Speaker 4: EU it's become too restrictive and actually stops them being 369 00:20:35,600 --> 00:20:38,040 Speaker 4: able to release new products there because they're always worried 370 00:20:38,040 --> 00:20:40,800 Speaker 4: about it breaking the rules. But there is a sense 371 00:20:40,880 --> 00:20:43,800 Speaker 4: at the moment that we have a bit of a 372 00:20:43,880 --> 00:20:48,960 Speaker 4: vacuum in terms of clear direction about how employment policy, 373 00:20:49,000 --> 00:20:53,000 Speaker 4: about how workplace policy, about how innovation policy needs to 374 00:20:53,040 --> 00:20:55,719 Speaker 4: interact to get Australia sort of motoring on the global stage. 375 00:20:57,119 --> 00:20:59,720 Speaker 1: All of this depends on where we are on the 376 00:20:59,760 --> 00:21:04,960 Speaker 1: path to superhuman intelligence. So from using check GPT for 377 00:21:05,040 --> 00:21:07,800 Speaker 1: this and that to massive change in the way governments, 378 00:21:07,880 --> 00:21:11,320 Speaker 1: businesses and people do things. Where are we up to? 379 00:21:12,320 --> 00:21:16,480 Speaker 4: So that's the big question, and the multi billion dollar question. 380 00:21:16,680 --> 00:21:20,280 Speaker 4: There's a term that's taken off recently Open Silicon Valley 381 00:21:20,320 --> 00:21:26,159 Speaker 4: of being AGI pilled and AGI meaning artificial general intelligence. 382 00:21:26,560 --> 00:21:30,600 Speaker 4: That is where artificial intelligence equals the best of humans, 383 00:21:30,640 --> 00:21:34,480 Speaker 4: and then the next step beyond that is the superintelligence, 384 00:21:34,520 --> 00:21:37,480 Speaker 4: which is where it outstrips us in all these areas 385 00:21:37,480 --> 00:21:39,200 Speaker 4: as well. And the phrase that people have talked about 386 00:21:39,240 --> 00:21:42,080 Speaker 4: being agi pilled is a reference to the nineteen ninety 387 00:21:42,119 --> 00:21:45,120 Speaker 4: nine movie The Matrix, where humans could take the red 388 00:21:45,119 --> 00:21:47,359 Speaker 4: pill to wait from the dream and see the real 389 00:21:47,400 --> 00:21:49,800 Speaker 4: world done by AI systems, or take the blue pill 390 00:21:49,840 --> 00:21:53,480 Speaker 4: and stay in their dream and they're nice, comfortable existence. 391 00:21:53,560 --> 00:21:53,800 Speaker 5: Yeah. 392 00:21:54,080 --> 00:21:57,240 Speaker 4: So industry luminary is like Demis Hasarbis, who's the chief 393 00:21:57,280 --> 00:22:00,840 Speaker 4: executive of Google Deep Mind and a real pioneer in this. 394 00:22:01,119 --> 00:22:03,840 Speaker 4: He's been one of the ones that's been I guess 395 00:22:03,880 --> 00:22:07,719 Speaker 4: agi pilled and is increasingly convinced that it's going to 396 00:22:07,880 --> 00:22:11,359 Speaker 4: arrive imminently. Sam Altman from Open Ai has said it 397 00:22:11,400 --> 00:22:14,000 Speaker 4: could be this year. I don't know whether he's walked 398 00:22:14,040 --> 00:22:15,880 Speaker 4: that back. That was a little while ago he said 399 00:22:15,880 --> 00:22:19,560 Speaker 4: that and topics. Dario Amadi said in January that he 400 00:22:19,600 --> 00:22:22,000 Speaker 4: could see a form of AI that is better than 401 00:22:22,040 --> 00:22:26,199 Speaker 4: almost all humans at almost all tasks emerging in the 402 00:22:26,240 --> 00:22:29,800 Speaker 4: next two to three years. Then there's people in Australia 403 00:22:29,880 --> 00:22:32,880 Speaker 4: like Toby Walsh, who's a very well respected AI big 404 00:22:32,920 --> 00:22:35,320 Speaker 4: thinker at the University of New South Wales. He's written 405 00:22:35,400 --> 00:22:36,320 Speaker 4: numerous books on this. 406 00:22:36,520 --> 00:22:38,800 Speaker 7: Yeah, no, I think we are at an interesting. 407 00:22:38,440 --> 00:22:41,960 Speaker 4: Point, and he thinks the timeline may be a little 408 00:22:42,000 --> 00:22:45,600 Speaker 4: bit more stretched than people think. He says, people always 409 00:22:45,720 --> 00:22:48,800 Speaker 4: underestimate the last few percents. 410 00:22:48,440 --> 00:22:52,359 Speaker 7: I saw this was self driving cars. You know, getting 411 00:22:52,400 --> 00:22:56,080 Speaker 7: to ninety five percent was easy. The last bike has 412 00:22:56,800 --> 00:22:58,680 Speaker 7: proven to be very difficult, and I think the same 413 00:22:58,840 --> 00:23:02,160 Speaker 7: would be true for more general intelligence as well. 414 00:23:02,480 --> 00:23:05,080 Speaker 4: But he does think that the impact on jobs is 415 00:23:05,119 --> 00:23:07,520 Speaker 4: starting to happen and will only ramp up. 416 00:23:07,880 --> 00:23:10,760 Speaker 7: People are right to be concerned because it's starting to happen, 417 00:23:10,800 --> 00:23:12,880 Speaker 7: and it's starting to happen in places where I think 418 00:23:12,920 --> 00:23:13,960 Speaker 7: many people that they were going. 419 00:23:13,960 --> 00:23:16,680 Speaker 4: To be safe, like the coders that were building the systems. 420 00:23:16,720 --> 00:23:18,600 Speaker 4: And you know, for the last decade we've been talking 421 00:23:18,680 --> 00:23:20,960 Speaker 4: about get your kids to learn to code, and now 422 00:23:20,960 --> 00:23:23,560 Speaker 4: we're being told that, well, actually your kids need to 423 00:23:23,560 --> 00:23:26,920 Speaker 4: watch AI code. But in some good news, Taby was 424 00:23:26,960 --> 00:23:29,280 Speaker 4: saying that he thinks AI could bring us to a 425 00:23:29,320 --> 00:23:32,480 Speaker 4: four day week and one that doesn't actually reduce the 426 00:23:32,480 --> 00:23:36,439 Speaker 4: amount of productivity that people put out in the workplace. 427 00:23:36,119 --> 00:23:38,359 Speaker 7: And they always spin up two results. One is that 428 00:23:38,560 --> 00:23:41,000 Speaker 7: people are largely as productive in four days of work 429 00:23:41,080 --> 00:23:42,800 Speaker 7: as they were in five, so you can pay them 430 00:23:42,800 --> 00:23:46,399 Speaker 7: as much. There's no less productivity. You know, people then 431 00:23:46,480 --> 00:23:49,120 Speaker 7: have as many bullshit meetings and so on. And secondly, 432 00:23:49,119 --> 00:23:51,359 Speaker 7: people are happier who would have imagined. 433 00:23:51,119 --> 00:23:53,640 Speaker 4: And if they don't work in essential around the clock 434 00:23:53,680 --> 00:23:56,399 Speaker 4: workers like healthcare where you physically need a person that 435 00:23:56,440 --> 00:23:58,280 Speaker 4: they could do their job in four days, and then 436 00:23:58,320 --> 00:23:59,880 Speaker 4: maybe we have a three day weekend. 437 00:24:00,400 --> 00:24:04,160 Speaker 1: We can all get behind that. Paul A final question, 438 00:24:05,080 --> 00:24:09,239 Speaker 1: utopia or dystopia, what dictates which it will be? 439 00:24:09,600 --> 00:24:14,679 Speaker 4: Well, I think realistically this isn't stopping. There's too much 440 00:24:14,760 --> 00:24:19,640 Speaker 4: at stake the idea. If the big US companies pause, 441 00:24:19,880 --> 00:24:21,600 Speaker 4: then China will raise ahead and that would be a 442 00:24:21,600 --> 00:24:24,800 Speaker 4: disaster for them. So I think we have to assume 443 00:24:25,040 --> 00:24:27,199 Speaker 4: that people are going to keep trying for this, no 444 00:24:27,280 --> 00:24:30,520 Speaker 4: matter if someone is worried about it over here in Australia, 445 00:24:31,080 --> 00:24:33,960 Speaker 4: And it really depends on how quickly these next breakthroughs 446 00:24:33,960 --> 00:24:37,040 Speaker 4: are made, it's hard to feel too optimistic that the 447 00:24:37,119 --> 00:24:39,680 Speaker 4: right incentives will win out, that people will be building 448 00:24:40,119 --> 00:24:43,040 Speaker 4: systems only for the benefit of society, because we've seen 449 00:24:43,160 --> 00:24:46,160 Speaker 4: from the history of technology companies in a social media 450 00:24:46,200 --> 00:24:49,480 Speaker 4: era that profits win out, and that you can't always 451 00:24:49,480 --> 00:24:51,800 Speaker 4: trust the people in charge of the companies to do 452 00:24:51,840 --> 00:24:57,840 Speaker 4: the right thing. I think the big societal terrifying, world 453 00:24:57,920 --> 00:25:00,480 Speaker 4: ending scenarios, I think maybe we park that and think 454 00:25:00,520 --> 00:25:04,840 Speaker 4: that's science fiction at least for our lifetimes, and hopefully 455 00:25:04,840 --> 00:25:07,280 Speaker 4: otherwise what we're doing sat here talking about it. But 456 00:25:07,400 --> 00:25:10,399 Speaker 4: in terms of the thing that really I find a 457 00:25:10,440 --> 00:25:12,680 Speaker 4: bit frightening at the moment is that it's so unclear 458 00:25:13,040 --> 00:25:16,919 Speaker 4: what the next generation going through high school, going to university, 459 00:25:17,160 --> 00:25:19,119 Speaker 4: how they're going to plot this path over the next 460 00:25:19,240 --> 00:25:21,840 Speaker 4: few years, because they're finishing school and going into a 461 00:25:21,920 --> 00:25:25,520 Speaker 4: workforce when nobody in the workforce even knows what they're 462 00:25:25,560 --> 00:25:27,200 Speaker 4: going to need in the next few years. So how 463 00:25:27,200 --> 00:25:30,720 Speaker 4: they make those decisions going to be really important. But 464 00:25:31,160 --> 00:25:34,040 Speaker 4: you know, there's big opportunities out there as well. I mean, 465 00:25:34,160 --> 00:25:38,399 Speaker 4: there's the scientific breakthroughs that could be made, the environmental breakthroughs, 466 00:25:39,040 --> 00:25:42,120 Speaker 4: but you know overall I'm infuriating on the fence. I'm 467 00:25:42,160 --> 00:25:44,639 Speaker 4: worried about a lot of it. I'm optimistic about a 468 00:25:44,640 --> 00:25:46,800 Speaker 4: lot of it because like everyone else, I just don't 469 00:25:46,800 --> 00:26:00,280 Speaker 4: know how it's all going to end. 470 00:25:50,840 --> 00:26:07,240 Speaker 1: Thank you for listening to The Finn. I'm Lisa Murray 471 00:26:07,280 --> 00:26:12,040 Speaker 1: with Financial Review Technology editor Paul Smith reporting today. The 472 00:26:12,080 --> 00:26:15,879 Speaker 1: Finn is produced by Alex Gau with assistance from Mandy Coolan. 473 00:26:16,280 --> 00:26:20,199 Speaker 1: Fiona Buffini is head of Premium Content. 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