1 00:00:01,430 --> 00:00:09,840 Speaker 1: I'm Daniel James, and you're listening to 7am. In the 2 00:00:09,860 --> 00:00:13,300 Speaker 1: last week, AI bosses around the world have suddenly grown 3 00:00:13,340 --> 00:00:16,900 Speaker 1: a conscience, urging a global slowdown amid fears the race 4 00:00:16,920 --> 00:00:21,190 Speaker 1: to develop artificial intelligence could outstrip humanity's ability to control it. 5 00:00:22,090 --> 00:00:25,490 Speaker 1: For Dex Hunter Torek, that realisation came a little sooner. 6 00:00:25,510 --> 00:00:29,710 Speaker 1: The big tech insider walked away last year. disillusioned after 7 00:00:29,730 --> 00:00:32,809 Speaker 1: spending 15 years inside the belly of the beast. He 8 00:00:32,850 --> 00:00:36,210 Speaker 1: wrote speeches for Mark Zuckerberg at Facebook, worked with Elon 9 00:00:36,250 --> 00:00:40,519 Speaker 1: Musk at SpaceX, and most recently helped Google DeepMind explain 10 00:00:40,540 --> 00:00:44,100 Speaker 1: the rise of artificial intelligence to the world. Now he 11 00:00:44,140 --> 00:00:47,280 Speaker 1: says society is making the same mistakes with AI as 12 00:00:47,320 --> 00:00:50,269 Speaker 1: it did in the social media era, sleepwalking into what 13 00:00:50,330 --> 00:00:54,310 Speaker 1: comes next. Today, founder and president of the Centre for Tomorrow, 14 00:00:54,590 --> 00:00:58,130 Speaker 1: Dex Hunter-Torik. gives us a glimpse inside the big tech 15 00:00:58,170 --> 00:01:12,620 Speaker 1: firms shaping our future. It's Wednesday, September 16. Dex, thanks 16 00:01:12,640 --> 00:01:15,740 Speaker 1: so much for joining us. You spent 15 years helping 17 00:01:15,800 --> 00:01:18,300 Speaker 1: some of the most powerful people in tech sell the 18 00:01:18,319 --> 00:01:21,660 Speaker 1: promise of technology. When did you stop believing technology? 19 00:01:22,530 --> 00:01:26,539 Speaker 2: I've never actually stopped believing in the promise of technology. 20 00:01:26,980 --> 00:01:31,920 Speaker 2: Technology can and should be something deeply hopeful. What I did, though, 21 00:01:31,959 --> 00:01:35,140 Speaker 2: was I stopped believing that a bunch of those leaders, 22 00:01:35,640 --> 00:01:39,289 Speaker 2: a bunch of those companies are configured to really serve 23 00:01:39,730 --> 00:01:42,970 Speaker 2: the interests of most people in our societies or around 24 00:01:42,990 --> 00:01:46,679 Speaker 2: the world. I think, you know, connecting people, that is 25 00:01:46,720 --> 00:01:48,810 Speaker 2: a good thing, but you have to manage it well. 26 00:01:49,330 --> 00:01:51,330 Speaker 2: You get a lot of new challenges that come along 27 00:01:51,370 --> 00:01:55,250 Speaker 2: with building this totally new form of human community in 28 00:01:55,270 --> 00:01:57,550 Speaker 2: the online realm in a world of eight and a 29 00:01:57,550 --> 00:02:00,980 Speaker 2: half billion people at this moment in history. And it 30 00:02:01,020 --> 00:02:05,320 Speaker 2: puts responsibilities on platforms to ensure that they're meeting their 31 00:02:05,360 --> 00:02:09,299 Speaker 2: obligations to protect users, that they're really providing the kind 32 00:02:09,340 --> 00:02:13,889 Speaker 2: of ecosystem in which healthy discourse can unfold. And I 33 00:02:13,930 --> 00:02:17,940 Speaker 2: think after 2016, when we saw the arrival of Donald 34 00:02:18,000 --> 00:02:23,820 Speaker 2: Trump as president, we saw increasing political populism and volatility. 35 00:02:24,220 --> 00:02:28,300 Speaker 2: We saw this huge spike in disinformation, hate speech online. 36 00:02:28,820 --> 00:02:31,540 Speaker 2: And I went on to work after Meta for an 37 00:02:31,580 --> 00:02:35,230 Speaker 2: organization called the Oversight Board. which was a body that 38 00:02:35,250 --> 00:02:38,470 Speaker 2: was set up to actually scrutinize content decisions on Facebook 39 00:02:38,490 --> 00:02:41,089 Speaker 2: and Instagram. And there you really saw at scale all 40 00:02:41,110 --> 00:02:43,690 Speaker 2: the mistakes that meta was making all over the world. 41 00:02:43,730 --> 00:02:45,950 Speaker 2: And it's impossible not to pay attention to that stuff 42 00:02:46,010 --> 00:02:46,570 Speaker 2: once you've seen it. 43 00:02:46,990 --> 00:02:50,190 Speaker 1: Did Mark Zuckerberg and the Facebook execs you worked with 44 00:02:50,540 --> 00:02:53,440 Speaker 1: have any regard for the power they held and some 45 00:02:53,460 --> 00:02:56,419 Speaker 1: of the adverse effects that started to emerge with things 46 00:02:56,460 --> 00:02:59,560 Speaker 1: like addiction and the disinformation that we've seen explode? 47 00:03:00,060 --> 00:03:03,260 Speaker 2: You know, often these were problems that people paid attention to. 48 00:03:03,919 --> 00:03:08,370 Speaker 2: But then there was just a woeful lack of response 49 00:03:09,250 --> 00:03:12,850 Speaker 2: and a lack of investment in truly treating these things 50 00:03:12,990 --> 00:03:16,109 Speaker 2: as the priorities they should have been. Perfect example, right? 51 00:03:16,450 --> 00:03:19,910 Speaker 2: How is it that Facebook 20 plus years later doesn't 52 00:03:19,970 --> 00:03:25,149 Speaker 2: have any effective customer support team or function? Every day 53 00:03:25,190 --> 00:03:28,030 Speaker 2: there are millions of people on Facebook, businesses all over 54 00:03:28,070 --> 00:03:32,030 Speaker 2: the world, communities who have problems with Facebook, and they 55 00:03:32,090 --> 00:03:34,380 Speaker 2: find it impossible to get in touch with a real human. 56 00:03:34,760 --> 00:03:36,740 Speaker 2: at this company, which is one of the world's wealthiest, 57 00:03:37,080 --> 00:03:39,840 Speaker 2: you know, it's absolutely staggering. So for me, even if 58 00:03:39,880 --> 00:03:42,240 Speaker 2: you have leaders who say, yeah, this is a real problem, 59 00:03:42,260 --> 00:03:45,000 Speaker 2: we should solve it, clearly the commitments didn't live up 60 00:03:45,020 --> 00:03:45,680 Speaker 2: to the reality. 61 00:03:50,430 --> 00:03:53,810 Speaker 1: Let's move on to AI, because you joined Google DeepMind 62 00:03:53,950 --> 00:03:58,490 Speaker 1: in 2023, just as ChatGPT had exploded and generative AI 63 00:03:58,530 --> 00:04:02,300 Speaker 1: suddenly became something everyone was talking about. You said you 64 00:04:02,340 --> 00:04:05,580 Speaker 1: were brought back to Google to fix Google's storytelling on AI. 65 00:04:06,100 --> 00:04:08,280 Speaker 1: What was the story Google wanted to tell people about 66 00:04:08,300 --> 00:04:08,840 Speaker 1: what was coming? 67 00:04:10,190 --> 00:04:12,450 Speaker 2: I think all the big tech labs love to tell 68 00:04:12,490 --> 00:04:14,330 Speaker 2: the story. They love telling it up to the present day, 69 00:04:14,730 --> 00:04:18,849 Speaker 2: which is we're inventing this amazing technology which will allow 70 00:04:18,890 --> 00:04:22,349 Speaker 2: us to solve basically all of our problems. For decades, 71 00:04:22,610 --> 00:04:26,520 Speaker 2: mathematicians have been working to solve this problem. They haven't 72 00:04:26,540 --> 00:04:27,230 Speaker 2: been able to crack it. 73 00:04:27,680 --> 00:04:29,719 Speaker 3: But AI, it just did it easily. 74 00:04:30,380 --> 00:04:33,510 Speaker 4: OpenAI sending this out saying we're sharing a solution. 75 00:04:33,589 --> 00:04:36,190 Speaker 2: It doesn't matter what they are, you know, pick the 76 00:04:36,230 --> 00:04:39,179 Speaker 2: most heroic ones because, of course, you know, that's the 77 00:04:39,190 --> 00:04:41,419 Speaker 2: best way to tell a story often. A lot of 78 00:04:41,460 --> 00:04:44,099 Speaker 2: the focus would be on things like science and on 79 00:04:44,160 --> 00:04:46,800 Speaker 2: health care, on medicines. because those are things that are 80 00:04:46,900 --> 00:04:48,490 Speaker 2: really important for people's lives. 81 00:04:48,750 --> 00:04:51,950 Speaker 5: Melbourne researchers have developed a tool to detect the risk 82 00:04:51,990 --> 00:04:55,890 Speaker 5: of breast cancer using an AI algorithm. The breakthrough program 83 00:04:55,950 --> 00:04:56,710 Speaker 5: can provide. 84 00:04:57,070 --> 00:04:58,290 Speaker 2: One out of two of us is going to get 85 00:04:58,330 --> 00:05:01,210 Speaker 2: cancer in our lives. Everybody wants to, you know, live 86 00:05:01,230 --> 00:05:03,260 Speaker 2: in good health for as long as possible. We want 87 00:05:03,300 --> 00:05:05,840 Speaker 2: our children to have healthy lives. If you could use 88 00:05:05,980 --> 00:05:09,860 Speaker 2: AI to discover new drugs that cure cancers, that would 89 00:05:09,880 --> 00:05:12,339 Speaker 2: be a very good thing for the future, right? So 90 00:05:12,440 --> 00:05:14,460 Speaker 2: I think in their minds, that was a story that 91 00:05:14,500 --> 00:05:17,680 Speaker 2: was sufficient to get people excited about the trajectory of 92 00:05:17,700 --> 00:05:20,760 Speaker 2: this technology and all the things they were building. Of course, 93 00:05:20,850 --> 00:05:23,710 Speaker 2: it left out all sorts of other massive questions about 94 00:05:24,110 --> 00:05:26,529 Speaker 2: what does a future shaped by the most powerful technology 95 00:05:26,570 --> 00:05:28,050 Speaker 2: in history really look like? 96 00:05:33,589 --> 00:05:35,210 Speaker 1: That was the story they were telling us. What were 97 00:05:35,230 --> 00:05:39,080 Speaker 1: they telling each other inside these companies about generative AI? 98 00:05:39,440 --> 00:05:42,020 Speaker 2: I mean, in all the companies... The way that the 99 00:05:42,060 --> 00:05:45,180 Speaker 2: last few years has been presented has been as a race. 100 00:05:45,779 --> 00:05:48,099 Speaker 2: It is a race to achieve more and more advanced 101 00:05:48,160 --> 00:05:53,469 Speaker 2: AI against the other companies. So it's OpenAI, Google, Anthropic, 102 00:05:53,770 --> 00:05:56,930 Speaker 2: and so on. But it's also about nations. 103 00:05:57,330 --> 00:05:58,830 Speaker 1: We're leading China in AI. 104 00:05:58,870 --> 00:06:01,190 Speaker 5: We're the most sophisticated country in the world. 105 00:06:01,950 --> 00:06:03,820 Speaker 4: And frankly, I want to keep it that way because 106 00:06:03,860 --> 00:06:05,260 Speaker 4: whoever wins AI wins. 107 00:06:06,080 --> 00:06:09,680 Speaker 2: It's about the ecosystems of the United States. versus China 108 00:06:10,060 --> 00:06:14,320 Speaker 2: competing to be the leaders in global AI without thinking, 109 00:06:14,680 --> 00:06:16,560 Speaker 2: what is this truly in the service of? Is this 110 00:06:16,600 --> 00:06:18,820 Speaker 2: really going to serve the interests of most people, not 111 00:06:18,860 --> 00:06:21,000 Speaker 2: just the few people in these labs and in the 112 00:06:21,040 --> 00:06:21,620 Speaker 2: tech industry? 113 00:06:22,060 --> 00:06:24,479 Speaker 1: You said the way that we talk about governing AI 114 00:06:24,580 --> 00:06:27,620 Speaker 1: is fundamentally broken. So what are governments getting wrong? 115 00:06:28,060 --> 00:06:32,240 Speaker 2: Governments working with big tech have scoped most of the 116 00:06:32,260 --> 00:06:35,720 Speaker 2: problems of AI over the last few years as mostly technical. 117 00:06:36,360 --> 00:06:40,240 Speaker 2: with mostly technical solutions. So for example, this week, there's 118 00:06:40,279 --> 00:06:42,880 Speaker 2: a researcher at Anthropic who's been making global headlines. 119 00:06:43,080 --> 00:06:47,920 Speaker 4: Anthropic AI researcher, Jacob Coxon, who previously worked at OpenAI, 120 00:06:48,400 --> 00:06:51,620 Speaker 4: arguing that both companies are, quote, gambling with our lives. 121 00:06:52,180 --> 00:06:54,850 Speaker 4: But it's this post about his reason for stepping down 122 00:06:54,880 --> 00:06:58,970 Speaker 4: that's going viral, racking up more than 100 million views. 123 00:06:59,410 --> 00:07:02,789 Speaker 4: It reads in part, the people building AI earnestly believe 124 00:07:02,890 --> 00:07:05,210 Speaker 4: it could kill us all by the end of the 125 00:07:05,270 --> 00:07:05,850 Speaker 4: next decade. 126 00:07:06,250 --> 00:07:09,450 Speaker 2: This is nonsense. This is the kind of view that 127 00:07:09,530 --> 00:07:12,970 Speaker 2: comes from organizations where there's a very small number of 128 00:07:13,550 --> 00:07:16,910 Speaker 2: generally young men who are obsessed with science fiction trying 129 00:07:16,930 --> 00:07:19,930 Speaker 2: to peddle their fringe sci-fi thinking and turn that into 130 00:07:19,970 --> 00:07:26,239 Speaker 2: a full-scale agenda for how AI should be managed. Actually, 131 00:07:26,640 --> 00:07:28,680 Speaker 2: the real way we should be thinking about AI and 132 00:07:29,020 --> 00:07:32,500 Speaker 2: the true risks from AI is these are societal challenges 133 00:07:32,640 --> 00:07:36,440 Speaker 2: and societal choices that are at stake. There's no clever 134 00:07:36,600 --> 00:07:39,790 Speaker 2: algorithmic fix that's coming for the fact that AI will 135 00:07:39,890 --> 00:07:42,910 Speaker 2: end up displacing large numbers of jobs. It is not 136 00:07:42,950 --> 00:07:46,290 Speaker 2: a technical problem, the fact that AI is being used 137 00:07:46,330 --> 00:07:48,210 Speaker 2: now to turbocharge warfare. 138 00:07:48,670 --> 00:07:52,010 Speaker 3: Advances in technology are making it possible to develop autonomous 139 00:07:52,050 --> 00:07:55,640 Speaker 3: weapon systems that can pick and attack their targets without 140 00:07:55,700 --> 00:08:00,040 Speaker 3: human guidance. Around 200 autonomous weapon systems have been deployed 141 00:08:00,080 --> 00:08:02,200 Speaker 3: across Ukraine, the Middle East and Africa. 142 00:08:02,840 --> 00:08:05,340 Speaker 2: We are already seeing the huge effects, including in places 143 00:08:05,380 --> 00:08:09,660 Speaker 2: like Australia, of AI on consumption of resources and on 144 00:08:09,680 --> 00:08:11,400 Speaker 2: the environment, on our natural world. 145 00:08:11,500 --> 00:08:15,440 Speaker 6: This forecast from the Australian Energy Market Operator is saying 146 00:08:15,480 --> 00:08:18,960 Speaker 6: that in 10 years' time, these data centres, and there 147 00:08:19,040 --> 00:08:21,680 Speaker 6: are just dozens and dozens of them popping up around 148 00:08:21,720 --> 00:08:27,340 Speaker 6: the country, will consume 13% of the energy supplied into 149 00:08:27,360 --> 00:08:30,220 Speaker 6: the grid, the national electricity market, up from 3%, so 150 00:08:30,240 --> 00:08:30,840 Speaker 6: a massive jump. 151 00:08:33,580 --> 00:08:37,220 Speaker 2: So those are not technical problems. These are really choices 152 00:08:37,240 --> 00:08:40,180 Speaker 2: about how we choose to manage these things, about who's 153 00:08:40,220 --> 00:08:42,800 Speaker 2: paying the bills for these things, how we choose to 154 00:08:42,840 --> 00:08:47,050 Speaker 2: ensure that communities and their interests are respected. It's much 155 00:08:47,130 --> 00:08:49,050 Speaker 2: easier for the tech industry to say, these are all 156 00:08:49,090 --> 00:08:51,449 Speaker 2: technical problems. We can solve that if we just do 157 00:08:51,470 --> 00:08:55,110 Speaker 2: some unspecified things behind the scenes. Because surprise, surprise, that 158 00:08:55,150 --> 00:08:57,750 Speaker 2: puts power back in the hands of those very small 159 00:08:57,790 --> 00:08:58,570 Speaker 2: number of tech labs. 160 00:09:01,950 --> 00:09:13,090 Speaker 1: Still to come. Dex's warning for Australia. Dex, if we 161 00:09:13,110 --> 00:09:15,630 Speaker 1: look at the power balance here, you've worked very closely 162 00:09:15,670 --> 00:09:18,260 Speaker 1: with people running these companies. How much power do a 163 00:09:18,320 --> 00:09:22,080 Speaker 1: very small number of executives actually have over the direction 164 00:09:22,120 --> 00:09:26,059 Speaker 1: this technology takes? And do you think governments are in 165 00:09:26,080 --> 00:09:27,380 Speaker 1: a position to challenge them? 166 00:09:27,720 --> 00:09:30,720 Speaker 2: I think those small number of leaders have a huge 167 00:09:30,760 --> 00:09:33,160 Speaker 2: amount of influence over the technology. I mean, when you 168 00:09:33,200 --> 00:09:35,840 Speaker 2: look at some of the individual leaders, right, you can 169 00:09:36,140 --> 00:09:39,840 Speaker 2: see publicly the kind of capricious decision making by people 170 00:09:39,860 --> 00:09:43,949 Speaker 2: like Elon Musk being turned into product decisions for X 171 00:09:44,179 --> 00:09:46,550 Speaker 2: almost in real time. But, you know, when it comes 172 00:09:46,590 --> 00:09:50,410 Speaker 2: to the power that governments and regulators and communities have 173 00:09:50,570 --> 00:09:52,550 Speaker 2: over all of those companies, I actually think we have 174 00:09:52,570 --> 00:09:56,030 Speaker 2: a tremendous amount of power, much greater power than big tech. 175 00:09:56,390 --> 00:09:59,969 Speaker 2: We've simply chosen in many cases to exaggerate big tech's power. 176 00:10:00,410 --> 00:10:02,820 Speaker 2: or not to exercise the power that we do have. 177 00:10:03,220 --> 00:10:06,540 Speaker 2: Power is ultimately an illusion. It resides where people think 178 00:10:06,580 --> 00:10:09,280 Speaker 2: it resides. For a long time, a lot of political 179 00:10:09,320 --> 00:10:12,620 Speaker 2: leaders have tricked themselves into thinking big tech is untouchable, 180 00:10:12,940 --> 00:10:14,880 Speaker 2: and that's not true at all. They have to work 181 00:10:14,900 --> 00:10:17,630 Speaker 2: with regulators and decision makers all over the world if 182 00:10:17,650 --> 00:10:19,890 Speaker 2: they want to access our markets, if they want to 183 00:10:19,929 --> 00:10:22,750 Speaker 2: comply with regulations so that they can serve users in 184 00:10:22,790 --> 00:10:25,370 Speaker 2: lots of communities, if they want to work with advertisers 185 00:10:25,470 --> 00:10:28,050 Speaker 2: and partners. Ultimately, we've just got to be tougher in 186 00:10:28,150 --> 00:10:30,010 Speaker 2: asking for the things that we want to see reflected. 187 00:10:30,450 --> 00:10:32,950 Speaker 1: You say society is at risk of making the same 188 00:10:32,990 --> 00:10:36,990 Speaker 1: mistakes with AI as it did in the social media era. 189 00:10:37,610 --> 00:10:38,610 Speaker 1: What do you mean by that, Dex? 190 00:10:39,010 --> 00:10:41,970 Speaker 2: Well, here's the question. We're now more than a decade 191 00:10:42,010 --> 00:10:45,150 Speaker 2: and a half into the social media boom. I think 192 00:10:45,170 --> 00:10:47,949 Speaker 2: we've had just more time to learn how is social 193 00:10:47,990 --> 00:10:50,900 Speaker 2: media working and how is it not working, we have 194 00:10:50,980 --> 00:10:54,339 Speaker 2: spent years arguing over social media before we then very 195 00:10:54,420 --> 00:10:57,319 Speaker 2: quickly brought in these age restrictions for young people on 196 00:10:57,380 --> 00:11:00,339 Speaker 2: social media. Things which, in many cases, have yet to 197 00:11:00,380 --> 00:11:05,230 Speaker 2: be enforced well, so they are imperfect regulations. Nobody, or 198 00:11:05,260 --> 00:11:07,709 Speaker 2: very few people certainly that I'm aware of, have made 199 00:11:07,750 --> 00:11:11,010 Speaker 2: the case yet for, should we be exploring having age 200 00:11:11,070 --> 00:11:16,030 Speaker 2: restrictions on generative AI for young people? if you concede 201 00:11:16,110 --> 00:11:18,940 Speaker 2: that AI is going to be the most powerful technology ever, 202 00:11:19,280 --> 00:11:21,840 Speaker 2: this could have huge effects on the way young people think, 203 00:11:22,120 --> 00:11:24,640 Speaker 2: the way their brains develop, the way they process information, 204 00:11:24,679 --> 00:11:27,760 Speaker 2: the way they learn. Should we be just letting a 205 00:11:27,780 --> 00:11:30,469 Speaker 2: whole generation be guinea pigs for these tools, or should 206 00:11:30,490 --> 00:11:33,650 Speaker 2: we proactively bring in those restrictions now and then try 207 00:11:33,670 --> 00:11:35,870 Speaker 2: to understand what the effects are before we simply open 208 00:11:35,910 --> 00:11:36,390 Speaker 2: the floodgates? 209 00:11:37,030 --> 00:11:40,590 Speaker 1: Australia is actively courting the same AI companies you used 210 00:11:40,630 --> 00:11:44,010 Speaker 1: to work for. What should our government be demanding from 211 00:11:44,050 --> 00:11:48,449 Speaker 1: them before that technology becomes deeply embedded here, particularly given 212 00:11:48,890 --> 00:11:52,829 Speaker 1: we're talking about a handful of foreign companies that may 213 00:11:52,929 --> 00:11:55,310 Speaker 1: actually impact our national sovereignty? 214 00:11:56,150 --> 00:12:00,480 Speaker 2: I think government should be absolutely demanding transparency in how 215 00:12:00,510 --> 00:12:05,720 Speaker 2: their systems are operating, the things that will impact our lives, communities, 216 00:12:05,780 --> 00:12:09,360 Speaker 2: the interests of our communities in which this tech will 217 00:12:09,380 --> 00:12:13,240 Speaker 2: be operating. I think absolutely everything Governments should be also 218 00:12:13,340 --> 00:12:16,340 Speaker 2: shopping around. It is a true buyer's market. It is 219 00:12:16,380 --> 00:12:18,580 Speaker 2: an era in which the technology is being commoditized very, 220 00:12:18,620 --> 00:12:22,110 Speaker 2: very rapidly. When governments get obsessed with trying to cut 221 00:12:22,150 --> 00:12:25,860 Speaker 2: deals with just a very small number of hyperscalers, going 222 00:12:25,900 --> 00:12:30,220 Speaker 2: for these multi-billion dollar commitments in spending. These are things 223 00:12:30,260 --> 00:12:33,180 Speaker 2: where I think there's actually a massive global ecosystem out there. 224 00:12:33,210 --> 00:12:36,170 Speaker 2: There's plenty of other companies, there's plenty of great Australian 225 00:12:36,250 --> 00:12:39,630 Speaker 2: startups and companies who are building great bits of technology, 226 00:12:39,870 --> 00:12:41,709 Speaker 2: which in many cases are free from the kind of 227 00:12:41,770 --> 00:12:45,410 Speaker 2: baggage that comes from US big tech. So these are 228 00:12:45,470 --> 00:12:48,000 Speaker 2: all some of the big strategic questions. There's obviously a 229 00:12:48,010 --> 00:12:55,510 Speaker 2: whole lot of very practical questions around things like data sovereignty, privacy, security, IP, infrastructure. 230 00:12:56,250 --> 00:12:58,890 Speaker 2: But certainly, I think in general, decision makers should be 231 00:12:58,950 --> 00:13:01,810 Speaker 2: pretty tough in saying that we need you to abide 232 00:13:01,850 --> 00:13:03,570 Speaker 2: by certain things if you want to serve us. And 233 00:13:03,610 --> 00:13:05,980 Speaker 2: if you can't reach agreement on those, it's okay. You 234 00:13:06,010 --> 00:13:07,560 Speaker 2: can go your own way and we'll do business with 235 00:13:07,580 --> 00:13:10,320 Speaker 2: somebody else who respects our values and our interests. 236 00:13:11,200 --> 00:13:14,300 Speaker 1: And finally, Dex, you spent years helping these companies tell 237 00:13:14,340 --> 00:13:16,990 Speaker 1: us what the future could look like. You've said too 238 00:13:17,040 --> 00:13:19,710 Speaker 1: few people have a say in helping shape that future. 239 00:13:20,380 --> 00:13:23,070 Speaker 1: So how do we give workers and ordinary people a 240 00:13:23,170 --> 00:13:27,170 Speaker 1: real say in how AI changes their jobs and their lives? 241 00:13:27,809 --> 00:13:32,610 Speaker 2: I would like to see every decision maker, every leader 242 00:13:33,210 --> 00:13:37,119 Speaker 2: have a genuine open conversation now, put their cards on 243 00:13:37,140 --> 00:13:39,860 Speaker 2: the table about what they think is going to happen 244 00:13:39,900 --> 00:13:43,760 Speaker 2: with AI. AI is still largely a very elite conversation. 245 00:13:43,820 --> 00:13:45,780 Speaker 2: It's not a thing I think most people are talking about. 246 00:13:46,140 --> 00:13:47,970 Speaker 2: People will sort of hear the headlines and think, oh, 247 00:13:48,070 --> 00:13:51,580 Speaker 2: there's some stuff in the news. Every big tech leader 248 00:13:52,260 --> 00:13:55,590 Speaker 2: premises the vision of this AI future on the idea 249 00:13:55,630 --> 00:13:58,230 Speaker 2: that AI will make us all much wealthier. The world 250 00:13:58,250 --> 00:14:01,530 Speaker 2: will become more prosperous, economies will grow, there'll be more jobs. 251 00:14:01,910 --> 00:14:04,230 Speaker 2: Lots of people don't believe it. I'm very skeptical that's 252 00:14:04,270 --> 00:14:06,550 Speaker 2: how it will unfold in the current way it's being organized. 253 00:14:06,820 --> 00:14:09,500 Speaker 2: But certainly, if your vision is that this will help 254 00:14:09,540 --> 00:14:13,320 Speaker 2: grow Australia's economy, then as a country, as communities, we 255 00:14:13,380 --> 00:14:16,140 Speaker 2: should get a question asked. What do we want to 256 00:14:16,179 --> 00:14:18,900 Speaker 2: do with all that wealth? How should we be using it? 257 00:14:19,210 --> 00:14:21,030 Speaker 2: What should we be allocating it for? How should it 258 00:14:21,050 --> 00:14:25,390 Speaker 2: be distributed? And so fundamentally, there are massive choices now 259 00:14:25,410 --> 00:14:29,080 Speaker 2: about our futures, about our children's futures. And we've got 260 00:14:29,140 --> 00:14:30,860 Speaker 2: very little time in which we might get to make 261 00:14:30,900 --> 00:14:33,680 Speaker 2: some very big choices about what kind of country we 262 00:14:33,700 --> 00:14:35,680 Speaker 2: want to live in, what kind of people do we 263 00:14:35,720 --> 00:14:38,180 Speaker 2: want to become in the future. And so this is 264 00:14:38,220 --> 00:14:40,360 Speaker 2: genuinely a conversation. We've just got to have it. Somebody 265 00:14:40,400 --> 00:14:43,080 Speaker 2: has to lead it. Um, and I think, um, anyone 266 00:14:43,100 --> 00:14:45,220 Speaker 2: who can help shape that and open it up, I 267 00:14:45,240 --> 00:14:46,860 Speaker 2: think has a responsibility to do that. 268 00:14:47,620 --> 00:14:49,640 Speaker 1: How much time do we have to have that conversation? 269 00:14:50,200 --> 00:14:53,820 Speaker 2: We have very little time for it because of course, uh, every, 270 00:14:54,380 --> 00:14:56,780 Speaker 2: you know, major AI lab will tell you, and I 271 00:14:56,860 --> 00:14:59,060 Speaker 2: do agree with them on this, that we will arrive 272 00:14:59,100 --> 00:15:02,800 Speaker 2: at a much more advanced form of AI, artificial general intelligence, 273 00:15:03,020 --> 00:15:07,120 Speaker 2: essentially human level intelligence and machines sometime in the next 274 00:15:07,120 --> 00:15:11,600 Speaker 2: 10 years. Most of those leaders believe it could be 275 00:15:11,620 --> 00:15:15,330 Speaker 2: closer to five years from now. OpenAI's leadership has just 276 00:15:15,350 --> 00:15:17,770 Speaker 2: been signaling in the last few days they believe they 277 00:15:17,790 --> 00:15:20,850 Speaker 2: may have already achieved it. Lots of disagreement about that. 278 00:15:21,170 --> 00:15:24,270 Speaker 2: Many people, including myself, think that's just marketing hype. And yet, 279 00:15:24,730 --> 00:15:28,800 Speaker 2: when that arrives, if we have not fundamentally reassessed some 280 00:15:28,820 --> 00:15:32,220 Speaker 2: of our thinking about our economies, about our societies, about 281 00:15:32,240 --> 00:15:35,660 Speaker 2: our institutions, our governance, then we will be out of 282 00:15:35,720 --> 00:15:38,490 Speaker 2: time and the technology will end up deciding for us. 283 00:15:38,850 --> 00:15:41,510 Speaker 2: Which is exactly what happened with social media when we 284 00:15:41,610 --> 00:15:44,790 Speaker 2: sleepwalked through a whole generation of technology, but we hadn't 285 00:15:44,850 --> 00:15:47,710 Speaker 2: taken it seriously before we entered that new era. And 286 00:15:47,770 --> 00:15:49,440 Speaker 2: I just don't want us to make that same mistake again. 287 00:15:52,210 --> 00:15:54,370 Speaker 1: Well, Dex, we're out of time for this conversation, but 288 00:15:54,430 --> 00:15:55,450 Speaker 1: thank you so much for yours. 289 00:15:55,870 --> 00:15:56,470 Speaker 2: Thanks for having me. 290 00:15:58,810 --> 00:16:02,650 Speaker 1: Dex Hunter-Torrick has been in Australia for the Philanthropy Australia Conference. 291 00:16:14,820 --> 00:16:17,680 Speaker 1: Also in the news, Pauline Hanson has offered a half 292 00:16:17,740 --> 00:16:22,120 Speaker 1: apology for her comments describing Indigenous Australians as primitive. saying 293 00:16:22,180 --> 00:16:24,460 Speaker 1: she's sorry if she's offended people. 294 00:16:25,280 --> 00:16:27,750 Speaker 5: We need to be united as a nation and stop 295 00:16:27,760 --> 00:16:29,490 Speaker 5: the division that's happening by politicians. 296 00:16:29,510 --> 00:16:31,890 Speaker 1: But the argument is that you're worsening it by saying 297 00:16:31,930 --> 00:16:34,510 Speaker 1: things like that they were the most primitive race on 298 00:16:34,570 --> 00:16:35,450 Speaker 1: earth at the time. 299 00:16:35,910 --> 00:16:39,170 Speaker 6: That that upsets a lot of Indigenous Australians. 300 00:16:40,030 --> 00:16:43,720 Speaker 5: I don't... Well, then I regret saying that because I 301 00:16:43,760 --> 00:16:48,480 Speaker 5: don't want to upset people. That's not my intentions. That 302 00:16:48,500 --> 00:16:50,440 Speaker 5: wasn't my intentions to hurt people. 303 00:16:51,000 --> 00:16:53,680 Speaker 1: Hanson also offered a half apology to the Prime Minister, 304 00:16:54,120 --> 00:16:56,880 Speaker 1: if he's taken offence, to her comments about his mum 305 00:16:57,320 --> 00:17:02,270 Speaker 1: living in a housing commission. Gold Coast Mayor Tom Tate 306 00:17:02,470 --> 00:17:04,450 Speaker 1: has sworn at a journalist and stormed out of a 307 00:17:04,510 --> 00:17:07,430 Speaker 1: press conference and made questions over a dinner he claims 308 00:17:07,470 --> 00:17:09,630 Speaker 1: to have had with Donald Trump earlier this year. 309 00:17:10,030 --> 00:17:11,109 Speaker 5: Why are you so aggressive? 310 00:17:11,130 --> 00:17:11,730 Speaker 1: Are you from the ABC? 311 00:17:11,790 --> 00:17:11,889 Speaker 2: Yes. 312 00:17:11,990 --> 00:17:12,310 Speaker 6: Yeah, f * * * off. 313 00:17:12,330 --> 00:17:12,960 Speaker 1: Excuse me? 314 00:17:12,970 --> 00:17:16,780 Speaker 2: F * * * off. I'm serious. I'm serious. 315 00:17:18,410 --> 00:17:20,990 Speaker 1: A statement from the Trump organisation claims the mayor's account 316 00:17:21,010 --> 00:17:24,980 Speaker 1: of what occurred is a complete fabrication. I'm Daniel James. 317 00:17:25,000 --> 00:17:27,760 Speaker 1: Thanks for listening to 7am. We'll be back tomorrow.