1 00:00:00,000 --> 00:00:03,160 All right, so get this, we're going deep on AI 2 00:00:03,160 --> 00:00:04,720 and the future of finance. 3 00:00:04,720 --> 00:00:07,920 Yeah, and everyone's kind of freaking out about it, right? 4 00:00:07,920 --> 00:00:11,640 Exactly, like will robots be managing our 401Ks? 5 00:00:11,640 --> 00:00:12,520 Uh-huh, right. 6 00:00:12,520 --> 00:00:15,200 And lucky for us, we've got this interview 7 00:00:15,200 --> 00:00:17,040 with MIT professor Andrew Lowe, 8 00:00:17,040 --> 00:00:20,600 he's like the E guy on this. 9 00:00:20,600 --> 00:00:22,720 Oh yeah, he knows his stuff for sure. 10 00:00:22,720 --> 00:00:24,560 So he actually thinks we're on the verge 11 00:00:24,560 --> 00:00:26,160 of a financial revolution. 12 00:00:26,160 --> 00:00:28,800 Whoa, a revolution, like what does that even mean? 13 00:00:28,800 --> 00:00:31,280 Well, think about this, he says these LLMs, 14 00:00:31,280 --> 00:00:33,840 those are the big AI brains everyone's talking about. 15 00:00:33,840 --> 00:00:34,680 Right. 16 00:00:34,680 --> 00:00:37,440 They can analyze those crazy financial reports, 17 00:00:37,440 --> 00:00:38,840 you know, the ones that put you to sleep. 18 00:00:38,840 --> 00:00:40,040 Oh yeah, the ones I pretend to read. 19 00:00:40,040 --> 00:00:41,320 Ha ha, exactly. 20 00:00:41,320 --> 00:00:44,000 Okay, but AI can actually understand those. 21 00:00:44,000 --> 00:00:46,440 Apparently way faster than any human team 22 00:00:46,440 --> 00:00:48,960 and they can spot all sorts of stuff, 23 00:00:48,960 --> 00:00:51,920 like hidden risks or even get this, 24 00:00:51,920 --> 00:00:54,120 market patterns that we totally miss. 25 00:00:54,120 --> 00:00:56,000 So it's like having a super powered stockbroker 26 00:00:56,000 --> 00:00:56,760 in your pocket. 27 00:00:56,760 --> 00:00:58,200 Kinda, but there's a catch. 28 00:00:58,200 --> 00:00:59,360 Oh, there's always a catch. 29 00:00:59,360 --> 00:01:02,840 Right, so these LLMs, they can sometimes see things 30 00:01:02,840 --> 00:01:04,000 that aren't really there. 31 00:01:04,000 --> 00:01:06,240 Wait, what, like they imagine stuff? 32 00:01:06,240 --> 00:01:08,160 It's called hallucinating. 33 00:01:08,160 --> 00:01:12,280 Hallucinating, that sounds a little unsettling, 34 00:01:12,280 --> 00:01:13,480 especially when it comes to my money. 35 00:01:13,480 --> 00:01:14,560 I know, right? 36 00:01:14,560 --> 00:01:17,880 So how do we trust these things with our hard earned cash 37 00:01:17,880 --> 00:01:20,160 if they're seeing ghosts in the data? 38 00:01:20,160 --> 00:01:22,600 That's a good question, maybe they need AI therapy. 39 00:01:22,600 --> 00:01:24,560 Ha ha, maybe. 40 00:01:24,560 --> 00:01:26,880 But professor Lowe's team is actually working 41 00:01:26,880 --> 00:01:29,360 on something called fiduciary AI. 42 00:01:29,360 --> 00:01:31,480 Fiduciary AI, huh? 43 00:01:31,480 --> 00:01:32,320 Sounds fancy. 44 00:01:32,320 --> 00:01:33,840 Well, it's a big deal in finance. 45 00:01:33,840 --> 00:01:38,280 It basically means putting the client's interests first. 46 00:01:38,280 --> 00:01:41,320 Oh, like a financial advisor who actually cares about you, 47 00:01:41,320 --> 00:01:42,320 not just their commission. 48 00:01:42,320 --> 00:01:44,880 Exactly, and they're trying to teach these AI's 49 00:01:44,880 --> 00:01:46,240 to be like that. 50 00:01:46,240 --> 00:01:48,640 So how do you teach an AI to be ethical? 51 00:01:48,640 --> 00:01:50,200 It's pretty wild, they're feeding it, 52 00:01:50,200 --> 00:01:53,400 not just market data, but like the whole history 53 00:01:53,400 --> 00:01:54,480 of financial law. 54 00:01:54,480 --> 00:01:57,080 Whoa, like all the ways people have tried to cheat the system? 55 00:01:57,080 --> 00:02:00,480 Yep, all the shady stuff, so the AI can learn what not to do. 56 00:02:00,480 --> 00:02:03,480 Ha ha, so it's like giving the AI a crash course 57 00:02:03,480 --> 00:02:04,400 in financial crime. 58 00:02:04,400 --> 00:02:06,720 Exactly, so hopefully it learns to be the good guy. 59 00:02:06,720 --> 00:02:08,840 Wow, that's reassuring, but this is all 60 00:02:08,840 --> 00:02:10,440 still pretty experimental, right? 61 00:02:10,440 --> 00:02:13,360 Definitely, we're not going to have robot financial advisors 62 00:02:13,360 --> 00:02:14,920 giving us stock tips tomorrow. 63 00:02:14,920 --> 00:02:16,760 OK, good, because I'm not sure I'm ready for that yet. 64 00:02:16,760 --> 00:02:19,840 Me neither, but it's definitely something to think about. 65 00:02:19,840 --> 00:02:21,720 You know, what's really got me thinking 66 00:02:21,720 --> 00:02:25,320 is this whole thing about AI and risk management? 67 00:02:25,320 --> 00:02:26,280 Yeah, that's a big one. 68 00:02:26,280 --> 00:02:28,280 Like imagine an AI that could actually 69 00:02:28,280 --> 00:02:30,280 explain your risk to you. 70 00:02:30,280 --> 00:02:32,880 Not just spit out numbers, but like tell your story. 71 00:02:32,880 --> 00:02:35,320 Right, like hey, if the market crashes, 72 00:02:35,320 --> 00:02:37,280 here's what could happen to your portfolio 73 00:02:37,280 --> 00:02:38,720 and here's what you can do about it. 74 00:02:38,720 --> 00:02:41,640 Exactly, and not in some jargon-filled report, 75 00:02:41,640 --> 00:02:42,640 but in plain English. 76 00:02:42,640 --> 00:02:44,640 Yeah, like a financial therapist who also 77 00:02:44,640 --> 00:02:45,760 understands the market. 78 00:02:45,760 --> 00:02:48,520 Ha ha, I like that. 79 00:02:48,520 --> 00:02:50,360 And speaking of feelings, Professor Lowe's 80 00:02:50,360 --> 00:02:53,800 work on sentiment analysis is pretty mind-blowing. 81 00:02:53,800 --> 00:02:57,600 Oh yeah, the whole AI reading the market's emotions thing. 82 00:02:57,600 --> 00:03:01,440 Right, like is the market feeling greedy today or fearful? 83 00:03:01,440 --> 00:03:04,000 And it does that by analyzing news and social media. 84 00:03:04,000 --> 00:03:06,600 Exactly, it's picking up on the vibes, the whispers, 85 00:03:06,600 --> 00:03:07,360 the rumors. 86 00:03:07,360 --> 00:03:10,800 So it's like AI is eavesdropping on the market's gossip. 87 00:03:10,800 --> 00:03:12,600 Uh-huh, kinda. 88 00:03:12,600 --> 00:03:15,320 Even fake news can move markets, and AI 89 00:03:15,320 --> 00:03:17,840 could potentially spot those trends before they blow up. 90 00:03:17,840 --> 00:03:20,880 Do you think those big hedge funds are already using this? 91 00:03:20,880 --> 00:03:22,400 Honestly, I wouldn't be surprised. 92 00:03:22,400 --> 00:03:23,160 Me neither. 93 00:03:23,160 --> 00:03:25,880 But Professor Lowe seems to think this tech will eventually 94 00:03:25,880 --> 00:03:27,680 be available to everyone. 95 00:03:27,680 --> 00:03:29,400 That would be a game changer for sure. 96 00:03:29,400 --> 00:03:32,600 Imagine having the same intel as the Wall Street bigwigs. 97 00:03:32,600 --> 00:03:34,240 Yeah, that'd be pretty sweet. 98 00:03:34,240 --> 00:03:36,280 But of course, there's got to be a downside, right? 99 00:03:36,280 --> 00:03:37,720 It's always, right. 100 00:03:37,720 --> 00:03:40,720 Professor Lowe keeps stressing we need more regulation, 101 00:03:40,720 --> 00:03:41,800 like yesterday. 102 00:03:41,800 --> 00:03:42,360 Why is that? 103 00:03:42,360 --> 00:03:46,000 He's worried about an AI arms race, basically. 104 00:03:46,000 --> 00:03:49,600 The bad guys using AI to gain the system even harder. 105 00:03:49,600 --> 00:03:52,320 Oh, like AI that helps you cheat on your taxes? 106 00:03:52,320 --> 00:03:53,440 Exactly. 107 00:03:53,440 --> 00:03:54,800 Or even worse stuff. 108 00:03:54,800 --> 00:03:58,480 So it's like a constant battle, the good AI versus the bad AI. 109 00:03:58,480 --> 00:04:00,280 And we need to make sure the good guys win. 110 00:04:00,280 --> 00:04:02,480 Well, that sounds like a good cliffhanger for part two, 111 00:04:02,480 --> 00:04:03,120 don't you think? 112 00:04:03,120 --> 00:04:04,360 Yeah, definitely. 113 00:04:04,360 --> 00:04:05,840 More AI adventures to come. 114 00:04:05,840 --> 00:04:07,120 Stay tuned, folks. 115 00:04:07,120 --> 00:04:08,320 We'll be right back. 116 00:04:08,320 --> 00:04:11,080 OK, so back to AI in finance. 117 00:04:11,080 --> 00:04:12,200 Right, where we left off? 118 00:04:12,200 --> 00:04:14,400 Yeah, remember that whole AI arms race thing? 119 00:04:14,400 --> 00:04:17,360 Uh-oh, the good AI versus the bad AI. 120 00:04:17,360 --> 00:04:18,280 Who's winning? 121 00:04:18,280 --> 00:04:21,120 Well, Professor Lowe says we need to think about regulation, 122 00:04:21,120 --> 00:04:22,480 like yesterday. 123 00:04:22,480 --> 00:04:24,240 But wouldn't that stifle innovation 124 00:04:24,240 --> 00:04:26,720 like hold back all the cool AI stuff? 125 00:04:26,720 --> 00:04:28,960 He says it's about finding the right balance. 126 00:04:28,960 --> 00:04:30,600 OK, easier said than done. 127 00:04:30,600 --> 00:04:32,000 Right, but he makes a good point. 128 00:04:32,000 --> 00:04:34,800 If we don't set some ground rules now, 129 00:04:34,800 --> 00:04:36,480 things could get out of control later. 130 00:04:36,480 --> 00:04:37,000 That's true. 131 00:04:37,000 --> 00:04:38,720 Like with any new tech, they're always 132 00:04:38,720 --> 00:04:40,600 going to be unintended consequences. 133 00:04:40,600 --> 00:04:41,200 Exactly. 134 00:04:41,200 --> 00:04:44,320 So it's better to be proactive than reactive. 135 00:04:44,320 --> 00:04:45,400 I guess that makes sense. 136 00:04:45,400 --> 00:04:48,000 But what kind of regulations are we even talking about? 137 00:04:48,000 --> 00:04:50,000 Well, he throws out a few ideas. 138 00:04:50,000 --> 00:04:52,200 First off, clear ethical guidelines 139 00:04:52,200 --> 00:04:54,480 for how AI is developed and used. 140 00:04:54,480 --> 00:04:57,280 So like a code of conduct for AI? 141 00:04:57,280 --> 00:05:01,120 Yeah, basically making sure AI aligns with our values, 142 00:05:01,120 --> 00:05:02,760 you know, like fairness, transparency, 143 00:05:02,760 --> 00:05:03,360 all that good stuff. 144 00:05:03,360 --> 00:05:04,520 OK, I can get behind that. 145 00:05:04,520 --> 00:05:04,920 Right. 146 00:05:04,920 --> 00:05:07,040 And then he's big on data privacy. 147 00:05:07,040 --> 00:05:09,400 Oh, yeah, that's a hot topic these days. 148 00:05:09,400 --> 00:05:09,800 Definitely. 149 00:05:09,800 --> 00:05:12,080 So he's saying individuals should have control 150 00:05:12,080 --> 00:05:13,720 over their own financial data. 151 00:05:13,720 --> 00:05:17,000 Like the right to know how it's being used, 152 00:05:17,000 --> 00:05:19,120 who has access to it, all that. 153 00:05:19,120 --> 00:05:19,600 Exactly. 154 00:05:19,600 --> 00:05:20,720 And the right to say no. 155 00:05:20,720 --> 00:05:22,320 OK, I can see why that's important, 156 00:05:22,320 --> 00:05:24,240 especially with all the data breaches happening. 157 00:05:24,240 --> 00:05:24,880 Right. 158 00:05:24,880 --> 00:05:27,000 And then finally, he talks about the need 159 00:05:27,000 --> 00:05:30,160 for constant monitoring, auditing these AI systems. 160 00:05:30,160 --> 00:05:32,960 So like making sure they're not going rogue. 161 00:05:32,960 --> 00:05:33,560 Pretty much. 162 00:05:33,560 --> 00:05:38,280 Looking for any bias, errors, or unexpected consequences. 163 00:05:38,280 --> 00:05:41,200 It's like we need AI police, making sure everything's 164 00:05:41,200 --> 00:05:42,280 running smoothly. 165 00:05:42,280 --> 00:05:44,640 Uh-huh, maybe. 166 00:05:44,640 --> 00:05:47,520 But seriously, we need some kind of oversight 167 00:05:47,520 --> 00:05:48,880 to keep things in check. 168 00:05:48,880 --> 00:05:49,400 I agree. 169 00:05:49,400 --> 00:05:51,640 It's like we're giving these AI so much power, 170 00:05:51,640 --> 00:05:53,720 we got to make sure they're using it for good. 171 00:05:53,720 --> 00:05:54,400 Exactly. 172 00:05:54,400 --> 00:05:56,520 And that brings us back to that whole job thing. 173 00:05:56,520 --> 00:05:57,120 Oh, yeah. 174 00:05:57,120 --> 00:05:59,000 Will robots be taking our jobs? 175 00:05:59,000 --> 00:06:01,440 Well, Professor Lowe says some jobs will definitely 176 00:06:01,440 --> 00:06:03,320 be automated, especially the ones that 177 00:06:03,320 --> 00:06:06,480 involve lots of repetitive tasks or data crunching. 178 00:06:06,480 --> 00:06:09,240 So like accountants and analysts might be out of luck. 179 00:06:09,240 --> 00:06:10,400 Maybe. 180 00:06:10,400 --> 00:06:13,760 But he's also optimistic that AI will create new jobs 181 00:06:13,760 --> 00:06:16,720 in areas like AI development, data security, stuff like that. 182 00:06:16,720 --> 00:06:18,280 OK, so it's not all doom and gloom. 183 00:06:18,280 --> 00:06:18,560 Right. 184 00:06:18,560 --> 00:06:21,480 It's more like a shift we got to adapt and learn new skills. 185 00:06:21,480 --> 00:06:23,880 Easier said than done for some people, though. 186 00:06:23,880 --> 00:06:24,280 True. 187 00:06:24,280 --> 00:06:26,640 And that's where education and retraining come in. 188 00:06:26,640 --> 00:06:29,280 So like going back to school to learn how to code? 189 00:06:29,280 --> 00:06:29,960 Maybe. 190 00:06:29,960 --> 00:06:31,880 But Professor Lowe thinks AI can actually 191 00:06:31,880 --> 00:06:32,640 help with that too. 192 00:06:32,640 --> 00:06:35,200 Like personalized learning programs 193 00:06:35,200 --> 00:06:36,440 tailor to your needs. 194 00:06:36,440 --> 00:06:40,400 Whoa, AI teaching is how to survive in the AI world. 195 00:06:40,400 --> 00:06:41,760 Kind of meta, right? 196 00:06:41,760 --> 00:06:42,120 Yeah. 197 00:06:42,120 --> 00:06:42,840 But it makes sense. 198 00:06:42,840 --> 00:06:45,880 AI can analyze your skills, your strengths, 199 00:06:45,880 --> 00:06:47,360 and point you in the right direction. 200 00:06:47,360 --> 00:06:48,440 OK, that's actually pretty cool. 201 00:06:48,440 --> 00:06:49,680 I could see that being helpful. 202 00:06:49,680 --> 00:06:51,880 Yeah, it's like having a career coach who also 203 00:06:51,880 --> 00:06:53,240 happens to be a supercomputer. 204 00:06:53,240 --> 00:06:54,640 Uh-huh, I like that. 205 00:06:54,640 --> 00:06:56,600 But even with all the new jobs and training, 206 00:06:56,600 --> 00:06:58,640 there's still going to be some bumps on the road. 207 00:06:58,640 --> 00:07:00,600 Yeah, people are going to lose their jobs. 208 00:07:00,600 --> 00:07:01,920 And that's a tough reality. 209 00:07:01,920 --> 00:07:02,440 Definitely. 210 00:07:02,440 --> 00:07:04,120 And Professor Lowe acknowledges that. 211 00:07:04,120 --> 00:07:08,280 He says, policymakers need to step up and provide support. 212 00:07:08,280 --> 00:07:11,840 Things like job training programs, social safety nets. 213 00:07:11,840 --> 00:07:13,040 So it's not just about the tech. 214 00:07:13,040 --> 00:07:14,440 It's about the people too. 215 00:07:14,440 --> 00:07:15,040 Exactly. 216 00:07:15,040 --> 00:07:17,560 We've got to make sure everyone benefits from this AI 217 00:07:17,560 --> 00:07:20,080 revolution, not just the tech giants. 218 00:07:20,080 --> 00:07:20,360 Right. 219 00:07:20,360 --> 00:07:22,920 It's about creating a more equitable future for all. 220 00:07:22,920 --> 00:07:23,480 Exactly. 221 00:07:23,480 --> 00:07:25,960 And that brings us to another big question. 222 00:07:25,960 --> 00:07:30,440 How will AI actually impact our everyday financial lives? 223 00:07:30,440 --> 00:07:32,080 OK, now we're getting to the good stuff, 224 00:07:32,080 --> 00:07:34,320 the stuff that affects our wallets. 225 00:07:34,320 --> 00:07:35,080 Right. 226 00:07:35,080 --> 00:07:37,840 So Professor Lowe thinks AI has the potential 227 00:07:37,840 --> 00:07:41,640 to personalize financial services like never before. 228 00:07:41,640 --> 00:07:44,240 Like those robo-advisors everyone's talking about. 229 00:07:44,240 --> 00:07:46,160 Yeah, but think even more personalized, 230 00:07:46,160 --> 00:07:49,400 like an AI that not only knows your financial data, 231 00:07:49,400 --> 00:07:53,480 but also understands your risk tolerance, your goals, 232 00:07:53,480 --> 00:07:55,760 even your emotional triggers when it comes to money. 233 00:07:55,760 --> 00:07:59,760 OK, now that's a little creepy, like AI reading my mind. 234 00:07:59,760 --> 00:08:00,560 Right. 235 00:08:00,560 --> 00:08:02,040 But it could also be super helpful. 236 00:08:02,040 --> 00:08:04,880 Imagine an AI that nudges you to save more 237 00:08:04,880 --> 00:08:07,240 when you're about to splurge on something you don't need. 238 00:08:07,240 --> 00:08:09,200 Or one that warns you about risky investments 239 00:08:09,200 --> 00:08:10,520 that you're emotionally attached to. 240 00:08:10,520 --> 00:08:11,040 Exactly. 241 00:08:11,040 --> 00:08:13,600 It's like having a personal finance guru in your pocket. 242 00:08:13,600 --> 00:08:15,080 I guess that could be pretty awesome. 243 00:08:15,080 --> 00:08:16,400 But again, what about privacy? 244 00:08:16,400 --> 00:08:17,080 Good point. 245 00:08:17,080 --> 00:08:18,960 Professor Lowe emphasizes the importance 246 00:08:18,960 --> 00:08:20,560 of transparency and control. 247 00:08:20,560 --> 00:08:23,720 Like you should always know how AI is being used 248 00:08:23,720 --> 00:08:26,000 and be able to opt out if you're not comfortable. 249 00:08:26,000 --> 00:08:27,920 So it's all about having choices, 250 00:08:27,920 --> 00:08:30,240 not being forced into using AI. 251 00:08:30,240 --> 00:08:30,740 Right. 252 00:08:30,740 --> 00:08:32,640 It's about empowering individuals, giving them 253 00:08:32,640 --> 00:08:35,360 the tools to make informed decisions. 254 00:08:35,360 --> 00:08:36,040 Makes sense. 255 00:08:36,040 --> 00:08:37,840 But let's be real, most people don't even 256 00:08:37,840 --> 00:08:39,760 read those long privacy policies. 257 00:08:39,760 --> 00:08:40,280 True. 258 00:08:40,280 --> 00:08:42,400 That's why we need clear regulations and easy 259 00:08:42,400 --> 00:08:43,680 to understand explanations. 260 00:08:43,680 --> 00:08:45,680 OK, so back to regulation again. 261 00:08:45,680 --> 00:08:47,200 Yeah, it keeps coming up. 262 00:08:47,200 --> 00:08:48,480 And for good reason. 263 00:08:48,480 --> 00:08:50,440 So what else does Professor Lowe suggest? 264 00:08:50,440 --> 00:08:55,120 He's big on auditing these AI systems for bias, 265 00:08:55,120 --> 00:08:57,560 making sure they're not discriminating against certain groups. 266 00:08:57,560 --> 00:08:58,520 Oh, yeah, that's crucial. 267 00:08:58,520 --> 00:09:01,600 We don't want AI perpetuating existing inequalities. 268 00:09:01,600 --> 00:09:02,100 Exactly. 269 00:09:02,100 --> 00:09:06,200 So we need ways to measure and mitigate bias 270 00:09:06,200 --> 00:09:07,200 in these algorithms. 271 00:09:07,200 --> 00:09:09,360 That sounds like a whole new field of expertise. 272 00:09:09,360 --> 00:09:10,080 It is actually. 273 00:09:10,080 --> 00:09:11,720 AI ethics is becoming a big deal. 274 00:09:11,720 --> 00:09:13,360 So it's not just about the tech itself. 275 00:09:13,360 --> 00:09:16,040 It's about the human values that we embed in it. 276 00:09:16,040 --> 00:09:16,480 Right. 277 00:09:16,480 --> 00:09:18,080 And that's why it's so important for everyone 278 00:09:18,080 --> 00:09:20,760 to be part of this conversation, not just the techies. 279 00:09:20,760 --> 00:09:24,960 OK, so what can we do besides reading up on AI and all that? 280 00:09:24,960 --> 00:09:28,440 Well, we can use our voices, contact our elected officials, 281 00:09:28,440 --> 00:09:30,080 let them know we care about this stuff. 282 00:09:30,080 --> 00:09:32,160 So like write letters, make phone calls. 283 00:09:32,160 --> 00:09:32,720 Yeah. 284 00:09:32,720 --> 00:09:34,560 And support organizations that are fighting 285 00:09:34,560 --> 00:09:38,360 for responsible AI spread the word on social media. 286 00:09:38,360 --> 00:09:39,720 Basically, make some noise. 287 00:09:39,720 --> 00:09:40,320 Exactly. 288 00:09:40,320 --> 00:09:42,400 The more people who speak up, the more likely 289 00:09:42,400 --> 00:09:43,920 we are to see real change. 290 00:09:43,920 --> 00:09:44,440 I like that. 291 00:09:44,440 --> 00:09:46,600 It's about taking action, not just sitting back 292 00:09:46,600 --> 00:09:47,960 and letting things happen. 293 00:09:47,960 --> 00:09:50,080 And you know what else Professor Lowe brings up? 294 00:09:50,080 --> 00:09:51,720 International collaboration. 295 00:09:51,720 --> 00:09:52,840 Oh, yeah. 296 00:09:52,840 --> 00:09:54,880 AI isn't bound by borders, is it? 297 00:09:54,880 --> 00:09:55,320 Nope. 298 00:09:55,320 --> 00:09:58,400 It's a global phenomenon, so we need global solutions. 299 00:09:58,400 --> 00:10:01,880 So like treaties or agreements between countries 300 00:10:01,880 --> 00:10:04,280 on how to develop AI ethically. 301 00:10:04,280 --> 00:10:04,800 Yeah. 302 00:10:04,800 --> 00:10:05,520 Something like that. 303 00:10:05,520 --> 00:10:07,440 We got to make sure everyone's on the same page. 304 00:10:07,440 --> 00:10:08,320 OK, that makes sense. 305 00:10:08,320 --> 00:10:10,880 But that seems even harder than just getting our own government 306 00:10:10,880 --> 00:10:11,800 to act. 307 00:10:11,800 --> 00:10:12,680 True. 308 00:10:12,680 --> 00:10:14,320 But it's essential. 309 00:10:14,320 --> 00:10:15,640 We can't solve this alone. 310 00:10:15,640 --> 00:10:16,640 It's a big challenge. 311 00:10:16,640 --> 00:10:18,640 But hopefully we can rise to the occasion. 312 00:10:18,640 --> 00:10:19,040 Yeah. 313 00:10:19,040 --> 00:10:22,160 It's about working together, finding common ground, 314 00:10:22,160 --> 00:10:25,480 and making sure AI benefits all of humanity, 315 00:10:25,480 --> 00:10:27,200 not just a select few. 316 00:10:27,200 --> 00:10:29,720 I'm feeling a little overwhelmed, to be honest. 317 00:10:29,720 --> 00:10:31,160 It's a lot to process, I know. 318 00:10:31,160 --> 00:10:33,680 But I also feel like this is important stuff. 319 00:10:33,680 --> 00:10:34,800 We got to talk about it. 320 00:10:34,800 --> 00:10:35,320 I agree. 321 00:10:35,320 --> 00:10:35,760 And you know what? 322 00:10:35,760 --> 00:10:36,440 We're not done yet. 323 00:10:36,440 --> 00:10:37,560 There's more to come. 324 00:10:37,560 --> 00:10:38,120 Wait, there's more. 325 00:10:38,120 --> 00:10:39,160 I thought this was part two. 326 00:10:39,160 --> 00:10:39,840 Uh-huh. 327 00:10:39,840 --> 00:10:41,600 There's always more to learn about AI. 328 00:10:41,600 --> 00:10:42,400 Oh boy. 329 00:10:42,400 --> 00:10:43,360 OK, bring it on. 330 00:10:43,360 --> 00:10:45,560 Stay tuned for part three, where we'll 331 00:10:45,560 --> 00:10:48,240 talk about what we can all do to make a difference. 332 00:10:48,240 --> 00:10:49,760 Don't go anywhere, folks. 333 00:10:49,760 --> 00:10:50,440 We'll be right back. 334 00:10:50,440 --> 00:10:53,440 OK, so we've covered a lot of ground here. 335 00:10:53,440 --> 00:10:55,000 Yeah, my brain is kind of fried. 336 00:10:55,000 --> 00:10:56,280 Mine too. 337 00:10:56,280 --> 00:10:58,160 But it's been fascinating, right? 338 00:10:58,160 --> 00:10:58,560 Totally. 339 00:10:58,560 --> 00:11:01,120 Like, I thought I knew a bit about AI, 340 00:11:01,120 --> 00:11:03,400 but this whole finance angle is crazy. 341 00:11:03,400 --> 00:11:04,480 Right. 342 00:11:04,480 --> 00:11:05,600 So much to think about. 343 00:11:05,600 --> 00:11:06,800 And so much at stake. 344 00:11:06,800 --> 00:11:09,760 Like, our jobs, our money, our privacy. 345 00:11:09,760 --> 00:11:10,720 Yeah, no pressure. 346 00:11:10,720 --> 00:11:11,680 Ha-ha, right. 347 00:11:11,680 --> 00:11:14,760 But OK, let's focus on what we can actually do about all this. 348 00:11:14,760 --> 00:11:18,640 Like, how can we make sure AI and finance is a good thing, 349 00:11:18,640 --> 00:11:19,880 not a scary thing? 350 00:11:19,880 --> 00:11:22,000 Well, I think the first step is just staying informed. 351 00:11:22,000 --> 00:11:23,080 OK, that makes sense. 352 00:11:23,080 --> 00:11:25,000 Knowledge is power and all that. 353 00:11:25,000 --> 00:11:25,560 Exactly. 354 00:11:25,560 --> 00:11:28,120 The more we understand about AI, what it can do, 355 00:11:28,120 --> 00:11:30,400 what it can do, the better equipped 356 00:11:30,400 --> 00:11:33,720 we are to advocate for responsible development. 357 00:11:33,720 --> 00:11:35,920 So like, where do we even start? 358 00:11:35,920 --> 00:11:37,560 Any good resources out there? 359 00:11:37,560 --> 00:11:38,520 Oh, yeah, tons. 360 00:11:38,520 --> 00:11:41,680 Like, MIT's Computer Science and AI Lab, 361 00:11:41,680 --> 00:11:44,280 they've got a website with articles, videos, even 362 00:11:44,280 --> 00:11:45,280 online courses. 363 00:11:45,280 --> 00:11:46,520 Cool, I'll check that out. 364 00:11:46,520 --> 00:11:49,960 And there's this group called the Future of Life Institute. 365 00:11:49,960 --> 00:11:53,160 They're focused on the ethical side of AI, not just in finance. 366 00:11:53,160 --> 00:11:54,080 Oh, yeah, I've heard of it. 367 00:11:54,080 --> 00:11:56,080 They're the ones who got all those tech big wigs 368 00:11:56,080 --> 00:11:57,440 to sign that open letter, right? 369 00:11:57,440 --> 00:11:58,240 Exactly. 370 00:11:58,240 --> 00:11:59,880 They're doing some really important work. 371 00:11:59,880 --> 00:12:01,880 OK, so we can educate ourselves. 372 00:12:01,880 --> 00:12:05,160 But what else can we do to actually make a difference? 373 00:12:05,160 --> 00:12:09,520 Well, we can use our voices, contact our elected officials, 374 00:12:09,520 --> 00:12:10,960 telling we care about this stuff. 375 00:12:10,960 --> 00:12:14,240 So like, write letters, make phone calls, all that. 376 00:12:14,240 --> 00:12:17,880 And support organizations that are fighting for responsible AI. 377 00:12:17,880 --> 00:12:21,480 Donate, volunteer, spread the word on social media. 378 00:12:21,480 --> 00:12:24,040 OK, so basically, be loud and be active. 379 00:12:24,040 --> 00:12:25,440 Uh-huh, pretty much. 380 00:12:25,440 --> 00:12:26,640 Every little bit helps. 381 00:12:26,640 --> 00:12:27,920 I like that it's empowering. 382 00:12:27,920 --> 00:12:32,600 We're not just helpless bystanders in this whole AI revolution. 383 00:12:32,600 --> 00:12:33,240 Exactly. 384 00:12:33,240 --> 00:12:34,880 We can actually shape the future. 385 00:12:34,880 --> 00:12:35,880 That's a great way to put it. 386 00:12:35,880 --> 00:12:37,600 So it's not just about building better AI. 387 00:12:37,600 --> 00:12:41,760 It's about building a better society that can use AI for good. 388 00:12:41,760 --> 00:12:42,400 Totally. 389 00:12:42,400 --> 00:12:43,840 And you know what else we need to do? 390 00:12:43,840 --> 00:12:44,480 What's that? 391 00:12:44,480 --> 00:12:45,600 Talk to each other. 392 00:12:45,600 --> 00:12:48,560 I have conversations about this stuff with our friends, 393 00:12:48,560 --> 00:12:49,920 our family, our colleagues. 394 00:12:49,920 --> 00:12:52,880 Yeah, I get people thinking about the implications, 395 00:12:52,880 --> 00:12:55,040 the potential benefits, and risks. 396 00:12:55,040 --> 00:12:57,200 Right, because the more we talk about it, 397 00:12:57,200 --> 00:13:00,680 the more likely we are to make good decisions as a society. 398 00:13:00,680 --> 00:13:01,600 That's so true. 399 00:13:01,600 --> 00:13:03,600 Like, we can't just leave it up to the experts 400 00:13:03,600 --> 00:13:04,640 to figure this all out. 401 00:13:04,640 --> 00:13:05,280 Exactly. 402 00:13:05,280 --> 00:13:06,640 We all have a role to play. 403 00:13:06,640 --> 00:13:08,520 Well, I'm feeling a lot more hopeful now, 404 00:13:08,520 --> 00:13:10,200 knowing that we're not alone in this. 405 00:13:10,200 --> 00:13:11,200 Me too. 406 00:13:11,200 --> 00:13:13,880 It's a big challenge, but it's also an incredible opportunity. 407 00:13:13,880 --> 00:13:15,720 Yeah, to really shape the future. 408 00:13:15,720 --> 00:13:18,760 Not just for ourselves, but for generations to come. 409 00:13:18,760 --> 00:13:19,480 That's right. 410 00:13:19,480 --> 00:13:22,040 And you know, that's what's so exciting about this whole AI 411 00:13:22,040 --> 00:13:22,880 thing. 412 00:13:22,880 --> 00:13:24,360 It's not just about technology. 413 00:13:24,360 --> 00:13:26,680 It's about what kind of world we want to create. 414 00:13:26,680 --> 00:13:27,280 I love that. 415 00:13:27,280 --> 00:13:29,680 It's a reminder that we're all in this together. 416 00:13:29,680 --> 00:13:30,440 Totally. 417 00:13:30,440 --> 00:13:32,560 We got to work together, learn from each other, 418 00:13:32,560 --> 00:13:34,600 and make sure AI is a force for good. 419 00:13:34,600 --> 00:13:36,400 Well said. 420 00:13:36,400 --> 00:13:39,320 On that note, I think it's time to wrap up this deep dive. 421 00:13:39,320 --> 00:13:41,280 Yeah, I think we've covered just about everything. 422 00:13:41,280 --> 00:13:44,360 Huge thanks to Professor Low for sharing his insights with us. 423 00:13:44,360 --> 00:13:45,800 Yeah, he's a real visionary. 424 00:13:45,800 --> 00:13:48,720 And to our listeners, thanks for joining us on this journey 425 00:13:48,720 --> 00:13:50,880 into the world of AI and finance. 426 00:13:50,880 --> 00:13:53,000 It's been a blast exploring this stuff with you. 427 00:13:53,000 --> 00:13:54,920 We'll be back soon with more deep dives 428 00:13:54,920 --> 00:13:56,880 into the topics that matter most. 429 00:13:56,880 --> 00:14:01,520 Until then, stay curious, stay informed, and stay engaged. 430 00:14:01,520 --> 00:14:23,160 And remember, the future is what we make it.