1 00:00:05,160 --> 00:00:07,599 Speaker 1: This week's episode of the trip Cast is sponsored by 2 00:00:07,599 --> 00:00:19,239 the Texas Tribune Membership program as we celebrate Amplify Austin. Hello, 3 00:00:19,280 --> 00:00:22,120 and welcome to the Texas Tribune Trip Cast for March fourth, 4 00:00:22,120 --> 00:00:25,320 twenty twenty five. I'm Matthew Watkins, editor in Chief of 5 00:00:25,359 --> 00:00:29,199 the Tribune. My two co hosts, Eleanor Klibanoff and James 6 00:00:29,199 --> 00:00:33,840 Berragon are nursing their oscar parties hangover, aren't able to 7 00:00:33,880 --> 00:00:36,880 make it today, so instead I am joined by Cherry Greenberg, 8 00:00:36,920 --> 00:00:39,520 a former state representative and professor of practice at the 9 00:00:39,640 --> 00:00:42,399 LBJ School of Government at the UT Austin. 10 00:00:42,799 --> 00:00:43,920 Speaker 3: Hello, Sherry, thanks for being. 11 00:00:43,840 --> 00:00:45,159 Speaker 2: Here, my pleasure. Hello. 12 00:00:45,479 --> 00:00:48,159 Speaker 1: So today we are going to be talking about a 13 00:00:48,240 --> 00:00:51,280 subject that you have been studying for several years now, 14 00:00:51,280 --> 00:00:54,200 many years even before it became sort of the buzzword 15 00:00:54,280 --> 00:00:57,719 in the Texas capital and beyond the idea of artificial 16 00:00:57,759 --> 00:01:01,359 intelligence and regulating it at this date level, When the 17 00:01:01,399 --> 00:01:04,400 idea of regulating businesses comes up in the legislature, there's 18 00:01:04,519 --> 00:01:08,439 usually a pretty strong consensus among Republicans to sort of 19 00:01:08,599 --> 00:01:10,480 stay out of the way in the name of growth 20 00:01:10,519 --> 00:01:14,040 and free enterprise. But the conversation this year around regulating 21 00:01:14,079 --> 00:01:16,840 AI is turning out to be a little bit more complex. 22 00:01:17,040 --> 00:01:20,799 You have powerful conservatives such as Senate Business and Commerce 23 00:01:20,879 --> 00:01:24,959 Chairman Charles Schwartner and the Chair of the House Doge Committee, 24 00:01:25,319 --> 00:01:30,920 Giovanni Copriglioni, comparing carrying bills that would impose strong guardrails 25 00:01:30,959 --> 00:01:34,079 and rules for the technology, but they're finding some opposition 26 00:01:34,120 --> 00:01:37,079 from members of their own party. Senator Lewis Cole course 27 00:01:37,200 --> 00:01:41,079 was questioning a bill by Schwartner earlier last week. Tech 28 00:01:41,959 --> 00:01:45,200 impresario Joe Lonsdale has really come out against some of 29 00:01:45,239 --> 00:01:49,439 the legislation, despite being pretty usually aligned with Republicans in 30 00:01:49,480 --> 00:01:51,760 the state. It's a fight that sort of avoids that 31 00:01:51,840 --> 00:01:55,439 partisan brack breakdown. But I think there's some fear kind 32 00:01:55,439 --> 00:01:58,239 of driving both sides. On one hand, you have lawmakers 33 00:01:58,280 --> 00:02:01,560 worried about the dangers of AI on people's privacy, their freedom, 34 00:02:01,840 --> 00:02:04,680 and the possibility that really important decisions might be made 35 00:02:04,719 --> 00:02:07,239 by computers not people. On the other side, you have 36 00:02:07,280 --> 00:02:10,120 folks who are worried about going too far and restricting 37 00:02:10,199 --> 00:02:13,240 AI that would leave Texas behind other states in the 38 00:02:13,280 --> 00:02:17,199 technology and maybe even pulling the United States with them 39 00:02:17,520 --> 00:02:22,199 behind adversaries like China. So Sherry, You, like I said, 40 00:02:22,199 --> 00:02:24,199 have been watching this for a very long time. A 41 00:02:24,240 --> 00:02:26,759 lot of the focus so far earlier on this session 42 00:02:27,159 --> 00:02:30,960 is on a major bill called TREGA, the Texas Responsible 43 00:02:31,039 --> 00:02:34,479 AI Governance Act. Can we start by just having you 44 00:02:34,599 --> 00:02:36,400 explain what's in that bill? 45 00:02:36,840 --> 00:02:40,439 Speaker 2: Sure? And for background, which you really alluded to, is 46 00:02:40,439 --> 00:02:43,280 what I call the promise in peril of AI. Right, 47 00:02:43,520 --> 00:02:47,800 there's great promise with AI with artificial intelligence and healthcare 48 00:02:47,919 --> 00:02:51,280 detecting diseases that we wouldn't be able to, but there's 49 00:02:51,360 --> 00:02:53,639 peril too. So if we can use healthcare and as 50 00:02:53,639 --> 00:02:58,719 an example, big privacy issues, and we also talk about 51 00:02:59,000 --> 00:03:08,000 balancing innovation with rules and policies and regulations that provide transparency, 52 00:03:08,199 --> 00:03:12,680 accountability and guard against invasion and privacy. And so that's 53 00:03:12,719 --> 00:03:16,639 really what we're dealing with here. And with artificial intelligence, 54 00:03:17,159 --> 00:03:20,199 we do find that there are a lot of common 55 00:03:20,319 --> 00:03:25,879 concerns across political parties and sometimes you find alliances that 56 00:03:25,919 --> 00:03:28,319 you wouldn't elsewhere, and you also alluded to that. So 57 00:03:28,400 --> 00:03:31,360 with TREGA, this is a bill that was filed its 58 00:03:31,400 --> 00:03:36,639 House Bill seventeen oh nine by Representative Giovanni Capriconi, and 59 00:03:36,840 --> 00:03:39,759 there was a lot of discussion about this bill over 60 00:03:39,800 --> 00:03:43,439 the interim. He had a very large stakeholder group that 61 00:03:43,879 --> 00:03:48,800 many of us participated in meetings and whatnot, and I 62 00:03:48,840 --> 00:03:51,319 think he knew that this is a bill that would 63 00:03:51,960 --> 00:03:55,719 have a lot of discussion once it was filed. So 64 00:03:56,120 --> 00:04:02,759 TREGA is really a builds based on risk mitigation, and 65 00:04:02,879 --> 00:04:05,800 this is what the EU bill really is based on. 66 00:04:05,960 --> 00:04:09,879 And also other states such as Colorado which we can 67 00:04:09,919 --> 00:04:14,639 look to, and it's mitigating against risk, which is also 68 00:04:14,879 --> 00:04:21,480 what this the Nationaltitude for Standards has really set out 69 00:04:21,519 --> 00:04:24,839 in its framework, which is part of the National Science Foundation. 70 00:04:25,000 --> 00:04:30,079 So TREGA would create obligations for developers and deployers of 71 00:04:30,240 --> 00:04:34,000 any AI system that is a contribution, you know, decisions 72 00:04:34,040 --> 00:04:39,000 relating to employment, finance, healthcare. Texas would also be the 73 00:04:39,040 --> 00:04:43,079 first state to require high risk AI system distributors to 74 00:04:43,160 --> 00:04:47,360 take reasonable care. The bill would ban AI systems that 75 00:04:47,439 --> 00:04:53,600 pose unacceptable risk. Private litigans would have limited right of action. 76 00:04:54,199 --> 00:04:57,600 The law would require generative AI to developers to keep 77 00:04:57,639 --> 00:05:01,720 detailed records of data sets used to It would exempt 78 00:05:01,720 --> 00:05:04,439 many small businesses. So you can see it's very much 79 00:05:04,519 --> 00:05:10,519 a risk based system. It is also a build that 80 00:05:10,639 --> 00:05:14,560 very much focuses on what we call algorithmic discrimination, and 81 00:05:14,600 --> 00:05:17,800 in the bill, that means any condition in which an 82 00:05:17,920 --> 00:05:23,680 artificial intelligence system, when deployed, creates an on lawful discrimination 83 00:05:23,839 --> 00:05:27,720 of a protected classification in violation of the laws of 84 00:05:27,759 --> 00:05:30,279 this state or federal law. And then it further goes 85 00:05:30,360 --> 00:05:34,240 on because you're wondering, what's an artificial intelligence system? Right? 86 00:05:34,319 --> 00:05:39,279 That means the use of machine learning and related technologies 87 00:05:39,560 --> 00:05:43,680 that use data to train statistical models for the purpose 88 00:05:43,759 --> 00:05:48,839 of enabling computer systems to perform tasks normally associated with 89 00:05:48,920 --> 00:05:51,240 human intelligence. And this is really where we get into 90 00:05:51,279 --> 00:05:56,040 the AI, the artificial intelligence realm or perception such as 91 00:05:56,079 --> 00:06:01,160 computer vision, speech, or natural language processing and content generation. 92 00:06:01,800 --> 00:06:04,399 Speaker 1: Okay, so there's a few things that are sort of 93 00:06:05,120 --> 00:06:08,079 key phrases in this bill, one of which you already 94 00:06:08,079 --> 00:06:11,040 mentioned high risk AI systems. What do we mean by 95 00:06:11,040 --> 00:06:13,160 a high risk system in this case. 96 00:06:13,120 --> 00:06:17,040 Speaker 2: So a high risk system in this bill, and again 97 00:06:17,079 --> 00:06:21,639 this bill is really based on risk mitigation. High risk 98 00:06:21,759 --> 00:06:26,040 artificial intelligence system means an artificial intelligence system that is 99 00:06:26,560 --> 00:06:31,399 a substantial factor in a consequential decision. The term, though, 100 00:06:31,480 --> 00:06:34,959 does not include an artificial system. If the artificial intelligence 101 00:06:34,959 --> 00:06:38,879 system is intended to detect decision making patterns or deviation 102 00:06:39,439 --> 00:06:43,279 from prior decision making patterns, and is not intended to 103 00:06:43,279 --> 00:06:48,360 replace or influence a previously completed human assessment without sufficient 104 00:06:48,439 --> 00:06:54,319 human review. So the following technologies unless the technologies, when deployed, 105 00:06:54,399 --> 00:06:58,600 make or a substantial factor in making a consequential decision. 106 00:06:58,639 --> 00:07:04,680 And a malware anti virus calculation, cybersecurity database is data storage, firewall, 107 00:07:05,639 --> 00:07:08,079 internal domain. The list goes on and on. 108 00:07:08,279 --> 00:07:10,800 Speaker 3: So those are things that are not included in the building. 109 00:07:10,920 --> 00:07:14,680 Speaker 1: But what we're really talking about here are basically using 110 00:07:14,800 --> 00:07:19,000 AI using computers to make kind of important, impactful decisions 111 00:07:19,000 --> 00:07:21,480 about customers or people in this state. 112 00:07:21,639 --> 00:07:23,240 Speaker 2: That's exactly right, okay, And. 113 00:07:23,560 --> 00:07:25,519 Speaker 1: I think the other interesting thing is the idea of 114 00:07:25,600 --> 00:07:32,240 using reasonable care. Right, this this idea that if essentially 115 00:07:32,360 --> 00:07:35,399 it's up to the developers, the people you know, like 116 00:07:35,480 --> 00:07:39,000 open ai or or you know, Twitters developing some some 117 00:07:39,120 --> 00:07:42,560 AI systems and things like that, or even the distributors 118 00:07:42,639 --> 00:07:45,600 or the employer, the deployers, the people who are you know, 119 00:07:46,279 --> 00:07:51,040 utilizing an AI system to evaluate, you know, whatever it 120 00:07:51,079 --> 00:07:54,240 is they might do, make decisions about healthcare, health insurance 121 00:07:54,240 --> 00:07:56,560 and things like that. What it's basically saying is that 122 00:07:56,600 --> 00:08:00,800 they need to take steps that are done reasonably to 123 00:08:00,879 --> 00:08:03,720 protect people from that kind of discrimination in the system. 124 00:08:03,800 --> 00:08:04,240 Speaker 3: Is that right? 125 00:08:04,319 --> 00:08:08,439 Speaker 2: That is exactly right? And there is a kind of 126 00:08:09,319 --> 00:08:12,279 I guess provision you would say for piloting, you know, 127 00:08:12,360 --> 00:08:17,680 with a sandbox where there can be some innovation taking place. 128 00:08:18,079 --> 00:08:21,480 Speaker 1: Okay, okay, very good. And so I mean what's interesting here. 129 00:08:21,519 --> 00:08:23,560 This is the bill that's gotten a lot of attention. 130 00:08:23,800 --> 00:08:27,120 It'll be interesting to see whether it advances in its 131 00:08:27,160 --> 00:08:29,040 current form, and we can talk about that a little 132 00:08:29,079 --> 00:08:31,839 bit more. But what's really struck me about this is 133 00:08:32,039 --> 00:08:34,559 there was a lot of conversation, you know, when when 134 00:08:34,639 --> 00:08:37,559 chat GPT was really out there, a lot of conversation 135 00:08:37,639 --> 00:08:41,000 about the dangers of AI. A lot of those felt 136 00:08:41,000 --> 00:08:44,879 like sort of conversations around existential dangers for humanity. 137 00:08:45,000 --> 00:08:46,840 Speaker 3: Right, are the right going to take over? 138 00:08:47,039 --> 00:08:49,720 Speaker 2: Yes, sentient and they're not cynient. 139 00:08:49,440 --> 00:08:53,120 Speaker 1: Exactly exactly, And that's not really what this is protecting about. 140 00:08:53,200 --> 00:08:57,360 This is more about privacy concerns. Are AI you know, 141 00:08:57,440 --> 00:08:59,799 basically things without a conscience is going to be making 142 00:09:00,080 --> 00:09:03,879 you know, life or death or you know, major financial 143 00:09:03,919 --> 00:09:06,159 decisions for the lives of people in Texas. 144 00:09:06,240 --> 00:09:06,879 Speaker 3: Is that is that right? 145 00:09:07,080 --> 00:09:11,440 Speaker 2: Yes, this is not about whether AI is, as we say, sentient, right, 146 00:09:11,919 --> 00:09:16,240 It is about looking at those areas that people are 147 00:09:16,279 --> 00:09:20,360 most concerned about when they talk about AI, protecting their privacy, 148 00:09:20,759 --> 00:09:25,600 having transparency, having accountability, knowing when you know AI is 149 00:09:25,639 --> 00:09:31,000 being used. The bill, you know, requires the as we said, 150 00:09:31,120 --> 00:09:36,080 an unacceptable risk. It prohibits systems that without express consent, 151 00:09:36,279 --> 00:09:42,120 identify emotions, capture biometic intent, you know, those attributes that 152 00:09:42,200 --> 00:09:48,440 were really sensitive about as people in this atmosphere. It 153 00:09:48,519 --> 00:09:53,519 also would require generative AI developers to keep detailed records 154 00:09:53,519 --> 00:09:56,679 of data sets that they used to train. So the bill, 155 00:09:57,039 --> 00:10:02,639 again going back to the unist frame work, really looks 156 00:10:02,720 --> 00:10:08,679 at risk and risk management and some of those perils 157 00:10:08,679 --> 00:10:14,759 that we talk about. The risk management framework looks at governmap, 158 00:10:15,000 --> 00:10:20,000 measure and manage and that is a framework that has 159 00:10:20,039 --> 00:10:23,919 been used by NIS, really by the EU, by Colorado 160 00:10:24,399 --> 00:10:27,440 and other states. Now that's not to say that people 161 00:10:27,879 --> 00:10:32,519 everyone is happy about it, right, and really with AI, 162 00:10:32,840 --> 00:10:36,399 we can go back to nineteen fifty with Alan Turing r. 163 00:10:37,000 --> 00:10:39,759 AI has been with us a long time and in 164 00:10:39,799 --> 00:10:44,000 our daily lives. But until chat GPT appeared on the scene, 165 00:10:44,039 --> 00:10:48,080 people weren't really cognizant about it. Once people became cognizant, 166 00:10:48,080 --> 00:10:51,480 then it's oh, what does this mean for my privacy? 167 00:10:51,639 --> 00:10:55,679 My data? Is there transparency? Do I know when AI 168 00:10:55,799 --> 00:11:00,000 is being used? However, there is this, as I said, 169 00:11:00,120 --> 00:11:04,679 promise in peril or this also this issue of how 170 00:11:04,679 --> 00:11:08,480 do we have innovation right without too much risk? As 171 00:11:08,519 --> 00:11:13,759 you mentioned, people are concerned if this stifles innovation, where 172 00:11:13,799 --> 00:11:17,039 will that mean for us as a state? We know 173 00:11:17,279 --> 00:11:19,720 that we're getting ready to have some big investments in 174 00:11:19,759 --> 00:11:22,519 this state right in AI. What would that mean for 175 00:11:22,639 --> 00:11:25,559 the country you mentioned China, And of course we've heard 176 00:11:25,559 --> 00:11:30,159 a lot about China and AI recently. But on the 177 00:11:30,200 --> 00:11:33,200 other hand, people really are concerned about I would say, 178 00:11:33,240 --> 00:11:38,720 their privacy and about this algorithmic discrimination in decision making 179 00:11:39,039 --> 00:11:42,279 and also other areas. There are other bills, of course, 180 00:11:42,320 --> 00:11:46,679 have been filed dealing with using AI for mental health, 181 00:11:47,240 --> 00:11:51,919 or using AI and making decisions with insurance and healthcare. 182 00:11:52,200 --> 00:11:54,200 So there are other concerns that people have. 183 00:11:54,639 --> 00:11:58,720 Speaker 1: Yeah, it seems like the would you say, the broad 184 00:11:59,080 --> 00:12:01,519 kind of fee of a lot of these bills is 185 00:12:01,559 --> 00:12:06,440 sort of designed from a kind of consumer protection standpoint. 186 00:12:06,799 --> 00:12:09,559 Speaker 2: Yes, I would say it is designed from a consumer 187 00:12:09,600 --> 00:12:15,600 protection and transparency standpoint. The bills, you know, they may say, well, 188 00:12:15,840 --> 00:12:18,600 you can use it for mental health, but there has 189 00:12:18,679 --> 00:12:22,080 to be a provider involved. Keeping the human in the loop. 190 00:12:22,159 --> 00:12:26,399 I would say, you know, when you're looking at health insurance, 191 00:12:26,440 --> 00:12:29,360 you know you have to disclose perhaps that you're using 192 00:12:29,399 --> 00:12:31,879 eye and you have to if it's for specialty care, 193 00:12:32,000 --> 00:12:36,840 specialist for instance, has to review it. So consumer protection, 194 00:12:38,399 --> 00:12:44,159 transparency and accountability and kind of I would say, keeping 195 00:12:44,200 --> 00:12:45,559 that human in the loop. 196 00:12:46,320 --> 00:12:49,360 Speaker 1: It's interesting because in some ways this feels like a 197 00:12:49,519 --> 00:12:54,480 very familiar kind of conversation between innovation and industry and 198 00:12:54,960 --> 00:12:58,080 creation and all those kinds of things, and you know, 199 00:12:58,200 --> 00:13:03,240 the consumer protection, the fears about the negative impacts of 200 00:13:03,240 --> 00:13:06,360 this technology, and I just I find it a little 201 00:13:06,399 --> 00:13:09,240 bit striking that we're seeing, you know, at least a 202 00:13:10,200 --> 00:13:14,720 significant segment of the Republican Party sort of going in 203 00:13:14,799 --> 00:13:18,200 the direction of consumer protection this time around. What do 204 00:13:18,240 --> 00:13:22,000 you think it is that's different about AI that's setting 205 00:13:22,080 --> 00:13:22,840 up this conversation. 206 00:13:23,080 --> 00:13:27,440 Speaker 2: Well, certainly, I think that there are a lot of 207 00:13:27,679 --> 00:13:33,480 legislators who have followed the path that for instance, social 208 00:13:33,519 --> 00:13:39,159 media took and lack of privacy with data and they're 209 00:13:39,159 --> 00:13:42,159 feeling that this is a big concern of their constituents. 210 00:13:42,240 --> 00:13:45,879 And seeing now with AI, you know, your data, your 211 00:13:45,919 --> 00:13:48,559 personal data is being used to train it. For instance, 212 00:13:49,200 --> 00:13:52,720 your personal data may be available. You may not know 213 00:13:52,919 --> 00:13:55,159 when it's being used. It may you know, is it 214 00:13:55,279 --> 00:13:57,840 making decisions without a human and a loop. And I 215 00:13:57,879 --> 00:14:01,559 think that those are issues that you know trands, they're 216 00:14:01,679 --> 00:14:07,600 they're beyond party boundaries, and that many constituents across the 217 00:14:07,639 --> 00:14:15,120 board are very concerned with these issues and concerned with 218 00:14:15,879 --> 00:14:19,399 the I would say, the path for instance, that data 219 00:14:19,799 --> 00:14:22,720 and social media has taken with you know, lack of 220 00:14:22,759 --> 00:14:25,639 privacy and now seeing AI. 221 00:14:26,399 --> 00:14:29,759 Speaker 1: Yeah, I mean among the things in this this trega bill, 222 00:14:30,200 --> 00:14:35,879 it bans deep fakes right, and certain use of biomarkers 223 00:14:36,000 --> 00:14:38,720 like facial recognition that you know, they don't want people 224 00:14:38,720 --> 00:14:41,039 pulling a bunch of pictures from Facebook to be able 225 00:14:41,080 --> 00:14:44,240 to identify your face, you know, wherever you are walking 226 00:14:44,279 --> 00:14:47,879 across the street. Another thing it bans is social scoring, 227 00:14:48,200 --> 00:14:51,399 which I'm quoting from the MIT Technology Review. The definition 228 00:14:51,399 --> 00:14:55,679 of that a practice in which authoritarian governments, specifically China, 229 00:14:56,080 --> 00:15:00,200 rank people's trustworthiness and punish them for undesirable behaviors such 230 00:15:00,200 --> 00:15:03,159 as stealing or not paying back loans. Right essentially seen 231 00:15:03,240 --> 00:15:06,559 as a you know, sort of way to rank citizens 232 00:15:06,639 --> 00:15:10,360 or or identify citizens as types of risk and that 233 00:15:10,519 --> 00:15:13,679 kind of I mean, I think, you know, another big 234 00:15:13,759 --> 00:15:16,279 part of the Republican Party is freedom right. And there 235 00:15:16,279 --> 00:15:19,080 were a little bit about surveillance and just you know, 236 00:15:19,200 --> 00:15:22,320 whether it's big companies or the government itself sort of 237 00:15:22,720 --> 00:15:25,840 you know, reaching into the personal lives in a way 238 00:15:25,879 --> 00:15:27,480 that feels uncomfortable to that's right. 239 00:15:27,519 --> 00:15:32,399 Speaker 2: It's that privacy issue. They're very concerned about you not 240 00:15:32,559 --> 00:15:34,480 knowing your data is being used, you not knowing that 241 00:15:34,519 --> 00:15:37,960 your face is being used, to the biometric markers, your 242 00:15:38,080 --> 00:15:40,559 voice being taken. You know, there was a case in 243 00:15:41,399 --> 00:15:46,559 Arizona over a year ago, a really horrible situation, and 244 00:15:46,679 --> 00:15:51,519 there was legislation in the Arizona legislature where there was 245 00:15:51,600 --> 00:15:56,000 a deep fake of a young woman's voice and it 246 00:15:56,039 --> 00:15:58,600 was it was her voice, and they called her mother 247 00:15:59,080 --> 00:16:01,759 and her younger was there too, and said that she 248 00:16:01,840 --> 00:16:05,600 had been kidnapped asking for ransom. Well, in fact, she 249 00:16:05,720 --> 00:16:09,120 had not been kidnapped, and that was not her voice, 250 00:16:09,440 --> 00:16:12,440 but it was a replica, let's say, of her voice 251 00:16:12,480 --> 00:16:16,000 a deep fake. So there are a lot of concerns 252 00:16:16,039 --> 00:16:20,639 I think about criminal elements, about privacy, and as you said, 253 00:16:20,720 --> 00:16:24,759 about freedom, my freedom to walk down the street without 254 00:16:24,960 --> 00:16:30,679 being ranked as a threat to society, or my freedom 255 00:16:30,759 --> 00:16:35,360 to control how my image and likeness and voices being used. 256 00:16:35,720 --> 00:16:36,120 Speaker 3: All right. 257 00:16:36,200 --> 00:16:40,039 Speaker 1: Today's trip cast is presented by the Texas Tribune Membership program. 258 00:16:40,320 --> 00:16:43,759 The Texas Tribune's in depth coverage of Texas politics relies 259 00:16:43,799 --> 00:16:47,000 on donations from people like you. Right now, your donation 260 00:16:47,120 --> 00:16:49,879 to support this reporting goes twice as far thanks to 261 00:16:49,960 --> 00:16:53,600 a fifteen thousand dollars match for Amplify Austin Day. Support 262 00:16:53,679 --> 00:16:58,440 independent journalism by making a donation online today. Okay, So 263 00:16:58,600 --> 00:17:01,639 I want to ask you a little bit about just 264 00:17:02,399 --> 00:17:05,240 the state's ability to succeed in this process. 265 00:17:05,400 --> 00:17:05,559 Speaker 3: Right. 266 00:17:05,839 --> 00:17:09,480 Speaker 1: We saw a you know, after this bill came out. 267 00:17:09,559 --> 00:17:11,839 Joe Lonsdale, who I mentioned sort of in the opening, 268 00:17:12,200 --> 00:17:15,680 a venture capitalist, a very influential one both politically and 269 00:17:15,920 --> 00:17:19,359 in the tech world, came out very strongly against this 270 00:17:19,480 --> 00:17:23,359 trega bill. He says he did kill innovation, kill jobs, 271 00:17:23,720 --> 00:17:27,039 let China win the AI race. He essentially argued that 272 00:17:27,079 --> 00:17:30,440 it would create a new AI governing agency in Texas 273 00:17:30,559 --> 00:17:33,960 and see the regulation of AI to you know, bureaucrats, right, 274 00:17:34,000 --> 00:17:37,440 the dread of bureaucrats tell me a little bit about 275 00:17:37,519 --> 00:17:39,200 the industry response. 276 00:17:39,359 --> 00:17:44,000 Speaker 2: Sure, sure, and it's not you know, you mentioned his statements, 277 00:17:44,000 --> 00:17:45,799 but he's not the only one. There were articles, I 278 00:17:45,880 --> 00:17:50,279 think in Forbes there was an opinion piece, and I 279 00:17:50,319 --> 00:17:52,319 believe the Dallas Morning News last week. 280 00:17:52,920 --> 00:17:57,960 Speaker 1: If you google TREGA, all the top links are industry 281 00:17:58,000 --> 00:18:01,039 aligned groups with articles and other things kind of speaking 282 00:18:01,039 --> 00:18:01,519 out against this. 283 00:18:01,759 --> 00:18:05,200 Speaker 2: Right, you know, there was another article, everything is bigger 284 00:18:05,200 --> 00:18:09,640 in Texas. TREGA is no exception. But will it, you know, 285 00:18:09,720 --> 00:18:14,960 provide accountability? So and they're saying no, it wouldn't. And 286 00:18:15,960 --> 00:18:19,759 so any time that you file a significant bill, Having 287 00:18:19,799 --> 00:18:22,680 spent ten years in the legislature myself, I can tell 288 00:18:22,720 --> 00:18:25,640 you that you're going it's a starting point, and you're 289 00:18:25,640 --> 00:18:28,799 going to expect that there will be changes, that there 290 00:18:28,880 --> 00:18:33,559 will be amendments. And with a bill like this, even 291 00:18:33,680 --> 00:18:37,039 though there was a stakeholder group and a lot of input, 292 00:18:37,200 --> 00:18:40,759 I think the bill that's filed, I think it's safe 293 00:18:40,799 --> 00:18:42,799 to say probably is not going to be the final 294 00:18:42,880 --> 00:18:48,960 piece of legislation, and so we take it as a 295 00:18:49,000 --> 00:18:52,400 starting point. And certainly there is this concern about innovation. 296 00:18:53,440 --> 00:18:57,160 You know, we're in another industrial revolution, and with every 297 00:18:57,160 --> 00:18:59,720 industrial revolution, whether you say we're in the fourth or 298 00:18:59,759 --> 00:19:03,519 fifth or whatever, you know, we have seen concerns about 299 00:19:04,559 --> 00:19:07,440 the you know, the perils of the new technology, but 300 00:19:07,480 --> 00:19:12,200 also the promise. And there are concerns, you know, with 301 00:19:12,400 --> 00:19:15,880 AI about work and future work, for instance, will people 302 00:19:15,920 --> 00:19:18,039 be out of jobs or will there be new jobs? 303 00:19:18,039 --> 00:19:19,839 And we can look back at history and see this, 304 00:19:19,960 --> 00:19:23,200 So I think there there is a real issue here 305 00:19:23,559 --> 00:19:29,599 with balancing innovation and protecting people's freedom and privacy and 306 00:19:29,640 --> 00:19:34,640 having that transparency and that when you file a bill 307 00:19:34,839 --> 00:19:37,240 like this, you know you can expect that there will 308 00:19:37,279 --> 00:19:37,599 be some. 309 00:19:37,640 --> 00:19:40,079 Speaker 3: Amendments, right right, absolutely, you know. 310 00:19:40,240 --> 00:19:43,079 Speaker 1: I Lonsdale, after he put out a little sort of 311 00:19:43,240 --> 00:19:46,440 a tweet threadgras this, he came back not too long 312 00:19:46,519 --> 00:19:50,200 later said he met with quote relevant leaders in Texas 313 00:19:50,400 --> 00:19:53,880 and that they agreed, again I'm quoting him, conservatives must 314 00:19:53,880 --> 00:19:57,119 block the creation of AI regulatory agencies. 315 00:19:57,720 --> 00:20:00,000 Speaker 3: So I think, you know, you're exactly right. 316 00:20:00,079 --> 00:20:02,799 Speaker 1: It sounds like there is there's going to be some 317 00:20:02,880 --> 00:20:06,200 resistance to some of these ideas. Right here, I want 318 00:20:06,240 --> 00:20:09,279 to talk a little bit about enforcement here. So the 319 00:20:09,319 --> 00:20:14,279 bill as it's currently laid out, would place enforcement in 320 00:20:14,319 --> 00:20:18,000 the hands of the Attorney generals. That's correct, organizations that 321 00:20:18,559 --> 00:20:21,279 violate the rules and that would be subject to fines 322 00:20:21,319 --> 00:20:25,480 in the like ten thousand dollars range per instance. But 323 00:20:25,559 --> 00:20:27,359 of course we know that a lot of these things 324 00:20:27,400 --> 00:20:30,319 are done on a mass scale, so those ten thousand 325 00:20:30,319 --> 00:20:32,880 dollars finds can can really add up. I mean, you 326 00:20:32,920 --> 00:20:38,440 may remember the Attorney General's lawsuit against Facebook for use 327 00:20:38,480 --> 00:20:42,319 of facial recognition. Again, it was one of those you know, 328 00:20:42,400 --> 00:20:45,519 individual finds. Those individual finds ended up adding up to 329 00:20:45,559 --> 00:20:48,559 one point four billion dollars worth of settlements. So you 330 00:20:48,599 --> 00:20:52,000 could really see, you know, some aggressive actions related to this. 331 00:20:52,720 --> 00:20:54,200 But I mean, one of the things I wonder about 332 00:20:54,240 --> 00:20:58,000 is I read this bill is Texas state government isn't 333 00:20:58,039 --> 00:21:01,440 exactly known for being a tech know, logically advanced, and 334 00:21:01,440 --> 00:21:03,279 how it goes about things. I mean, you know, the 335 00:21:03,359 --> 00:21:06,160 computer systems, all those types of things. 336 00:21:06,279 --> 00:21:10,400 Speaker 2: Well, there is another bill that calls for training of 337 00:21:10,519 --> 00:21:14,680 certain employees on cybersecurity and artificial intelligence. 338 00:21:14,880 --> 00:21:15,440 Speaker 3: Well there you go. 339 00:21:15,519 --> 00:21:20,440 Speaker 1: I mean, what does Texas have the capacity to regulate this. 340 00:21:20,640 --> 00:21:23,200 Do you think if even if a bill like this 341 00:21:23,240 --> 00:21:23,640 were to. 342 00:21:23,599 --> 00:21:30,319 Speaker 2: Be passed, you know, the Attorney General's Office, as you said, 343 00:21:30,440 --> 00:21:35,079 would be the enforcement mechanism, not the Department of Information Resources, 344 00:21:35,519 --> 00:21:38,119 does it have the capacity? I think that depends on 345 00:21:38,279 --> 00:21:42,559 the who are the employees and what training do they have? 346 00:21:43,039 --> 00:21:46,960 And as I said, I think that is incredibly important 347 00:21:47,920 --> 00:21:51,240 having of course the systems in place, but also the 348 00:21:51,319 --> 00:21:53,240 training of state employees. 349 00:21:53,880 --> 00:21:59,839 Speaker 1: Okay, and so the other thing here to be thinking 350 00:21:59,839 --> 00:22:02,960 of is just again that debate. I mean, this is 351 00:22:03,039 --> 00:22:05,119 going on in a lot of different ways. I think 352 00:22:05,160 --> 00:22:07,640 one conversation is do you do this in a piecemeal approach? 353 00:22:07,759 --> 00:22:12,880 Right with individual you know, here's an AI healthcare bill, 354 00:22:13,119 --> 00:22:15,799 as an AI education bill and all those types of things. 355 00:22:15,799 --> 00:22:17,920 There are a lot of different measures about that. But 356 00:22:18,000 --> 00:22:21,079 even when you get into the individual cases, it can 357 00:22:21,359 --> 00:22:22,920 it can get a little bit dicey when you go 358 00:22:22,920 --> 00:22:25,599 into the details. There was a conversation in the Senate 359 00:22:25,640 --> 00:22:29,480 Business and Commerce Committee last week Charles Schwartner finding a 360 00:22:29,480 --> 00:22:32,000 bill that would ban health insurers from using AI to 361 00:22:32,079 --> 00:22:36,759 deny treatment or downcoading patient's treatment. He argued pretty passionately 362 00:22:36,839 --> 00:22:40,599 against the idea I'm quoting here that insurers are quote 363 00:22:40,720 --> 00:22:43,759 deploying AI that is focused on their bottom line in 364 00:22:43,759 --> 00:22:47,359 my opinion, over you know, patient well being basically. 365 00:22:47,680 --> 00:22:49,039 Speaker 3: But los culd course. 366 00:22:49,000 --> 00:22:53,119 Speaker 1: Another very conservative senator came right back at it and said, 367 00:22:53,200 --> 00:22:57,039 you know, this bill could cost billions of dollars to 368 00:22:57,160 --> 00:23:00,000 the state, right that we have you know, Medicaid programs 369 00:23:00,039 --> 00:23:02,559 and things like that that might be able to use 370 00:23:02,599 --> 00:23:06,119 AI to root out fraud or identify in efficiencies and 371 00:23:06,160 --> 00:23:09,920 things like that. And I understand that there's fears, but 372 00:23:09,960 --> 00:23:12,319 there's also real opportunities here for. 373 00:23:12,279 --> 00:23:15,240 Speaker 2: It to get back to the promise and the peril again, right, 374 00:23:15,440 --> 00:23:18,440 And this has been a national issue. You've probably seen 375 00:23:18,480 --> 00:23:25,079 some headlines nationally about insurers using AI and were they 376 00:23:25,119 --> 00:23:30,759 relying solely on an algorithm to deny coverage and insurance, 377 00:23:30,960 --> 00:23:34,680 particularly for specialty care. And there have been several bills filed, 378 00:23:34,920 --> 00:23:38,519 as I mentioned, dealing with healthcare, with mental health, and 379 00:23:38,599 --> 00:23:41,200 with health insurance. And I think the question will be 380 00:23:43,680 --> 00:23:47,200 do you have a bill that denies the use of 381 00:23:47,240 --> 00:23:50,400 AI completely or do you have a bill that says 382 00:23:50,440 --> 00:23:52,440 you can use AI. But as I said, you have 383 00:23:52,519 --> 00:23:54,519 to have a human in the loop, a human has 384 00:23:54,599 --> 00:23:58,680 to review it. And you know there are other bills 385 00:23:58,680 --> 00:24:02,599 that have been filed that say, well, you can use AI. However, 386 00:24:02,599 --> 00:24:05,880 if it's specialty care, the specialist, for instance, has to 387 00:24:05,960 --> 00:24:09,000 review it, so you keep that human in the loop. 388 00:24:09,480 --> 00:24:11,680 And a lot of what we're seeing around the country 389 00:24:11,680 --> 00:24:15,920 and around the world is that discussion of whether it's 390 00:24:16,119 --> 00:24:20,000 in domestic violence cases in Spain where you had a 391 00:24:20,039 --> 00:24:26,880 situation where a particularly police department was relying solely on 392 00:24:27,079 --> 00:24:31,920 AI predictive analysis to say whether an abuse or would 393 00:24:31,920 --> 00:24:34,359 abuse again, and there was not a human in the loop, 394 00:24:34,880 --> 00:24:38,759 and a woman ended up dying. And so a lot 395 00:24:38,759 --> 00:24:42,799 of the conversation now has turned to using it but 396 00:24:43,079 --> 00:24:47,920 ensuring that a human makes the final decision and is reviewing. 397 00:24:48,039 --> 00:24:51,960 So I think it's this discussion of where are you 398 00:24:52,039 --> 00:24:54,519 on this continuum. Do you not use it at all, 399 00:24:55,440 --> 00:24:59,279 do you use it and you solely rely on the AI, 400 00:25:00,160 --> 00:25:03,400 or are you somewhere in the middle in this continuum 401 00:25:03,400 --> 00:25:07,400 where you use it. But you must have humans and 402 00:25:07,519 --> 00:25:10,519 professionals who are in the loop and who are reviewing 403 00:25:10,599 --> 00:25:12,279 and making the final decision. 404 00:25:12,839 --> 00:25:16,359 Speaker 1: How important is it that the legislature figure out some 405 00:25:16,480 --> 00:25:19,359 answers to that question this session. I mean one of 406 00:25:19,400 --> 00:25:22,279 the challenges of the Texas legislature is they only meet 407 00:25:22,319 --> 00:25:24,920 every two years. That's right, at the pace that technology 408 00:25:24,960 --> 00:25:27,480 is growing and changing. Is this sort of their last 409 00:25:27,559 --> 00:25:29,599 chance to sort of put down a marker on this, 410 00:25:29,720 --> 00:25:30,880 do you think? Well? 411 00:25:30,920 --> 00:25:33,160 Speaker 2: I think that's why you have seen so many bills 412 00:25:33,279 --> 00:25:37,319 filed this session. As you said, technology is changing, as 413 00:25:37,359 --> 00:25:41,319 we are doing, as we are talking right now, right, 414 00:25:41,559 --> 00:25:47,279 and with the biennial legislature, you do have limited opportunities. 415 00:25:47,640 --> 00:25:50,559 And again with chat GPT, with what we've seen with 416 00:25:50,640 --> 00:25:54,240 health insurance and others. Yes, I think that there are 417 00:25:54,279 --> 00:25:57,599 many members across the board who feel that it is 418 00:25:57,680 --> 00:26:02,160 important this session to get a handle on this and 419 00:26:02,720 --> 00:26:04,680 pass some legislation. 420 00:26:05,440 --> 00:26:08,960 Speaker 1: Okay, I mean my other question is is the state 421 00:26:09,079 --> 00:26:11,119 level the right level to be doing this? 422 00:26:11,279 --> 00:26:11,440 Speaker 3: Right? 423 00:26:11,480 --> 00:26:13,480 Speaker 1: I mean, a lot of this employment will I mean, 424 00:26:13,839 --> 00:26:16,559 this AI deployment will be happening outside the state but 425 00:26:16,599 --> 00:26:20,400 affecting Texans, but it also affects you know, Californians and 426 00:26:20,599 --> 00:26:24,279 right Vermontors and everyone or else? I mean, should this 427 00:26:24,440 --> 00:26:27,000 not be a federal level discussion as opposed to a 428 00:26:27,039 --> 00:26:28,720 state level well? 429 00:26:28,839 --> 00:26:33,440 Speaker 2: Or should it be a worldwide I mean technology does 430 00:26:33,480 --> 00:26:37,039 not know boundaries, right. And this is a really good 431 00:26:37,079 --> 00:26:41,160 question because as we know, you know, federal law superseded 432 00:26:41,240 --> 00:26:45,039 state laws, and state laws supersede local laws. So the 433 00:26:45,160 --> 00:26:48,640 Austin City of Austin has been looking at policies and 434 00:26:48,799 --> 00:26:51,200 looking closely at what's happening with TREGA. They want to, 435 00:26:51,440 --> 00:26:54,839 you know, align they have common issues and concerns, for instance. 436 00:26:55,279 --> 00:26:58,160 But what you tend to see is when you don't 437 00:26:58,480 --> 00:27:01,440 have action at the federal level. So we have had 438 00:27:01,480 --> 00:27:07,200 no congressional action and we you know, the Biden executive 439 00:27:07,319 --> 00:27:11,480 Order of course no longer exists. And so when you 440 00:27:11,519 --> 00:27:17,400 don't have action at the federal level, and legislators have constituents, 441 00:27:17,480 --> 00:27:20,160 and if those constituents have concerns, what you see is 442 00:27:20,200 --> 00:27:23,519 there's this vacuum, and you will see the states, not 443 00:27:23,680 --> 00:27:28,440 just Texas, step in. And if constituents at the local 444 00:27:28,519 --> 00:27:32,440 level have concerns, right, and the states are not stepping in, 445 00:27:32,720 --> 00:27:36,240 you will see individual cities step in. And then you 446 00:27:36,279 --> 00:27:38,680 will see industry say, wait a minute, we have this 447 00:27:38,799 --> 00:27:43,480 patchwork of different cities within the state or different states, right. 448 00:27:44,920 --> 00:27:50,200 I think that what happens in a Texas is very 449 00:27:50,240 --> 00:27:56,839 important whether it's textbooks or AI right regulation because we 450 00:27:57,480 --> 00:28:01,519 have a very large population here in this state, right, 451 00:28:01,960 --> 00:28:05,200 and so that's important whether it's Texas or California or Florida, 452 00:28:05,480 --> 00:28:09,759 New York. And you do see this kind of alignment 453 00:28:10,960 --> 00:28:15,599 of states who have already passed or are considering around 454 00:28:15,640 --> 00:28:19,799 this NIST model, the one that the e used use, 455 00:28:19,839 --> 00:28:23,160 the one that Colorado used around mitigating risk. 456 00:28:24,039 --> 00:28:25,880 Speaker 3: Okay, okay, and. 457 00:28:27,440 --> 00:28:31,039 Speaker 1: What about just there's other aspects to this too, which 458 00:28:31,079 --> 00:28:34,599 is trying to attract you know, while you're thinking about 459 00:28:34,640 --> 00:28:39,599 how you regulate it, you're also trying to attract companies 460 00:28:39,680 --> 00:28:43,359 and developers into this state. I mean, Joe Lonsdale is 461 00:28:43,400 --> 00:28:46,759 an example of that. You came from California two crisis. 462 00:28:47,000 --> 00:28:49,480 There has been a lot of activity recently. You saw 463 00:28:49,599 --> 00:28:53,119 Apple make an announcement of a development data center in Houston. 464 00:28:54,160 --> 00:28:57,319 Facebook bringing their content moderation staff here. I mean yes, 465 00:28:57,519 --> 00:29:00,839 you know, particularly after Trump one the election, there is 466 00:29:01,000 --> 00:29:03,480 data centers exactly. There seems to be a lot of 467 00:29:03,599 --> 00:29:07,640 interest in bringing folks here. But that creates its own challenges, 468 00:29:07,680 --> 00:29:09,400 not just in terms of how you regulate it, but 469 00:29:09,400 --> 00:29:10,640 also how do you build. 470 00:29:10,480 --> 00:29:12,119 Speaker 3: Up the infrastructure to support it. 471 00:29:12,599 --> 00:29:14,759 Speaker 1: Let's talk a little bit about the power grid and 472 00:29:14,799 --> 00:29:16,039 how that ruts into this. 473 00:29:16,559 --> 00:29:20,119 Speaker 2: Yes, certainly we've heard a lot about the power grid 474 00:29:20,160 --> 00:29:23,839 in Texas over the past few years. We seem to 475 00:29:25,039 --> 00:29:29,000 everyone or be having some very very cold weather at times, 476 00:29:29,720 --> 00:29:32,240 and we know that we have our own grid. Now 477 00:29:32,240 --> 00:29:36,279 there's discussion about some connectivity with another grid, but we'll 478 00:29:36,279 --> 00:29:39,079 put that aside for the moment. Texas has its own 479 00:29:39,119 --> 00:29:42,279 power grid. And it's not just power, it's water. So 480 00:29:42,400 --> 00:29:47,240 these data centers, whether they're beings for AI or crypto right, 481 00:29:48,279 --> 00:29:51,480 use an enormous amount of power and an enormous amount 482 00:29:51,519 --> 00:29:55,519 of water and they're noisy, right, And so there are 483 00:29:55,599 --> 00:29:59,119 concerns about the power grid and will there be the 484 00:29:59,200 --> 00:30:03,279 capacity and should there be requirements for some of these 485 00:30:03,359 --> 00:30:06,000 data centers to have their own source of power you 486 00:30:06,039 --> 00:30:11,039 know many nuclear or other sources that people are talking about. 487 00:30:11,440 --> 00:30:14,359 And what does it mean also for water, we know 488 00:30:14,480 --> 00:30:19,359 that this is a major session for water and last 489 00:30:19,359 --> 00:30:21,680 session was too a lot of funding, but this is 490 00:30:21,720 --> 00:30:26,559 a really really major session for water and water supply 491 00:30:26,680 --> 00:30:30,720 and distribution. And how does that fit in with the 492 00:30:30,799 --> 00:30:32,839 data centers because they also use a lot of water? 493 00:30:33,119 --> 00:30:35,880 Speaker 1: Absolutely, absolutely, and then there's one more aspect that I 494 00:30:35,920 --> 00:30:38,319 want to talk about, which is how are we preparing 495 00:30:39,200 --> 00:30:44,039 you know, our students are our future workforce for an 496 00:30:44,119 --> 00:30:49,319 AI world. Is that a topic that is that is 497 00:30:49,759 --> 00:30:51,559 being discussed in the capital as well. Oh? 498 00:30:51,640 --> 00:30:54,519 Speaker 2: Absolutely, And it's a topic that I have spent a 499 00:30:54,559 --> 00:30:57,039 lot of time on the past years and continue to. 500 00:30:57,200 --> 00:31:02,240 You know, I think that learning begins, you know, the 501 00:31:02,319 --> 00:31:04,880 day you're born, and it ends the day you leave 502 00:31:04,960 --> 00:31:08,079 this earth, and that it's very important that we be 503 00:31:08,200 --> 00:31:12,720 cognizant starting in elementary school all the way through people's PhDs, 504 00:31:13,160 --> 00:31:17,680 that they have the appropriate curriculum related to AI. You know, 505 00:31:18,119 --> 00:31:21,119 is coding going away, Well, it's coding at a different level. 506 00:31:22,039 --> 00:31:24,880 I think that it's very important that we focus on 507 00:31:25,359 --> 00:31:31,480 our students and the residents being continuous learners, having critical 508 00:31:31,519 --> 00:31:35,400 thinking skills, having people's skills, being able to write, and 509 00:31:35,640 --> 00:31:39,160 continuous learning, and that we look at jobs where they 510 00:31:39,200 --> 00:31:43,839 may need new trading right as we say, upskilling or reskilling, 511 00:31:44,799 --> 00:31:48,640 and that this be part of our curriculum in an 512 00:31:48,680 --> 00:31:55,319 appropriate manner throughout education and beyond, whether we're partnering with 513 00:31:56,240 --> 00:32:00,640 community colleges or industry. And there are many that need 514 00:32:00,759 --> 00:32:06,519 within their own organizations to have this continuous training, whether 515 00:32:06,559 --> 00:32:11,519 you're a large city or a major nonprofit, or a 516 00:32:11,599 --> 00:32:14,680 big company or even a smaller company. 517 00:32:14,839 --> 00:32:17,359 Speaker 1: So I mean, I hear when people talk about sort 518 00:32:17,359 --> 00:32:22,240 of AI's impact on work in the you know, near future, 519 00:32:22,680 --> 00:32:25,440 they talk a lot about how, you know, AI can 520 00:32:25,480 --> 00:32:29,559 be a very very speedy and useful intern or entry 521 00:32:29,640 --> 00:32:30,440 level employee. 522 00:32:30,480 --> 00:32:32,960 Speaker 2: Right right, everybody's adding an assistant exactly. 523 00:32:33,079 --> 00:32:35,799 Speaker 1: You can you talk about coding it? Can it can 524 00:32:35,839 --> 00:32:39,960 write code when given direction, Yes, if you're if you're 525 00:32:39,960 --> 00:32:41,799 at a law firm, you know, it can maybe do 526 00:32:41,920 --> 00:32:44,799 some of that paralegal work. That's that early kind of 527 00:32:44,839 --> 00:32:49,039 work in sort of reviewing documents, legal system exactly what 528 00:32:49,160 --> 00:32:54,559 it's not quite there yet on is making big strategic 529 00:32:54,920 --> 00:32:58,319 decisions and everything like that. So how how does the 530 00:32:58,480 --> 00:33:02,200 education system adjust for that world? 531 00:33:02,640 --> 00:33:04,720 Speaker 2: One of the ways that the education system needs to 532 00:33:04,759 --> 00:33:08,240 adjust for that world is really focusing on the critical 533 00:33:08,319 --> 00:33:13,200 thinking skills of students. Right, So, you may be a 534 00:33:15,559 --> 00:33:19,079 financial analyst, but it's no longer there are no more 535 00:33:19,279 --> 00:33:23,000 Excel spreadsheets, right, you have AI, and you need those 536 00:33:23,160 --> 00:33:27,559 higher link level critical thinking skills to do the analysis. 537 00:33:27,920 --> 00:33:29,799 You may be a coder, but you're coding at a 538 00:33:29,799 --> 00:33:33,279 different level because AI is doing the we'll call it 539 00:33:33,599 --> 00:33:39,960 fundamental coding. Right. You know, you may be a paralegal, 540 00:33:40,039 --> 00:33:44,039 but you are now needing to think at that higher level. 541 00:33:44,480 --> 00:33:47,400 And so that is really what is so important, those 542 00:33:47,480 --> 00:33:53,680 analytical skills, those critical thinking skills, being nimble. Also, there 543 00:33:53,680 --> 00:33:58,160 are various situations where AI does not and I don't 544 00:33:58,160 --> 00:34:01,319 think ever will have the capability. And that's for instance, 545 00:34:01,359 --> 00:34:05,519 if empathy is required, right, if it's a situation with 546 00:34:05,599 --> 00:34:07,279 a doctor or a lawyer, or a teacher or an 547 00:34:07,400 --> 00:34:10,360 educator where you have to have those people skills, the 548 00:34:10,400 --> 00:34:13,679 empathy leadership within organizations. 549 00:34:14,679 --> 00:34:19,920 Speaker 1: Okay, and so I guess here's my last question. How 550 00:34:19,960 --> 00:34:24,199 confident do you feel in the state's ability to get 551 00:34:24,199 --> 00:34:29,599 this right this session? How this feels like a complicated issue. 552 00:34:30,519 --> 00:34:32,679 It feels like there's a lot of nuance, a lot 553 00:34:32,719 --> 00:34:38,119 of expertise needed. Is the Texas legislature equipped to end 554 00:34:38,159 --> 00:34:40,079 in a good place in early June? 555 00:34:42,719 --> 00:34:48,639 Speaker 2: Texas legislature has dealt, is dealing and will deal with 556 00:34:48,800 --> 00:34:52,280 in the future a lot of very complicated issues. And 557 00:34:52,400 --> 00:34:57,159 I think that the process is set up, you know, 558 00:34:57,280 --> 00:35:00,360 it's set up frankly, to kill bills, not to pass them. Say, 559 00:35:00,599 --> 00:35:05,199 visualize the Summer Olympics with those people who are running 560 00:35:05,199 --> 00:35:08,119 the hurdles one after another. So the system is set 561 00:35:08,199 --> 00:35:11,599 up really to vet bills, to get input, to have amendments, 562 00:35:11,639 --> 00:35:14,400 to have discussion, to get to a place where people 563 00:35:14,400 --> 00:35:15,280 feel comfortable. 564 00:35:16,199 --> 00:35:19,960 Speaker 1: All right, well, we will watch and see what happens. Indeed, 565 00:35:20,679 --> 00:35:22,679 thank you so much for being here. Thank you to 566 00:35:23,119 --> 00:35:27,280 Rob and Chris. A reminder the Texas Tribuunion membership program 567 00:35:27,360 --> 00:35:31,880 as participating in Amplify Austin this week. Please check out 568 00:35:31,880 --> 00:35:34,719 our website if you would like to donate and contribute. 569 00:35:35,599 --> 00:35:38,840 Eleanor and James will be back next week and we'll 570 00:35:38,880 --> 00:35:39,280 see you then