1 00:00:01,679 --> 00:00:04,240 Every year, Becker's annual meeting brings health care 2 00:00:04,240 --> 00:00:06,799 leaders together to unpack the most pressing issues 3 00:00:06,799 --> 00:00:07,779 facing the industry. 4 00:00:08,160 --> 00:00:10,980 And every year, those conversations shift in profound 5 00:00:11,039 --> 00:00:12,419 and unexpected ways. 6 00:00:12,785 --> 00:00:15,025 This April, more than 3,500 7 00:00:15,025 --> 00:00:17,204 healthcare executives will return to Chicago 8 00:00:17,505 --> 00:00:19,445 for Becker's sixteenth annual meeting. 9 00:00:19,824 --> 00:00:22,785 Seven ninety five elite speakers will offer new 10 00:00:22,785 --> 00:00:25,809 lessons, new case studies, and predictions about what 11 00:00:25,809 --> 00:00:26,550 comes next. 12 00:00:26,850 --> 00:00:29,109 Join us April 13 through the sixteenth. 13 00:00:29,489 --> 00:00:33,890 For the agenda and event details, visit beckershospitalreview.com 14 00:00:33,890 --> 00:00:35,809 and click on the events tab in the 15 00:00:35,809 --> 00:00:36,629 upper right. 16 00:00:37,969 --> 00:00:40,289 Welcome to the Becker's Healthcare podcast. I'm Chris 17 00:00:40,289 --> 00:00:42,304 Sosa, your host. I'm very happy today to 18 00:00:42,304 --> 00:00:44,085 be joined by doctor Giovanni Bialimonte. 19 00:00:44,625 --> 00:00:47,765 He's a professor of pediatrics, biochemistry, and molecular 20 00:00:47,905 --> 00:00:50,244 biology and a researcher at Tulane University. 21 00:00:50,704 --> 00:00:52,304 He also chaired his task force on the 22 00:00:52,304 --> 00:00:54,179 use of AI in research, which is our 23 00:00:54,179 --> 00:00:55,799 topic for our discussion today. 24 00:00:56,100 --> 00:00:58,520 Doctor Bialimonte, thank you for joining us today. 25 00:00:59,060 --> 00:01:00,979 Thank you for inviting me, Chris. I really 26 00:01:00,979 --> 00:01:01,880 appreciate it. 27 00:01:02,420 --> 00:01:04,840 Wonderful. So doctor, you've been, researching 28 00:01:05,219 --> 00:01:07,239 a number of topics for better 29 00:01:07,540 --> 00:01:09,075 part of thirty years now. 30 00:01:09,474 --> 00:01:10,914 But for those in our audience who may 31 00:01:10,914 --> 00:01:11,494 not be, 32 00:01:12,034 --> 00:01:15,314 intimately familiar with yourself and your organization, could 33 00:01:15,314 --> 00:01:17,155 could you please introduce yourself and let us 34 00:01:17,155 --> 00:01:18,454 know a little bit about that? 35 00:01:18,754 --> 00:01:21,715 Yeah. I'm a physician scientist, basically, and I've 36 00:01:21,715 --> 00:01:23,655 been practicing respiratory medicine 37 00:01:24,680 --> 00:01:27,099 clinically for about three decades. 38 00:01:27,480 --> 00:01:29,980 And about two decades, I've been 39 00:01:30,520 --> 00:01:32,939 generously funded, for my research, 40 00:01:33,319 --> 00:01:34,459 in several areas, 41 00:01:34,840 --> 00:01:36,540 of biology and respiratory 42 00:01:36,920 --> 00:01:38,379 diseases by NIH. 43 00:01:39,134 --> 00:01:39,634 I 44 00:01:40,655 --> 00:01:43,634 I added also a significant component to administrative 45 00:01:43,935 --> 00:01:45,155 duties over time, 46 00:01:46,015 --> 00:01:49,534 serving as division chief first, the department chair 47 00:01:49,534 --> 00:01:50,515 for many years. 48 00:01:51,549 --> 00:01:53,969 Then I spent seven years at Cleveland Clinic 49 00:01:54,109 --> 00:01:56,829 as the president of the Cleveland Clinic Children's 50 00:01:56,829 --> 00:01:57,329 Hospital. 51 00:01:57,710 --> 00:02:00,750 And most recently, I joined, Tulane. I worked 52 00:02:00,750 --> 00:02:02,990 for six years. I served as vice president 53 00:02:02,990 --> 00:02:03,650 for research. 54 00:02:04,334 --> 00:02:04,834 Recently, 55 00:02:05,215 --> 00:02:07,935 I stepped down for that and started my 56 00:02:07,935 --> 00:02:09,875 first sabbatical in my career, 57 00:02:10,574 --> 00:02:12,034 which I'm, thoroughly 58 00:02:12,974 --> 00:02:13,474 enjoying. 59 00:02:14,175 --> 00:02:17,395 And, the sabbatical has given me, the opportunity 60 00:02:17,455 --> 00:02:18,514 to to to 61 00:02:19,229 --> 00:02:19,729 evolve 62 00:02:20,189 --> 00:02:21,650 new areas of research, 63 00:02:22,430 --> 00:02:23,169 but also, 64 00:02:23,629 --> 00:02:24,129 to, 65 00:02:24,830 --> 00:02:28,129 go deeper into my ongoing interest as 66 00:02:28,590 --> 00:02:30,129 now several years old, 67 00:02:30,750 --> 00:02:32,129 for artificial intelligence, 68 00:02:32,590 --> 00:02:33,650 quantum computing, 69 00:02:34,284 --> 00:02:35,504 and advanced technologies 70 00:02:36,044 --> 00:02:38,685 applied to health care that, as you know, 71 00:02:38,685 --> 00:02:41,004 I'm sure everybody will agree on this. I'm 72 00:02:41,004 --> 00:02:42,145 gonna completely 73 00:02:43,245 --> 00:02:45,104 change the the the the landscape, 74 00:02:45,645 --> 00:02:46,625 of how we 75 00:02:46,980 --> 00:02:48,280 think and how we, 76 00:02:48,740 --> 00:02:51,219 manage and how we deliver health care, 77 00:02:51,540 --> 00:02:53,400 for many, many years. 78 00:02:54,099 --> 00:02:56,340 You can say that again, doctor Bienle. There's 79 00:02:56,340 --> 00:02:58,360 so much to discuss. And as I mentioned, 80 00:02:58,500 --> 00:03:00,659 you chaired Tulane's task force on AI and 81 00:03:00,659 --> 00:03:01,159 research. 82 00:03:02,074 --> 00:03:03,834 So let's start there. So could you please 83 00:03:03,834 --> 00:03:06,314 take us through simply how the task force 84 00:03:06,314 --> 00:03:06,814 evolved, 85 00:03:07,275 --> 00:03:08,794 which I know could take a lot of 86 00:03:08,794 --> 00:03:10,715 time, but that's okay. We got time. And 87 00:03:10,715 --> 00:03:13,275 just highlight the the most significant findings from 88 00:03:13,275 --> 00:03:14,414 the last couple years. 89 00:03:15,150 --> 00:03:17,409 Well, you know, it was a great experience 90 00:03:17,469 --> 00:03:18,689 because I had the opportunity 91 00:03:19,069 --> 00:03:20,930 to interact with a lot of, 92 00:03:22,349 --> 00:03:25,169 brilliant minds, and most of them actually 93 00:03:25,709 --> 00:03:28,004 with the little to do with health care, 94 00:03:28,485 --> 00:03:28,965 including, 95 00:03:29,365 --> 00:03:29,865 engineers, 96 00:03:30,805 --> 00:03:31,305 mathematicians, 97 00:03:33,605 --> 00:03:36,105 and the like. And so open, 98 00:03:37,284 --> 00:03:37,784 several 99 00:03:38,245 --> 00:03:39,465 different angles 100 00:03:39,844 --> 00:03:40,485 to read, 101 00:03:41,610 --> 00:03:43,930 you know, to read what the opportunities are 102 00:03:43,930 --> 00:03:46,650 and what the risks are for for for 103 00:03:46,650 --> 00:03:47,870 this new technology. 104 00:03:48,650 --> 00:03:49,150 And, 105 00:03:49,770 --> 00:03:52,030 and we wrote a blueprint that 106 00:03:52,569 --> 00:03:53,069 summarizes, 107 00:03:54,745 --> 00:03:57,405 some of these concept that emerged. And, 108 00:03:59,064 --> 00:04:01,004 to make a a very short summary, 109 00:04:01,625 --> 00:04:03,224 there is no doubt that, 110 00:04:03,705 --> 00:04:06,425 the specific area that we, were interested in, 111 00:04:06,425 --> 00:04:07,405 which was research, 112 00:04:07,719 --> 00:04:09,580 is gonna be impacted dramatically 113 00:04:10,439 --> 00:04:11,900 in any component 114 00:04:12,680 --> 00:04:14,539 by by the introduction 115 00:04:14,840 --> 00:04:16,060 of artificial intelligence, 116 00:04:17,560 --> 00:04:18,540 already is. 117 00:04:19,480 --> 00:04:22,040 I predict, and I'm a little bit radical 118 00:04:22,040 --> 00:04:23,784 in this, but I predict that, 119 00:04:24,185 --> 00:04:26,125 virtually every single component 120 00:04:26,904 --> 00:04:29,084 of what today is the administration 121 00:04:29,464 --> 00:04:29,964 management 122 00:04:30,425 --> 00:04:32,284 or grants, for example, is gonna 123 00:04:32,904 --> 00:04:33,404 become, 124 00:04:34,345 --> 00:04:36,925 virtually independent from human input. 125 00:04:37,339 --> 00:04:39,520 And the reason for this is that most 126 00:04:39,580 --> 00:04:40,080 are 127 00:04:41,100 --> 00:04:43,439 repetitive tasks that the computers 128 00:04:43,819 --> 00:04:46,720 will do already do in some part, 129 00:04:48,379 --> 00:04:50,699 with with the in a fraction of the 130 00:04:50,699 --> 00:04:51,199 time, 131 00:04:51,535 --> 00:04:52,834 with minimal cost 132 00:04:53,134 --> 00:04:54,995 and with the incredible visibility. 133 00:04:55,615 --> 00:04:58,115 For example, the preparation of a grant, 134 00:04:58,654 --> 00:05:00,595 the the assembly of a grant, 135 00:05:01,134 --> 00:05:03,855 the submission of a grant, the verification of 136 00:05:03,855 --> 00:05:04,435 a grant, 137 00:05:05,009 --> 00:05:06,229 some other functions 138 00:05:06,529 --> 00:05:07,029 that 139 00:05:07,410 --> 00:05:08,870 already a lot of investigators 140 00:05:09,410 --> 00:05:11,970 are dealing with, but they're gonna become more 141 00:05:11,970 --> 00:05:12,629 and more, 142 00:05:13,649 --> 00:05:15,189 stringent. For example, 143 00:05:16,610 --> 00:05:17,110 recently 144 00:05:17,569 --> 00:05:19,490 in the last years, we have seen a 145 00:05:19,490 --> 00:05:22,604 significant increase in the cases of 146 00:05:23,785 --> 00:05:24,764 plagiarism or, 147 00:05:26,345 --> 00:05:26,845 publication 148 00:05:27,225 --> 00:05:28,185 of, of, 149 00:05:28,745 --> 00:05:29,964 data that were not, 150 00:05:30,904 --> 00:05:33,004 either accurate or completely fabricated. 151 00:05:33,699 --> 00:05:35,620 And the reason for that increase is is 152 00:05:35,620 --> 00:05:36,439 quite simple. 153 00:05:36,819 --> 00:05:39,080 A lot of the fabrication of data 154 00:05:39,460 --> 00:05:42,339 could escape at UNI, but will not escape 155 00:05:42,339 --> 00:05:44,360 at the visual intelligence and computerized. 156 00:05:46,020 --> 00:05:49,355 And today, there are plenty of softwares that 157 00:05:49,355 --> 00:05:49,855 allow 158 00:05:50,235 --> 00:05:51,774 people to actually verify 159 00:05:52,394 --> 00:05:52,875 whether, 160 00:05:53,194 --> 00:05:54,074 something has been, 161 00:05:54,714 --> 00:05:55,214 simply, 162 00:05:56,394 --> 00:05:58,495 built on somebody's imagination 163 00:05:58,795 --> 00:06:01,194 or whether it's real data. So there are 164 00:06:01,194 --> 00:06:03,134 millions of different aspects 165 00:06:03,889 --> 00:06:05,330 that artificial intelligence 166 00:06:06,050 --> 00:06:09,430 another one, for example, I do epidemiologic research 167 00:06:09,490 --> 00:06:10,710 and population research. 168 00:06:11,810 --> 00:06:12,290 And, 169 00:06:13,810 --> 00:06:15,970 the current study that I'm running is the 170 00:06:15,970 --> 00:06:17,990 first one in which we're gonna use artificial 171 00:06:18,210 --> 00:06:18,710 intelligence 172 00:06:19,355 --> 00:06:21,455 algorithms to analyze the data. 173 00:06:21,915 --> 00:06:24,334 And, already, we're seeing a lot of, 174 00:06:25,435 --> 00:06:25,935 driving, 175 00:06:27,514 --> 00:06:28,495 phenomena that, 176 00:06:30,235 --> 00:06:31,115 very unlikely 177 00:06:31,514 --> 00:06:33,694 it's very unlikely that we could have picked 178 00:06:34,339 --> 00:06:36,680 if we were just using our 179 00:06:37,379 --> 00:06:37,879 brains. 180 00:06:38,339 --> 00:06:38,839 So 181 00:06:40,100 --> 00:06:42,819 in an extreme world, basically, I will say 182 00:06:42,819 --> 00:06:43,139 that, 183 00:06:44,180 --> 00:06:45,240 a lot of experiments 184 00:06:45,699 --> 00:06:46,519 may become 185 00:06:47,379 --> 00:06:47,879 obsolete, 186 00:06:48,895 --> 00:06:51,395 because it can be can be reproduced 187 00:06:52,495 --> 00:06:53,714 in digital formats, 188 00:06:54,334 --> 00:06:54,834 and 189 00:06:55,375 --> 00:06:55,694 and, 190 00:06:56,254 --> 00:06:56,915 and therefore, 191 00:06:58,814 --> 00:07:01,475 problem solved in a fraction of the time. 192 00:07:01,879 --> 00:07:03,720 And so all the all those things are 193 00:07:03,720 --> 00:07:04,939 great, and I expect 194 00:07:05,720 --> 00:07:06,459 a significant 195 00:07:06,919 --> 00:07:07,419 acceleration 196 00:07:07,800 --> 00:07:09,899 in the development, for example, of, 197 00:07:10,839 --> 00:07:11,659 new drugs, 198 00:07:11,959 --> 00:07:12,360 of, 199 00:07:13,000 --> 00:07:13,740 new therapeutics. 200 00:07:15,055 --> 00:07:17,714 I suspect that one of the areas of 201 00:07:18,334 --> 00:07:19,394 immediate progress, 202 00:07:19,694 --> 00:07:21,935 and and substantial progress is gonna be in 203 00:07:21,935 --> 00:07:22,834 robotic surgery, 204 00:07:23,294 --> 00:07:26,014 which already is, is evolving and so forth. 205 00:07:26,014 --> 00:07:28,274 It's gonna it's gonna be a a complete 206 00:07:28,415 --> 00:07:28,915 new 207 00:07:30,319 --> 00:07:32,420 word. I I a friend of mine, 208 00:07:33,040 --> 00:07:34,660 sometime ago said that 209 00:07:35,120 --> 00:07:37,920 to apply for, med school or law law 210 00:07:37,920 --> 00:07:38,899 school today 211 00:07:39,199 --> 00:07:41,995 is is stupid because by the time you 212 00:07:41,995 --> 00:07:42,495 graduate, 213 00:07:43,115 --> 00:07:44,954 the computers are gone and the and the 214 00:07:44,954 --> 00:07:46,175 robots are gonna do 215 00:07:46,475 --> 00:07:47,774 the work of doctors 216 00:07:48,154 --> 00:07:48,634 and, 217 00:07:49,194 --> 00:07:51,774 lawyers. It's a little bit extreme, but 218 00:07:52,154 --> 00:07:54,975 the the this history of artificial intelligence 219 00:07:55,660 --> 00:07:57,120 has shown us that, 220 00:07:57,579 --> 00:07:58,319 things that 221 00:07:58,779 --> 00:08:00,800 sound stupid, sound impossible, 222 00:08:01,660 --> 00:08:02,160 become 223 00:08:02,540 --> 00:08:04,399 very possible and very, 224 00:08:05,180 --> 00:08:06,160 almost simple, 225 00:08:06,939 --> 00:08:08,720 within years. And so 226 00:08:09,115 --> 00:08:11,595 I think that definitely the new doctors and 227 00:08:11,595 --> 00:08:13,534 the new lawyers are gonna 228 00:08:14,474 --> 00:08:17,854 be collaborating primarily with the with the computers 229 00:08:18,235 --> 00:08:18,894 and robots, 230 00:08:20,314 --> 00:08:23,169 and the the the the scope and and 231 00:08:23,169 --> 00:08:25,569 and the and the applications of their work 232 00:08:25,569 --> 00:08:26,870 is gonna be completely, 233 00:08:27,490 --> 00:08:27,990 revolutionized. 234 00:08:29,329 --> 00:08:30,310 At the same time, 235 00:08:31,889 --> 00:08:35,409 it was an excellent opportunity to collaborating with 236 00:08:35,409 --> 00:08:36,070 my colleagues 237 00:08:37,394 --> 00:08:38,134 to assess 238 00:08:38,514 --> 00:08:41,175 what I think needs to be central 239 00:08:41,715 --> 00:08:43,014 in the in our analysis 240 00:08:43,394 --> 00:08:44,774 of, artificial intelligence 241 00:08:45,795 --> 00:08:48,535 and new technologies, and that are the risks 242 00:08:48,835 --> 00:08:51,254 that are associated with this, technology. 243 00:08:51,634 --> 00:08:52,295 And frankly, 244 00:08:53,450 --> 00:08:55,450 this is becoming a a main focus of 245 00:08:55,450 --> 00:08:57,070 my of my interest. 246 00:08:57,529 --> 00:08:59,610 And one of the things that we did 247 00:08:59,610 --> 00:09:01,149 was we tried to categorize, 248 00:09:02,970 --> 00:09:05,230 the different types of risks that are associated 249 00:09:05,529 --> 00:09:08,355 with the with the the introduction of, for 250 00:09:08,355 --> 00:09:09,495 example, Gen AI. 251 00:09:10,355 --> 00:09:12,774 And it specified that at the time we 252 00:09:12,834 --> 00:09:14,774 basically were discussing these matters, 253 00:09:15,394 --> 00:09:17,735 everybody was concentrating on Gen AI. 254 00:09:18,514 --> 00:09:19,014 Today, 255 00:09:19,610 --> 00:09:22,490 most people concentrate on Gen AI with it 256 00:09:22,490 --> 00:09:23,790 is a totally different 257 00:09:24,490 --> 00:09:24,990 universe, 258 00:09:25,930 --> 00:09:26,889 and and, 259 00:09:27,250 --> 00:09:28,750 and, it's gonna 260 00:09:29,290 --> 00:09:30,509 make most 261 00:09:31,050 --> 00:09:32,924 or all of our conclusions, 262 00:09:36,504 --> 00:09:37,004 irrelevant 263 00:09:37,704 --> 00:09:39,404 because Genetec AI 264 00:09:40,105 --> 00:09:41,804 is not just an evolution 265 00:09:42,904 --> 00:09:45,625 of, Gen AI. It is a it's a 266 00:09:45,625 --> 00:09:46,934 a a change, 267 00:09:47,250 --> 00:09:47,750 a 268 00:09:48,690 --> 00:09:49,990 drastic, complete 269 00:09:50,450 --> 00:09:51,669 change in the way 270 00:09:52,129 --> 00:09:54,529 we are gonna interact with the with the 271 00:09:54,610 --> 00:09:55,429 with this technology. 272 00:09:56,289 --> 00:09:58,850 At at the time, talking about GenAI, we 273 00:09:58,850 --> 00:09:59,350 identified 274 00:10:00,049 --> 00:10:00,870 the the major 275 00:10:01,409 --> 00:10:02,950 types of risks as 276 00:10:03,625 --> 00:10:06,684 intellectual property risk, for example, and the confidentiality 277 00:10:07,065 --> 00:10:07,565 breach. 278 00:10:08,985 --> 00:10:10,125 These technologies 279 00:10:10,664 --> 00:10:13,084 are gonna make almost impossible to keep, 280 00:10:14,105 --> 00:10:14,584 data, 281 00:10:15,065 --> 00:10:15,565 confidential, 282 00:10:15,944 --> 00:10:18,480 safe, and so forth, not with the current 283 00:10:18,480 --> 00:10:18,980 technologies. 284 00:10:20,000 --> 00:10:21,779 That is gonna create a lot of problem 285 00:10:21,919 --> 00:10:22,559 for the, 286 00:10:23,200 --> 00:10:24,419 respect of, 287 00:10:25,039 --> 00:10:27,839 intellectual property. It's gonna create a lot of 288 00:10:27,839 --> 00:10:28,339 problem 289 00:10:28,639 --> 00:10:29,139 with 290 00:10:29,919 --> 00:10:31,360 the attempts to block, 291 00:10:32,705 --> 00:10:36,545 individuals that are trying to get into critical 292 00:10:36,545 --> 00:10:37,045 databases. 293 00:10:38,144 --> 00:10:40,804 And that becomes, can become very problematic 294 00:10:41,105 --> 00:10:41,585 because, 295 00:10:42,545 --> 00:10:43,684 I give you an example. 296 00:10:44,720 --> 00:10:46,720 We know very well that there are very 297 00:10:46,720 --> 00:10:48,740 large databases already in existence, 298 00:10:50,399 --> 00:10:53,139 containing genomic data on on individuals. 299 00:10:54,240 --> 00:10:56,879 And, and this new technology is gonna make, 300 00:10:57,600 --> 00:10:59,264 are gonna make almost impossible to 301 00:11:00,125 --> 00:11:01,264 keep this safe, 302 00:11:02,605 --> 00:11:04,705 unless we develop a new, 303 00:11:05,084 --> 00:11:06,384 very complex strategies 304 00:11:06,764 --> 00:11:09,184 for, to secure those data. 305 00:11:09,644 --> 00:11:13,105 Another element is the biased and the balanced 306 00:11:13,325 --> 00:11:13,825 coverage. 307 00:11:15,509 --> 00:11:17,910 It is true that, some people see in 308 00:11:17,910 --> 00:11:21,029 AI, a democratic force that is gonna put 309 00:11:21,029 --> 00:11:23,269 everybody in the same level. That that is 310 00:11:23,269 --> 00:11:23,769 not 311 00:11:24,149 --> 00:11:27,029 necessarily gonna happen. There is a very big 312 00:11:27,029 --> 00:11:28,294 risk that, 313 00:11:29,714 --> 00:11:31,495 the GI systems are trained, 314 00:11:32,355 --> 00:11:34,434 on a large amount of data, and the 315 00:11:34,434 --> 00:11:35,554 data is not, 316 00:11:36,195 --> 00:11:37,254 heavily distributed, 317 00:11:37,634 --> 00:11:38,615 does not give 318 00:11:39,809 --> 00:11:40,870 a fair, 319 00:11:43,090 --> 00:11:45,429 weight to all the components of society. 320 00:11:45,970 --> 00:11:47,269 So that can 321 00:11:48,450 --> 00:11:50,950 actually increase the risk of, 322 00:11:52,769 --> 00:11:53,269 inequalities. 323 00:11:54,315 --> 00:11:56,975 Another element is, the the cost. 324 00:11:57,754 --> 00:12:00,154 Attention intelligence costs a lot of money, and 325 00:12:00,154 --> 00:12:02,075 it's gonna break a lot of banks, and 326 00:12:02,075 --> 00:12:02,735 it's gonna 327 00:12:03,035 --> 00:12:04,554 be out of the reach of a lot 328 00:12:04,554 --> 00:12:05,215 of people. 329 00:12:05,835 --> 00:12:07,754 And one of the most critical area of 330 00:12:07,754 --> 00:12:09,215 cost is gonna be energy. 331 00:12:09,779 --> 00:12:11,080 It's not, by, 332 00:12:12,019 --> 00:12:13,139 serendipity that, 333 00:12:13,579 --> 00:12:14,019 China's, 334 00:12:15,459 --> 00:12:16,839 run a very aggressive 335 00:12:17,940 --> 00:12:20,679 campaign for many years to increase their ability 336 00:12:20,820 --> 00:12:23,845 to have large sources of energy. Because, 337 00:12:24,545 --> 00:12:26,004 this is, an incredibly 338 00:12:26,384 --> 00:12:26,884 unprecedented, 339 00:12:27,825 --> 00:12:28,325 unprecedented 340 00:12:29,345 --> 00:12:29,845 requirement 341 00:12:30,384 --> 00:12:31,285 on the, 342 00:12:31,985 --> 00:12:32,485 power, 343 00:12:32,945 --> 00:12:33,845 need needs, 344 00:12:34,304 --> 00:12:36,404 that we had before AI. 345 00:12:36,839 --> 00:12:38,039 Another one is the, 346 00:12:39,559 --> 00:12:40,779 ecosystem volatility. 347 00:12:41,959 --> 00:12:43,100 So in other terms, 348 00:12:43,879 --> 00:12:45,659 we were used to change 349 00:12:46,039 --> 00:12:47,339 and upgrade systems 350 00:12:47,720 --> 00:12:48,220 every 351 00:12:49,079 --> 00:12:50,459 certain number of years. 352 00:12:51,295 --> 00:12:52,894 Pretty soon, we are gonna go into the 353 00:12:52,894 --> 00:12:53,394 weeks. 354 00:12:54,095 --> 00:12:56,654 And, a lot of technologies are evolving at 355 00:12:56,654 --> 00:12:58,675 a speed that that is unprecedented. 356 00:12:59,375 --> 00:13:02,014 And, therefore, that is may create problems because, 357 00:13:03,690 --> 00:13:06,090 you know, you acquire a certain technology and 358 00:13:06,090 --> 00:13:06,490 becomes, 359 00:13:07,290 --> 00:13:10,490 deja vu within within months. So that creates, 360 00:13:10,490 --> 00:13:12,429 again, a significant cost problem. 361 00:13:12,889 --> 00:13:15,610 And I left for last, the one that 362 00:13:15,610 --> 00:13:17,149 I think is most concerning 363 00:13:18,554 --> 00:13:20,315 in terms that the more we rely on 364 00:13:20,315 --> 00:13:22,875 artificial intelligence, the more we are at risk 365 00:13:22,875 --> 00:13:24,254 of the so called hallucinations. 366 00:13:24,875 --> 00:13:25,774 Artificial intelligence 367 00:13:26,394 --> 00:13:27,934 is not perfect. 368 00:13:29,595 --> 00:13:30,975 I think it's gonna become 369 00:13:31,409 --> 00:13:33,750 less and less imperfect over time, but, 370 00:13:34,289 --> 00:13:36,309 you understand that, you put, 371 00:13:36,929 --> 00:13:39,350 a lot of vital functions of the society 372 00:13:39,409 --> 00:13:41,490 and even human beings in the hands of 373 00:13:41,490 --> 00:13:42,309 artificial intelligence, 374 00:13:43,089 --> 00:13:45,169 you know, when you have an hallucination that 375 00:13:45,169 --> 00:13:45,829 can cost 376 00:13:46,304 --> 00:13:48,144 a lot, not only in terms of money, 377 00:13:48,144 --> 00:13:50,245 but also in terms of of human lives. 378 00:13:51,105 --> 00:13:51,605 So, 379 00:13:53,585 --> 00:13:55,445 I think the the best 380 00:13:56,625 --> 00:13:58,965 part of this experience was the understanding 381 00:13:59,345 --> 00:14:01,044 of the very delicate balance, 382 00:14:01,470 --> 00:14:05,389 very delicate balance existing between the advantages of 383 00:14:05,389 --> 00:14:06,049 this technology 384 00:14:06,589 --> 00:14:08,610 and the disadvantages of this technology. 385 00:14:09,389 --> 00:14:10,449 And and, 386 00:14:10,750 --> 00:14:14,204 again, all these considerations are gonna go on 387 00:14:14,204 --> 00:14:15,584 a different scale 388 00:14:16,044 --> 00:14:16,544 when, 389 00:14:18,365 --> 00:14:18,865 Agentic 390 00:14:19,804 --> 00:14:22,625 AI is gonna be, is gonna become more, 391 00:14:23,164 --> 00:14:23,664 prevalent. 392 00:14:24,365 --> 00:14:26,444 And that is gonna be Agentic AI is 393 00:14:26,444 --> 00:14:27,745 gonna be the introduction 394 00:14:28,429 --> 00:14:31,009 and and the need needed bridge 395 00:14:31,709 --> 00:14:32,209 into, 396 00:14:33,629 --> 00:14:36,850 embodied AI, which means the production robots. 397 00:14:37,789 --> 00:14:40,529 Those two are the much more disruptive 398 00:14:41,404 --> 00:14:44,524 potential on our society and our technologies and 399 00:14:44,524 --> 00:14:45,745 our, operations 400 00:14:46,205 --> 00:14:48,785 than Gen AI. Gen AI depends on us. 401 00:14:49,165 --> 00:14:49,665 Gen 402 00:14:50,365 --> 00:14:52,945 AI depends critically on the input of data, 403 00:14:53,884 --> 00:14:55,585 on the on the programming. 404 00:14:56,370 --> 00:14:58,789 The human component is still dominant 405 00:14:59,090 --> 00:14:59,669 in Gen 406 00:15:00,049 --> 00:15:01,669 AI. In Genetec AI, 407 00:15:02,049 --> 00:15:02,789 that flips. 408 00:15:03,410 --> 00:15:05,669 And that is where, I think, 409 00:15:06,049 --> 00:15:07,570 that that is the reason I say that 410 00:15:07,570 --> 00:15:09,350 we have not seen not even the beginning 411 00:15:09,894 --> 00:15:11,815 of this revolution. When we are gonna see 412 00:15:11,815 --> 00:15:12,475 the revolution, 413 00:15:12,855 --> 00:15:14,774 it's gonna be when a GenTIC AI is 414 00:15:14,774 --> 00:15:17,514 gonna become more sophisticated, more prevalent. 415 00:15:18,294 --> 00:15:22,634 And, I have reasons to believe that 2026 416 00:15:22,855 --> 00:15:25,274 is gonna be an historic year because 417 00:15:25,679 --> 00:15:27,519 the 2025 418 00:15:27,519 --> 00:15:28,019 was 419 00:15:28,639 --> 00:15:29,139 kind 420 00:15:29,480 --> 00:15:29,980 of 421 00:15:30,320 --> 00:15:30,820 eventful. 422 00:15:31,279 --> 00:15:33,679 It was, seemed like, you know, a a 423 00:15:33,679 --> 00:15:34,580 breaking point, 424 00:15:35,120 --> 00:15:36,899 but I think it was just an introduction 425 00:15:37,039 --> 00:15:39,200 to what is gonna happen in 2026 426 00:15:39,200 --> 00:15:40,639 and 2027 427 00:15:40,639 --> 00:15:41,139 when 428 00:15:41,519 --> 00:15:44,375 the technology that has been maturing over time 429 00:15:44,375 --> 00:15:46,315 is gonna come to full fruition. 430 00:15:47,175 --> 00:15:49,815 And at that point, really, the world is 431 00:15:49,815 --> 00:15:51,754 gonna change in ways that are 432 00:15:53,095 --> 00:15:54,475 in great part unpredictable. 433 00:15:55,740 --> 00:15:57,440 Thank you for laying all that out, doctor. 434 00:15:57,820 --> 00:16:00,460 There's so much that's exciting and scary at 435 00:16:00,460 --> 00:16:02,639 the same time and really unavoidable 436 00:16:03,340 --> 00:16:05,179 in terms of how AI is gonna affect 437 00:16:05,179 --> 00:16:06,240 all of us, including, 438 00:16:06,860 --> 00:16:08,865 health systems and health care in general. 439 00:16:09,184 --> 00:16:11,445 I do wanna ask I'm curious. So 440 00:16:11,985 --> 00:16:14,304 given how much you've been embedded in AI 441 00:16:14,304 --> 00:16:15,205 and its research, 442 00:16:15,904 --> 00:16:18,804 what would you say your comfort level is 443 00:16:19,345 --> 00:16:22,279 with AI in terms of how how well 444 00:16:22,279 --> 00:16:24,139 do you trust it? You mentioned hallucinations. 445 00:16:25,000 --> 00:16:26,379 And and what do you think 446 00:16:26,759 --> 00:16:29,019 has to happen for humans 447 00:16:29,720 --> 00:16:32,120 to trust it more than they do now? 448 00:16:32,120 --> 00:16:33,179 Does that make sense? 449 00:16:33,985 --> 00:16:35,924 Yes. It does. It's a great question. 450 00:16:36,304 --> 00:16:36,804 And, 451 00:16:37,424 --> 00:16:39,904 I may surprise you, but hallucinations are not 452 00:16:39,904 --> 00:16:41,665 the part of AI that scares me the 453 00:16:41,665 --> 00:16:42,165 most. 454 00:16:42,705 --> 00:16:44,465 The part of AI that scares me the 455 00:16:44,465 --> 00:16:45,605 most is 456 00:16:47,600 --> 00:16:48,419 the risk 457 00:16:49,039 --> 00:16:49,539 of 458 00:16:51,120 --> 00:16:51,940 skill reprogramming 459 00:16:53,200 --> 00:16:55,459 and skill down regulation in humans. 460 00:16:56,559 --> 00:16:58,019 And I give you an example. 461 00:16:59,745 --> 00:17:01,445 I'm old enough that when 462 00:17:01,985 --> 00:17:04,224 I was in school, they you know, I 463 00:17:04,224 --> 00:17:05,525 became very good at 464 00:17:05,904 --> 00:17:06,404 mathematics. 465 00:17:07,345 --> 00:17:09,105 I didn't like it at all, but, you 466 00:17:09,105 --> 00:17:10,805 know, I knew how to do, 467 00:17:11,345 --> 00:17:13,045 basic calculations at least, 468 00:17:13,664 --> 00:17:15,529 by end with no support. 469 00:17:16,390 --> 00:17:19,130 And then we start getting the 470 00:17:19,670 --> 00:17:20,170 calculators, 471 00:17:20,549 --> 00:17:22,970 and then the calculators get better and better. 472 00:17:23,590 --> 00:17:25,830 I don't know if today I I will 473 00:17:25,830 --> 00:17:27,450 be able to run 474 00:17:28,070 --> 00:17:29,370 a square root analysis 475 00:17:30,914 --> 00:17:32,454 or even basic mathematical 476 00:17:32,835 --> 00:17:33,335 skills. 477 00:17:34,515 --> 00:17:36,615 Why? Because I don't need to. 478 00:17:37,474 --> 00:17:39,894 Now if you expand that to 479 00:17:40,434 --> 00:17:41,255 all the incredible 480 00:17:42,450 --> 00:17:42,950 potential 481 00:17:43,250 --> 00:17:44,549 of artificial intelligence 482 00:17:45,569 --> 00:17:47,349 and to the knowledge that, 483 00:17:49,250 --> 00:17:51,730 I don't think there are many students today 484 00:17:51,730 --> 00:17:54,289 that don't rely on artificial intelligence and Gen 485 00:17:54,289 --> 00:17:54,789 AI 486 00:17:55,169 --> 00:17:57,750 to to do their, their their work. 487 00:17:58,424 --> 00:18:00,105 I think that we risk to, 488 00:18:00,585 --> 00:18:02,744 generations of people who are gonna forget how 489 00:18:02,744 --> 00:18:05,005 to read, they're gonna forget how to think, 490 00:18:05,304 --> 00:18:07,464 they're gonna forget how to calculate, they're gonna 491 00:18:07,464 --> 00:18:08,605 forget how to 492 00:18:09,144 --> 00:18:09,644 strategize, 493 00:18:10,330 --> 00:18:12,490 because all those things can be done very 494 00:18:12,490 --> 00:18:14,430 quickly and very easily by, 495 00:18:14,890 --> 00:18:15,869 by this tool. 496 00:18:16,490 --> 00:18:17,309 And so, 497 00:18:18,930 --> 00:18:21,049 the the this this is a risk. In 498 00:18:21,049 --> 00:18:21,950 fact, I 499 00:18:22,330 --> 00:18:23,390 I'm I'm 500 00:18:24,615 --> 00:18:27,255 in a very tough positions because I'm really 501 00:18:27,255 --> 00:18:29,035 trying to understand all aspects, 502 00:18:29,974 --> 00:18:32,234 relevant to my area of interest, 503 00:18:33,815 --> 00:18:35,434 concerning AI, Gen 504 00:18:36,055 --> 00:18:36,555 AI, 505 00:18:37,015 --> 00:18:38,555 and and the related technologies. 506 00:18:40,329 --> 00:18:41,950 But I try to use it 507 00:18:42,889 --> 00:18:44,109 the the least I can, 508 00:18:44,970 --> 00:18:46,809 if it makes any sense to you. Oh, 509 00:18:46,809 --> 00:18:48,669 certainly. Certainly. Because 510 00:18:49,130 --> 00:18:51,389 I want my brain to go keep working. 511 00:18:52,169 --> 00:18:53,769 And and and and, 512 00:18:54,875 --> 00:18:55,195 and, 513 00:18:55,674 --> 00:18:57,434 I don't want to be in a situation 514 00:18:57,434 --> 00:18:59,535 like the same way I lost my 515 00:18:59,835 --> 00:19:02,555 calculations still. I think, for example, I don't 516 00:19:02,555 --> 00:19:03,055 write, 517 00:19:04,555 --> 00:19:05,295 my penmanship 518 00:19:05,674 --> 00:19:07,455 is not the same as it was. 519 00:19:07,914 --> 00:19:08,975 I don't need it. 520 00:19:09,650 --> 00:19:12,130 I don't I I am afraid even that 521 00:19:12,130 --> 00:19:12,789 my memory 522 00:19:13,409 --> 00:19:14,069 is gonna, 523 00:19:15,250 --> 00:19:15,750 be, 524 00:19:16,369 --> 00:19:16,950 is gonna, 525 00:19:17,490 --> 00:19:18,230 be reduced 526 00:19:19,970 --> 00:19:22,950 because that's the nature of, Darwinian 527 00:19:23,569 --> 00:19:24,069 systems 528 00:19:24,855 --> 00:19:25,755 and evolution. 529 00:19:26,775 --> 00:19:29,174 So in a world where all those things, 530 00:19:29,174 --> 00:19:30,775 all the things that we do, all the 531 00:19:30,775 --> 00:19:32,075 expression of our, 532 00:19:32,615 --> 00:19:33,515 of our intelligence 533 00:19:35,174 --> 00:19:37,595 can be achieved in a much easier way, 534 00:19:38,809 --> 00:19:40,269 What is gonna be left? 535 00:19:41,289 --> 00:19:43,549 That that is that is an enormous concern 536 00:19:43,769 --> 00:19:45,950 that I have. Another concern is, 537 00:19:47,130 --> 00:19:49,390 what this is gonna do to our workforce. 538 00:19:50,089 --> 00:19:50,589 And 539 00:19:51,605 --> 00:19:53,545 there is a little bit of 540 00:19:54,325 --> 00:19:56,884 pride in me because, at the con at 541 00:19:56,884 --> 00:19:58,025 the Baker's conference, 542 00:19:59,205 --> 00:20:00,585 a couple of years back, 543 00:20:02,164 --> 00:20:03,705 when everybody was 544 00:20:04,529 --> 00:20:04,930 cheering, 545 00:20:05,330 --> 00:20:08,930 and, we're partying and we're so excited about 546 00:20:08,930 --> 00:20:10,950 all the potential of artificial intelligence, 547 00:20:11,490 --> 00:20:13,970 I said, be careful because it's gonna kill 548 00:20:13,970 --> 00:20:14,869 a lot of jobs. 549 00:20:17,035 --> 00:20:19,434 And I I got criticized, and several of 550 00:20:19,434 --> 00:20:21,914 my colleagues said, you know, you're you're being 551 00:20:21,914 --> 00:20:22,654 over pessimistic. 552 00:20:23,115 --> 00:20:24,815 Well, it was very interesting, 553 00:20:25,914 --> 00:20:26,414 yesterday. 554 00:20:27,275 --> 00:20:28,335 I follow closely 555 00:20:28,634 --> 00:20:29,434 the that was, 556 00:20:30,154 --> 00:20:31,500 meetings, the the 557 00:20:32,380 --> 00:20:34,319 to hear that CEO, the largest 558 00:20:34,779 --> 00:20:35,920 bank in the in the world, 559 00:20:36,619 --> 00:20:38,299 I believe, or in The United States for 560 00:20:38,299 --> 00:20:39,279 sure, that is, 561 00:20:40,140 --> 00:20:40,640 Jamie, 562 00:20:41,259 --> 00:20:41,759 Dimon 563 00:20:42,619 --> 00:20:45,839 of j j JP JP Morgan Chase. 564 00:20:47,025 --> 00:20:47,765 And Jamie 565 00:20:48,384 --> 00:20:50,244 basically said exactly the same things. 566 00:20:50,785 --> 00:20:53,744 Jamie, in in a nutshell, said that if 567 00:20:53,744 --> 00:20:55,825 we do not I'm not very careful with 568 00:20:55,825 --> 00:20:56,484 the implementation, 569 00:20:56,945 --> 00:20:57,605 the launch, 570 00:20:58,384 --> 00:21:01,184 the use of artificial intelligence, particularly in the 571 00:21:01,184 --> 00:21:04,839 in the in the new generation of artificial 572 00:21:04,839 --> 00:21:05,339 intelligence 573 00:21:05,640 --> 00:21:06,140 algorithms, 574 00:21:06,759 --> 00:21:09,660 we're gonna lose an enormous number of jobs, 575 00:21:09,880 --> 00:21:12,519 and we have to be proactive in thinking 576 00:21:12,519 --> 00:21:14,599 what these people are gonna do. For example, 577 00:21:14,599 --> 00:21:16,200 in the work in the world of health 578 00:21:16,200 --> 00:21:19,375 care, as I said before, the opportunities are 579 00:21:19,375 --> 00:21:19,875 endless. 580 00:21:20,734 --> 00:21:22,914 But when you look at any, 581 00:21:23,375 --> 00:21:24,914 large health care system, 582 00:21:26,014 --> 00:21:28,254 there is a certain small number or a 583 00:21:28,254 --> 00:21:29,794 fairly small number of doctors. 584 00:21:30,929 --> 00:21:33,409 All the rest are people that actually do 585 00:21:33,409 --> 00:21:34,309 highly repetitive 586 00:21:34,929 --> 00:21:37,329 tasks. You know, the doctors do highly repetitive 587 00:21:37,329 --> 00:21:40,129 tasks. But Sometimes. Yeah. When you look when 588 00:21:40,129 --> 00:21:42,869 you look at, for example, verification of insurance, 589 00:21:46,154 --> 00:21:47,454 checking of the patients, 590 00:21:49,355 --> 00:21:49,855 analysis 591 00:21:50,154 --> 00:21:50,894 and submission 592 00:21:51,195 --> 00:21:52,015 of the claims, 593 00:21:53,195 --> 00:21:54,174 all the work 594 00:21:54,795 --> 00:21:58,174 we already know can be done much, much, 595 00:21:58,839 --> 00:21:59,899 faster, easier 596 00:22:01,000 --> 00:22:03,099 by system that don't get sick, 597 00:22:04,359 --> 00:22:05,579 and and they're very cheap. 598 00:22:05,960 --> 00:22:07,019 And another thing, 599 00:22:07,639 --> 00:22:09,319 that, Jamie said, 600 00:22:09,720 --> 00:22:10,519 yesterday is 601 00:22:11,815 --> 00:22:12,394 But, unfortunately, 602 00:22:12,775 --> 00:22:15,494 this is not a a process that can 603 00:22:15,494 --> 00:22:17,595 be modulated that much. Why? 604 00:22:17,974 --> 00:22:19,974 Because let's assume that you are the CEO 605 00:22:19,974 --> 00:22:21,755 of a of a larger care system, 606 00:22:22,215 --> 00:22:23,115 and you decide 607 00:22:23,494 --> 00:22:24,154 for your 608 00:22:24,929 --> 00:22:27,589 principles that you don't want to get involved 609 00:22:27,649 --> 00:22:28,549 with in AI, 610 00:22:29,329 --> 00:22:31,569 and not in the implementation AI in your 611 00:22:31,569 --> 00:22:32,549 health care system, 612 00:22:32,849 --> 00:22:34,929 you're gonna be killed on a financial basis 613 00:22:34,929 --> 00:22:37,490 because all your competitors are gonna leap in 614 00:22:37,490 --> 00:22:40,024 front of you and achieve the same performance 615 00:22:40,244 --> 00:22:41,544 or much higher performance 616 00:22:41,845 --> 00:22:43,384 with much lower cost. 617 00:22:44,085 --> 00:22:44,585 So, 618 00:22:45,204 --> 00:22:47,444 this is not gonna stop. There is no 619 00:22:47,444 --> 00:22:49,845 no no possibility of stopping this. So I 620 00:22:49,845 --> 00:22:51,784 think that one of the most challenging 621 00:22:52,244 --> 00:22:53,544 aspect of, 622 00:22:54,400 --> 00:22:56,099 particularly, Genentech AI, 623 00:22:56,640 --> 00:22:57,859 is going to be 624 00:22:58,320 --> 00:22:58,820 before 625 00:23:00,000 --> 00:23:03,059 we launch on very large scale these technologies, 626 00:23:03,440 --> 00:23:05,220 we have to start thinking about 627 00:23:05,680 --> 00:23:07,619 what to do with people. 628 00:23:08,115 --> 00:23:09,414 All the people that 629 00:23:10,194 --> 00:23:12,115 are going to lose their jobs. You know, 630 00:23:12,115 --> 00:23:13,875 one of the things I noticed, there is 631 00:23:13,875 --> 00:23:15,335 a lot of attempts. I understand 632 00:23:16,035 --> 00:23:17,654 to reduce the, 633 00:23:18,194 --> 00:23:19,494 how can I say, the panic? 634 00:23:19,920 --> 00:23:20,420 Mhmm. 635 00:23:21,359 --> 00:23:22,240 But but, 636 00:23:22,880 --> 00:23:24,400 I also think that we need to be 637 00:23:24,400 --> 00:23:24,900 realistic. 638 00:23:25,440 --> 00:23:26,900 There are very few things 639 00:23:27,359 --> 00:23:27,859 that, 640 00:23:29,279 --> 00:23:30,740 robots, artificial intelligence 641 00:23:31,039 --> 00:23:32,924 are not gonna be able to do. 642 00:23:33,965 --> 00:23:36,445 One of the most shocking experiences as a 643 00:23:36,445 --> 00:23:38,945 physician was I'm a a a respirologist, 644 00:23:40,125 --> 00:23:40,625 and, 645 00:23:41,485 --> 00:23:43,725 you know, for many years, I thought that 646 00:23:43,725 --> 00:23:46,125 you always needed a a physician to do 647 00:23:46,125 --> 00:23:48,705 a bronchoscopy, for example, any type of endoscopy. 648 00:23:50,250 --> 00:23:51,789 Today, there are several systems, 649 00:23:53,210 --> 00:23:54,750 that do bronchoscopies, 650 00:23:55,529 --> 00:23:56,750 in a totally robotics 651 00:23:57,130 --> 00:23:57,630 way, 652 00:23:58,650 --> 00:23:59,630 requiring minimal, 653 00:24:00,250 --> 00:24:01,950 additional effort from humans. 654 00:24:02,595 --> 00:24:03,954 And, you know, it's just a matter of 655 00:24:03,954 --> 00:24:05,815 time that they're gonna be completely independent. 656 00:24:06,595 --> 00:24:06,994 And, 657 00:24:07,474 --> 00:24:08,535 there are already, 658 00:24:09,554 --> 00:24:12,515 hospitals in Japan where the entire and also 659 00:24:12,515 --> 00:24:15,794 in China, where the entire staff, nursing staff, 660 00:24:15,954 --> 00:24:18,134 and physician staff is made of robots. 661 00:24:19,049 --> 00:24:20,109 It's just the beginning. 662 00:24:20,730 --> 00:24:23,049 When you project those trends and you realize 663 00:24:23,049 --> 00:24:24,589 that the technology is there, 664 00:24:25,609 --> 00:24:28,089 we better be at least be ready be 665 00:24:28,089 --> 00:24:30,009 ready, for example, to a world in which 666 00:24:30,009 --> 00:24:31,950 humans probably are not gonna work 667 00:24:32,414 --> 00:24:33,535 five days, but only, 668 00:24:35,055 --> 00:24:36,035 three days a week. 669 00:24:36,815 --> 00:24:37,555 If that. 670 00:24:38,174 --> 00:24:39,934 And one says, well, great. I mean, the 671 00:24:39,934 --> 00:24:42,015 more time for us. Yes. But then we 672 00:24:42,015 --> 00:24:44,174 have to find the way to pay these 673 00:24:44,174 --> 00:24:44,674 people. 674 00:24:45,179 --> 00:24:47,259 And already in Europe, there are a lot 675 00:24:47,259 --> 00:24:49,419 of, there's a lot of discussion about, 676 00:24:50,700 --> 00:24:51,200 providing 677 00:24:51,899 --> 00:24:52,880 basic salaries, 678 00:24:54,619 --> 00:24:55,919 you know, from the state. 679 00:24:57,454 --> 00:24:59,535 In France, for example, they have a project 680 00:24:59,535 --> 00:25:02,335 like that because they already know that a 681 00:25:02,335 --> 00:25:03,695 lot of people are not gonna have a 682 00:25:03,695 --> 00:25:06,654 job. So and you cannot have a the 683 00:25:06,654 --> 00:25:08,994 majority of the population will have a job 684 00:25:09,375 --> 00:25:12,009 No. Because they get very angry. And that 685 00:25:12,009 --> 00:25:14,250 is the reason of the revolutions around the 686 00:25:14,410 --> 00:25:15,230 that occurred, 687 00:25:16,170 --> 00:25:18,990 around the the the first industrial revolution. 688 00:25:19,849 --> 00:25:22,170 But the first industrial revolution was nothing in 689 00:25:22,170 --> 00:25:24,750 the present to what we are walking to. 690 00:25:25,924 --> 00:25:28,644 You know, there were now machines that were 691 00:25:28,644 --> 00:25:30,565 able to do the work of hundreds of 692 00:25:30,565 --> 00:25:31,065 people. 693 00:25:31,605 --> 00:25:33,525 Now we have computers that are gonna be 694 00:25:33,525 --> 00:25:35,845 able to do the work of tens of 695 00:25:35,845 --> 00:25:38,099 thousands of hundreds of thousands of people. 696 00:25:38,900 --> 00:25:41,220 And you already see several companies that are 697 00:25:41,220 --> 00:25:42,039 laying off, 698 00:25:44,179 --> 00:25:46,259 big segments of their workforce. They are doing 699 00:25:46,259 --> 00:25:47,000 it gradually. 700 00:25:47,779 --> 00:25:48,519 But, again, 701 00:25:49,059 --> 00:25:49,799 you just 702 00:25:50,894 --> 00:25:52,355 projected this trend 703 00:25:52,734 --> 00:25:53,234 forward, 704 00:25:54,015 --> 00:25:57,615 realize the speed at which, artificial intelligence is 705 00:25:57,615 --> 00:25:59,855 growing. When you see the difference between the 706 00:25:59,855 --> 00:26:00,355 first 707 00:26:00,654 --> 00:26:02,974 version of chat GPT and and the current 708 00:26:02,974 --> 00:26:05,615 version of chat GPT are two completely different 709 00:26:05,615 --> 00:26:06,115 words. 710 00:26:06,869 --> 00:26:09,269 Then you realize that we have a significant 711 00:26:09,269 --> 00:26:11,750 problem. And I am I feel a little 712 00:26:11,750 --> 00:26:14,549 bit vindicated in a way that that that 713 00:26:14,549 --> 00:26:16,390 CEO of the largest bank in The United 714 00:26:16,390 --> 00:26:18,710 States, yes, they said exactly the same things. 715 00:26:18,710 --> 00:26:21,109 And what they did what they did was 716 00:26:21,109 --> 00:26:21,769 be careful. 717 00:26:22,224 --> 00:26:23,524 We need to time 718 00:26:23,984 --> 00:26:27,184 this process. Otherwise, we're gonna have a big, 719 00:26:27,184 --> 00:26:29,684 big significant social problem in our hands, 720 00:26:30,065 --> 00:26:32,784 which is gonna be very dangerous from on 721 00:26:32,784 --> 00:26:35,125 a political level and a social level. 722 00:26:36,119 --> 00:26:38,359 Doctor, that's all just fascinating. I mean, I 723 00:26:38,359 --> 00:26:38,859 especially, 724 00:26:39,160 --> 00:26:40,619 key in on a part where 725 00:26:41,160 --> 00:26:42,680 so much of it comes down to how 726 00:26:42,680 --> 00:26:44,539 much we're willing to give up 727 00:26:44,840 --> 00:26:45,500 in terms 728 00:26:45,960 --> 00:26:46,619 of thinking 729 00:26:47,160 --> 00:26:47,980 and strategy. 730 00:26:48,544 --> 00:26:50,384 Right? And certainly the human element is is 731 00:26:50,384 --> 00:26:52,404 very important now, and we 732 00:26:52,944 --> 00:26:54,464 to put it out there, I don't expect 733 00:26:54,464 --> 00:26:56,224 any of us to have an answer to 734 00:26:56,224 --> 00:26:57,825 this question in this moment, but we have 735 00:26:57,825 --> 00:26:59,424 to decide how much of it is is 736 00:26:59,424 --> 00:27:01,845 worth it. Right? So it's it's just 737 00:27:02,670 --> 00:27:03,170 fascinating 738 00:27:03,470 --> 00:27:05,789 and scary, and it's it's, again, still exciting 739 00:27:05,789 --> 00:27:06,769 in a lot of ways. 740 00:27:07,390 --> 00:27:09,390 But don't don't forget the element of greed, 741 00:27:09,390 --> 00:27:09,890 though. 742 00:27:10,990 --> 00:27:11,809 I I wouldn't. 743 00:27:12,670 --> 00:27:13,330 It's impossible. 744 00:27:13,710 --> 00:27:14,210 Again, 745 00:27:14,750 --> 00:27:17,970 artificial intelligence is gonna have major financial implications. 746 00:27:18,965 --> 00:27:21,785 So the risk, which is what, Jamie, 747 00:27:22,164 --> 00:27:23,545 Timon said, yes. 748 00:27:24,085 --> 00:27:26,105 The risk is that basically people go 749 00:27:26,404 --> 00:27:26,884 looking, 750 00:27:27,285 --> 00:27:29,605 go forward. They're looking exclusively at the bottom 751 00:27:29,605 --> 00:27:30,105 line, 752 00:27:30,484 --> 00:27:32,025 and that is gonna be devastating. 753 00:27:32,910 --> 00:27:35,110 And and then I basically ended with the 754 00:27:35,150 --> 00:27:37,410 with a a word of of 755 00:27:37,789 --> 00:27:38,289 of 756 00:27:38,670 --> 00:27:39,170 hope, 757 00:27:39,789 --> 00:27:42,430 saying that humans are still gonna be relevant 758 00:27:42,430 --> 00:27:43,090 and important. 759 00:27:44,269 --> 00:27:46,509 There is no doubt about that, but our 760 00:27:46,509 --> 00:27:47,410 many humans 761 00:27:48,055 --> 00:27:49,035 are gonna be 762 00:27:49,654 --> 00:27:50,154 relevant. 763 00:27:51,335 --> 00:27:53,994 And he he talked also about, 764 00:27:55,174 --> 00:27:55,674 reskilling. 765 00:27:56,934 --> 00:27:57,434 Yeah. 766 00:27:57,815 --> 00:27:58,315 And, 767 00:27:58,934 --> 00:28:01,710 Chris, I'm I'm afraid that they're taking the 768 00:28:01,710 --> 00:28:03,490 issue with scaling a little bit 769 00:28:03,950 --> 00:28:06,910 too lightly because Yeah. It's not easy to 770 00:28:06,910 --> 00:28:09,230 get a 50 year old, that has done 771 00:28:09,230 --> 00:28:11,069 a certain job all his life or all 772 00:28:11,069 --> 00:28:13,490 her life and basically convert it 773 00:28:13,789 --> 00:28:14,769 into a Google 774 00:28:15,150 --> 00:28:15,650 engineer. 775 00:28:17,724 --> 00:28:19,404 And there is there is a certain For 776 00:28:19,404 --> 00:28:21,484 sure. There is a certain limit. I mean, 777 00:28:21,484 --> 00:28:23,484 for the new generations, maybe. But what are 778 00:28:23,484 --> 00:28:25,804 you gonna do with all all those people 779 00:28:25,804 --> 00:28:26,125 that 780 00:28:27,724 --> 00:28:29,724 I don't think I remember one thing that, 781 00:28:30,470 --> 00:28:32,650 you know, I I found very interesting. 782 00:28:33,910 --> 00:28:34,890 I I was, 783 00:28:35,589 --> 00:28:36,890 at the Cleveland Clinic. 784 00:28:37,910 --> 00:28:40,730 I participated to the launch of, an upgrade 785 00:28:40,789 --> 00:28:42,009 that, of Epic. 786 00:28:42,390 --> 00:28:43,609 I remember distinctly 787 00:28:43,990 --> 00:28:47,025 that a lot of the older physicians just 788 00:28:47,025 --> 00:28:47,525 quit. 789 00:28:48,065 --> 00:28:50,384 They said they want to to deal with 790 00:28:50,384 --> 00:28:52,384 the you know? They were very comfortable with 791 00:28:52,384 --> 00:28:53,365 paper charts. 792 00:28:53,984 --> 00:28:54,484 Obviously, 793 00:28:55,025 --> 00:28:56,085 we know that, 794 00:28:57,105 --> 00:28:57,765 you know, 795 00:28:58,789 --> 00:29:01,269 electronic medical record systems are much more efficient, 796 00:29:01,269 --> 00:29:02,809 much I mean, enormous advantages. 797 00:29:03,829 --> 00:29:05,909 But I'm old enough to remember when we 798 00:29:05,909 --> 00:29:07,909 didn't have that, and, you know, a lot 799 00:29:07,909 --> 00:29:09,909 of people spend most of their career. It 800 00:29:09,909 --> 00:29:11,285 was a absolutely 801 00:29:11,904 --> 00:29:13,684 curl a cultural shock 802 00:29:14,384 --> 00:29:15,605 when when, 803 00:29:16,465 --> 00:29:19,025 electronic medical systems were introduced. And, again, I 804 00:29:19,025 --> 00:29:20,705 think there were a lot of problems when 805 00:29:20,705 --> 00:29:21,184 the first, 806 00:29:21,904 --> 00:29:22,404 EMS 807 00:29:23,184 --> 00:29:24,005 were implemented. 808 00:29:24,465 --> 00:29:26,085 So we have to 809 00:29:27,000 --> 00:29:27,500 continue, 810 00:29:27,880 --> 00:29:28,460 I think, 811 00:29:29,080 --> 00:29:31,320 at least make every attempt to put the 812 00:29:31,320 --> 00:29:32,859 human being at the center 813 00:29:34,279 --> 00:29:35,980 because artificial intelligence, 814 00:29:36,359 --> 00:29:37,180 Gen AI, 815 00:29:38,279 --> 00:29:39,500 and all the 816 00:29:39,960 --> 00:29:40,460 derivatives 817 00:29:41,744 --> 00:29:45,105 are going to be helpful and useful only 818 00:29:45,105 --> 00:29:48,085 for as much are gonna make people happier. 819 00:29:49,184 --> 00:29:51,424 And so to put the humans at the 820 00:29:51,424 --> 00:29:53,825 service of the machines is gonna be a 821 00:29:53,825 --> 00:29:54,964 a a major strategic, 822 00:29:56,545 --> 00:29:57,045 ever. 823 00:29:58,039 --> 00:29:59,660 That's well said, doctor Villalemonte. 824 00:30:00,519 --> 00:30:02,519 And and certainly as it relates to health 825 00:30:02,519 --> 00:30:03,019 care, 826 00:30:03,400 --> 00:30:05,400 you speak to any health care leader, and 827 00:30:05,400 --> 00:30:05,900 they 828 00:30:06,440 --> 00:30:09,240 always say that the patients and their staff 829 00:30:09,240 --> 00:30:10,994 is front and center. And we have every 830 00:30:10,994 --> 00:30:12,914 reason to to believe that's true. Right? I 831 00:30:12,914 --> 00:30:14,595 I believe that when when they tell me 832 00:30:14,595 --> 00:30:16,674 that. They they wouldn't be in this this 833 00:30:16,674 --> 00:30:19,795 business, this area, this sector, otherwise. Right? So 834 00:30:19,795 --> 00:30:21,494 so that is encouraging, certainly. 835 00:30:22,355 --> 00:30:24,710 Lastly, doctor, I simply wanna ask you. You 836 00:30:24,710 --> 00:30:26,389 are on a sabbatical now as you mentioned. 837 00:30:26,389 --> 00:30:27,769 Well deserved, clearly. 838 00:30:28,389 --> 00:30:28,889 But 839 00:30:29,269 --> 00:30:31,509 what do you think is is next for 840 00:30:31,509 --> 00:30:33,429 you? I mean, you have plenty that you 841 00:30:33,589 --> 00:30:35,669 to draw on. So so what do you 842 00:30:35,669 --> 00:30:38,174 look forward to doing in the next year, 843 00:30:38,174 --> 00:30:39,234 five years, whatever, 844 00:30:39,774 --> 00:30:40,595 time span, 845 00:30:40,974 --> 00:30:43,214 you know, you you see appropriate? Well, if 846 00:30:43,214 --> 00:30:44,914 I don't retire, which is supposedly, 847 00:30:46,894 --> 00:30:49,134 I definitely want to continue my research. I 848 00:30:49,134 --> 00:30:50,920 want definitely want to continue to do what 849 00:30:50,920 --> 00:30:52,680 I've done all my life, which is taking 850 00:30:52,680 --> 00:30:54,299 care of patients, which I still 851 00:30:55,320 --> 00:30:57,960 enjoy for as long as the robots are 852 00:30:57,960 --> 00:30:59,180 gonna allow me to. 853 00:31:00,759 --> 00:31:03,880 But in terms of this particular field of 854 00:31:03,880 --> 00:31:04,380 interest, 855 00:31:04,724 --> 00:31:06,184 I am particularly 856 00:31:06,484 --> 00:31:07,625 excited about 857 00:31:08,644 --> 00:31:09,865 how these technologies 858 00:31:10,164 --> 00:31:11,384 are going to, 859 00:31:11,924 --> 00:31:14,265 talk to each other, how they're gonna interact. 860 00:31:14,565 --> 00:31:15,464 And particularly 861 00:31:15,845 --> 00:31:16,664 at the 862 00:31:17,509 --> 00:31:18,009 crossroads 863 00:31:18,389 --> 00:31:20,089 between artificial intelligence, 864 00:31:21,429 --> 00:31:23,210 particularly agentic AI, 865 00:31:24,309 --> 00:31:25,450 quantum computing 866 00:31:25,909 --> 00:31:26,889 that is gonna 867 00:31:27,829 --> 00:31:28,329 change 868 00:31:29,029 --> 00:31:29,529 dramatically 869 00:31:30,525 --> 00:31:33,265 the speed of calculation. Therefore, it's gonna increase 870 00:31:33,404 --> 00:31:34,785 enormously the ability 871 00:31:35,404 --> 00:31:37,265 of artificial intelligence to function. 872 00:31:37,884 --> 00:31:38,285 And, 873 00:31:38,684 --> 00:31:39,664 I believe clouds 874 00:31:39,965 --> 00:31:42,144 that basically are gonna allow these 875 00:31:43,085 --> 00:31:44,945 technologies to talk to each other. 876 00:31:45,710 --> 00:31:47,470 And as you know, a lot of hybrid 877 00:31:47,470 --> 00:31:49,089 clouds are are, 878 00:31:49,789 --> 00:31:50,289 proprietary. 879 00:31:51,470 --> 00:31:54,430 So Yeah. That's where the competition is, in 880 00:31:54,430 --> 00:31:56,670 my opinion, is gonna be. Not that much 881 00:31:56,670 --> 00:31:58,750 on the quantum side, not that much on 882 00:31:58,750 --> 00:31:58,910 the, 883 00:32:00,455 --> 00:32:01,434 Ajentic AI, 884 00:32:02,455 --> 00:32:04,154 but to have the clouds, 885 00:32:05,975 --> 00:32:07,894 where most of the data are gonna be 886 00:32:07,894 --> 00:32:09,815 stored or all of the data, and they're 887 00:32:09,815 --> 00:32:12,715 gonna be allowing this, this crosstalking. 888 00:32:13,890 --> 00:32:16,210 That is where that is where I think 889 00:32:16,210 --> 00:32:18,450 the competition is gonna be, and that's where 890 00:32:18,450 --> 00:32:19,750 we are gonna see the most 891 00:32:20,769 --> 00:32:21,269 extraordinary 892 00:32:22,210 --> 00:32:22,710 manifestation 893 00:32:23,250 --> 00:32:24,309 of this technological, 894 00:32:25,970 --> 00:32:26,470 progress. 895 00:32:27,170 --> 00:32:29,349 Again, a lot of excitement, but 896 00:32:30,444 --> 00:32:32,764 but also the I think we have to 897 00:32:32,764 --> 00:32:33,504 be realistic, 898 00:32:34,924 --> 00:32:37,964 when this, this perfect storm is gonna is 899 00:32:37,964 --> 00:32:39,424 gonna is gonna hit. 900 00:32:40,605 --> 00:32:43,069 I hope that we are prepared 901 00:32:43,690 --> 00:32:44,190 because 902 00:32:44,569 --> 00:32:46,089 it's not gonna be the same world. It's 903 00:32:46,089 --> 00:32:47,769 not gonna be the same society. It's not 904 00:32:47,769 --> 00:32:48,909 gonna be the same 905 00:32:49,450 --> 00:32:49,950 organization. 906 00:32:50,250 --> 00:32:51,929 It's not gonna be the same culture. It's 907 00:32:51,929 --> 00:32:54,009 not gonna be the same way of doing 908 00:32:54,009 --> 00:32:54,509 things. 909 00:32:55,235 --> 00:32:57,235 I hope the very same, doctor. Thank you 910 00:32:57,235 --> 00:32:59,795 so much for bringing all your your decades 911 00:32:59,795 --> 00:33:01,174 worth of challenge and 912 00:33:01,555 --> 00:33:04,515 expertise and insight on on AI to our 913 00:33:04,515 --> 00:33:05,815 Becker's audience today. 914 00:33:06,434 --> 00:33:09,210 As I've mentioned before, we love seeing you 915 00:33:09,210 --> 00:33:10,990 at conferences. I'm sure we will again. 916 00:33:11,690 --> 00:33:14,190 Yeah. Enjoy your sabbatical, and, 917 00:33:14,570 --> 00:33:16,890 thank you again, and until next time. Thank 918 00:33:16,890 --> 00:33:18,349 you very much, Chris.