1 00:00:07,440 --> 00:00:13,520 Alessandro Oppo: Welcome to another episode of the Democracy Noiser podcast, and our guest of today is Alfa Alfdan 2 00:00:13,395 --> 00:00:17,155 Alessandro Oppo: Alfan Linge. So thank you for your time and for being here. 3 00:00:18,435 --> 00:00:19,475 Alessandro Oppo: And I 4 00:00:20,195 --> 00:00:20,995 Alessandro Oppo: have... 5 00:00:21,235 --> 00:00:26,675 Alessandro Oppo: I mean, the first question is if you can say something about you, your experience, your background. 6 00:00:27,880 --> 00:00:28,680 Alessandro Oppo: So 7 00:00:28,920 --> 00:00:30,440 Halfdan Lynge: Yeah. No. Thanks thanks 8 00:00:31,400 --> 00:00:38,040 Halfdan Lynge: thanks, Alessandro, and thanks for inviting me to to to speak on on your podcast, and I'm looking forward to this conversation. 9 00:00:38,360 --> 00:00:44,190 Halfdan Lynge: Yeah. So my name is Helfdan Lunge. You were close enough. It's a it's a Danish name. I'm from Denmark. It's a 10 00:00:44,190 --> 00:00:47,635 little bit hard for non Danes to pronounce, so you were close enough. 11 00:00:48,995 --> 00:00:50,835 Halfdan Lynge: I'm currently a 12 00:00:50,995 --> 00:00:55,315 Halfdan Lynge: chief advisor in the Danish Agency for Digital Government, 13 00:00:55,475 --> 00:00:59,075 Halfdan Lynge: which is the government agency in Denmark that runs most of the 14 00:01:00,170 --> 00:01:00,970 Halfdan Lynge: digital 15 00:01:01,290 --> 00:01:02,730 Halfdan Lynge: public infrastructure, 16 00:01:05,050 --> 00:01:07,850 Halfdan Lynge: identity systems, payment services, 17 00:01:07,930 --> 00:01:08,730 Halfdan Lynge: etcetera, 18 00:01:08,730 --> 00:01:10,730 Halfdan Lynge: etcetera. I work specifically 19 00:01:10,730 --> 00:01:14,330 Halfdan Lynge: on data governance and sort of open data infrastructure. 20 00:01:16,625 --> 00:01:23,905 Halfdan Lynge: We run-in open data platform, the Danish the national Danish national open data platform called DataVyVisa, 21 00:01:23,905 --> 00:01:26,225 Halfdan Lynge: which is a metadata catalog for 22 00:01:26,465 --> 00:01:27,265 Halfdan Lynge: for 23 00:01:28,145 --> 00:01:34,570 Halfdan Lynge: government data from across government. I think it's about 300 oh no, three and a half thousand data sets now 24 00:01:35,130 --> 00:01:36,570 Halfdan Lynge: from more than 25 00:01:37,050 --> 00:01:40,090 Halfdan Lynge: around 100 agencies from across government. 26 00:01:40,730 --> 00:01:42,650 Halfdan Lynge: So that's my daytime job. In addition to that, 27 00:01:43,855 --> 00:01:50,895 Halfdan Lynge: I'm a visiting senior researcher at Wits University in South Africa, where I'm also a research fellow 28 00:01:51,295 --> 00:01:52,575 Halfdan Lynge: at something called 29 00:01:53,295 --> 00:01:54,975 Halfdan Lynge: Tyreseus Centre for 30 00:01:55,375 --> 00:01:56,335 Halfdan Lynge: Digital Governance, 31 00:01:57,530 --> 00:01:58,970 Halfdan Lynge: which is hosted at 32 00:01:59,290 --> 00:02:00,410 Halfdan Lynge: Witch University. 33 00:02:02,570 --> 00:02:03,450 Halfdan Lynge: The reason 34 00:02:03,690 --> 00:02:07,290 Halfdan Lynge: I'm attached to a university in South Africa is that I was previously 35 00:02:08,330 --> 00:02:09,130 Halfdan Lynge: a 36 00:02:09,290 --> 00:02:10,090 Halfdan Lynge: faculty 37 00:02:10,090 --> 00:02:12,410 Halfdan Lynge: member, a staff at Witch University. 38 00:02:13,505 --> 00:02:15,505 Halfdan Lynge: I was a senior lecturer there, 39 00:02:16,145 --> 00:02:17,905 Halfdan Lynge: taught political economy 40 00:02:17,985 --> 00:02:21,105 Halfdan Lynge: and quantitative methods and and and was 41 00:02:21,265 --> 00:02:27,665 Halfdan Lynge: part of a small team that contributed to setting up this this center, the Thyatira Center on Digital Governance. 42 00:02:30,060 --> 00:02:31,180 Halfdan Lynge: Prior to that, 43 00:02:32,540 --> 00:02:37,580 Halfdan Lynge: I mean, I've worked in this space for more than twenty years now. I 44 00:02:38,380 --> 00:02:40,620 Halfdan Lynge: started my career as a 45 00:02:41,020 --> 00:02:43,420 Halfdan Lynge: UN official. I was working with UNDP, 46 00:02:43,635 --> 00:02:46,115 Halfdan Lynge: United Nations Development Program in... 47 00:02:46,835 --> 00:02:48,355 Halfdan Lynge: First in in... 48 00:02:48,515 --> 00:02:52,595 Halfdan Lynge: Shortly in Ethiopia, then Mozambique, and and lastly in in Bangladesh 49 00:02:52,595 --> 00:02:59,503 Halfdan Lynge: where I was... These were the very sort of early phases of of what we today call digital government. At the time, 50 00:02:59,503 --> 00:03:06,410 it was called... I think we called it e e government at the time. So these were very sort of early stage 51 00:03:06,410 --> 00:03:09,550 initiatives on how to introduce technology in in public administration. 52 00:03:12,415 --> 00:03:14,735 Halfdan Lynge: In Mozambique, I was I was 53 00:03:15,055 --> 00:03:15,935 Halfdan Lynge: involved... 54 00:03:16,975 --> 00:03:19,855 Halfdan Lynge: We were working with the electoral commission of 55 00:03:20,415 --> 00:03:22,175 Halfdan Lynge: of Mozambique assisting 56 00:03:24,100 --> 00:03:28,740 Halfdan Lynge: the technical secretariat with setting up biometric voter registration and verification 57 00:03:28,740 --> 00:03:30,020 Halfdan Lynge: and introducing 58 00:03:30,260 --> 00:03:34,420 Halfdan Lynge: sort of digital systems for the transfer of results. 59 00:03:34,820 --> 00:03:39,860 Halfdan Lynge: But this is, you know, these are standard things today, but twenty years ago 60 00:03:39,115 --> 00:03:40,235 Halfdan Lynge: it was fairly new. 61 00:03:41,275 --> 00:03:42,315 Halfdan Lynge: In Bangladesh, 62 00:03:42,315 --> 00:03:43,115 Halfdan Lynge: I worked 63 00:03:44,475 --> 00:03:50,875 Halfdan Lynge: in what was called the resident coordinator's office. So that's the part of the UN that's responsible for coordinating 64 00:03:52,170 --> 00:03:55,210 Halfdan Lynge: activities from across the different UN agencies. 65 00:03:55,930 --> 00:03:56,730 Halfdan Lynge: And, 66 00:03:56,730 --> 00:03:57,530 Halfdan Lynge: specifically, 67 00:03:57,530 --> 00:04:02,570 Halfdan Lynge: I was involved in the initiative that eventually led to Bangladesh's first digitalization 68 00:04:02,570 --> 00:04:04,490 Halfdan Lynge: strategy called Digital Bangladesh. 69 00:04:04,490 --> 00:04:05,290 Halfdan Lynge: Again, 70 00:04:05,735 --> 00:04:06,615 Halfdan Lynge: these were 71 00:04:06,935 --> 00:04:08,215 Halfdan Lynge: is twenty years ago, 72 00:04:08,455 --> 00:04:12,455 Halfdan Lynge: these were fairly sort of new things at the time, but nowadays they're 73 00:04:12,455 --> 00:04:13,495 Halfdan Lynge: common practice. 74 00:04:15,655 --> 00:04:19,270 Halfdan Lynge: After about six years, I think I left the UN 75 00:04:19,750 --> 00:04:21,990 Halfdan Lynge: and went back to university 76 00:04:22,310 --> 00:04:27,910 Halfdan Lynge: to pursue a PhD. I was a PhD researcher at Oxford University 77 00:04:28,870 --> 00:04:30,150 Halfdan Lynge: and did that for about, 78 00:04:30,935 --> 00:04:37,975 Halfdan Lynge: well, too long. These things often take longer than they are meant to. I think I was on and off in Oxford 79 00:04:37,975 --> 00:04:39,255 for about six years. 80 00:04:40,215 --> 00:04:41,895 Halfdan Lynge: And in the meantime, I 81 00:04:42,855 --> 00:04:44,455 Halfdan Lynge: actually returned to Mozambique 82 00:04:44,980 --> 00:04:46,660 Halfdan Lynge: and set up a 83 00:04:47,140 --> 00:04:48,420 Halfdan Lynge: a Govtech 84 00:04:48,900 --> 00:04:50,580 Halfdan Lynge: startup working 85 00:04:50,580 --> 00:04:51,380 Halfdan Lynge: on... 86 00:04:52,100 --> 00:04:55,300 Halfdan Lynge: Essentially, what we we did was develop a a platform 87 00:04:55,300 --> 00:04:58,500 Halfdan Lynge: that allowed us to crowdsource 88 00:04:58,315 --> 00:04:59,195 Halfdan Lynge: information 89 00:04:59,835 --> 00:05:01,035 Halfdan Lynge: through mobile 90 00:05:01,035 --> 00:05:01,835 Halfdan Lynge: phones. 91 00:05:03,435 --> 00:05:07,195 Halfdan Lynge: And it was a fairly simple technology based on 92 00:05:07,915 --> 00:05:12,090 Halfdan Lynge: sort of third generation mobile technology, so SMS and USST. 93 00:05:12,090 --> 00:05:17,130 Halfdan Lynge: And we set up this platform that allowed us to send bulk SMS out and collect, 94 00:05:17,850 --> 00:05:18,650 Halfdan Lynge: you know, 95 00:05:20,010 --> 00:05:21,290 Halfdan Lynge: little questionnaires. 96 00:05:22,905 --> 00:05:25,145 Halfdan Lynge: And it was a way of collecting 97 00:05:25,145 --> 00:05:26,025 Halfdan Lynge: information 98 00:05:26,265 --> 00:05:28,985 Halfdan Lynge: from citizens, and we used it for anything from 99 00:05:29,305 --> 00:05:30,185 Halfdan Lynge: political 100 00:05:30,185 --> 00:05:37,060 Halfdan Lynge: polling to market research. But the real sort of interest in application, I think, was for crowdsourcing and 101 00:05:37,380 --> 00:05:44,114 Halfdan Lynge: creating a platform that allowed sort of citizens engagement real time in a and I think that's important to keep in mind. 102 00:05:44,114 --> 00:05:44,914 Mozambique 103 00:05:45,300 --> 00:05:50,180 Halfdan Lynge: at the time and to some extent still today was a very sort of low connectivity environment. 104 00:05:51,855 --> 00:05:53,695 Halfdan Lynge: There was no three, 105 00:05:55,295 --> 00:05:59,135 Halfdan Lynge: four, five gs coverage across the country, so you can't use smartphones, 106 00:05:59,135 --> 00:06:02,495 Halfdan Lynge: you can't use Internet. So you have to design technological 107 00:06:02,495 --> 00:06:04,895 Halfdan Lynge: solutions that allow people to use 108 00:06:05,590 --> 00:06:07,830 Halfdan Lynge: sort of simple feature phones, SMS, 109 00:06:08,310 --> 00:06:09,590 Halfdan Lynge: and that kind of things. 110 00:06:10,230 --> 00:06:11,670 Halfdan Lynge: So I did that for 111 00:06:13,750 --> 00:06:17,430 Halfdan Lynge: about also six years or so before I then 112 00:06:17,750 --> 00:06:18,550 Halfdan Lynge: joined 113 00:06:18,790 --> 00:06:21,110 Halfdan Lynge: the university in South Africa. So 114 00:06:23,155 --> 00:06:27,395 Halfdan Lynge: it's a long story and my career has taken many twists and turns, 115 00:06:27,635 --> 00:06:28,835 Halfdan Lynge: but I think the 116 00:06:29,315 --> 00:06:30,115 Halfdan Lynge: underlying 117 00:06:31,475 --> 00:06:32,595 Halfdan Lynge: threat is an interest 118 00:06:34,050 --> 00:06:40,530 Halfdan Lynge: in how technology can be deployed. Specifically, I mean, I come from a kind of a data science background or 119 00:06:40,930 --> 00:06:42,770 Halfdan Lynge: computational social science, 120 00:06:43,890 --> 00:06:45,010 Halfdan Lynge: and that's 121 00:06:45,010 --> 00:06:51,555 Halfdan Lynge: always been my sort of interest in how we can use technology and specifically sort of data 122 00:06:51,555 --> 00:06:56,355 Halfdan Lynge: and data analytics to improve public service delivery, 123 00:06:56,675 --> 00:06:57,795 Halfdan Lynge: whether that's through 124 00:06:58,035 --> 00:07:00,355 Halfdan Lynge: fixing things in government or it's through, 125 00:07:00,960 --> 00:07:07,440 Halfdan Lynge: you know, kind of a civic tech approach where you can use these kind of tools to hold government accountable, 126 00:07:07,600 --> 00:07:10,000 Halfdan Lynge: etcetera. But that's really sort of the 127 00:07:10,400 --> 00:07:11,360 Halfdan Lynge: center of 128 00:07:12,400 --> 00:07:14,320 Halfdan Lynge: my interest and 129 00:07:14,865 --> 00:07:18,385 Halfdan Lynge: what I I suppose kind of connects all these different 130 00:07:19,265 --> 00:07:20,145 Halfdan Lynge: different 131 00:07:20,785 --> 00:07:23,985 Halfdan Lynge: elements of of of my professional career. Yeah. 132 00:07:25,825 --> 00:07:28,385 Alessandro Oppo: So you you have worked on a lot of things. 133 00:07:29,260 --> 00:07:30,220 Alessandro Oppo: And I 134 00:07:31,740 --> 00:07:33,340 Alessandro Oppo: was wondering with some 135 00:07:33,740 --> 00:07:34,700 Alessandro Oppo: friends that 136 00:07:34,940 --> 00:07:40,140 Alessandro Oppo: I was interviewed here in the podcast. Sometimes we were talking about the different... About 137 00:07:41,260 --> 00:07:44,300 Alessandro Oppo: civic tech and gov tech, if it makes sense 138 00:07:44,635 --> 00:07:47,355 Alessandro Oppo: to make two categories or not. 139 00:07:48,475 --> 00:07:50,955 Alessandro Oppo: And what do you think? Yeah. I mean, 140 00:07:51,995 --> 00:07:58,555 Halfdan Lynge: I have had extensive conversations with my previous colleagues and now friends at WITS University. 141 00:07:59,760 --> 00:08:00,800 Halfdan Lynge: So at 142 00:08:02,080 --> 00:08:03,360 Halfdan Lynge: Witsch University 143 00:08:03,520 --> 00:08:06,960 Halfdan Lynge: and under the umbrella of the Thyatrisja Center 144 00:08:07,120 --> 00:08:08,720 Halfdan Lynge: for Digital Governance, 145 00:08:09,440 --> 00:08:11,360 Halfdan Lynge: we hosted something called 146 00:08:11,840 --> 00:08:14,405 Halfdan Lynge: the Civic Tech Innovation Network, 147 00:08:15,445 --> 00:08:18,085 Halfdan Lynge: which is a network of researchers, 148 00:08:18,245 --> 00:08:19,285 Halfdan Lynge: activists, 149 00:08:19,285 --> 00:08:21,685 Halfdan Lynge: sort of civic techies from across 150 00:08:22,885 --> 00:08:24,325 Halfdan Lynge: the African Continent. 151 00:08:25,765 --> 00:08:33,540 Halfdan Lynge: And until today, sit on what's called the reference group, so kind of like the body that oversees 152 00:08:33,540 --> 00:08:39,917 Halfdan Lynge: there's a small secretariat that manages sort of day to day activities, but I still sit on that reference group. And in 153 00:08:39,917 --> 00:08:45,715 that context, we often have these conversations, what's govtech, what's civic tech, and are we talking about the same thing? 154 00:08:46,275 --> 00:08:47,395 Halfdan Lynge: In my 155 00:08:48,355 --> 00:08:49,795 Halfdan Lynge: conceptualization, 156 00:08:51,395 --> 00:08:53,075 Halfdan Lynge: civic tech 157 00:08:54,530 --> 00:08:56,770 Halfdan Lynge: is deployment of technology 158 00:08:56,770 --> 00:08:58,450 Halfdan Lynge: with the purpose of 159 00:08:59,490 --> 00:09:01,410 Halfdan Lynge: enhancing transparency, 160 00:09:01,490 --> 00:09:03,570 Halfdan Lynge: enhancing accountability, 161 00:09:04,210 --> 00:09:05,090 Halfdan Lynge: etcetera. 162 00:09:05,410 --> 00:09:11,905 Halfdan Lynge: So it's kind of like working with the mechanics of a democratic state as a way to, 163 00:09:13,665 --> 00:09:21,330 Halfdan Lynge: I suppose, force governments to deliver what they're supposed to. Right? If you increase transparency and accountability, it's a way 164 00:09:21,330 --> 00:09:23,630 of ensuring that governments are actually 165 00:09:24,510 --> 00:09:26,670 Halfdan Lynge: delivering what they're supposed to deliver. 166 00:09:28,270 --> 00:09:29,070 Halfdan Lynge: Now, 167 00:09:32,510 --> 00:09:36,715 Halfdan Lynge: maybe I should say, GovTech for me is kind of the I 168 00:09:37,195 --> 00:09:42,475 Halfdan Lynge: think I lean very much on the sort of OACD definition of GovTech here. It's the collaboration 169 00:09:42,475 --> 00:09:43,275 Halfdan Lynge: between 170 00:09:43,355 --> 00:09:46,475 Halfdan Lynge: public sector and private sector, be it 171 00:09:46,960 --> 00:09:48,000 Halfdan Lynge: for profit 172 00:09:49,280 --> 00:09:50,800 Halfdan Lynge: corporations or 173 00:09:51,440 --> 00:09:54,480 Halfdan Lynge: civil society initiatives, but it's a collaboration 174 00:09:54,720 --> 00:09:58,800 Halfdan Lynge: between public and private with a view to improving 175 00:09:58,800 --> 00:10:01,440 Halfdan Lynge: government service delivery, right? So improving 176 00:10:01,945 --> 00:10:02,745 Halfdan Lynge: systems, 177 00:10:02,825 --> 00:10:03,625 Halfdan Lynge: processes, 178 00:10:04,105 --> 00:10:08,185 Halfdan Lynge: etc. Within government. But it very much centers on the sort of collaboration 179 00:10:09,145 --> 00:10:11,145 Halfdan Lynge: between government and 180 00:10:13,465 --> 00:10:14,825 Halfdan Lynge: non governmental sectors. 181 00:10:17,120 --> 00:10:25,291 Halfdan Lynge: One of the reasons I think why there's often a confusion, and specifically in the context of Africa, is that the whole 182 00:10:25,291 --> 00:10:27,520 civic tech concept for me presupposes 183 00:10:29,765 --> 00:10:32,965 Halfdan Lynge: a functioning democratic state. Like, 184 00:10:34,005 --> 00:10:34,805 Halfdan Lynge: if 185 00:10:36,085 --> 00:10:37,525 Halfdan Lynge: greater accountability, 186 00:10:37,605 --> 00:10:38,805 Halfdan Lynge: greater transparency, 187 00:10:38,805 --> 00:10:39,605 Halfdan Lynge: etcetera, 188 00:10:42,180 --> 00:10:46,340 Halfdan Lynge: If that should lead to increased or improved service delivery, 189 00:10:47,460 --> 00:10:51,140 Halfdan Lynge: it presupposes that there is some kind of relative functioning 190 00:10:51,380 --> 00:10:52,500 Halfdan Lynge: state already, 191 00:10:52,740 --> 00:10:53,540 Halfdan Lynge: that 192 00:10:53,620 --> 00:10:56,340 Halfdan Lynge: the state, that the government is able to deliver something. 193 00:10:56,825 --> 00:11:03,480 Halfdan Lynge: It might not do it for XYZ reasons. There can be sort of political economy questions. There can be capacity issues, but 194 00:11:03,480 --> 00:11:06,505 there is like the core is in order and by 195 00:11:07,545 --> 00:11:09,465 Halfdan Lynge: exposing inefficiencies 196 00:11:09,465 --> 00:11:10,345 Halfdan Lynge: or by 197 00:11:10,940 --> 00:11:14,540 Halfdan Lynge: pointing to deficiencies in government service delivery, 198 00:11:14,700 --> 00:11:16,780 Halfdan Lynge: it's assumed that you can kind of like 199 00:11:17,260 --> 00:11:19,100 Halfdan Lynge: push or notch or 200 00:11:19,580 --> 00:11:22,380 Halfdan Lynge: force government to address its issues, right? 201 00:11:22,940 --> 00:11:23,740 Halfdan Lynge: Now, 202 00:11:23,820 --> 00:11:25,500 Halfdan Lynge: in the context of Africa, 203 00:11:25,660 --> 00:11:27,945 Halfdan Lynge: that does not necessarily exist, 204 00:11:28,425 --> 00:11:29,225 Halfdan Lynge: right? 205 00:11:31,385 --> 00:11:33,065 Halfdan Lynge: Even if you expose, 206 00:11:33,865 --> 00:11:36,745 Halfdan Lynge: let's say, corruption or inefficiencies 207 00:11:36,745 --> 00:11:40,585 Halfdan Lynge: in the public sector in 208 00:11:40,250 --> 00:11:43,610 Halfdan Lynge: let's take Mozambique, which is a country I worked in for many years, 209 00:11:44,090 --> 00:11:47,210 Halfdan Lynge: there is no guarantee that that will translate to 210 00:11:47,450 --> 00:11:52,810 Halfdan Lynge: any change, any improvement because of the incentives that are built into the system 211 00:11:54,085 --> 00:11:57,365 Halfdan Lynge: and the sort of lack of fundamental accountability, 212 00:11:57,365 --> 00:11:59,845 Halfdan Lynge: right? So the concept of civic tech, 213 00:12:01,525 --> 00:12:04,565 Halfdan Lynge: in my view, does not necessarily apply if 214 00:12:04,725 --> 00:12:06,165 Halfdan Lynge: the basics are not in order. 215 00:12:07,270 --> 00:12:09,670 Halfdan Lynge: And the implication of that is that 216 00:12:10,230 --> 00:12:12,630 Halfdan Lynge: if you look at the initiatives 217 00:12:12,630 --> 00:12:14,310 Halfdan Lynge: and the organisations 218 00:12:14,310 --> 00:12:18,790 Halfdan Lynge: and the people that are active and involved in the Civic Tech Innovation 219 00:12:18,790 --> 00:12:20,950 Halfdan Lynge: Network, which is an Africa specific 220 00:12:21,270 --> 00:12:25,105 Halfdan Lynge: network, you would often see that the applications, 221 00:12:25,185 --> 00:12:26,145 Halfdan Lynge: the deployments, 222 00:12:26,145 --> 00:12:31,185 Halfdan Lynge: the projects they get involved in is much closer to what I would consider GovTech, 223 00:12:31,585 --> 00:12:33,025 Halfdan Lynge: simply because 224 00:12:34,240 --> 00:12:38,880 Halfdan Lynge: they are essentially trying to fill the vacuum or fill the, 225 00:12:40,800 --> 00:12:43,440 Halfdan Lynge: yeah, the vacuum that's missing. The 226 00:12:44,400 --> 00:12:48,560 Halfdan Lynge: absent state creates a vacuum, right? And now civil society, 227 00:12:48,945 --> 00:12:52,305 Halfdan Lynge: private sector are trying to fill that vacuum, 228 00:12:52,545 --> 00:12:53,985 Halfdan Lynge: be it in terms of 229 00:12:54,225 --> 00:12:55,665 Halfdan Lynge: making sure that 230 00:12:56,145 --> 00:12:57,745 Halfdan Lynge: services reach the 231 00:12:58,705 --> 00:13:02,705 Halfdan Lynge: most remote areas or that citizens have basic information. 232 00:13:03,120 --> 00:13:05,680 Halfdan Lynge: So it's much closer to GovTech, whereas 233 00:13:09,360 --> 00:13:12,000 Halfdan Lynge: as the sort of traditional 234 00:13:12,400 --> 00:13:14,400 Halfdan Lynge: civic tech initiatives, 235 00:13:14,960 --> 00:13:21,355 Halfdan Lynge: even if it's called the Civic Tech Innovation Network, they are not necessarily the sort of bigger bulk of 236 00:13:22,955 --> 00:13:24,155 Halfdan Lynge: initiatives or 237 00:13:24,715 --> 00:13:30,635 Halfdan Lynge: projects in the African Continent. Now, that's my personal view, and I have had many conversations with my colleagues 238 00:13:32,990 --> 00:13:39,666 Halfdan Lynge: at this university and across the African Continent, and they don't necessarily agree, but at least it's kind of like my thinking 239 00:13:39,666 --> 00:13:41,790 around it that there's a clear distinction. 240 00:13:41,870 --> 00:13:48,552 Halfdan Lynge: Oh, there's obviously an overlap in the mid, but they are fundamentally two things that... And and they are and they are 241 00:13:48,552 --> 00:13:50,375 solutions to different types of problems. 242 00:13:53,575 --> 00:13:59,335 Halfdan Lynge: That's a long answer to something that shouldn't necessarily be that complex, but I hope you understand what I'm saying. 243 00:14:00,730 --> 00:14:02,090 Alessandro Oppo: Yeah. Absolutely. 244 00:14:02,170 --> 00:14:03,530 Alessandro Oppo: I think that... 245 00:14:04,810 --> 00:14:05,850 Alessandro Oppo: I mean, if 246 00:14:06,330 --> 00:14:08,090 Alessandro Oppo: people that are in this field 247 00:14:08,570 --> 00:14:09,530 Alessandro Oppo: repeatedly 248 00:14:09,930 --> 00:14:10,890 Alessandro Oppo: talk about 249 00:14:11,370 --> 00:14:12,970 Alessandro Oppo: the distinction 250 00:14:13,355 --> 00:14:15,915 Alessandro Oppo: of civic tech and gov tech maybe 251 00:14:16,635 --> 00:14:17,835 Alessandro Oppo: is not so... 252 00:14:19,115 --> 00:14:22,555 Alessandro Oppo: I mean, it's worth it to think about it. And I 253 00:14:23,195 --> 00:14:25,595 Alessandro Oppo: was thinking in relation to the context of Africa, 254 00:14:26,190 --> 00:14:29,390 Alessandro Oppo: I can imagine that many other things were different, 255 00:14:31,710 --> 00:14:35,390 Alessandro Oppo: but if you could maybe highlight some differences between 256 00:14:36,830 --> 00:14:38,190 Alessandro Oppo: Africa and 257 00:14:39,470 --> 00:14:41,470 Alessandro Oppo: maybe Europe in term of 258 00:14:42,165 --> 00:14:43,765 Alessandro Oppo: digital transformation 259 00:14:44,005 --> 00:14:44,805 Alessandro Oppo: or... 260 00:14:45,845 --> 00:14:47,525 Halfdan Lynge: Yeah. I mean, it's a very 261 00:14:48,405 --> 00:14:49,285 Halfdan Lynge: interesting, 262 00:14:49,685 --> 00:14:50,965 Halfdan Lynge: but also extremely 263 00:14:51,285 --> 00:14:52,885 Halfdan Lynge: broad question, obviously. 264 00:14:54,645 --> 00:14:55,525 Halfdan Lynge: I think I can, 265 00:14:56,970 --> 00:15:02,890 Halfdan Lynge: I mean, I can only speak from my personal experience there? I think when 266 00:15:03,690 --> 00:15:06,170 Halfdan Lynge: we started out, when my 267 00:15:08,330 --> 00:15:10,330 Halfdan Lynge: business partner and I set up 268 00:15:12,675 --> 00:15:18,995 Halfdan Lynge: the Govtech startup initially, we weren't really thinking of Govtech or Civic Tech. We were just thinking about a 269 00:15:19,235 --> 00:15:20,595 Halfdan Lynge: a a 270 00:15:21,635 --> 00:15:24,435 Halfdan Lynge: creating an organization that could deliver 271 00:15:24,755 --> 00:15:25,795 Halfdan Lynge: data products, 272 00:15:27,550 --> 00:15:30,910 Halfdan Lynge: developing a platform that would allow us to 273 00:15:31,470 --> 00:15:33,550 Halfdan Lynge: generate more information 274 00:15:33,630 --> 00:15:34,430 Halfdan Lynge: about 275 00:15:36,670 --> 00:15:37,870 Halfdan Lynge: the realities 276 00:15:37,870 --> 00:15:40,110 Halfdan Lynge: of rural Mozambique, 277 00:15:40,830 --> 00:15:42,110 Halfdan Lynge: of rural Africa, 278 00:15:44,725 --> 00:15:48,965 Halfdan Lynge: and thereby creating a knowledge base that policy 279 00:15:49,765 --> 00:15:53,365 Halfdan Lynge: can be built upon, right? Creating evidence for 280 00:15:54,165 --> 00:15:56,085 Halfdan Lynge: government and other policymakers. 281 00:15:58,440 --> 00:15:59,240 Halfdan Lynge: Now, 282 00:16:01,160 --> 00:16:03,480 Halfdan Lynge: the first challenge obviously is 283 00:16:04,360 --> 00:16:05,240 Halfdan Lynge: how 284 00:16:06,040 --> 00:16:13,975 Halfdan Lynge: you I mean, there's a fundamental infrastructure issue. I briefly spoke about it. So designing or developing an application 285 00:16:14,055 --> 00:16:16,375 Halfdan Lynge: that allows us to connect 286 00:16:16,855 --> 00:16:19,015 Halfdan Lynge: to rural Mozambique 287 00:16:19,255 --> 00:16:20,375 Halfdan Lynge: required 288 00:16:21,415 --> 00:16:27,980 Halfdan Lynge: you know, you have to simplify it as much as possible, simply because we cannot assume that people have smartphones. 289 00:16:28,220 --> 00:16:30,780 Halfdan Lynge: We cannot assume that people have 290 00:16:32,700 --> 00:16:33,580 Halfdan Lynge: three, 291 00:16:33,580 --> 00:16:35,420 Halfdan Lynge: four, five gs connectivity. 292 00:16:35,660 --> 00:16:37,340 Halfdan Lynge: We cannot even 293 00:16:37,340 --> 00:16:40,595 Halfdan Lynge: if they have a smartphone, even if they have connectivity, 294 00:16:40,595 --> 00:16:42,835 Halfdan Lynge: we cannot assume they have access to 295 00:16:43,635 --> 00:16:44,435 Halfdan Lynge: data. 296 00:16:45,395 --> 00:16:46,995 Halfdan Lynge: So the fundamental 297 00:16:46,995 --> 00:16:48,435 Halfdan Lynge: infrastructural 298 00:16:48,435 --> 00:16:51,075 Halfdan Lynge: issues are different in a context 299 00:16:51,635 --> 00:16:53,795 Halfdan Lynge: like Mozambique. So you have to build 300 00:16:54,560 --> 00:17:01,160 Halfdan Lynge: on that, and you have to start with the realities. And that's why we ended up with this very simple application that 301 00:17:01,160 --> 00:17:01,960 used SMS 302 00:17:03,120 --> 00:17:04,160 Halfdan Lynge: exchanges, 303 00:17:06,160 --> 00:17:07,040 Halfdan Lynge: USSD 304 00:17:07,040 --> 00:17:08,800 Halfdan Lynge: sessions, which is another 305 00:17:09,555 --> 00:17:17,075 Halfdan Lynge: simple mobile product call that allowed us to make these very simple questionnaires. We could ask very short questions, 306 00:17:17,075 --> 00:17:22,435 Halfdan Lynge: and we could ask, you know, maybe 15, 20 questions through kind of like an interaction. 307 00:17:25,050 --> 00:17:26,250 Halfdan Lynge: So the 308 00:17:26,410 --> 00:17:28,330 Halfdan Lynge: the fundamental 309 00:17:30,650 --> 00:17:32,490 Halfdan Lynge: deployment of technology 310 00:17:32,490 --> 00:17:33,290 Halfdan Lynge: is completely 311 00:17:34,170 --> 00:17:34,970 Halfdan Lynge: different. 312 00:17:35,290 --> 00:17:39,130 Halfdan Lynge: I think a second difference is that 313 00:17:39,825 --> 00:17:41,265 Halfdan Lynge: the business 314 00:17:41,265 --> 00:17:42,705 Halfdan Lynge: models around 315 00:17:43,985 --> 00:17:46,865 Halfdan Lynge: GovTech or Civic Tech is also completely different 316 00:17:47,105 --> 00:17:47,905 Halfdan Lynge: because 317 00:17:49,265 --> 00:17:52,385 Halfdan Lynge: you cannot use the same kind of 318 00:17:52,220 --> 00:17:54,540 Halfdan Lynge: you cannot rely on micropayments, 319 00:17:54,540 --> 00:17:56,700 Halfdan Lynge: really. You cannot rely 320 00:17:56,940 --> 00:17:59,580 Halfdan Lynge: on on people willing to 321 00:18:00,460 --> 00:18:02,060 Halfdan Lynge: pay for services. 322 00:18:02,380 --> 00:18:09,065 Halfdan Lynge: You cannot rely on on advertisement or anything. I mean, any kind of application 323 00:18:09,065 --> 00:18:11,865 Halfdan Lynge: deployment has to have some kind of of of 324 00:18:12,265 --> 00:18:13,065 Halfdan Lynge: financial 325 00:18:14,105 --> 00:18:15,065 Halfdan Lynge: economic base. 326 00:18:17,800 --> 00:18:19,320 Halfdan Lynge: You cannot rely 327 00:18:19,720 --> 00:18:23,880 Halfdan Lynge: it was very difficult my experience is it's very difficult to get, like, 328 00:18:24,200 --> 00:18:26,440 Halfdan Lynge: sort of seed funding 329 00:18:26,840 --> 00:18:29,160 Halfdan Lynge: innovation grants 330 00:18:28,725 --> 00:18:30,565 Halfdan Lynge: that are quite common to 331 00:18:30,965 --> 00:18:36,645 Halfdan Lynge: access in Europe and especially North America. So you really also have to think of an operation 332 00:18:37,685 --> 00:18:41,525 Halfdan Lynge: where you have to start you have to start making money from day one. Right? 333 00:18:42,630 --> 00:18:46,710 Halfdan Lynge: You have to be able because, I mean, you cannot it's 334 00:18:46,710 --> 00:18:51,990 Halfdan Lynge: unlikely or you have to be very good to kind of get an investor on board to say, Okay, I'll pay for 335 00:18:51,990 --> 00:18:53,430 your expenses or, you know, here's, 336 00:18:53,750 --> 00:18:54,550 Halfdan Lynge: I don't know, 337 00:18:55,275 --> 00:18:56,395 Halfdan Lynge: a few million 338 00:18:56,635 --> 00:19:03,015 Halfdan Lynge: a few million dollars to run the operation for the first two, three years. It's very unlikely to happen. So you have 339 00:19:03,015 --> 00:19:05,915 to think of ways that creates a cash flow already 340 00:19:05,995 --> 00:19:07,115 Halfdan Lynge: from the beginning. 341 00:19:07,355 --> 00:19:13,668 Halfdan Lynge: You have to think of I mean, our ambition was also let's create let's set up this company in such a way 342 00:19:13,668 --> 00:19:15,390 that we have a commercial arm 343 00:19:15,550 --> 00:19:18,830 Halfdan Lynge: that generates revenue. We can use the same application, 344 00:19:18,830 --> 00:19:20,270 Halfdan Lynge: the same platform to 345 00:19:20,590 --> 00:19:23,655 Halfdan Lynge: sell data product services for 346 00:19:23,655 --> 00:19:24,935 Halfdan Lynge: private companies, 347 00:19:26,295 --> 00:19:27,815 Halfdan Lynge: non governmental organization, 348 00:19:27,815 --> 00:19:29,735 Halfdan Lynge: UN agencies, etcetera, we 349 00:19:31,015 --> 00:19:35,255 Halfdan Lynge: can generate some kind of revenue over here and then we can use that to 350 00:19:36,260 --> 00:19:37,540 Halfdan Lynge: subsidize 351 00:19:38,660 --> 00:19:39,780 Halfdan Lynge: sort of more 352 00:19:41,060 --> 00:19:47,700 Halfdan Lynge: civil society, civic tech type initiatives. We think it's important that we generate some information about XYZ 353 00:19:47,780 --> 00:19:50,900 Halfdan Lynge: and we now have a revenue stream that can subsidize. 354 00:19:51,435 --> 00:19:52,555 Halfdan Lynge: That was our 355 00:19:53,035 --> 00:19:54,155 Halfdan Lynge: ambition from 356 00:19:54,635 --> 00:19:56,395 Halfdan Lynge: the very beginning, but you see it 357 00:19:58,475 --> 00:20:01,355 Halfdan Lynge: really depends on the ability of identifying that 358 00:20:01,675 --> 00:20:03,595 Halfdan Lynge: revenue stream, that cash flow. 359 00:20:04,310 --> 00:20:10,150 Halfdan Lynge: I think that's also completely different, at least. I mean, I haven't worked in kind of like the startup ecosystems 360 00:20:10,150 --> 00:20:10,950 Halfdan Lynge: in 361 00:20:11,190 --> 00:20:12,950 Halfdan Lynge: Europe, but from what I observe 362 00:20:13,350 --> 00:20:15,190 Halfdan Lynge: in my current role 363 00:20:15,430 --> 00:20:16,230 Halfdan Lynge: is that 364 00:20:17,125 --> 00:20:23,685 Halfdan Lynge: most of them have some kind of grant or some kind of investor that allows them to, 365 00:20:24,165 --> 00:20:24,965 Halfdan Lynge: you know, 366 00:20:25,605 --> 00:20:28,485 Halfdan Lynge: spend at least a year, maybe two years developing 367 00:20:28,485 --> 00:20:29,685 Halfdan Lynge: an organization, 368 00:20:29,685 --> 00:20:36,736 Halfdan Lynge: developing a product, developing services before they're required to actually start making money. And it completely changes your mindset 369 00:20:36,736 --> 00:20:41,190 and how you approach it. I think that's also a big difference 370 00:20:43,725 --> 00:20:47,965 Halfdan Lynge: from how these initiatives are structured in an African context versus 371 00:20:48,925 --> 00:20:49,965 Halfdan Lynge: a European 372 00:20:49,965 --> 00:20:50,845 Halfdan Lynge: context. 373 00:20:50,925 --> 00:20:55,405 Halfdan Lynge: The third I want to I mean, again, that's a very long question or very long answer. 374 00:20:55,960 --> 00:20:59,320 Halfdan Lynge: The third leg, I would say, is kind of regulatory. 375 00:21:02,520 --> 00:21:03,320 Halfdan Lynge: Often 376 00:21:04,760 --> 00:21:05,960 Halfdan Lynge: the regulatory 377 00:21:05,960 --> 00:21:07,480 Halfdan Lynge: environment is 378 00:21:07,720 --> 00:21:09,480 Halfdan Lynge: not as clearly defined. 379 00:21:10,635 --> 00:21:14,235 Halfdan Lynge: There might be areas that are not fully regulated 380 00:21:14,235 --> 00:21:18,715 Halfdan Lynge: in an African context, and even if it is regulated on paper, 381 00:21:19,115 --> 00:21:21,755 Halfdan Lynge: the enforcement of the regulation is inconsistent. 382 00:21:23,610 --> 00:21:27,290 Halfdan Lynge: And obviously, that makes it very difficult to navigate as 383 00:21:28,170 --> 00:21:29,450 Halfdan Lynge: a startup, because 384 00:21:30,730 --> 00:21:37,066 Halfdan Lynge: it's not entirely clear what you're allowed to do and what you're now allowed to do, and some things might not be 385 00:21:37,066 --> 00:21:37,930 allowed, but still, 386 00:21:39,985 --> 00:21:41,665 Halfdan Lynge: if you go ahead and do it, 387 00:21:42,225 --> 00:21:46,545 Halfdan Lynge: nobody will say anything. I mean, one of the concrete challenges we had was that 388 00:21:46,865 --> 00:21:47,825 Halfdan Lynge: in the 389 00:21:48,545 --> 00:21:50,785 Halfdan Lynge: market we were operating in, 390 00:21:51,505 --> 00:21:52,305 Halfdan Lynge: meaning 391 00:21:56,960 --> 00:22:00,320 Halfdan Lynge: companies that were selling kind of like data services, data products. 392 00:22:00,960 --> 00:22:04,480 Halfdan Lynge: We often experienced that we were competing with 393 00:22:05,520 --> 00:22:06,320 Halfdan Lynge: international, 394 00:22:09,015 --> 00:22:10,295 Halfdan Lynge: non Mozambican, 395 00:22:10,295 --> 00:22:15,815 Halfdan Lynge: non African companies without any kind of legal basis for operating in the continent, 396 00:22:17,335 --> 00:22:20,375 Halfdan Lynge: thereby technically not 397 00:22:19,430 --> 00:22:20,710 Halfdan Lynge: being allowed to 398 00:22:21,190 --> 00:22:23,350 Halfdan Lynge: sell those services, and yet they 399 00:22:23,830 --> 00:22:25,030 Halfdan Lynge: still did. So 400 00:22:27,190 --> 00:22:31,670 Halfdan Lynge: they were doing things they were not allowed to do, and yet we often lost 401 00:22:32,870 --> 00:22:37,270 Halfdan Lynge: contract to some of these big 402 00:22:35,015 --> 00:22:37,575 Halfdan Lynge: international organizations or international 403 00:22:37,975 --> 00:22:39,095 Halfdan Lynge: companies. 404 00:22:39,495 --> 00:22:42,055 Halfdan Lynge: So again, the regulatory environment is 405 00:22:42,695 --> 00:22:45,415 Halfdan Lynge: very difficult to understand, to navigate, 406 00:22:45,495 --> 00:22:46,295 Halfdan Lynge: and 407 00:22:47,335 --> 00:22:48,215 Halfdan Lynge: often 408 00:22:49,240 --> 00:22:52,120 Halfdan Lynge: the most successful is the one who's willing to 409 00:22:53,400 --> 00:22:55,800 Halfdan Lynge: take the most risks and operate 410 00:22:56,280 --> 00:22:58,520 Halfdan Lynge: on sort of the regulatory 411 00:22:58,600 --> 00:23:04,975 Halfdan Lynge: gray zone. And that makes it, at least in my experience, makes it very difficult. At times, yeah, 412 00:23:07,375 --> 00:23:08,175 Halfdan Lynge: it's 413 00:23:08,175 --> 00:23:10,975 Halfdan Lynge: not very nice when you're unsure 414 00:23:11,455 --> 00:23:16,938 Halfdan Lynge: of what is allowed and what's not allowed, and you can see that people who are consistently breaking the law are still 415 00:23:16,938 --> 00:23:17,935 getting away with it. 416 00:23:20,490 --> 00:23:24,410 Halfdan Lynge: Yeah. So those were the kind of three areas, the technological infrastructure, 417 00:23:24,410 --> 00:23:29,530 Halfdan Lynge: the sort of financial models around Govtech, and then the regulatory environment. 418 00:23:30,490 --> 00:23:33,850 Halfdan Lynge: In all different spheres, they are completely different. 419 00:23:35,815 --> 00:23:38,375 Alessandro Oppo: Yeah. I can imagine a lot of differences. 420 00:23:39,255 --> 00:23:40,055 Alessandro Oppo: Also, 421 00:23:40,135 --> 00:23:40,935 Alessandro Oppo: social. 422 00:23:41,415 --> 00:23:46,295 Alessandro Oppo: And as well, of course. Yeah. Yeah. Yeah. Yeah. And going back to, 423 00:23:47,415 --> 00:23:48,375 Alessandro Oppo: let's say, to Europe. 424 00:23:49,360 --> 00:23:51,120 Alessandro Oppo: Yeah. Maybe to 425 00:23:51,120 --> 00:23:52,320 Alessandro Oppo: to Denmark. 426 00:23:55,040 --> 00:23:59,120 Alessandro Oppo: Yeah. What... I mean, you you said that you work for the 427 00:23:59,840 --> 00:24:02,080 Alessandro Oppo: Danish agency for digital government. 428 00:24:02,585 --> 00:24:04,985 Alessandro Oppo: Yeah. And in that case, 429 00:24:05,865 --> 00:24:06,825 Alessandro Oppo: what were, like, 430 00:24:08,105 --> 00:24:11,785 Alessandro Oppo: let's say, the job to do and also what what was, 431 00:24:12,105 --> 00:24:14,505 Alessandro Oppo: let's say, difficult or particularly 432 00:24:14,505 --> 00:24:15,305 Alessandro Oppo: interesting? 433 00:24:16,330 --> 00:24:17,290 Halfdan Lynge: Yeah. I 434 00:24:19,690 --> 00:24:20,650 Halfdan Lynge: mean, should say, 435 00:24:21,850 --> 00:24:24,170 Halfdan Lynge: work at the agency for district government, 436 00:24:26,010 --> 00:24:29,290 Halfdan Lynge: but obviously, I can't speak on behalf of the agency. So 437 00:24:30,665 --> 00:24:32,905 Halfdan Lynge: my views are only my views, 438 00:24:34,585 --> 00:24:37,785 Halfdan Lynge: so just to be clear about that. I think 439 00:24:40,265 --> 00:24:42,505 Halfdan Lynge: I mean, obviously so I 440 00:24:42,985 --> 00:24:48,430 Halfdan Lynge: joined the Danish government about a little bit more than two years ago after spending 441 00:24:49,870 --> 00:24:52,030 Halfdan Lynge: most of my professional life in 442 00:24:55,230 --> 00:24:56,030 Halfdan Lynge: Southern Africa. 443 00:24:57,945 --> 00:24:58,985 Halfdan Lynge: And I think 444 00:25:00,745 --> 00:25:04,105 Halfdan Lynge: coming from that angle and going into 445 00:25:04,585 --> 00:25:05,385 Halfdan Lynge: a 446 00:25:06,665 --> 00:25:08,505 Halfdan Lynge: government entity like, 447 00:25:08,985 --> 00:25:12,985 Halfdan Lynge: like the Danish or the Danish Asian Futility Government, it's it's, 448 00:25:13,650 --> 00:25:15,090 Halfdan Lynge: It's a very 449 00:25:15,970 --> 00:25:17,650 Halfdan Lynge: highly functioning, 450 00:25:17,970 --> 00:25:19,730 Halfdan Lynge: highly efficient 451 00:25:21,490 --> 00:25:22,370 Halfdan Lynge: organisational 452 00:25:22,370 --> 00:25:27,730 Halfdan Lynge: system where I mean, I think Denmark has been extremely successful in already 453 00:25:27,355 --> 00:25:29,275 Halfdan Lynge: fifteen, twenty years ago. 454 00:25:30,395 --> 00:25:31,915 Halfdan Lynge: The government took some 455 00:25:32,475 --> 00:25:34,475 Halfdan Lynge: bold decisions and started 456 00:25:34,635 --> 00:25:37,195 Halfdan Lynge: implementing digital public infrastructure, 457 00:25:38,235 --> 00:25:39,915 Halfdan Lynge: forcing government agencies 458 00:25:41,320 --> 00:25:43,800 Halfdan Lynge: to use sort of digital platforms, 459 00:25:43,800 --> 00:25:46,200 Halfdan Lynge: forcing citizens to engage with 460 00:25:47,720 --> 00:25:53,320 Halfdan Lynge: government through digital channels. So there were some very bold, ambitious and very 461 00:25:54,465 --> 00:25:56,865 Halfdan Lynge: visionary decisions that were taken 462 00:25:57,505 --> 00:26:01,345 Halfdan Lynge: fifteen, twenty years ago. And I think even until today, 463 00:26:01,585 --> 00:26:02,385 Halfdan Lynge: the 464 00:26:02,385 --> 00:26:04,945 Halfdan Lynge: Danish public sector benefits 465 00:26:05,105 --> 00:26:09,630 Halfdan Lynge: from that. That has kind of like kept a high level of 466 00:26:11,550 --> 00:26:16,270 Halfdan Lynge: quality in digital governments and service provision for many, many years. 467 00:26:17,150 --> 00:26:18,590 Halfdan Lynge: I think also 468 00:26:18,590 --> 00:26:21,950 Halfdan Lynge: it has become a little bit of 469 00:26:22,935 --> 00:26:24,535 Halfdan Lynge: how should I put it 470 00:26:27,415 --> 00:26:28,295 Halfdan Lynge: I think 471 00:26:29,015 --> 00:26:33,655 Halfdan Lynge: because it has been such a success and it has sustained a high level over many years, 472 00:26:34,055 --> 00:26:36,375 Halfdan Lynge: I think also there's 473 00:26:36,375 --> 00:26:37,815 Halfdan Lynge: a little bit of sort of 474 00:26:38,890 --> 00:26:40,730 Halfdan Lynge: I don't know if it's inertia 475 00:26:40,730 --> 00:26:41,530 Halfdan Lynge: or 476 00:26:41,610 --> 00:26:42,570 Halfdan Lynge: kind of like 477 00:26:43,290 --> 00:26:46,890 Halfdan Lynge: comfort in, Okay, we've already received the high level. So, 478 00:26:48,010 --> 00:26:50,905 Halfdan Lynge: I feel that kind of like innovation 479 00:26:50,905 --> 00:26:52,665 Halfdan Lynge: has not really kept up, 480 00:26:54,025 --> 00:26:57,465 Halfdan Lynge: and you can see that, for example, in the latest OECD 481 00:26:57,705 --> 00:26:59,305 Halfdan Lynge: digital government index 482 00:26:59,305 --> 00:27:00,425 Halfdan Lynge: last year. 483 00:27:01,225 --> 00:27:06,645 Halfdan Lynge: Denmark dropped from, I think, a third to an eighth place. And I don't I mean, these indices are what they are, 484 00:27:06,645 --> 00:27:07,630 and it's just a 485 00:27:08,110 --> 00:27:09,150 Halfdan Lynge: proxy measure. 486 00:27:09,470 --> 00:27:11,390 Halfdan Lynge: But I think it 487 00:27:12,510 --> 00:27:14,750 Halfdan Lynge: reflects a little bit of 488 00:27:16,745 --> 00:27:19,625 Halfdan Lynge: yeah, I think it's time that people 489 00:27:20,665 --> 00:27:23,865 Halfdan Lynge: set new goals and kind of start 490 00:27:23,865 --> 00:27:24,665 Halfdan Lynge: thinking 491 00:27:24,825 --> 00:27:26,345 Halfdan Lynge: not just of 492 00:27:26,665 --> 00:27:27,945 Halfdan Lynge: fixing the little 493 00:27:29,065 --> 00:27:31,465 Halfdan Lynge: shortcomings here and there, but actually start 494 00:27:31,960 --> 00:27:38,886 Halfdan Lynge: creating a vision for what do we want digital government to look like in five, ten, fifteen years. And a lot of 495 00:27:38,886 --> 00:27:41,720 that work has already started. So two years ago, 496 00:27:42,040 --> 00:27:44,120 Halfdan Lynge: the government created a 497 00:27:45,145 --> 00:27:46,345 Halfdan Lynge: intergovernmental 498 00:27:46,345 --> 00:27:48,745 Halfdan Lynge: task force on artificial 499 00:27:48,745 --> 00:27:49,705 Halfdan Lynge: intelligence, 500 00:27:49,705 --> 00:27:50,985 Halfdan Lynge: and there's 501 00:27:50,985 --> 00:27:52,425 Halfdan Lynge: a lot of things happening, 502 00:27:54,025 --> 00:27:55,625 Halfdan Lynge: but it still hasn't 503 00:27:55,625 --> 00:27:56,905 Halfdan Lynge: fully materialized 504 00:27:56,905 --> 00:27:58,585 Halfdan Lynge: into like a concrete 505 00:27:58,665 --> 00:28:02,230 Halfdan Lynge: vision. I I hope hope it's coming, and I 506 00:28:02,470 --> 00:28:04,390 Halfdan Lynge: think so, because, I mean, 507 00:28:04,790 --> 00:28:08,470 Halfdan Lynge: these are views that I hear also from many colleagues, 508 00:28:08,710 --> 00:28:11,110 Halfdan Lynge: but we are not quite there yet. We need to kind of set 509 00:28:13,825 --> 00:28:16,705 Halfdan Lynge: the next goals. I think in concrete 510 00:28:17,905 --> 00:28:21,665 Halfdan Lynge: case, again, on open data and open data portals, 511 00:28:23,665 --> 00:28:27,665 Halfdan Lynge: one of the things we are seeing is that there is an increased activity 512 00:28:29,550 --> 00:28:30,990 Halfdan Lynge: from AI agents 513 00:28:32,270 --> 00:28:33,150 Halfdan Lynge: because 514 00:28:34,350 --> 00:28:35,150 Halfdan Lynge: citizens 515 00:28:35,150 --> 00:28:42,410 Halfdan Lynge: start using AI agents to they're not just using a browser anymore, they use an AI agent. So, you know, you can 516 00:28:42,410 --> 00:28:43,210 imagine that 517 00:28:45,745 --> 00:28:46,625 Halfdan Lynge: Citizen 518 00:28:46,785 --> 00:28:48,865 Halfdan Lynge: X received some kind of 519 00:28:51,025 --> 00:28:55,265 Halfdan Lynge: letter from government that, you know, they no longer qualify for something, 520 00:28:55,665 --> 00:29:01,343 Halfdan Lynge: and for that citizen to make sense of it, what they will typically do is they'll take the letter and upload it 521 00:29:01,343 --> 00:29:03,150 in, you know, some kind of a 522 00:29:03,550 --> 00:29:05,070 Halfdan Lynge: Claude or ChatGPT 523 00:29:05,070 --> 00:29:06,590 Halfdan Lynge: or whatever they use, 524 00:29:08,030 --> 00:29:10,270 Halfdan Lynge: and ask that agent 525 00:29:10,270 --> 00:29:11,710 Halfdan Lynge: or assistant to 526 00:29:12,325 --> 00:29:13,205 Halfdan Lynge: interpret 527 00:29:13,525 --> 00:29:14,565 Halfdan Lynge: the information. 528 00:29:14,965 --> 00:29:16,645 Halfdan Lynge: They also ask that agent 529 00:29:17,285 --> 00:29:18,965 Halfdan Lynge: to seek information. 530 00:29:19,045 --> 00:29:25,920 Halfdan Lynge: Okay, so what are my options now? Can I appeal the decision? Do I qualify for something else, etcetera? So all of 531 00:29:25,920 --> 00:29:28,420 a sudden you realize that that agent becomes 532 00:29:31,140 --> 00:29:33,860 Halfdan Lynge: the interface between citizens 533 00:29:33,940 --> 00:29:38,420 Halfdan Lynge: and certainly information about government, but soon also 534 00:29:38,820 --> 00:29:39,620 Halfdan Lynge: actual 535 00:29:39,985 --> 00:29:46,225 Halfdan Lynge: engagement with the government, right? They will very soon expect that agent also to prepare applications, 536 00:29:46,225 --> 00:29:48,065 Halfdan Lynge: maybe even file applications, 537 00:29:48,145 --> 00:29:49,185 Halfdan Lynge: etcetera, etcetera. 538 00:29:49,665 --> 00:29:56,300 Halfdan Lynge: And all of a sudden you have this situation where the relationship between government and citizens become agent mediated, 539 00:29:56,700 --> 00:29:57,580 Halfdan Lynge: and governments 540 00:29:58,380 --> 00:30:02,220 Halfdan Lynge: do not control the agent. They are provided by third party providers. 541 00:30:02,620 --> 00:30:05,020 Halfdan Lynge: Governments can develop their own agents, and 542 00:30:05,980 --> 00:30:12,821 Halfdan Lynge: that's happening all over. I mean, you briefly spoke about the Agencik State Initiative. That's the whole idea of how do we 543 00:30:12,821 --> 00:30:14,065 set up government to 544 00:30:15,505 --> 00:30:16,305 Halfdan Lynge: develop 545 00:30:16,305 --> 00:30:21,505 Halfdan Lynge: and run government business through AI agents, right? I think 546 00:30:22,450 --> 00:30:25,090 Halfdan Lynge: so that's kind of the government side of things. 547 00:30:25,410 --> 00:30:27,970 Halfdan Lynge: I think a much bigger challenge and 548 00:30:29,250 --> 00:30:30,690 Halfdan Lynge: something that requires 549 00:30:30,690 --> 00:30:34,770 Halfdan Lynge: much greater rethinking of how government is restructured is the fact that 550 00:30:35,435 --> 00:30:38,155 Halfdan Lynge: the agents become the interface. 551 00:30:38,475 --> 00:30:41,675 Halfdan Lynge: The third party agents become the interface of 552 00:30:43,355 --> 00:30:50,129 Halfdan Lynge: government citizen relations. So how do we make sure that even if we don't control that, the front end that's technically what 553 00:30:50,129 --> 00:30:56,902 it becomes the front end of governments become a third party agent. Now what can we do with the back end of 554 00:30:56,902 --> 00:30:57,702 government? 555 00:30:57,370 --> 00:31:02,330 Halfdan Lynge: What can we do with the digital public infrastructure to ensure that the information 556 00:31:02,730 --> 00:31:11,118 Halfdan Lynge: that's or that that information is accessible and available so that the agent doesn't, you know, the third party agent doesn't hallucinate 557 00:31:11,118 --> 00:31:13,405 and misinform the citizens, etcetera, etcetera. 558 00:31:13,645 --> 00:31:15,405 Halfdan Lynge: So there's some kind of fundamental 559 00:31:15,725 --> 00:31:16,525 Halfdan Lynge: rethinking 560 00:31:19,010 --> 00:31:20,450 Halfdan Lynge: that has to be done 561 00:31:21,890 --> 00:31:23,570 Halfdan Lynge: where we have to 562 00:31:24,770 --> 00:31:25,810 Halfdan Lynge: understand 563 00:31:26,050 --> 00:31:26,850 Halfdan Lynge: and 564 00:31:28,290 --> 00:31:30,130 Halfdan Lynge: perhaps redirect initiatives, 565 00:31:30,130 --> 00:31:31,010 Halfdan Lynge: investments to accommodate 566 00:31:32,415 --> 00:31:37,455 Halfdan Lynge: for the scenario when that third party agent becomes an important interface 567 00:31:38,095 --> 00:31:40,095 Halfdan Lynge: between citizens and the state. 568 00:31:40,415 --> 00:31:46,803 Halfdan Lynge: For us, in the case of sort of open data portal and access to open data, that means that, so, okay, we 569 00:31:46,803 --> 00:31:52,030 have this portal now, but if it's if the future user of that portal is not a researcher, 570 00:31:52,190 --> 00:31:53,950 Halfdan Lynge: a student, a journalist, 571 00:31:53,950 --> 00:31:54,750 Halfdan Lynge: a 572 00:31:55,870 --> 00:32:00,190 Halfdan Lynge: civil society activist or whatever, who is either 573 00:31:59,375 --> 00:32:03,055 Halfdan Lynge: going to a portal and searching for specific data or 574 00:32:03,535 --> 00:32:10,735 Halfdan Lynge: coding up some kind of data pipeline where, you know, connect to this API, connect, you know, there's always a human kind 575 00:32:10,735 --> 00:32:14,335 of sitting in that, and that's how the platform was developed 576 00:32:14,880 --> 00:32:18,080 Halfdan Lynge: and that's how we have assumed it was used. 577 00:32:18,480 --> 00:32:24,720 Halfdan Lynge: But now we are seeing that actually already we see that it's being used autonomously 578 00:32:24,800 --> 00:32:26,080 Halfdan Lynge: by agents. 579 00:32:26,240 --> 00:32:32,535 Halfdan Lynge: They might be agents prompted by citizens, but they are acting, you know, they are prompted in a way, 580 00:32:35,175 --> 00:32:35,975 Halfdan Lynge: I 581 00:32:35,975 --> 00:32:36,855 Halfdan Lynge: want to know 582 00:32:37,495 --> 00:32:42,135 Halfdan Lynge: XYZ about government, and then the agent itself goes and looks for data, 583 00:32:42,295 --> 00:32:43,095 Halfdan Lynge: starts 584 00:32:43,800 --> 00:32:50,200 Halfdan Lynge: compiling data set, merging data set and trying to answer the questions. That raises a lot of questions about 585 00:32:50,440 --> 00:32:52,360 Halfdan Lynge: the architecture of the portal. 586 00:32:56,315 --> 00:32:57,915 Halfdan Lynge: The metadata we 587 00:32:58,715 --> 00:33:00,235 Halfdan Lynge: publish on the portal, 588 00:33:00,555 --> 00:33:03,355 Halfdan Lynge: what metadata standards, what metadata fields, 589 00:33:03,995 --> 00:33:05,755 Halfdan Lynge: other kinds of protocols. 590 00:33:07,115 --> 00:33:10,940 Halfdan Lynge: Maybe it's not enough just to have an API, maybe we need something called 591 00:33:11,980 --> 00:33:12,780 Halfdan Lynge: context 592 00:33:12,860 --> 00:33:14,220 Halfdan Lynge: protocol, which is a 593 00:33:14,460 --> 00:33:18,940 Halfdan Lynge: type of protocol that accommodates specifically or that caters specifically 594 00:33:19,180 --> 00:33:24,255 Halfdan Lynge: to AI agents. So it raises a lot of questions and we've only kind of like started 595 00:33:24,255 --> 00:33:27,775 Halfdan Lynge: addressing some of these issues and to really understand 596 00:33:28,895 --> 00:33:29,775 Halfdan Lynge: how 597 00:33:30,575 --> 00:33:32,015 Halfdan Lynge: AI agents 598 00:33:32,575 --> 00:33:34,575 Halfdan Lynge: interact with infrastructure, 599 00:33:34,575 --> 00:33:36,255 Halfdan Lynge: specifically Open Data Portal, 600 00:33:36,335 --> 00:33:38,495 Halfdan Lynge: and what it means in terms of or 601 00:33:39,270 --> 00:33:42,070 Halfdan Lynge: what the implications are for us in terms of 602 00:33:42,790 --> 00:33:45,590 Halfdan Lynge: changing or adapting or 603 00:33:46,790 --> 00:33:47,830 Halfdan Lynge: reconfiguring 604 00:33:48,150 --> 00:33:49,830 Halfdan Lynge: the portal and the broader infrastructure. 605 00:33:53,015 --> 00:33:58,455 Alessandro Oppo: Yeah. I saw that these things about AI agents change a lot. Also, 606 00:33:59,095 --> 00:34:01,015 Alessandro Oppo: I saw recently a news that 607 00:34:01,255 --> 00:34:02,855 Alessandro Oppo: can since are related, like, 608 00:34:03,575 --> 00:34:05,655 Alessandro Oppo: that as an example, Anthropic, 609 00:34:05,655 --> 00:34:06,455 Alessandro Oppo: Cload. 610 00:34:07,040 --> 00:34:11,440 Alessandro Oppo: Basically, they are not using Git anymore. They built a new protocol because 611 00:34:12,000 --> 00:34:18,219 Alessandro Oppo: Git was good for humans and not for AI agents. Because when AI agents read, they have to write in a very 612 00:34:18,219 --> 00:34:20,480 quick way Yeah. Then Git is not enough. 613 00:34:22,555 --> 00:34:27,675 Alessandro Oppo: So I was thinking about how all the infrastructure now is made for humans. 614 00:34:27,835 --> 00:34:30,315 Alessandro Oppo: But if we are moving toward an 615 00:34:30,315 --> 00:34:31,115 Alessandro Oppo: Internet 616 00:34:32,075 --> 00:34:38,720 Alessandro Oppo: that is mainly used by AI agents, then Yeah. Maybe call me. I suspect you are referring to the model 617 00:34:39,600 --> 00:34:46,640 Halfdan Lynge: context protocol, MCP, which was developed initially by Anthropic, but now I think it was handed over to the Linux Foundation. So 618 00:34:46,640 --> 00:34:47,440 it is 619 00:34:48,095 --> 00:34:50,815 Halfdan Lynge: it was a protocol developed by Anthropic, 620 00:34:50,815 --> 00:34:55,295 Halfdan Lynge: but it's slowly becoming the kind of standard for how 621 00:34:57,375 --> 00:35:05,295 Halfdan Lynge: agents interact with databases. So you can take an existing database and you can implement an 622 00:35:04,490 --> 00:35:08,250 Halfdan Lynge: MCP server around it, and that allows the agents to 623 00:35:09,530 --> 00:35:11,930 Halfdan Lynge: interact with that data in a standardized 624 00:35:11,930 --> 00:35:13,770 Halfdan Lynge: format. So it's one of the 625 00:35:14,170 --> 00:35:15,850 Halfdan Lynge: steps that we are considering 626 00:35:17,025 --> 00:35:18,945 Halfdan Lynge: whether we need to implement that around 627 00:35:19,985 --> 00:35:21,105 Halfdan Lynge: government data 628 00:35:21,425 --> 00:35:26,065 Halfdan Lynge: in order for AI agents to actually fully utilize and fully, 629 00:35:28,465 --> 00:35:30,145 Halfdan Lynge: yeah, to have access to the full, 630 00:35:31,970 --> 00:35:36,290 Halfdan Lynge: depth of all information available within government instead of guessing. 631 00:35:37,570 --> 00:35:43,890 Alessandro Oppo: Yeah. Now in that case, was about the Git protocol, so the one that is, let's say, under GitHub. 632 00:35:45,105 --> 00:35:49,585 Alessandro Oppo: Oh, okay. Sorry. I misunderstood you. Yeah. Yeah. No. Sorry for the pronunciation maybe. 633 00:35:49,905 --> 00:35:50,705 Alessandro Oppo: And... But, 634 00:35:51,505 --> 00:35:54,545 Alessandro Oppo: yeah, it was interesting because it showed the difference between Yeah. 635 00:35:56,145 --> 00:35:57,105 Alessandro Oppo: What this was 636 00:35:58,130 --> 00:35:58,930 Alessandro Oppo: I mean, 637 00:35:59,490 --> 00:36:04,050 Alessandro Oppo: was okay in the past, maybe not okay in the future, that Yeah. This protocol. 638 00:36:04,850 --> 00:36:05,650 Alessandro Oppo: And 639 00:36:07,570 --> 00:36:09,650 Alessandro Oppo: and and, yeah, before you say, like, 640 00:36:11,365 --> 00:36:12,885 Alessandro Oppo: how, like, a digital, 641 00:36:13,765 --> 00:36:14,965 Alessandro Oppo: I don't know, government 642 00:36:15,285 --> 00:36:20,245 Alessandro Oppo: or... Could look or should look like in five, ten or more years. 643 00:36:21,365 --> 00:36:22,165 Alessandro Oppo: And, 644 00:36:22,565 --> 00:36:24,325 Alessandro Oppo: we mentioned also the agentic state. 645 00:36:25,280 --> 00:36:26,240 Alessandro Oppo: And 646 00:36:26,240 --> 00:36:27,040 Alessandro Oppo: so... 647 00:36:27,280 --> 00:36:28,960 Alessandro Oppo: Because we don't have, like, 648 00:36:29,360 --> 00:36:31,360 Alessandro Oppo: let's say, an exact timeline, 649 00:36:31,520 --> 00:36:34,800 Alessandro Oppo: we can just see that technology is evolving very faster. 650 00:36:34,960 --> 00:36:36,800 Alessandro Oppo: Yeah. And also citizens 651 00:36:36,800 --> 00:36:39,680 Alessandro Oppo: are start using technology also. Yeah. 652 00:36:39,920 --> 00:36:40,720 Alessandro Oppo: I mean, 653 00:36:41,335 --> 00:36:42,615 Alessandro Oppo: also before technology. 654 00:36:42,855 --> 00:36:43,655 Alessandro Oppo: I mean, specifically 655 00:36:43,975 --> 00:36:44,775 Alessandro Oppo: AI. 656 00:36:45,655 --> 00:36:47,255 Alessandro Oppo: And so I wonder if you have 657 00:36:47,975 --> 00:36:48,935 Alessandro Oppo: a sort of 658 00:36:50,135 --> 00:36:54,055 Alessandro Oppo: possible timeline. I know I know it's very difficult to to 659 00:36:54,295 --> 00:36:59,520 Alessandro Oppo: say, but Yeah. How do you imagine, like, the future of digital transformation and democracy? 660 00:37:01,680 --> 00:37:04,560 Halfdan Lynge: Yeah. No. I I I don't dare... Because listen. 661 00:37:06,400 --> 00:37:10,160 Halfdan Lynge: One one year ago or let's say one one and a half years ago, 662 00:37:12,195 --> 00:37:13,155 Halfdan Lynge: it was 663 00:37:14,595 --> 00:37:15,715 Halfdan Lynge: only experts 664 00:37:17,475 --> 00:37:18,275 Halfdan Lynge: who 665 00:37:19,555 --> 00:37:21,635 Halfdan Lynge: knew what an AI agent was. 666 00:37:22,035 --> 00:37:24,195 Halfdan Lynge: And now, I think over 667 00:37:24,595 --> 00:37:29,180 Halfdan Lynge: the last perhaps six to nine months, it's now it's everywhere. Everyone's talking about it. 668 00:37:31,500 --> 00:37:37,020 Halfdan Lynge: Even my dad, who's nearly 80 years old, he understands it. He knows what it is, and he's 669 00:37:37,215 --> 00:37:41,615 Halfdan Lynge: he's using cloth to to seek information. So it's just to say it's 670 00:37:42,015 --> 00:37:43,135 Halfdan Lynge: it's moving 671 00:37:43,295 --> 00:37:44,655 Halfdan Lynge: extremely fast. 672 00:37:44,895 --> 00:37:46,895 Halfdan Lynge: And and my 673 00:37:48,655 --> 00:37:50,575 Halfdan Lynge: I I I don't dare 674 00:37:50,950 --> 00:37:51,750 Halfdan Lynge: guessing, 675 00:37:52,070 --> 00:37:53,350 Halfdan Lynge: predicting what 676 00:37:54,390 --> 00:37:55,910 Halfdan Lynge: the timeline is. I think 677 00:37:56,870 --> 00:37:59,990 Halfdan Lynge: I'm pretty confident that I have an well, 678 00:38:00,550 --> 00:38:01,590 Halfdan Lynge: what I think 679 00:38:03,365 --> 00:38:07,445 Halfdan Lynge: will look like, digital transformation or digital government, what it will look like, 680 00:38:08,725 --> 00:38:10,485 Halfdan Lynge: I don't know if it'll be 681 00:38:11,445 --> 00:38:13,845 Halfdan Lynge: one, three, five, ten years. 682 00:38:14,165 --> 00:38:16,565 Halfdan Lynge: My concern, though, is that 683 00:38:17,410 --> 00:38:18,850 Halfdan Lynge: the technology 684 00:38:19,970 --> 00:38:21,890 Halfdan Lynge: and people's citizens' 685 00:38:21,970 --> 00:38:22,930 Halfdan Lynge: expectations 686 00:38:22,930 --> 00:38:23,730 Halfdan Lynge: are 687 00:38:24,530 --> 00:38:26,450 Halfdan Lynge: moving faster than 688 00:38:27,650 --> 00:38:30,370 Halfdan Lynge: governments can respond to. What do I mean by that? 689 00:38:30,770 --> 00:38:31,810 Halfdan Lynge: I think 690 00:38:32,205 --> 00:38:38,045 Halfdan Lynge: right now you will see that governments all over the world are busy developing sort of first generation AI 691 00:38:38,445 --> 00:38:41,965 Halfdan Lynge: assistance. Maybe they've already piloted some of them or they're, 692 00:38:41,965 --> 00:38:42,765 Halfdan Lynge: you know, 693 00:38:43,965 --> 00:38:46,365 Halfdan Lynge: deploying the first examples of 694 00:38:46,710 --> 00:38:49,510 Halfdan Lynge: AI assistants or AI agents that can... 695 00:38:49,750 --> 00:38:51,670 Halfdan Lynge: That typically, you know, they'll implement 696 00:38:51,910 --> 00:38:58,363 Halfdan Lynge: an AI assistant on top of some national citizens portal, and that gives you kind of like a very simplified way of 697 00:38:58,363 --> 00:38:59,830 interacting with the content of 698 00:39:00,310 --> 00:39:01,110 Halfdan Lynge: that portal. 699 00:39:03,405 --> 00:39:04,205 Halfdan Lynge: Now, 700 00:39:05,245 --> 00:39:06,285 Halfdan Lynge: I think 701 00:39:06,525 --> 00:39:09,565 Halfdan Lynge: that by the time we fully 702 00:39:10,765 --> 00:39:13,725 Halfdan Lynge: deploy or launch these kind of solutions, 703 00:39:13,965 --> 00:39:16,685 Halfdan Lynge: citizens will already have 704 00:39:19,600 --> 00:39:20,480 Halfdan Lynge: absorbed 705 00:39:20,960 --> 00:39:22,880 Halfdan Lynge: Claude or ChatGPPG 706 00:39:22,880 --> 00:39:27,600 Halfdan Lynge: or DeepSeek or whatever into their daily life, which means the expectations 707 00:39:28,720 --> 00:39:30,160 Halfdan Lynge: to an AI agent, 708 00:39:30,915 --> 00:39:32,755 Halfdan Lynge: what it can do and 709 00:39:33,475 --> 00:39:40,995 Halfdan Lynge: how to interact with it and what kind of problems it can solve, is already fairly high because these are extremely capable 710 00:39:41,795 --> 00:39:42,755 Halfdan Lynge: applications. 711 00:39:43,395 --> 00:39:50,243 Halfdan Lynge: And then my concern is that, you know, with citizens' expectations already up here, you know, governments are taking their time because 712 00:39:50,243 --> 00:39:52,110 you have to be cautious, know, 713 00:39:52,750 --> 00:39:55,230 Halfdan Lynge: whether it's kind of like a standard government 714 00:39:55,550 --> 00:40:00,030 Halfdan Lynge: bureaucracy, procurement takes time, etcetera. It just takes time to develop things in government 715 00:40:00,725 --> 00:40:05,685 Halfdan Lynge: for good reasons, because you have to be sure these are public money. You have to make sure that it's spent in 716 00:40:07,685 --> 00:40:09,365 Halfdan Lynge: a defensible way. 717 00:40:10,645 --> 00:40:14,565 Halfdan Lynge: But my fear is we are taking too long, and by the time we launch a product, 718 00:40:15,810 --> 00:40:16,850 Halfdan Lynge: its technical 719 00:40:18,210 --> 00:40:19,490 Halfdan Lynge: performance is 720 00:40:19,650 --> 00:40:22,850 Halfdan Lynge: down here when citizens are already expecting something here. 721 00:40:24,050 --> 00:40:26,290 Halfdan Lynge: So that creates kind of like a, 722 00:40:27,010 --> 00:40:34,610 Halfdan Lynge: again, vacuum between what citizens expect and what governments are capable of delivering. And you will see a private sector that very 723 00:40:34,610 --> 00:40:38,755 quickly will kind of like step in and fill up that vacuum. 724 00:40:41,395 --> 00:40:44,595 Halfdan Lynge: That can be a good thing. That is what I would define 725 00:40:44,860 --> 00:40:47,900 Halfdan Lynge: as govtech. We had the conversation about govtechcivictech. 726 00:40:47,900 --> 00:40:49,980 Halfdan Lynge: If governments could start collaborating 727 00:40:49,980 --> 00:40:53,820 Halfdan Lynge: with private sector, with civil society around, okay, 728 00:40:54,540 --> 00:40:55,340 Halfdan Lynge: for 729 00:40:55,580 --> 00:40:58,220 Halfdan Lynge: good reasons, government can only deliver 730 00:40:58,300 --> 00:41:00,380 Halfdan Lynge: this kind of like technical performance. 731 00:41:00,885 --> 00:41:02,965 Halfdan Lynge: Citizens are expecting something else. 732 00:41:03,205 --> 00:41:06,325 Halfdan Lynge: How can we create an ecosystem 733 00:41:06,565 --> 00:41:10,565 Halfdan Lynge: where we jointly try to fill that gap or fill that vacuum? 734 00:41:11,845 --> 00:41:12,805 Halfdan Lynge: That is my 735 00:41:13,250 --> 00:41:14,610 Halfdan Lynge: ideal scenario. 736 00:41:15,010 --> 00:41:18,370 Halfdan Lynge: My fear is that that vacuum would be filled by 737 00:41:19,090 --> 00:41:21,170 Halfdan Lynge: big mega tech companies 738 00:41:22,770 --> 00:41:26,290 Halfdan Lynge: that... Well, we're already seeing signs of it and that it kind of becomes, 739 00:41:28,395 --> 00:41:34,635 Halfdan Lynge: how should I put it, a new Google. If you think of Google in the mid two thousands, that kind of became 740 00:41:34,635 --> 00:41:37,755 the the face of the Internet for many for many people. 741 00:41:38,315 --> 00:41:40,200 Halfdan Lynge: And thereby thereby 742 00:41:40,280 --> 00:41:42,680 Halfdan Lynge: we're able to extract advertisement, 743 00:41:42,680 --> 00:41:44,040 Halfdan Lynge: you know, money, 744 00:41:44,040 --> 00:41:46,280 Halfdan Lynge: etcetera. And because of of that, 745 00:41:47,080 --> 00:41:51,160 Halfdan Lynge: I I fear that could be that could happen again because you have these 746 00:41:52,105 --> 00:41:55,465 Halfdan Lynge: big tech companies that are already providing this kind of 747 00:41:57,545 --> 00:41:59,945 Halfdan Lynge: that become the new interface. 748 00:41:59,945 --> 00:42:02,665 Halfdan Lynge: I mean, if people are engaging with the 749 00:42:03,145 --> 00:42:03,945 Halfdan Lynge: the web, 750 00:42:04,440 --> 00:42:11,320 Halfdan Lynge: with with the outside world through an AI agent, well, then that AI agent, despite what they claim and despite their, 751 00:42:11,480 --> 00:42:13,480 Halfdan Lynge: you know, lofty words about, 752 00:42:14,360 --> 00:42:15,240 Halfdan Lynge: humanity 753 00:42:15,240 --> 00:42:21,682 Halfdan Lynge: and safety and blah, blah, blah, blah, it gives you a lot of power if you become that window into the world. 754 00:42:21,682 --> 00:42:22,482 And 755 00:42:22,935 --> 00:42:29,655 Halfdan Lynge: and I think that's what... From my personal perspective, that's that's my my concern that we we create these kind of, like, 756 00:42:32,480 --> 00:42:33,360 Halfdan Lynge: extremely 757 00:42:33,840 --> 00:42:36,800 Halfdan Lynge: dominant players in in in in the market. 758 00:42:39,200 --> 00:42:40,640 Alessandro Oppo: Yeah. Also because, 759 00:42:41,760 --> 00:42:47,115 Alessandro Oppo: I mean, there are not there are not so many players. I mean, if we talk about AI. 760 00:42:49,595 --> 00:42:51,275 Alessandro Oppo: And so also there is the question 761 00:42:52,395 --> 00:42:53,195 Alessandro Oppo: with, 762 00:42:53,195 --> 00:42:54,315 Alessandro Oppo: let's say, the... 763 00:42:55,915 --> 00:42:58,075 Alessandro Oppo: And and this was also with Google, 764 00:42:58,235 --> 00:43:00,555 Alessandro Oppo: like, if Google is providing services, 765 00:43:01,230 --> 00:43:03,230 Alessandro Oppo: I mean different kind of services 766 00:43:03,630 --> 00:43:04,430 Alessandro Oppo: in... 767 00:43:07,230 --> 00:43:08,110 Alessandro Oppo: Sorry, 768 00:43:08,270 --> 00:43:09,870 Alessandro Oppo: different kind of services 769 00:43:10,830 --> 00:43:11,950 Alessandro Oppo: than the state, 770 00:43:12,110 --> 00:43:14,430 Alessandro Oppo: because maybe the state is offering welfare and so 771 00:43:15,625 --> 00:43:16,425 Alessandro Oppo: And... 772 00:43:16,505 --> 00:43:19,225 Alessandro Oppo: But, yeah, then I I wonder who is 773 00:43:19,785 --> 00:43:21,065 Alessandro Oppo: who is the state? 774 00:43:21,305 --> 00:43:27,625 Alessandro Oppo: Like, because let's say, if I don't have to go on the, I don't know, italy.gov.it, 775 00:43:27,625 --> 00:43:32,310 Alessandro Oppo: but I can just, I don't know, on Google or on Charge to 776 00:43:33,830 --> 00:43:35,510 Alessandro Oppo: use it as a interface 777 00:43:36,790 --> 00:43:40,550 Alessandro Oppo: Yeah. Instead of on the official website of the government, 778 00:43:41,510 --> 00:43:46,805 Alessandro Oppo: then my relation is with Google or JGPT instead of that with 779 00:43:46,805 --> 00:43:47,845 Alessandro Oppo: the government. 780 00:43:48,965 --> 00:43:50,805 Alessandro Oppo: And also I was thinking That's a good point. Yeah. 781 00:43:51,365 --> 00:43:52,245 Alessandro Oppo: And 782 00:43:52,885 --> 00:43:56,005 Alessandro Oppo: I'm thinking the same maybe could be also with universities 783 00:43:57,240 --> 00:44:00,200 Alessandro Oppo: because I had this thought some years ago when 784 00:44:00,440 --> 00:44:02,040 Alessandro Oppo: we switched basically 785 00:44:02,920 --> 00:44:03,720 Alessandro Oppo: from... 786 00:44:03,800 --> 00:44:07,560 Alessandro Oppo: The Milan University switched from their hosted email 787 00:44:07,560 --> 00:44:08,440 Alessandro Oppo: account 788 00:44:08,440 --> 00:44:09,240 Alessandro Oppo: to 789 00:44:10,120 --> 00:44:14,485 Alessandro Oppo: Microsoft once. Mhmm. So everything was organized inside Microsoft. 790 00:44:14,485 --> 00:44:16,485 Alessandro Oppo: And so I was like... Basically, 791 00:44:17,445 --> 00:44:21,125 Alessandro Oppo: it was a sort of digital twin of the university inside Microsoft. Yeah. 792 00:44:22,325 --> 00:44:23,605 Alessandro Oppo: So I had this kind of thoughts. 793 00:44:24,300 --> 00:44:25,100 Alessandro Oppo: And 794 00:44:25,260 --> 00:44:32,370 Alessandro Oppo: then I was thinking if there is the, let's say, a sort of agentic state or different version of the agentic state 795 00:44:32,370 --> 00:44:33,340 in different countries, 796 00:44:33,580 --> 00:44:34,380 Alessandro Oppo: like, 797 00:44:35,180 --> 00:44:36,700 Alessandro Oppo: do you think that the, 798 00:44:37,455 --> 00:44:39,615 Alessandro Oppo: let's say, representative system 799 00:44:40,015 --> 00:44:42,655 Alessandro Oppo: should be adopted in some way? 800 00:44:43,375 --> 00:44:45,775 Alessandro Oppo: Because also the representative system was 801 00:44:47,295 --> 00:44:48,095 Alessandro Oppo: built 802 00:44:48,975 --> 00:44:50,815 Alessandro Oppo: and there were not AI agents. 803 00:44:51,460 --> 00:44:56,660 Alessandro Oppo: So I wonder, like, in the future if also the political system should be 804 00:44:57,060 --> 00:44:57,860 Alessandro Oppo: adapted 805 00:44:59,220 --> 00:45:01,140 Alessandro Oppo: to the new kind of infrastructure, 806 00:45:01,140 --> 00:45:01,940 Alessandro Oppo: Realik. 807 00:45:03,165 --> 00:45:08,525 Halfdan Lynge: It's a good question, and I I don't think I have a... I have an answer. I I do think that 808 00:45:12,845 --> 00:45:16,045 Halfdan Lynge: at some point... And, again, I don't know whether that's one, 809 00:45:16,560 --> 00:45:20,000 Halfdan Lynge: two, three, five, ten, twenty five years from now. 810 00:45:20,640 --> 00:45:21,680 Halfdan Lynge: But I think, 811 00:45:22,720 --> 00:45:25,280 Halfdan Lynge: you know, our our democracies 812 00:45:26,480 --> 00:45:31,475 Halfdan Lynge: have worked in the same way. In many ways, the fundamental 813 00:45:33,075 --> 00:45:33,875 Halfdan Lynge: processes 814 00:45:36,195 --> 00:45:37,795 Halfdan Lynge: and institutions 815 00:45:38,435 --> 00:45:39,235 Halfdan Lynge: and 816 00:45:40,195 --> 00:45:41,715 Halfdan Lynge: means of engagement 817 00:45:42,435 --> 00:45:43,235 Halfdan Lynge: are 818 00:45:43,500 --> 00:45:45,020 Halfdan Lynge: largely the same 819 00:45:46,060 --> 00:45:49,660 Halfdan Lynge: for the last, what I mean, it depends on how you define it, but 820 00:45:50,300 --> 00:45:54,860 Halfdan Lynge: you could say one hundred or two hundred years depending on kind of like how strict you are. 821 00:45:59,555 --> 00:46:00,675 Halfdan Lynge: And we have 822 00:46:01,235 --> 00:46:04,755 Halfdan Lynge: obviously, over a period of one or two hundred years, there's been like 823 00:46:06,035 --> 00:46:07,715 Halfdan Lynge: technological developments, 824 00:46:09,555 --> 00:46:17,040 Halfdan Lynge: but we've still been able to accommodate for these technological developments within the existing framework 825 00:46:17,200 --> 00:46:18,000 Halfdan Lynge: by, 826 00:46:18,080 --> 00:46:21,200 Halfdan Lynge: you know, tweaking things, extending things, 827 00:46:21,200 --> 00:46:28,867 Halfdan Lynge: you know, oh, I mean, just to look at over the last twenty five years, oh, we can do public hearings online 828 00:46:28,867 --> 00:46:29,667 or, 829 00:46:31,215 --> 00:46:32,015 Halfdan Lynge: you know, 830 00:46:32,495 --> 00:46:35,055 Halfdan Lynge: we don't need to be physically present 831 00:46:35,055 --> 00:46:35,855 Halfdan Lynge: to vote, 832 00:46:36,655 --> 00:46:37,455 Halfdan Lynge: you know. So 833 00:46:39,380 --> 00:46:40,180 Halfdan Lynge: accommodated 834 00:46:40,180 --> 00:46:42,100 Halfdan Lynge: for the technological developments 835 00:46:42,340 --> 00:46:47,060 Halfdan Lynge: in some ways without fundamentally rethinking the system. But I think 836 00:46:47,460 --> 00:46:49,940 Halfdan Lynge: at some point we're 837 00:46:49,940 --> 00:46:50,900 Halfdan Lynge: going to reach 838 00:46:51,905 --> 00:46:53,265 Halfdan Lynge: as kind of like, you 839 00:46:54,465 --> 00:46:57,585 Halfdan Lynge: know, we are stretching the elastic a little bit. Right? And 840 00:46:58,145 --> 00:47:00,705 Halfdan Lynge: my concern is at some point it's gonna snap. Right? 841 00:47:01,345 --> 00:47:02,625 Halfdan Lynge: The technological 842 00:47:02,625 --> 00:47:03,745 Halfdan Lynge: realities, 843 00:47:04,545 --> 00:47:07,980 Halfdan Lynge: the daily lives of citizens is now too far 844 00:47:08,060 --> 00:47:09,500 Halfdan Lynge: from the assumptions 845 00:47:09,900 --> 00:47:11,180 Halfdan Lynge: of a 846 00:47:11,260 --> 00:47:12,220 Halfdan Lynge: democracy. 847 00:47:12,780 --> 00:47:17,420 Halfdan Lynge: And I think before before it snaps, I think we need to rethink. 848 00:47:17,420 --> 00:47:18,220 Halfdan Lynge: Okay. 849 00:47:18,380 --> 00:47:24,165 Halfdan Lynge: If we we if we want to maintain the same principles that are embedded in democracy, 850 00:47:24,725 --> 00:47:28,325 Halfdan Lynge: but we want to apply those or we want to give 851 00:47:28,405 --> 00:47:32,245 Halfdan Lynge: them some kind of concrete form given our technological 852 00:47:32,245 --> 00:47:33,045 Halfdan Lynge: context, 853 00:47:33,125 --> 00:47:34,885 Halfdan Lynge: we need to start rethinking 854 00:47:35,205 --> 00:47:36,005 Halfdan Lynge: what... 855 00:47:36,325 --> 00:47:37,205 Halfdan Lynge: How do we vote? 856 00:47:37,890 --> 00:47:41,970 Halfdan Lynge: How do we engage with citizens? How do citizens 857 00:47:41,970 --> 00:47:49,170 Halfdan Lynge: organize themselves? How do they aggregate interest? How do we represent those interests in parliament? How does the parliament work? 858 00:47:51,205 --> 00:47:53,925 Halfdan Lynge: How does a legislative process work, etcetera? 859 00:47:54,085 --> 00:48:00,245 Halfdan Lynge: All of these fundamental things that have really I mean, we've tweaked with it, but we haven't really fundamentally changed them for, 860 00:48:01,525 --> 00:48:04,485 Halfdan Lynge: yeah, I want to say hundreds of years, certainly in some countries. 861 00:48:06,520 --> 00:48:10,120 Halfdan Lynge: But I think we need to do that. I don't have the answers, 862 00:48:10,120 --> 00:48:11,400 Halfdan Lynge: but my 863 00:48:12,360 --> 00:48:16,280 Halfdan Lynge: concern is that we are still too focused 864 00:48:16,680 --> 00:48:17,480 Halfdan Lynge: and 865 00:48:17,480 --> 00:48:19,080 Halfdan Lynge: too focused on 866 00:48:19,895 --> 00:48:20,775 Halfdan Lynge: changing, 867 00:48:20,775 --> 00:48:23,255 Halfdan Lynge: adapting the existing institutions 868 00:48:23,655 --> 00:48:26,455 Halfdan Lynge: rather than rethinking the institution themselves. 869 00:48:26,855 --> 00:48:28,215 Halfdan Lynge: I understand why. 870 00:48:31,190 --> 00:48:36,580 Halfdan Lynge: The reason for that is obviously that it's extremely risky. If you kind of like open it up and say, Okay, you 871 00:48:36,580 --> 00:48:39,030 know, let's just think out of the box and basically 872 00:48:40,390 --> 00:48:41,910 Halfdan Lynge: reinvent democratic 873 00:48:41,910 --> 00:48:42,870 Halfdan Lynge: institutions, 874 00:48:43,190 --> 00:48:48,656 Halfdan Lynge: it's a risky process. We have something that has served us well for many, many years, and if we now open it 875 00:48:48,656 --> 00:48:52,135 up and say, now we can think of something else, it's a very delicate 876 00:48:52,455 --> 00:48:54,615 Halfdan Lynge: process or a delicate point in time. 877 00:48:54,935 --> 00:48:56,695 Halfdan Lynge: So rather than do that, 878 00:48:57,175 --> 00:49:00,375 Halfdan Lynge: let's try to, you know, make these little tweaks and adjustments 879 00:49:02,000 --> 00:49:05,200 Halfdan Lynge: around it without completely breaking the existing institution. 880 00:49:05,760 --> 00:49:10,240 Halfdan Lynge: And that, I think, surely can, you know, we can keep going like that for another 881 00:49:10,800 --> 00:49:14,000 Halfdan Lynge: I don't know, maybe we can continue that like that for another 882 00:49:14,240 --> 00:49:19,539 Halfdan Lynge: fifty or one hundred years, I don't know. But my concern is that at some point, you know, the elastic is stretched 883 00:49:19,539 --> 00:49:21,225 too far and it's going to snap, 884 00:49:21,545 --> 00:49:22,345 Halfdan Lynge: and then 885 00:49:23,305 --> 00:49:24,745 Halfdan Lynge: are kind of like caught 886 00:49:25,065 --> 00:49:26,905 Halfdan Lynge: off guard and as 887 00:49:26,905 --> 00:49:27,785 Halfdan Lynge: societies, 888 00:49:27,785 --> 00:49:31,545 Halfdan Lynge: we are not, you know, we're not ready for it. We haven't done our homework. 889 00:49:33,220 --> 00:49:36,420 Halfdan Lynge: But I think I know you've spoken on your podcast also with 890 00:49:37,140 --> 00:49:41,140 Halfdan Lynge: other people who spent more time than me thinking about these kind of like fundamental 891 00:49:41,140 --> 00:49:42,500 Halfdan Lynge: democratic issues. 892 00:49:43,540 --> 00:49:44,340 Halfdan Lynge: So, 893 00:49:46,495 --> 00:49:48,415 Halfdan Lynge: yeah. I I think that's 894 00:49:48,415 --> 00:49:50,735 Halfdan Lynge: as close as I'll get to answering your question. 895 00:49:51,295 --> 00:49:54,255 Alessandro Oppo: No. I mean, I I know they are 896 00:49:55,055 --> 00:49:57,935 Alessandro Oppo: open question. Basically, there are no 897 00:49:59,295 --> 00:50:00,335 Alessandro Oppo: no 898 00:50:00,990 --> 00:50:02,670 Alessandro Oppo: answers. I I mean, I I 899 00:50:03,150 --> 00:50:04,910 Alessandro Oppo: believe, as you said, that 900 00:50:05,390 --> 00:50:08,190 Alessandro Oppo: the elastic will stretch at a certain point. 901 00:50:12,190 --> 00:50:13,790 Alessandro Oppo: Yeah. I also don't know when. 902 00:50:15,025 --> 00:50:20,785 Alessandro Oppo: I mean, I saw that in history there were several changes in how people took decisions, 903 00:50:20,785 --> 00:50:24,705 Alessandro Oppo: so I can imagine that also in the future there will be maybe another one. 904 00:50:25,185 --> 00:50:26,545 Alessandro Oppo: Then I wonder if... 905 00:50:28,390 --> 00:50:32,310 Alessandro Oppo: Also, we don't know if we will have technology in one hundredth year. 906 00:50:33,350 --> 00:50:35,270 Alessandro Oppo: Yeah. Yeah. We assume. 907 00:50:35,590 --> 00:50:36,390 Halfdan Lynge: Yeah. 908 00:50:36,550 --> 00:50:41,590 Halfdan Lynge: But for example, I mean, I always think about it. Okay. So why did we invent representative democracy? 909 00:50:42,455 --> 00:50:45,095 Halfdan Lynge: We invented representative democracy because 910 00:50:47,335 --> 00:50:48,615 Halfdan Lynge: taking decisions 911 00:50:48,615 --> 00:50:49,495 Halfdan Lynge: required 912 00:50:49,495 --> 00:50:50,935 Halfdan Lynge: physical proximity, 913 00:50:50,935 --> 00:50:55,255 Halfdan Lynge: right? We had to sit together to discuss issues and take a decision about A or B. 914 00:50:55,960 --> 00:50:58,120 Halfdan Lynge: Now, before there was telephone, 915 00:50:59,880 --> 00:51:04,600 Halfdan Lynge: internet, any kind of technology, that required a physical person to travel from 916 00:51:06,040 --> 00:51:09,720 Halfdan Lynge: district X to the capital and meet with other representatives. 917 00:51:09,800 --> 00:51:15,635 Halfdan Lynge: So that's, for me at least, is the kind of like the fundamental reason why we create a representative democracy. 918 00:51:15,955 --> 00:51:16,755 Halfdan Lynge: Now, 919 00:51:16,835 --> 00:51:19,555 Halfdan Lynge: that condition no longer exists. First of all, 920 00:51:20,435 --> 00:51:23,475 Halfdan Lynge: we don't need to be physically present in the same location. 921 00:51:23,955 --> 00:51:24,755 Halfdan Lynge: So 922 00:51:24,850 --> 00:51:26,370 Halfdan Lynge: do we need 923 00:51:27,010 --> 00:51:28,690 Halfdan Lynge: representative democracy in 924 00:51:29,170 --> 00:51:31,250 Halfdan Lynge: a kind of like a twenty first century? 925 00:51:32,530 --> 00:51:33,730 Halfdan Lynge: Not necessarily. 926 00:51:33,730 --> 00:51:35,330 Halfdan Lynge: You could imagine 927 00:51:35,810 --> 00:51:37,170 Halfdan Lynge: other ways of 928 00:51:38,125 --> 00:51:39,565 Halfdan Lynge: organizing citizens, 929 00:51:39,565 --> 00:51:41,485 Halfdan Lynge: of aggregating their interest, of 930 00:51:41,885 --> 00:51:45,725 Halfdan Lynge: channeling their interests into government and into decision making 931 00:51:46,365 --> 00:51:51,245 Halfdan Lynge: in all kinds of ways that do not presuppose this kind of delegation of authority or representation. 932 00:51:52,310 --> 00:51:57,963 Halfdan Lynge: But still we are hanging on to that. I mean, we're hanging on to elected representatives who then represent a constituency or 933 00:51:57,963 --> 00:52:00,790 a group of people or class or whatever it might be, 934 00:52:01,110 --> 00:52:01,910 Halfdan Lynge: but 935 00:52:01,990 --> 00:52:03,190 Halfdan Lynge: that's not a 936 00:52:03,430 --> 00:52:04,870 Halfdan Lynge: sort of the 937 00:52:04,870 --> 00:52:07,270 Halfdan Lynge: only way you could imagine a democracy 938 00:52:07,745 --> 00:52:08,545 Halfdan Lynge: working, 939 00:52:08,705 --> 00:52:15,117 Halfdan Lynge: and yet that's what we have, because it worked very well. And then, okay, now maybe the representative is still sitting in 940 00:52:15,117 --> 00:52:16,865 their district and they are attending 941 00:52:17,345 --> 00:52:18,705 Halfdan Lynge: parliamentary hearings 942 00:52:18,785 --> 00:52:19,585 Halfdan Lynge: online, 943 00:52:19,890 --> 00:52:24,370 Halfdan Lynge: but the logic is still what it was set up for in, you know, 944 00:52:25,570 --> 00:52:27,170 Halfdan Lynge: pre industrial times. Right? 945 00:52:28,770 --> 00:52:29,570 Alessandro Oppo: Yeah. 946 00:52:29,810 --> 00:52:33,170 Alessandro Oppo: Maybe we can ask also AI how to simplify the government. 947 00:52:33,825 --> 00:52:36,385 Alessandro Oppo: And I was thinking maybe the same thing for law. 948 00:52:36,705 --> 00:52:37,505 Alessandro Oppo: Interesting. 949 00:52:37,985 --> 00:52:41,345 Halfdan Lynge: For law. Yeah. Yeah. I mean, there's a lot of 950 00:52:41,665 --> 00:52:44,545 Halfdan Lynge: a lot of experiments with that having AI, 951 00:52:47,780 --> 00:52:50,660 Halfdan Lynge: you know, map out laws and contradictions 952 00:52:50,660 --> 00:52:54,500 Halfdan Lynge: and overlaps in legislation. And I think there's a lot of potential to be 953 00:52:56,900 --> 00:52:59,060 Halfdan Lynge: reaped from doing that for sure. 954 00:53:00,925 --> 00:53:04,685 Alessandro Oppo: Yeah. Yeah. A lot of, let's say, open questions 955 00:53:04,765 --> 00:53:05,565 Alessandro Oppo: that 956 00:53:05,565 --> 00:53:07,805 Alessandro Oppo: maybe in the future we will have an answer. 957 00:53:08,605 --> 00:53:09,565 Alessandro Oppo: And... Yeah. 958 00:53:10,285 --> 00:53:11,565 Alessandro Oppo: Do you have some 959 00:53:12,125 --> 00:53:14,765 Alessandro Oppo: open questions? I don't know. Something you would like to 960 00:53:15,480 --> 00:53:16,920 Alessandro Oppo: talk about or 961 00:53:17,320 --> 00:53:19,240 Alessandro Oppo: some question in your mind. 962 00:53:22,600 --> 00:53:30,206 Halfdan Lynge: No. I think... Listen. I I think I've already touched them. I mean, for me right now in my in my current 963 00:53:30,206 --> 00:53:32,280 role, and and and I'm I'm 964 00:53:31,825 --> 00:53:35,105 Halfdan Lynge: I think that for me, the fundamental question is how this 965 00:53:37,825 --> 00:53:38,705 Halfdan Lynge: very rapid 966 00:53:43,040 --> 00:53:49,360 Halfdan Lynge: growth or very rapid absorption of agentic AI and how quickly people are 967 00:53:50,400 --> 00:53:54,000 Halfdan Lynge: integrating it into their daily lives and what it means 968 00:53:56,165 --> 00:53:58,965 Halfdan Lynge: for government and for relations between 969 00:53:59,845 --> 00:54:01,445 Halfdan Lynge: the state and citizens. 970 00:54:01,445 --> 00:54:02,325 Halfdan Lynge: I think that's 971 00:54:02,725 --> 00:54:05,045 Halfdan Lynge: I really think that is a fundamental 972 00:54:05,445 --> 00:54:06,325 Halfdan Lynge: change 973 00:54:08,320 --> 00:54:12,400 Halfdan Lynge: and it's and it's happening so fast that I'm I'm afraid that, 974 00:54:12,720 --> 00:54:13,520 Halfdan Lynge: you know, 975 00:54:14,160 --> 00:54:21,262 Halfdan Lynge: that our systems, our institutions, governments, etcetera, that we are not ready for it. It's happening quicker than we can respond 976 00:54:21,262 --> 00:54:22,062 to. 977 00:54:22,725 --> 00:54:24,645 Halfdan Lynge: And I'm a little bit concerned with 978 00:54:25,285 --> 00:54:27,125 Halfdan Lynge: what the implication of 979 00:54:27,285 --> 00:54:28,565 Halfdan Lynge: that will be. 980 00:54:29,525 --> 00:54:33,365 Halfdan Lynge: So, those are really the questions that are on my mind right 981 00:54:35,285 --> 00:54:36,085 Alessandro Oppo: now. 982 00:54:39,470 --> 00:54:40,270 Halfdan Lynge: Yeah. 983 00:54:40,590 --> 00:54:41,390 Alessandro Oppo: And... 984 00:54:42,030 --> 00:54:43,310 Alessandro Oppo: Yeah. I I mean, 985 00:54:44,510 --> 00:54:47,790 Alessandro Oppo: I agree that they are, let's say, important open questions. 986 00:54:48,145 --> 00:54:50,625 Alessandro Oppo: I don't have an answer, unfortunately. 987 00:54:52,305 --> 00:54:53,105 Alessandro Oppo: And 988 00:54:53,345 --> 00:54:58,385 Alessandro Oppo: and, yeah, if you have, I don't know, a sort of final message for all the people that are working 989 00:54:59,265 --> 00:55:02,545 Alessandro Oppo: in the field or similar field, digital transformation,, 990 00:55:03,185 --> 00:55:03,985 Alessandro Oppo: and GovTech. 991 00:55:05,160 --> 00:55:05,960 Alessandro Oppo: And 992 00:55:07,160 --> 00:55:13,320 Halfdan Lynge: Yeah. I think maybe, I mean, you you... I I I didn't think about it, but I... But your question about democracy 993 00:55:13,320 --> 00:55:14,120 Halfdan Lynge: and... 994 00:55:14,280 --> 00:55:18,840 Halfdan Lynge: Made me think that I hope some people out there are thinking about that. You know, what what 995 00:55:19,385 --> 00:55:20,185 Halfdan Lynge: if 996 00:55:21,865 --> 00:55:22,665 Halfdan Lynge: we 997 00:55:22,665 --> 00:55:25,785 Halfdan Lynge: started with what we have today, how people 998 00:55:26,825 --> 00:55:32,105 Halfdan Lynge: live their lives today, how people use technology today, and if we wanted to develop a 999 00:55:32,425 --> 00:55:34,585 Halfdan Lynge: or conceptualize a new 1000 00:55:35,090 --> 00:55:38,850 Halfdan Lynge: democracy two point o that takes 1001 00:55:41,090 --> 00:55:47,103 Halfdan Lynge: at the starting point the reality of today, what would it look like? I hope there are people out there, maybe some 1002 00:55:47,103 --> 00:55:47,903 of your 1003 00:55:48,210 --> 00:55:49,250 Halfdan Lynge: guests that 1004 00:55:49,595 --> 00:55:51,595 Halfdan Lynge: are thinking about that because, yeah, 1005 00:55:53,115 --> 00:55:53,915 Halfdan Lynge: I 1006 00:55:54,795 --> 00:55:59,915 Halfdan Lynge: think I fear that this elastic is about to snap, and 1007 00:56:03,320 --> 00:56:04,440 Halfdan Lynge: shouldn't only think 1008 00:56:05,240 --> 00:56:06,440 Halfdan Lynge: about how we can 1009 00:56:06,760 --> 00:56:09,880 Halfdan Lynge: tweak the existing systems. I think also we need to think of 1010 00:56:10,120 --> 00:56:11,720 Halfdan Lynge: completely new systems that 1011 00:56:15,415 --> 00:56:18,375 Halfdan Lynge: yeah, that takes are a different starting point than 1012 00:56:19,015 --> 00:56:19,815 Halfdan Lynge: Europe 1013 00:56:20,695 --> 00:56:21,655 Halfdan Lynge: in the 1014 00:56:23,575 --> 00:56:26,055 Halfdan Lynge: pre nineteenth century or mid nineteenth century. 1015 00:56:28,950 --> 00:56:35,430 Halfdan Lynge: So that that... That's my final encouragement to to to you and perhaps some of your guests on the on the podcast. 1016 00:56:36,310 --> 00:56:38,950 Halfdan Lynge: And and and let let the rest of us know when you find the answer. 1017 00:56:40,795 --> 00:56:45,035 Alessandro Oppo: Yeah. Maybe so to to be a little bit creative so that we can 1018 00:56:45,515 --> 00:56:46,875 Alessandro Oppo: experiment and 1019 00:56:47,115 --> 00:56:47,995 Alessandro Oppo: find new 1020 00:56:48,235 --> 00:56:49,515 Alessandro Oppo: possible ways, 1021 00:56:49,755 --> 00:56:51,275 Alessandro Oppo: democratic ways. 1022 00:56:51,435 --> 00:56:52,315 Alessandro Oppo: Yeah. Yeah. 1023 00:56:53,090 --> 00:56:55,090 Alessandro Oppo: Exactly. Thank you a lot, Arthur. Thank 1024 00:56:57,250 --> 00:56:58,930 Halfdan Lynge: you very much, Alessandro. 1025 00:56:58,930 --> 00:57:02,130 Halfdan Lynge: And, yeah, thanks for the conversation. I really enjoyed it. And 1026 00:57:03,090 --> 00:57:04,050 Alessandro Oppo: Thank you. All the best.