1 00:00:51,801 --> 00:00:54,234 Best Case scenario We can work 2 00:00:54,234 --> 00:00:55,967 Best Case scenario We can work on 30% of our normal capacity 3 00:00:55,967 --> 00:00:57,533 on 30% of our normal capacity just talking about our sector 4 00:00:57,533 --> 00:01:00,000 just talking about our sector or this bar we try to create 5 00:01:00,000 --> 00:01:02,466 or this bar we try to create something and then suddenly 6 00:01:02,466 --> 00:01:05,166 something and then suddenly it’s apparently not really 7 00:01:05,166 --> 00:01:07,266 it’s apparently not really worth anything. I’m pretty much 8 00:01:07,266 --> 00:01:08,000 worth anything. I’m pretty much online. all the time you know 9 00:01:08,000 --> 00:01:09,667 online. all the time you know like I do videos I did videos 10 00:01:09,667 --> 00:01:11,667 like I do videos I did videos before I did collaborations 11 00:01:11,667 --> 00:01:12,866 before I did collaborations with other artists before but 12 00:01:12,866 --> 00:01:13,534 with other artists before but to be honest and this is why 13 00:01:13,534 --> 00:01:17,300 to be honest and this is why I’m on so I call it negative. 14 00:01:17,300 --> 00:01:19,466 I’m on so I call it negative. uh the fact of being in one 15 00:01:19,466 --> 00:01:21,100 uh the fact of being in one room or in one open air 16 00:01:21,100 --> 00:01:22,500 room or in one open air situation with the audience 17 00:01:22,500 --> 00:01:24,934 situation with the audience sweating together. This is 18 00:01:24,934 --> 00:01:27,266 sweating together. This is something I don’t wanna miss 19 00:01:27,266 --> 00:01:28,800 something I don’t wanna miss people don’t wanna miss future 20 00:01:28,800 --> 00:01:29,533 people don’t wanna miss future of the job of the artist will 21 00:01:29,533 --> 00:01:31,767 of the job of the artist will be to be even more connected to 22 00:01:31,767 --> 00:01:34,434 be to be even more connected to the materials that are used in 23 00:01:34,434 --> 00:01:37,333 the materials that are used in in um uh either analog or aways 24 00:01:37,333 --> 00:01:39,933 in um uh either analog or aways or a new media ways or whatever 25 00:01:39,933 --> 00:01:41,566 or a new media ways or whatever ways will come because art was 26 00:01:41,566 --> 00:01:43,900 ways will come because art was always here and always thinking 27 00:01:43,900 --> 00:01:46,999 always here and always thinking about these 28 00:01:52,467 --> 00:01:54,133 things. se développer et 29 00:01:54,133 --> 00:01:55,067 things. se développer et peut-être que effectivement ici 30 00:01:55,067 --> 00:01:56,066 peut-être que effectivement ici aussi dans nos régions 31 00:01:56,066 --> 00:01:57,300 aussi dans nos régions frontalières, c’est une chance 32 00:01:57,300 --> 00:01:58,066 frontalières, c’est une chance par exemple au point de vue de 33 00:01:58,066 --> 00:01:58,867 par exemple au point de vue de l’environnement, parce qu’on en 34 00:01:58,867 --> 00:01:59,667 l’environnement, parce qu’on en a quand même des flux de 35 00:01:59,667 --> 00:02:02,900 a quand même des flux de travailleurs 36 00:02:21,300 --> 00:02:24,201 frontaliers importants. 37 00:02:24,201 --> 00:02:27,234 frontaliers importants. Companies that are um change 38 00:02:27,234 --> 00:02:29,000 Companies that are um change oriented that they will survive 39 00:02:29,000 --> 00:02:32,334 oriented that they will survive and they will go further and 40 00:02:32,334 --> 00:02:39,967 and they will go further and see what I mean um 41 00:02:44,333 --> 00:02:52,633 at 42 00:02:54,099 --> 00:02:58,534 ten. and. 43 00:03:28,533 --> 00:03:32,334 più insieme. Mangi noch nicht 44 00:03:32,334 --> 00:03:33,333 più insieme. Mangi noch nicht was auf sie zukommt, aber wir 45 00:03:33,333 --> 00:03:35,201 was auf sie zukommt, aber wir werden viel mit Roboter äh 46 00:03:35,201 --> 00:03:37,167 werden viel mit Roboter äh arbeiten müssen. Ja, ich hoffe, 47 00:03:37,167 --> 00:03:40,267 arbeiten müssen. Ja, ich hoffe, wenn Manufakturen überlebt und 48 00:03:40,267 --> 00:03:42,000 wenn Manufakturen überlebt und was macht Mensch und mit Hand, 49 00:03:42,000 --> 00:03:44,234 was macht Mensch und mit Hand, das ist wichtig immer und und 50 00:03:44,234 --> 00:03:46,801 das ist wichtig immer und und das bleibt so auch später. Äh 51 00:03:46,801 --> 00:03:48,467 das bleibt so auch später. Äh wenn das Handarbeit, ich finde 52 00:03:48,467 --> 00:03:50,700 wenn das Handarbeit, ich finde etwas schön und ist etwas 53 00:03:50,700 --> 00:03:52,233 etwas schön und ist etwas wichtig. Alle alle kann man 54 00:03:52,233 --> 00:03:53,801 wichtig. Alle alle kann man nie, die die Maschine machen 55 00:03:53,801 --> 00:03:55,967 nie, die die Maschine machen und die Roboter. Der Roboter 56 00:03:55,967 --> 00:03:59,067 und die Roboter. Der Roboter sage ich so. 57 00:04:12,733 --> 00:04:15,233 Welcome to our Panel on 58 00:04:15,233 --> 00:04:17,034 Welcome to our Panel on Inclusive Future for Workours 59 00:04:17,034 --> 00:04:19,333 Inclusive Future for Workours in Europe. Mein Name ist 60 00:04:19,333 --> 00:04:19,867 in Europe. Mein Name ist Guntram Wolf, in einem The 61 00:04:19,867 --> 00:04:21,233 Guntram Wolf, in einem The Director of Brüggel and I’m the 62 00:04:21,233 --> 00:04:23,867 Director of Brüggel and I’m the light to welcome and to eh eh 63 00:04:23,867 --> 00:04:26,267 light to welcome and to eh eh welcome you to this session of 64 00:04:26,267 --> 00:04:27,800 welcome you to this session of prügels and you’re meeting 65 00:04:27,800 --> 00:04:31,167 prügels and you’re meeting twenty twenty and all online äh 66 00:04:31,167 --> 00:04:33,100 twenty twenty and all online äh Event ähm Norderthan Event Ware 67 00:04:33,100 --> 00:04:34,700 Event ähm Norderthan Event Ware Wecan see you lot of people, 68 00:04:34,700 --> 00:04:36,000 Wecan see you lot of people, but I hope a lot of people can 69 00:04:36,000 --> 00:04:38,900 but I hope a lot of people can it least listen, to uss and to 70 00:04:38,900 --> 00:04:40,700 it least listen, to uss and to our excellence speakers. I’m to 71 00:04:40,700 --> 00:04:45,566 our excellence speakers. I’m to like to to Um welcome in 72 00:04:45,566 --> 00:04:47,333 like to to Um welcome in particular um to uh in 73 00:04:47,333 --> 00:04:49,667 particular um to uh in particular Shaina uh Singh, who 74 00:04:49,667 --> 00:04:51,434 particular Shaina uh Singh, who is the founder and president of 75 00:04:51,434 --> 00:04:53,367 is the founder and president of the Mastercard Center for 76 00:04:53,367 --> 00:04:54,767 the Mastercard Center for Inclusive growth and also an 77 00:04:54,767 --> 00:04:57,267 Inclusive growth and also an executive vice president for 78 00:04:57,267 --> 00:04:59,400 executive vice president for sustainability MasterCard and 79 00:04:59,400 --> 00:05:01,834 sustainability MasterCard and Uhm, and I will talk first 80 00:05:01,834 --> 00:05:04,434 Uhm, and I will talk first about um uh a joint 81 00:05:04,434 --> 00:05:05,833 about um uh a joint collaboration that we are about 82 00:05:05,833 --> 00:05:07,434 collaboration that we are about to embark on uh that we are 83 00:05:07,434 --> 00:05:09,867 to embark on uh that we are embarking on which is uh uh a 84 00:05:09,867 --> 00:05:12,834 embarking on which is uh uh a mighty year project. Which um 85 00:05:12,834 --> 00:05:16,433 mighty year project. Which um uh we will uh engage in a 86 00:05:16,433 --> 00:05:20,833 uh we will uh engage in a research um on really um the 87 00:05:20,833 --> 00:05:24,167 research um on really um the impact of automation the impact 88 00:05:24,167 --> 00:05:28,234 impact of automation the impact of technology on the work and 89 00:05:28,234 --> 00:05:31,266 of technology on the work and then reflect on um what can be 90 00:05:31,266 --> 00:05:33,967 then reflect on um what can be um the social the labor market 91 00:05:33,967 --> 00:05:36,833 um the social the labor market and other policy responses 92 00:05:36,833 --> 00:05:39,034 and other policy responses education responses to help 93 00:05:39,034 --> 00:05:41,801 education responses to help workers across Europe. With 94 00:05:41,801 --> 00:05:44,400 workers across Europe. With this, this is a mighty project 95 00:05:44,400 --> 00:05:47,400 this, this is a mighty project and um we will work together 96 00:05:47,400 --> 00:05:50,234 and um we will work together with scholars um across Europe 97 00:05:50,234 --> 00:05:52,266 with scholars um across Europe um engaged with policy makers 98 00:05:52,266 --> 00:05:54,533 um engaged with policy makers um and really uh try to uh push 99 00:05:54,533 --> 00:05:57,633 um and really uh try to uh push and push the debate on. I think 100 00:05:57,633 --> 00:05:59,234 and push the debate on. I think a very very important topic 101 00:05:59,234 --> 00:06:01,967 a very very important topic because beyond the pandemic, I 102 00:06:01,967 --> 00:06:04,800 because beyond the pandemic, I think one of the keys of many 103 00:06:04,800 --> 00:06:07,400 think one of the keys of many citizens many workers is how 104 00:06:07,400 --> 00:06:08,733 citizens many workers is how their life will change how they 105 00:06:08,733 --> 00:06:11,666 their life will change how they work will change. What kind of 106 00:06:11,666 --> 00:06:14,333 work will change. What kind of um uh jobs they will have 107 00:06:14,333 --> 00:06:15,600 um uh jobs they will have whether they would still be 108 00:06:15,600 --> 00:06:17,867 whether they would still be able to make a living um and I 109 00:06:17,867 --> 00:06:19,234 able to make a living um and I think if anything the pandemic 110 00:06:19,234 --> 00:06:22,234 think if anything the pandemic that we are currently having is 111 00:06:22,234 --> 00:06:23,201 that we are currently having is accelerating these trends 112 00:06:23,201 --> 00:06:25,633 accelerating these trends because it is accelerating 113 00:06:25,633 --> 00:06:27,200 because it is accelerating digitalization. it is 114 00:06:27,200 --> 00:06:29,767 digitalization. it is accelerating um the way um we 115 00:06:29,767 --> 00:06:32,767 accelerating um the way um we move to a new world in which a 116 00:06:32,767 --> 00:06:34,367 move to a new world in which a digital technologies are ever 117 00:06:34,367 --> 00:06:38,434 digital technologies are ever more um uh present um uh with a 118 00:06:38,434 --> 00:06:39,934 more um uh present um uh with a lot of different consequences 119 00:06:39,934 --> 00:06:42,834 lot of different consequences and um before I give the. Um 120 00:06:42,834 --> 00:06:45,800 and um before I give the. Um let me uh let me also welcome 121 00:06:45,800 --> 00:06:47,333 let me uh let me also welcome um our two panelists that are 122 00:06:47,333 --> 00:06:50,767 um our two panelists that are here to discuss this with us um 123 00:06:50,767 --> 00:06:53,600 here to discuss this with us um so Tito um was the president of 124 00:06:53,600 --> 00:06:55,200 so Tito um was the president of the Italian National security 125 00:06:55,200 --> 00:06:57,300 the Italian National security in institute and is a professor 126 00:06:57,300 --> 00:07:00,333 in institute and is a professor at the University of Boko um in 127 00:07:00,333 --> 00:07:04,267 at the University of Boko um in uh in in Milan in Italy and 128 00:07:04,267 --> 00:07:06,834 uh in in Milan in Italy and Susan Loan um is a part of 129 00:07:06,834 --> 00:07:08,267 Susan Loan um is a part of McKenzie and has um also 130 00:07:08,267 --> 00:07:10,467 McKenzie and has um also recently written a report on 131 00:07:10,467 --> 00:07:13,666 recently written a report on exactly. The questions, der ähm 132 00:07:13,666 --> 00:07:15,700 exactly. The questions, der ähm just this casting am vom in 133 00:07:15,700 --> 00:07:19,067 just this casting am vom in this panel today. So, thank you 134 00:07:19,067 --> 00:07:21,801 this panel today. So, thank you to ähm first awalor Lisners for 135 00:07:21,801 --> 00:07:24,400 to ähm first awalor Lisners for eh dilag in for Listening in äh 136 00:07:24,400 --> 00:07:26,000 eh dilag in for Listening in äh we will have time to what’s the 137 00:07:26,000 --> 00:07:28,801 we will have time to what’s the and of the panel ähm to ehm 138 00:07:28,801 --> 00:07:30,867 and of the panel ähm to ehm take you questions, so please 139 00:07:30,867 --> 00:07:34,766 take you questions, so please go on äh the Website Slido, SLI 140 00:07:34,766 --> 00:07:37,733 go on äh the Website Slido, SLI dot deo and Tipe in ähm die 141 00:07:37,733 --> 00:07:38,967 dot deo and Tipe in ähm die Code Bum, so Brüggel and your 142 00:07:38,967 --> 00:07:41,766 Code Bum, so Brüggel and your meeting beam twent Bumped 143 00:07:41,766 --> 00:07:44,234 meeting beam twent Bumped twenty um and then type your 144 00:07:44,234 --> 00:07:45,234 twenty um and then type your questions and I will try to 145 00:07:45,234 --> 00:07:46,399 questions and I will try to take as many questions as 146 00:07:46,399 --> 00:07:48,867 take as many questions as possible to our panelists um 147 00:07:48,867 --> 00:07:51,467 possible to our panelists um towards the end of this uh this 148 00:07:51,467 --> 00:07:52,933 towards the end of this uh this panel um but let me know give 149 00:07:52,933 --> 00:07:56,834 panel um but let me know give the floor uh Tom with whom we 150 00:07:56,834 --> 00:07:58,367 the floor uh Tom with whom we will start um this 151 00:07:58,367 --> 00:07:59,600 will start um this collaboration we are starting 152 00:07:59,600 --> 00:08:01,767 collaboration we are starting this school year uh 153 00:08:01,767 --> 00:08:03,467 this school year uh collaborative project Shaina 154 00:08:03,467 --> 00:08:04,767 collaborative project Shaina over to you and thank you again 155 00:08:04,767 --> 00:08:08,833 over to you and thank you again for joining us to all of you. 156 00:08:08,833 --> 00:08:10,434 for joining us to all of you. Thank you guru and thank you 157 00:08:10,434 --> 00:08:11,433 Thank you guru and thank you all for having me here today. 158 00:08:11,433 --> 00:08:13,600 all for having me here today. It’s a real pleasure to be part 159 00:08:13,600 --> 00:08:16,833 It’s a real pleasure to be part of the uh be part of the panel. 160 00:08:16,833 --> 00:08:19,367 of the uh be part of the panel. Um you know it’s been said that 161 00:08:19,367 --> 00:08:21,299 Um you know it’s been said that we started this journey with 162 00:08:21,299 --> 00:08:23,866 we started this journey with about 5 years ago when we 163 00:08:23,866 --> 00:08:25,267 about 5 years ago when we started um this research on 164 00:08:25,267 --> 00:08:27,733 started um this research on inclusive growth and what it 165 00:08:27,733 --> 00:08:29,333 inclusive growth and what it means what it looks like, 166 00:08:29,333 --> 00:08:31,433 means what it looks like, especially for Europe and you 167 00:08:31,433 --> 00:08:33,534 especially for Europe and you know 5 years later, we’re 168 00:08:33,534 --> 00:08:35,600 know 5 years later, we’re seeing with the pandemic. a lot 169 00:08:35,600 --> 00:08:37,234 seeing with the pandemic. a lot of what we talked about that 170 00:08:37,234 --> 00:08:38,967 of what we talked about that those years ago is sort of 171 00:08:38,967 --> 00:08:40,533 those years ago is sort of coming to pass that the supply 172 00:08:40,533 --> 00:08:42,966 coming to pass that the supply and In terms of work, skill 173 00:08:42,966 --> 00:08:46,267 and In terms of work, skill sets and jobs are mismatched um 174 00:08:46,267 --> 00:08:48,933 sets and jobs are mismatched um the automation is increasing 175 00:08:48,933 --> 00:08:50,333 the automation is increasing um, but I think most 176 00:08:50,333 --> 00:08:51,900 um, but I think most importantly the safety nets 177 00:08:51,900 --> 00:08:53,467 importantly the safety nets haven’t kept up with um with 178 00:08:53,467 --> 00:08:54,867 haven’t kept up with um with what’s going on especially 179 00:08:54,867 --> 00:08:57,600 what’s going on especially around and so what we really 180 00:08:57,600 --> 00:09:01,267 around and so what we really need I think are uh urgently 181 00:09:01,267 --> 00:09:02,933 need I think are uh urgently are practical actionable 182 00:09:02,933 --> 00:09:05,466 are practical actionable pragmatic solutions grounded in 183 00:09:05,466 --> 00:09:06,966 pragmatic solutions grounded in rigorous research and clear 184 00:09:06,966 --> 00:09:09,299 rigorous research and clear calls to action not only for 185 00:09:09,299 --> 00:09:11,199 calls to action not only for policy makers. I think but also 186 00:09:11,199 --> 00:09:12,900 policy makers. I think but also for private-sector leaders who 187 00:09:12,900 --> 00:09:15,399 for private-sector leaders who um indeed do supply. Of the 188 00:09:15,399 --> 00:09:18,167 um indeed do supply. Of the actual jobs um workforce 189 00:09:18,167 --> 00:09:20,000 actual jobs um workforce development leaders um and many 190 00:09:20,000 --> 00:09:22,400 development leaders um and many other stakeholders across that 191 00:09:22,400 --> 00:09:26,467 other stakeholders across that uh future work ecosystem um as 192 00:09:26,467 --> 00:09:27,967 uh future work ecosystem um as gum, said this new partnership 193 00:09:27,967 --> 00:09:30,233 gum, said this new partnership will bring together academics 194 00:09:30,233 --> 00:09:31,799 will bring together academics policy makers practitioners and 195 00:09:31,799 --> 00:09:35,201 policy makers practitioners and the private sector uh to 196 00:09:35,201 --> 00:09:35,934 the private sector uh to exchange critical insights at 197 00:09:35,934 --> 00:09:39,204 exchange critical insights at the nexus of 198 00:09:40,004 --> 00:09:42,437 A diverse set of countries and 199 00:09:42,437 --> 00:09:44,304 A diverse set of countries and cities across Europe and 200 00:09:44,304 --> 00:09:47,903 cities across Europe and elevating them the global stage 201 00:09:47,903 --> 00:09:49,537 elevating them the global stage um you know the thing that 202 00:09:49,537 --> 00:09:51,804 um you know the thing that we’re really focused on here 203 00:09:51,804 --> 00:09:53,137 we’re really focused on here Besides the pragmatic solutions 204 00:09:53,137 --> 00:09:54,771 Besides the pragmatic solutions is putting that into practice 205 00:09:54,771 --> 00:09:57,737 is putting that into practice and so as part of this uh new 206 00:09:57,737 --> 00:09:59,704 and so as part of this uh new research to action network, 207 00:09:59,704 --> 00:10:02,404 research to action network, we’ve also brought in a new uh 208 00:10:02,404 --> 00:10:05,104 we’ve also brought in a new uh Brandee uh called bass impact. 209 00:10:05,104 --> 00:10:07,637 Brandee uh called bass impact. um they’re French start up and 210 00:10:07,637 --> 00:10:09,837 um they’re French start up and um and the RSA, which is um a 211 00:10:09,837 --> 00:10:12,538 um and the RSA, which is um a British fellowship. Digital 212 00:10:12,538 --> 00:10:13,971 British fellowship. Digital coaching services in the hands 213 00:10:13,971 --> 00:10:15,970 coaching services in the hands of workers who ultimately 214 00:10:15,970 --> 00:10:17,738 of workers who ultimately leverage AI and algorithmic 215 00:10:17,738 --> 00:10:19,071 leverage AI and algorithmic knowledge to help connect 216 00:10:19,071 --> 00:10:21,371 knowledge to help connect people to the skill building 217 00:10:21,371 --> 00:10:23,070 people to the skill building opportunity. Um so this is 218 00:10:23,070 --> 00:10:24,538 opportunity. Um so this is really a partnership not only 219 00:10:24,538 --> 00:10:26,337 really a partnership not only with the research and the 220 00:10:26,337 --> 00:10:27,971 with the research and the policy and the private sector 221 00:10:27,971 --> 00:10:31,970 policy and the private sector side of the house, but also in 222 00:10:31,970 --> 00:10:33,504 side of the house, but also in practical uh partnership with 223 00:10:33,504 --> 00:10:35,170 practical uh partnership with the practitioner Organization 224 00:10:35,170 --> 00:10:36,638 the practitioner Organization to in this case for at the 225 00:10:36,638 --> 00:10:38,938 to in this case for at the start, RSA and bass impact so 226 00:10:38,938 --> 00:10:41,004 start, RSA and bass impact so really trying to bring um the 227 00:10:41,004 --> 00:10:44,403 really trying to bring um the research and the. Together with 228 00:10:44,403 --> 00:10:45,637 research and the. Together with the organizations that are 229 00:10:45,637 --> 00:10:46,838 the organizations that are actually working together on 230 00:10:46,838 --> 00:10:48,504 actually working together on the ground to get it done so 231 00:10:48,504 --> 00:10:50,138 the ground to get it done so we’ve you know like I said 232 00:10:50,138 --> 00:10:51,337 we’ve you know like I said We’ve had this partnership with 233 00:10:51,337 --> 00:10:53,905 We’ve had this partnership with Benjamin. for over 5 years. 234 00:10:53,905 --> 00:10:55,704 Benjamin. for over 5 years. delighted to see it continue 235 00:10:55,704 --> 00:10:59,337 delighted to see it continue and grow and um we are looking 236 00:10:59,337 --> 00:11:00,371 and grow and um we are looking forward to getting ahead of 237 00:11:00,371 --> 00:11:02,004 forward to getting ahead of this work as much as we can and 238 00:11:02,004 --> 00:11:03,637 this work as much as we can and working with all of you um to 239 00:11:03,637 --> 00:11:05,804 working with all of you um to make it happen. so thanks again 240 00:11:05,804 --> 00:11:07,137 make it happen. so thanks again for having me look forward to 241 00:11:07,137 --> 00:11:09,637 for having me look forward to being part of the conversation. 242 00:11:09,637 --> 00:11:10,404 being part of the conversation. well, Thank you. Thank you 243 00:11:10,404 --> 00:11:12,671 well, Thank you. Thank you Sheena and uh we’ll be really 244 00:11:12,671 --> 00:11:14,271 Sheena and uh we’ll be really looking forward to um to 245 00:11:14,271 --> 00:11:15,471 looking forward to um to continue on as you say a 246 00:11:15,471 --> 00:11:17,104 continue on as you say a deepening that partnership that 247 00:11:17,104 --> 00:11:20,403 deepening that partnership that uh we. A few years ago and III 248 00:11:20,403 --> 00:11:21,904 uh we. A few years ago and III really do think that was always 249 00:11:21,904 --> 00:11:23,604 really do think that was always a very productive discussion 250 00:11:23,604 --> 00:11:25,604 a very productive discussion always very productive 251 00:11:25,604 --> 00:11:26,538 always very productive partnership. so so I really 252 00:11:26,538 --> 00:11:28,537 partnership. so so I really look forward to um the work 253 00:11:28,537 --> 00:11:29,804 look forward to um the work stream. That’s really gonna 254 00:11:29,804 --> 00:11:31,171 stream. That’s really gonna come out here in the next 255 00:11:31,171 --> 00:11:33,537 come out here in the next couple of years, but let’s 256 00:11:33,537 --> 00:11:34,838 couple of years, but let’s really zoom in now on the 257 00:11:34,838 --> 00:11:36,804 really zoom in now on the substance and um you know we’ve 258 00:11:36,804 --> 00:11:38,138 substance and um you know we’ve we’ve heard already a lot of 259 00:11:38,138 --> 00:11:39,604 we’ve heard already a lot of questions that that were raised 260 00:11:39,604 --> 00:11:43,171 questions that that were raised and uh and let me turn first to 261 00:11:43,171 --> 00:11:45,570 and uh and let me turn first to our two panelists um um I think 262 00:11:45,570 --> 00:11:50,404 our two panelists um um I think uh Tito um. Scheduled to um or 263 00:11:50,404 --> 00:11:52,471 uh Tito um. Scheduled to um or was it that was scheduled to 264 00:11:52,471 --> 00:11:53,171 was it that was scheduled to speak first. I think you were 265 00:11:53,171 --> 00:11:55,604 speak first. I think you were you were sketch to speak first 266 00:11:55,604 --> 00:11:58,204 you were sketch to speak first um and I think you have also um 267 00:11:58,204 --> 00:11:59,637 um and I think you have also um a few slides uh to kick us off 268 00:11:59,637 --> 00:12:02,870 a few slides uh to kick us off um on the substance so so thank 269 00:12:02,870 --> 00:12:03,871 um on the substance so so thank you so much for joining us 270 00:12:03,871 --> 00:12:08,137 you so much for joining us today and over to you. 271 00:12:25,005 --> 00:12:26,537 Okay, so, so wie Lost, wie 272 00:12:26,537 --> 00:12:30,571 Okay, so, so wie Lost, wie Lost, Tito, Aperentley, ähm 273 00:12:30,571 --> 00:12:31,903 Lost, Tito, Aperentley, ähm Suprebs, wie, wie äh Change the 274 00:12:31,903 --> 00:12:34,537 Suprebs, wie, wie äh Change the order, denn and äh Susan I hope 275 00:12:34,537 --> 00:12:36,271 order, denn and äh Susan I hope yourselv, so why a susan whide 276 00:12:36,271 --> 00:12:38,471 yourselv, so why a susan whide und you present abit from from 277 00:12:38,471 --> 00:12:40,437 und you present abit from from your riesen Report and after 278 00:12:40,437 --> 00:12:44,003 your riesen Report and after Rits we go to Tito. Thank you 279 00:12:44,003 --> 00:12:45,204 Rits we go to Tito. Thank you for having me. It’s a pleasure 280 00:12:45,204 --> 00:12:48,104 for having me. It’s a pleasure and honor to be here um we did 281 00:12:48,104 --> 00:12:50,471 and honor to be here um we did work over the last year before 282 00:12:50,471 --> 00:12:52,938 work over the last year before Copic broke out on looking at 283 00:12:52,938 --> 00:12:55,371 Copic broke out on looking at the future work trends across 284 00:12:55,371 --> 00:12:57,938 the future work trends across Europe at a local level um it 285 00:12:57,938 --> 00:12:59,737 Europe at a local level um it obviously changed a lot of 286 00:12:59,737 --> 00:13:02,038 obviously changed a lot of that. We then went back and 287 00:13:02,038 --> 00:13:02,938 that. We then went back and revised uh we’re going to 288 00:13:02,938 --> 00:13:04,938 revised uh we’re going to release in late March just when 289 00:13:04,938 --> 00:13:06,670 release in late March just when everything was shutting down uh 290 00:13:06,670 --> 00:13:08,138 everything was shutting down uh but we did release the report 291 00:13:08,138 --> 00:13:09,871 but we did release the report in June. so I think there are 292 00:13:09,871 --> 00:13:10,837 in June. so I think there are three key messages first when 293 00:13:10,837 --> 00:13:13,571 three key messages first when you think about labor market. 294 00:13:13,571 --> 00:13:14,905 you think about labor market. You need to think about local 295 00:13:14,905 --> 00:13:16,538 You need to think about local labor markets you can’t talk 296 00:13:16,538 --> 00:13:17,938 labor markets you can’t talk about Europe as a whole or even 297 00:13:17,938 --> 00:13:20,204 about Europe as a whole or even a single country as a whole 298 00:13:20,204 --> 00:13:21,503 a single country as a whole because the local dynamics are 299 00:13:21,503 --> 00:13:23,971 because the local dynamics are very different. so we built a 300 00:13:23,971 --> 00:13:27,104 very different. so we built a database looking at over 1100 301 00:13:27,104 --> 00:13:29,838 database looking at over 1100 nuts three regions across the 302 00:13:29,838 --> 00:13:32,237 nuts three regions across the EU, plus Switzerland and and 303 00:13:32,237 --> 00:13:34,204 EU, plus Switzerland and and the UK um and what we found is 304 00:13:34,204 --> 00:13:36,004 the UK um and what we found is that we clustered them into 305 00:13:36,004 --> 00:13:37,438 that we clustered them into thirteen different archetypes 306 00:13:37,438 --> 00:13:38,971 thirteen different archetypes of economies and there were 307 00:13:38,971 --> 00:13:41,471 of economies and there were huge divergence between how 308 00:13:41,471 --> 00:13:42,038 huge divergence between how these different types of 309 00:13:42,038 --> 00:13:44,070 these different types of economies are performing so in 310 00:13:44,070 --> 00:13:46,503 economies are performing so in one hand. Forty-eight regions 311 00:13:46,503 --> 00:13:48,304 one hand. Forty-eight regions that we call the dynamic growth 312 00:13:48,304 --> 00:13:50,604 that we call the dynamic growth hub and that includes Amsterdam 313 00:13:50,604 --> 00:13:52,504 hub and that includes Amsterdam Stockholm London Paris The 314 00:13:52,504 --> 00:13:54,271 Stockholm London Paris The usual suspects there’s spread 315 00:13:54,271 --> 00:13:56,370 usual suspects there’s spread across the continent, but they 316 00:13:56,370 --> 00:13:58,604 across the continent, but they account for just 20% of the 317 00:13:58,604 --> 00:14:00,503 account for just 20% of the population over the last 10 318 00:14:00,503 --> 00:14:02,403 population over the last 10 years. They’ve accounted for 319 00:14:02,403 --> 00:14:05,171 years. They’ve accounted for 35% of job growth and over the 320 00:14:05,171 --> 00:14:06,571 35% of job growth and over the next decade we project they 321 00:14:06,571 --> 00:14:09,071 next decade we project they could account for over half of 322 00:14:09,071 --> 00:14:11,770 could account for over half of job growth so both companies 323 00:14:11,770 --> 00:14:15,504 job growth so both companies and workers are going to be. 324 00:14:15,504 --> 00:14:18,403 and workers are going to be. Comes now there’s a question 325 00:14:18,403 --> 00:14:20,037 Comes now there’s a question what’s happening elsewhere 326 00:14:20,037 --> 00:14:22,671 what’s happening elsewhere about how the Europeans live in 327 00:14:22,671 --> 00:14:24,404 about how the Europeans live in a group that we call the stable 328 00:14:24,404 --> 00:14:26,337 a group that we call the stable economies. These include 329 00:14:26,337 --> 00:14:28,037 economies. These include advance manufacturing clusters, 330 00:14:28,037 --> 00:14:30,437 advance manufacturing clusters, some service-based economies 331 00:14:30,437 --> 00:14:32,071 some service-based economies diversified cities as well as 332 00:14:32,071 --> 00:14:34,670 diversified cities as well as some tourists in the southern 333 00:14:34,670 --> 00:14:36,138 some tourists in the southern Europe. These have about half 334 00:14:36,138 --> 00:14:38,138 Europe. These have about half of the population they’ve 335 00:14:38,138 --> 00:14:41,504 of the population they’ve counted um for about 40% of 336 00:14:41,504 --> 00:14:42,871 counted um for about 40% of future job growth, so they’re 337 00:14:42,871 --> 00:14:45,771 future job growth, so they’re doing not to. But then on the 338 00:14:45,771 --> 00:14:48,271 doing not to. But then on the other hand, you’ve got wing so 339 00:14:48,271 --> 00:14:50,371 other hand, you’ve got wing so a third of Europeans live in a 340 00:14:50,371 --> 00:14:53,337 a third of Europeans live in a region that has very little job 341 00:14:53,337 --> 00:14:55,537 region that has very little job growth, very rapid aging, a lot 342 00:14:55,537 --> 00:14:57,471 growth, very rapid aging, a lot of public sector support so 343 00:14:57,471 --> 00:14:59,537 of public sector support so over the past decade, the 344 00:14:59,537 --> 00:15:00,604 over the past decade, the shrinking regions of accounted 345 00:15:00,604 --> 00:15:03,438 shrinking regions of accounted for only 12% of job growth 346 00:15:03,438 --> 00:15:04,071 for only 12% of job growth going forward, it could be even 347 00:15:04,071 --> 00:15:08,270 going forward, it could be even lower the single digits so the 348 00:15:08,270 --> 00:15:09,570 lower the single digits so the policy needs will be different 349 00:15:09,570 --> 00:15:11,838 policy needs will be different in each type of economy and the 350 00:15:11,838 --> 00:15:12,737 in each type of economy and the stable and shrinking regions 351 00:15:12,737 --> 00:15:16,904 stable and shrinking regions The question. Can you get a job 352 00:15:16,904 --> 00:15:18,737 The question. Can you get a job creation or can remote works 353 00:15:18,737 --> 00:15:20,905 creation or can remote works solve the problem and the 354 00:15:20,905 --> 00:15:22,070 solve the problem and the dynamic cities the problem is 355 00:15:22,070 --> 00:15:24,137 dynamic cities the problem is more around. Can you ensure 356 00:15:24,137 --> 00:15:25,937 more around. Can you ensure continued migration so one of 357 00:15:25,937 --> 00:15:27,970 continued migration so one of the reasons these cities have 358 00:15:27,970 --> 00:15:29,838 the reasons these cities have generated such a large portion 359 00:15:29,838 --> 00:15:31,070 generated such a large portion of jobs is that they have been 360 00:15:31,070 --> 00:15:33,204 of jobs is that they have been able to draw migration from 361 00:15:33,204 --> 00:15:36,003 able to draw migration from across the EU after that, it’s 362 00:15:36,003 --> 00:15:37,570 across the EU after that, it’s not clear how that’s going to 363 00:15:37,570 --> 00:15:39,204 not clear how that’s going to play out issues like affordable 364 00:15:39,204 --> 00:15:42,738 play out issues like affordable housing um and fair uh working 365 00:15:42,738 --> 00:15:44,637 housing um and fair uh working standards are very important in 366 00:15:44,637 --> 00:15:47,971 standards are very important in those cities. Point that we 367 00:15:47,971 --> 00:15:50,737 those cities. Point that we found is look in the long term. 368 00:15:50,737 --> 00:15:52,038 found is look in the long term. The problem in Europe is not 369 00:15:52,038 --> 00:15:54,204 The problem in Europe is not too few jobs. It’s too few 370 00:15:54,204 --> 00:15:56,271 too few jobs. It’s too few workers now, I realize that we 371 00:15:56,271 --> 00:15:58,271 workers now, I realize that we are rising unemployment. We 372 00:15:58,271 --> 00:15:59,171 are rising unemployment. We have a lot of people that have 373 00:15:59,171 --> 00:16:00,638 have a lot of people that have been thrown out of work. Um we 374 00:16:00,638 --> 00:16:03,604 been thrown out of work. Um we have the deepest that um the 375 00:16:03,604 --> 00:16:06,004 have the deepest that um the advanced economies have seen 376 00:16:06,004 --> 00:16:08,070 advanced economies have seen since World War two um and 377 00:16:08,070 --> 00:16:10,338 since World War two um and we’re in a big hole but when we 378 00:16:10,338 --> 00:16:11,904 we’re in a big hole but when we look forward what we see is 379 00:16:11,904 --> 00:16:12,837 look forward what we see is that over the next decade, 380 00:16:12,837 --> 00:16:14,404 that over the next decade, there will be thirteen and a 381 00:16:14,404 --> 00:16:16,238 there will be thirteen and a half fewer Europeans of working 382 00:16:16,238 --> 00:16:19,204 half fewer Europeans of working age um at the same. The number 383 00:16:19,204 --> 00:16:20,438 age um at the same. The number of hours worked per week 384 00:16:20,438 --> 00:16:23,004 of hours worked per week continues to trend down to the 385 00:16:23,004 --> 00:16:25,704 continues to trend down to the long term the issue uh maybe 386 00:16:25,704 --> 00:16:29,438 long term the issue uh maybe can we get enough worker? Can 387 00:16:29,438 --> 00:16:30,871 can we get enough worker? Can we get enough workers with 388 00:16:30,871 --> 00:16:32,470 we get enough workers with skills and that brings me to 389 00:16:32,470 --> 00:16:33,403 skills and that brings me to the third point about the 390 00:16:33,403 --> 00:16:36,437 the third point about the massive job transitions ahead? 391 00:16:36,437 --> 00:16:38,871 massive job transitions ahead? I’m going as you pointed out 392 00:16:38,871 --> 00:16:41,371 I’m going as you pointed out our research suggest that it 393 00:16:41,371 --> 00:16:42,938 our research suggest that it has a fact accelerated some 394 00:16:42,938 --> 00:16:45,404 has a fact accelerated some types of digitalization of 395 00:16:45,404 --> 00:16:46,804 types of digitalization of customer channels and 396 00:16:46,804 --> 00:16:48,504 customer channels and automation of functions like 397 00:16:48,504 --> 00:16:50,104 automation of functions like ordering in a restaurant 398 00:16:50,104 --> 00:16:53,538 ordering in a restaurant checking out at a retail store 399 00:16:53,538 --> 00:16:54,803 checking out at a retail store um and ordering online as 400 00:16:54,803 --> 00:16:56,238 um and ordering online as opposed to going into stores 401 00:16:56,238 --> 00:16:59,738 opposed to going into stores and this is labor. And so we 402 00:16:59,738 --> 00:17:01,337 and this is labor. And so we thought even before the 403 00:17:01,337 --> 00:17:02,904 thought even before the pandemic um roughly half of the 404 00:17:02,904 --> 00:17:03,770 pandemic um roughly half of the European workforce, it’s gonna 405 00:17:03,770 --> 00:17:05,837 European workforce, it’s gonna need to learn new skills. 406 00:17:05,837 --> 00:17:07,471 need to learn new skills. There’s automation you can take 407 00:17:07,471 --> 00:17:10,138 There’s automation you can take over 20% or more of the 408 00:17:10,138 --> 00:17:11,538 over 20% or more of the activities they do in their job 409 00:17:11,538 --> 00:17:14,304 activities they do in their job and there were roughly 20000000 410 00:17:14,304 --> 00:17:15,470 and there were roughly 20000000 people that might need to 411 00:17:15,470 --> 00:17:17,537 people that might need to switch occupations altogether 412 00:17:17,537 --> 00:17:19,437 switch occupations altogether because they’re in declining 413 00:17:19,437 --> 00:17:21,838 because they’re in declining occupations um and typically 414 00:17:21,838 --> 00:17:24,403 occupations um and typically they have less than a tertiary 415 00:17:24,403 --> 00:17:25,737 they have less than a tertiary education and so the challenge 416 00:17:25,737 --> 00:17:27,438 education and so the challenge there will be can we step up 417 00:17:27,438 --> 00:17:30,071 there will be can we step up training and credential. To 418 00:17:30,071 --> 00:17:32,871 training and credential. To enable people to move out of 419 00:17:32,871 --> 00:17:33,938 enable people to move out of occupations that are seeing 420 00:17:33,938 --> 00:17:37,937 occupations that are seeing lower demand and into those 421 00:17:37,937 --> 00:17:39,504 lower demand and into those areas, so I’m gonna pause 422 00:17:39,504 --> 00:17:40,371 areas, so I’m gonna pause there. I know there will be 423 00:17:40,371 --> 00:17:42,437 there. I know there will be lots of questions um and I 424 00:17:42,437 --> 00:17:45,171 lots of questions um and I think we have Tito back as 425 00:17:45,171 --> 00:17:46,470 think we have Tito back as well. Uh thank you. Thank you. 426 00:17:46,470 --> 00:17:48,504 well. Uh thank you. Thank you. Susan. I’m in this. this was uh 427 00:17:48,504 --> 00:17:50,037 Susan. I’m in this. this was uh I think great and the and the 428 00:17:50,037 --> 00:17:51,405 I think great and the and the great overview and that’s 429 00:17:51,405 --> 00:17:52,771 great overview and that’s really lots of things to chew 430 00:17:52,771 --> 00:17:54,437 really lots of things to chew on there and lots of questions 431 00:17:54,437 --> 00:17:57,171 on there and lots of questions I would ask you rightly uh 432 00:17:57,171 --> 00:17:58,737 I would ask you rightly uh highlighted really I think 433 00:17:58,737 --> 00:18:00,071 highlighted really I think three big dimensions of this 434 00:18:00,071 --> 00:18:01,671 three big dimensions of this regional disparity, which is a 435 00:18:01,671 --> 00:18:04,771 regional disparity, which is a big. 436 00:18:36,303 --> 00:18:36,970 Presentation Thank you for 437 00:18:36,970 --> 00:18:39,204 Presentation Thank you for joining us. Thank you for 438 00:18:39,204 --> 00:18:41,537 joining us. Thank you for having me here to this very 439 00:18:41,537 --> 00:18:43,971 having me here to this very important meeting. Um let me 440 00:18:43,971 --> 00:18:48,604 important meeting. Um let me say that uh broadly speaking in 441 00:18:48,604 --> 00:18:52,670 say that uh broadly speaking in uh being uh brought about a new 442 00:18:52,670 --> 00:18:54,804 uh being uh brought about a new dimension of labor market 443 00:18:54,804 --> 00:18:57,738 dimension of labor market related to the health risk. at 444 00:18:57,738 --> 00:19:00,004 related to the health risk. at least that was not visits was 445 00:19:00,004 --> 00:19:03,204 least that was not visits was not perceived before uh by both 446 00:19:03,204 --> 00:19:07,137 not perceived before uh by both fours and the employees. If you 447 00:19:07,137 --> 00:19:10,638 fours and the employees. If you look at the structure, wages 448 00:19:10,638 --> 00:19:12,004 look at the structure, wages across different types of jobs 449 00:19:12,004 --> 00:19:15,204 across different types of jobs goals that are more exposed to 450 00:19:15,204 --> 00:19:17,204 goals that are more exposed to ideological risk and those that 451 00:19:17,204 --> 00:19:19,137 ideological risk and those that are less exposed to this type 452 00:19:19,137 --> 00:19:22,605 are less exposed to this type of risk to see that before 453 00:19:22,605 --> 00:19:23,971 of risk to see that before nineteen where we’re not the 454 00:19:23,971 --> 00:19:26,571 nineteen where we’re not the type of compensating wage 455 00:19:26,571 --> 00:19:28,870 type of compensating wage differential the typical 456 00:19:28,870 --> 00:19:31,404 differential the typical associated to higher risk uh in 457 00:19:31,404 --> 00:19:37,870 associated to higher risk uh in the labor more. So now the 458 00:19:37,870 --> 00:19:39,204 the labor more. So now the perception is that employers 459 00:19:39,204 --> 00:19:42,438 perception is that employers and Gifts are well aware of 460 00:19:42,438 --> 00:19:45,204 and Gifts are well aware of this ideological risk, and it’s 461 00:19:45,204 --> 00:19:47,504 this ideological risk, and it’s very important to look at how 462 00:19:47,504 --> 00:19:51,805 very important to look at how this uh a biological risk get 463 00:19:51,805 --> 00:19:53,170 this uh a biological risk get interact with the arteries in 464 00:19:53,170 --> 00:19:56,038 interact with the arteries in the labor market, including the 465 00:19:56,038 --> 00:19:59,538 the labor market, including the job loss. Now it turns out that 466 00:19:59,538 --> 00:20:02,637 job loss. Now it turns out that the job and risks are 467 00:20:02,637 --> 00:20:05,138 the job and risks are positively correlated. There is 468 00:20:05,138 --> 00:20:07,638 positively correlated. There is literature on this uh at some 469 00:20:07,638 --> 00:20:09,337 literature on this uh at some three dates, we call it the 470 00:20:09,337 --> 00:20:11,504 three dates, we call it the show the I respect that been 471 00:20:11,504 --> 00:20:13,671 show the I respect that been work that has been done after 472 00:20:13,671 --> 00:20:16,671 work that has been done after the. 473 00:21:20,405 --> 00:21:22,404 Together with a few colleagues 474 00:21:22,404 --> 00:21:27,171 Together with a few colleagues of mine Alessandro Kyi, they 475 00:21:27,171 --> 00:21:29,903 of mine Alessandro Kyi, they have been looking at the 476 00:21:29,903 --> 00:21:30,604 have been looking at the characteristics of the 477 00:21:30,604 --> 00:21:33,904 characteristics of the different jobs to assess the 478 00:21:33,904 --> 00:21:36,004 different jobs to assess the epidemiology risk associated 479 00:21:36,004 --> 00:21:38,005 epidemiology risk associated with the different occupations 480 00:21:38,005 --> 00:21:42,838 with the different occupations and uh we came out with uh uh a 481 00:21:42,838 --> 00:21:46,003 and uh we came out with uh uh a measure of the risk or unsafe 482 00:21:46,003 --> 00:21:47,005 measure of the risk or unsafe from the stand point of 483 00:21:47,005 --> 00:21:49,638 from the stand point of epidemiology risk jobs. Uh that 484 00:21:49,638 --> 00:21:52,605 epidemiology risk jobs. Uh that suggest that about 50% of the 485 00:21:52,605 --> 00:21:54,038 suggest that about 50% of the occupation currently carried 486 00:21:54,038 --> 00:21:58,838 occupation currently carried out in the U are risky. 487 00:22:34,937 --> 00:22:37,438 Job in that in that it is 488 00:22:37,438 --> 00:22:39,438 Job in that in that it is exposed to neurological risks 489 00:22:39,438 --> 00:22:41,404 exposed to neurological risks so it is important to 490 00:22:41,404 --> 00:22:47,170 so it is important to understand who this work um 491 00:22:47,170 --> 00:22:49,804 understand who this work um these wars are generally 492 00:22:49,804 --> 00:22:52,737 these wars are generally workers that are low level of 493 00:22:52,737 --> 00:22:55,070 workers that are low level of education who all the temporary 494 00:22:55,070 --> 00:22:57,605 education who all the temporary concert working here is small 495 00:22:57,605 --> 00:22:59,503 concert working here is small firms and in general they are 496 00:22:59,503 --> 00:23:01,404 firms and in general they are in uh so these are 497 00:23:01,404 --> 00:23:03,137 in uh so these are characteristics of the world 498 00:23:03,137 --> 00:23:04,704 characteristics of the world who carry with them this double 499 00:23:04,704 --> 00:23:09,571 who carry with them this double breast. And he kept all the 500 00:23:09,571 --> 00:23:12,203 breast. And he kept all the contracting uh the uh uh the 501 00:23:12,203 --> 00:23:15,138 contracting uh the uh uh the buyers um distribution is very 502 00:23:15,138 --> 00:23:17,504 buyers um distribution is very uneven across uh as you can see 503 00:23:17,504 --> 00:23:19,937 uneven across uh as you can see there are some sector where 504 00:23:19,937 --> 00:23:23,171 there are some sector where this uh uh double risk is more 505 00:23:23,171 --> 00:23:25,437 this uh uh double risk is more like trade uh accommodation and 506 00:23:25,437 --> 00:23:27,904 like trade uh accommodation and improve the uh while it is 507 00:23:27,904 --> 00:23:31,170 improve the uh while it is clearly way less in a number of 508 00:23:31,170 --> 00:23:36,037 clearly way less in a number of other financial and insurance 509 00:23:36,037 --> 00:23:36,570 other financial and insurance information and the 510 00:23:36,570 --> 00:23:40,738 information and the communication so there is a. 511 00:24:43,271 --> 00:24:45,971 We are facing in transforming 512 00:24:45,971 --> 00:24:48,438 We are facing in transforming their workplaces safe 513 00:24:48,438 --> 00:24:50,003 their workplaces safe workplaces and depends on what 514 00:24:50,003 --> 00:24:52,538 workplaces and depends on what the most of them are very 515 00:24:52,538 --> 00:24:53,537 the most of them are very concerned about the 516 00:24:53,537 --> 00:24:55,571 concerned about the productivity losses that we 517 00:24:55,571 --> 00:24:58,004 productivity losses that we will carry with it and that is 518 00:24:58,004 --> 00:25:00,871 will carry with it and that is transformation and also uh they 519 00:25:00,871 --> 00:25:02,938 transformation and also uh they also argue that there will be 520 00:25:02,938 --> 00:25:04,437 also argue that there will be an avoid the job losses 521 00:25:04,437 --> 00:25:06,404 an avoid the job losses associated to this uh to be 522 00:25:06,404 --> 00:25:09,337 associated to this uh to be close to that. there is I think 523 00:25:09,337 --> 00:25:10,870 close to that. there is I think from a policy standpoint the 524 00:25:10,870 --> 00:25:14,005 from a policy standpoint the problem. Double protection 525 00:25:14,005 --> 00:25:16,504 problem. Double protection there is a liability as it was 526 00:25:16,504 --> 00:25:18,071 there is a liability as it was arguing before and this 527 00:25:18,071 --> 00:25:20,703 arguing before and this requires a double protection so 528 00:25:20,703 --> 00:25:23,570 requires a double protection so the one thing we would need and 529 00:25:23,570 --> 00:25:26,004 the one thing we would need and passing out is the fracture um 530 00:25:26,004 --> 00:25:27,471 passing out is the fracture um which clearly uh it is very 531 00:25:27,471 --> 00:25:29,138 which clearly uh it is very important to prevent further 532 00:25:29,138 --> 00:25:31,671 important to prevent further outbreaks of infections so you 533 00:25:31,671 --> 00:25:33,870 outbreaks of infections so you should have early warning 534 00:25:33,870 --> 00:25:36,503 should have early warning system prevent this but at the 535 00:25:36,503 --> 00:25:37,370 system prevent this but at the same time we need to have a 536 00:25:37,370 --> 00:25:40,670 same time we need to have a quick the compressing social 537 00:25:40,670 --> 00:25:44,238 quick the compressing social protection infrastructure. 538 00:26:42,805 --> 00:26:45,871 protection 539 00:26:50,071 --> 00:26:53,071 qui 540 00:26:56,871 --> 00:27:00,004 business 541 00:27:15,503 --> 00:27:18,737 Measure like this and work and 542 00:27:18,737 --> 00:27:20,904 Measure like this and work and and entirely by general 543 00:27:20,904 --> 00:27:22,937 and entirely by general government, I mean and very 544 00:27:22,937 --> 00:27:26,005 government, I mean and very strictly particularly to be 545 00:27:26,005 --> 00:27:27,437 strictly particularly to be safe, They can be we need to 546 00:27:27,437 --> 00:27:29,005 safe, They can be we need to advice policies that promote 547 00:27:29,005 --> 00:27:31,504 advice policies that promote rather than hinder job 548 00:27:31,504 --> 00:27:34,605 rather than hinder job allocation. Also Susan Land was 549 00:27:34,605 --> 00:27:36,070 allocation. Also Susan Land was suggesting this before that I 550 00:27:36,070 --> 00:27:38,504 suggesting this before that I do that and be creative in some 551 00:27:38,504 --> 00:27:42,038 do that and be creative in some sectors and we should ease of 552 00:27:42,038 --> 00:27:46,104 sectors and we should ease of way not all they require. Hi 553 00:27:46,104 --> 00:27:48,537 way not all they require. Hi people praise us in sanitation 554 00:27:48,537 --> 00:27:52,005 people praise us in sanitation and if you get in a in a very 555 00:27:52,005 --> 00:27:54,903 and if you get in a in a very controls in monitoring um there 556 00:27:54,903 --> 00:27:56,571 controls in monitoring um there are a number of jobs that have 557 00:27:56,571 --> 00:27:58,070 are a number of jobs that have been created that won’t involve 558 00:27:58,070 --> 00:28:00,438 been created that won’t involve very high skills. They can also 559 00:28:00,438 --> 00:28:04,438 very high skills. They can also be um jobs for unskilled people 560 00:28:04,438 --> 00:28:07,004 be um jobs for unskilled people uh so it’s very important that 561 00:28:07,004 --> 00:28:08,504 uh so it’s very important that we do allow these people to 562 00:28:08,504 --> 00:28:10,003 we do allow these people to find alternative employment in 563 00:28:10,003 --> 00:28:11,903 find alternative employment in this new occupation that are 564 00:28:11,903 --> 00:28:15,570 this new occupation that are being uh create uh and In is 565 00:28:15,570 --> 00:28:16,937 being uh create uh and In is essential in in this conference 566 00:28:16,937 --> 00:28:18,471 essential in in this conference on the job training in the 567 00:28:18,471 --> 00:28:21,837 on the job training in the training of adults that will 568 00:28:21,837 --> 00:28:22,537 training of adults that will play a very major role, not 569 00:28:22,537 --> 00:28:24,371 play a very major role, not only because it will allow 570 00:28:24,371 --> 00:28:26,371 only because it will allow people to really use the 571 00:28:26,371 --> 00:28:28,003 people to really use the digitalization who carry out 572 00:28:28,003 --> 00:28:30,603 digitalization who carry out the job and occupation from 573 00:28:30,603 --> 00:28:33,070 the job and occupation from remotely uh but also because it 574 00:28:33,070 --> 00:28:35,371 remotely uh but also because it will uh clearly allow them to 575 00:28:35,371 --> 00:28:36,137 will uh clearly allow them to deal with the restructuring 576 00:28:36,137 --> 00:28:38,405 deal with the restructuring that is taking place in when 577 00:28:38,405 --> 00:28:40,870 that is taking place in when you risk of loss associated to 578 00:28:40,870 --> 00:28:42,338 you risk of loss associated to the enforcement of social 579 00:28:42,338 --> 00:28:46,137 the enforcement of social distancing automation that will 580 00:28:46,137 --> 00:28:48,870 distancing automation that will be invaded by this type of 581 00:28:48,870 --> 00:28:52,837 be invaded by this type of education and. 582 00:29:26,537 --> 00:29:30,871 For who are currently unsafe 583 00:29:30,871 --> 00:29:33,071 For who are currently unsafe jobs in the U, so I think that 584 00:29:33,071 --> 00:29:34,738 jobs in the U, so I think that the major efforts should be 585 00:29:34,738 --> 00:29:36,104 the major efforts should be done to the train this worker 586 00:29:36,104 --> 00:29:39,538 done to the train this worker to provide them and digital 587 00:29:39,538 --> 00:29:42,271 to provide them and digital literacy and uh this is an 588 00:29:42,271 --> 00:29:43,638 literacy and uh this is an effort that can be made uh 589 00:29:43,638 --> 00:29:46,471 effort that can be made uh without the running the risk of 590 00:29:46,471 --> 00:29:47,937 without the running the risk of wasting resources for pain. 591 00:29:47,937 --> 00:29:50,571 wasting resources for pain. This type of training is today 592 00:29:50,571 --> 00:29:54,438 This type of training is today at we we are right and we can 593 00:29:54,438 --> 00:29:57,370 at we we are right and we can be quiet reassured about also a 594 00:29:57,370 --> 00:30:00,071 be quiet reassured about also a good stop. Maybe you have 595 00:30:00,071 --> 00:30:02,604 good stop. Maybe you have questions from the floor. Thank 596 00:30:02,604 --> 00:30:05,070 questions from the floor. Thank you. Thank you. Tito um a great 597 00:30:05,070 --> 00:30:06,671 you. Thank you. Tito um a great uh great presentation really 598 00:30:06,671 --> 00:30:10,303 uh great presentation really also highlighting how labor um 599 00:30:10,303 --> 00:30:11,937 also highlighting how labor um and health risks are highly 600 00:30:11,937 --> 00:30:13,837 and health risks are highly correlated and what it all 601 00:30:13,837 --> 00:30:16,037 correlated and what it all means for for the labor market, 602 00:30:16,037 --> 00:30:18,104 means for for the labor market, particularly I know the strong 603 00:30:18,104 --> 00:30:19,804 particularly I know the strong emphasis on on training at the 604 00:30:19,804 --> 00:30:22,371 emphasis on on training at the end that that you gave um 605 00:30:22,371 --> 00:30:24,238 end that that you gave um perhaps um I can sort of have 606 00:30:24,238 --> 00:30:26,238 perhaps um I can sort of have one follow-up question, which 607 00:30:26,238 --> 00:30:30,504 one follow-up question, which is really related. To um and 608 00:30:30,504 --> 00:30:31,971 is really related. To um and also trying to link it a bit to 609 00:30:31,971 --> 00:30:34,405 also trying to link it a bit to what was saying uh related to 610 00:30:34,405 --> 00:30:36,371 what was saying uh related to the use because you didn’t talk 611 00:30:36,371 --> 00:30:38,638 the use because you didn’t talk much about the use um and um 612 00:30:38,638 --> 00:30:41,137 much about the use um and um what we see in the labor market 613 00:30:41,137 --> 00:30:42,504 what we see in the labor market of course, is that the young 614 00:30:42,504 --> 00:30:45,071 of course, is that the young actually very much affected at 615 00:30:45,071 --> 00:30:45,671 actually very much affected at the moment. Um it’s not just 616 00:30:45,671 --> 00:30:47,571 the moment. Um it’s not just the old. It’s the young that 617 00:30:47,571 --> 00:30:49,104 the old. It’s the young that affected they are less affected 618 00:30:49,104 --> 00:30:51,538 affected they are less affected uh in terms of the health risk, 619 00:30:51,538 --> 00:30:53,237 uh in terms of the health risk, but they are affected uh in 620 00:30:53,237 --> 00:30:54,637 but they are affected uh in terms of entering the labor 621 00:30:54,637 --> 00:30:56,038 terms of entering the labor market, not finding a job um 622 00:30:56,038 --> 00:30:59,537 market, not finding a job um and you know the. Is rising 623 00:30:59,537 --> 00:31:02,037 and you know the. Is rising quite quite significantly uh 624 00:31:02,037 --> 00:31:05,904 quite quite significantly uh among the young um now, Susan 625 00:31:05,904 --> 00:31:08,704 among the young um now, Susan is sort of gave us emo 626 00:31:08,704 --> 00:31:09,604 is sort of gave us emo geographical descriptions. sort 627 00:31:09,604 --> 00:31:11,937 geographical descriptions. sort of we have the left behind 628 00:31:11,937 --> 00:31:14,071 of we have the left behind regions and we have the sort of 629 00:31:14,071 --> 00:31:16,538 regions and we have the sort of the city’s um the dynamic city 630 00:31:16,538 --> 00:31:18,071 the city’s um the dynamic city centers, which sort of doing 631 00:31:18,071 --> 00:31:19,604 centers, which sort of doing okay, which is I think a 632 00:31:19,604 --> 00:31:21,437 okay, which is I think a long-term trend that we’ve been 633 00:31:21,437 --> 00:31:22,270 long-term trend that we’ve been seeing all around the world in 634 00:31:22,270 --> 00:31:24,604 seeing all around the world in the world and I’m wondering um 635 00:31:24,604 --> 00:31:27,070 the world and I’m wondering um I mean how do we square these 636 00:31:27,070 --> 00:31:28,571 I mean how do we square these two trends? I mean the the use 637 00:31:28,571 --> 00:31:31,871 two trends? I mean the the use isn’t the use uh typically. 638 00:31:31,871 --> 00:31:33,604 isn’t the use uh typically. Willing to go to the cities um 639 00:31:33,604 --> 00:31:36,104 Willing to go to the cities um and leave the countryside um 640 00:31:36,104 --> 00:31:37,804 and leave the countryside um and so therefore eventually be 641 00:31:37,804 --> 00:31:39,038 and so therefore eventually be fine. I mean I’ll be are we 642 00:31:39,038 --> 00:31:40,737 fine. I mean I’ll be are we seeing I mean it’s the it’s the 643 00:31:40,737 --> 00:31:42,671 seeing I mean it’s the it’s the use and employment problem is 644 00:31:42,671 --> 00:31:44,470 use and employment problem is that really just uh just a 645 00:31:44,470 --> 00:31:47,004 that really just uh just a temporary issue now because the 646 00:31:47,004 --> 00:31:50,004 temporary issue now because the Chakra so rapid. but overall, I 647 00:31:50,004 --> 00:31:52,204 Chakra so rapid. but overall, I mean the the use really has a 648 00:31:52,204 --> 00:31:54,671 mean the the use really has a lot of potential because they 649 00:31:54,671 --> 00:31:56,271 lot of potential because they move to the city because they 650 00:31:56,271 --> 00:31:58,604 move to the city because they typically have the digital 651 00:31:58,604 --> 00:31:59,270 typically have the digital skills. Uh what do we have 652 00:31:59,270 --> 00:32:00,804 skills. Uh what do we have really a particular problem 653 00:32:00,804 --> 00:32:02,671 really a particular problem among the among the young which 654 00:32:02,671 --> 00:32:04,604 among the among the young which you know goes well beyond um 655 00:32:04,604 --> 00:32:05,637 you know goes well beyond um sort of the current one of 656 00:32:05,637 --> 00:32:08,138 sort of the current one of shock. I mean I. Wondering if 657 00:32:08,138 --> 00:32:09,771 shock. I mean I. Wondering if you can enlarge a little bit on 658 00:32:09,771 --> 00:32:12,238 you can enlarge a little bit on this issue, but it’s no doubt 659 00:32:12,238 --> 00:32:14,405 this issue, but it’s no doubt that there is a digital divide 660 00:32:14,405 --> 00:32:15,171 that there is a digital divide and so young people are 661 00:32:15,171 --> 00:32:18,938 and so young people are generally more digital than the 662 00:32:18,938 --> 00:32:21,637 generally more digital than the older workers uh but still we 663 00:32:21,637 --> 00:32:23,005 older workers uh but still we have to be aware of the fact 664 00:32:23,005 --> 00:32:24,604 have to be aware of the fact that there is not a minor or 665 00:32:24,604 --> 00:32:27,103 that there is not a minor or component of the youth uh of 666 00:32:27,103 --> 00:32:28,737 component of the youth uh of people who are likely low level 667 00:32:28,737 --> 00:32:30,371 people who are likely low level of education and these people 668 00:32:30,371 --> 00:32:31,904 of education and these people have been extremely hardly the 669 00:32:31,904 --> 00:32:34,838 have been extremely hardly the classes and they do hold very 670 00:32:34,838 --> 00:32:37,937 classes and they do hold very much unsafe jobs. Uh so uh. 671 00:32:37,937 --> 00:32:40,438 much unsafe jobs. Uh so uh. Look at the distribution of 672 00:32:40,438 --> 00:32:43,404 Look at the distribution of unsafe jobs by age by you 673 00:32:43,404 --> 00:32:45,538 unsafe jobs by age by you notice that there are many 674 00:32:45,538 --> 00:32:47,138 notice that there are many young people holding this type 675 00:32:47,138 --> 00:32:50,937 young people holding this type of the of of jobs uh in in some 676 00:32:50,937 --> 00:32:52,003 of the of of jobs uh in in some occupation that young people 677 00:32:52,003 --> 00:32:55,171 occupation that young people are the majority that we stage 678 00:32:55,171 --> 00:32:56,738 are the majority that we stage so uh it is true that generally 679 00:32:56,738 --> 00:33:00,471 so uh it is true that generally held risk is is more of the uh 680 00:33:00,471 --> 00:33:03,570 held risk is is more of the uh uh mortality rate among young 681 00:33:03,570 --> 00:33:06,370 uh mortality rate among young affected by the uh by the call 682 00:33:06,370 --> 00:33:09,470 affected by the uh by the call it is lower but uh there is of 683 00:33:09,470 --> 00:33:10,171 it is lower but uh there is of the young people also from the 684 00:33:10,171 --> 00:33:12,870 the young people also from the health standpoint should not be 685 00:33:12,870 --> 00:33:15,437 health standpoint should not be underestimated at the. Yeah, I 686 00:33:15,437 --> 00:33:16,537 underestimated at the. Yeah, I agree with both Susan was 687 00:33:16,537 --> 00:33:18,271 agree with both Susan was saying about relocation. We’re 688 00:33:18,271 --> 00:33:19,737 saying about relocation. We’re changing the job of your jobs, 689 00:33:19,737 --> 00:33:22,071 changing the job of your jobs, although I don’t think that the 690 00:33:22,071 --> 00:33:24,671 although I don’t think that the more we are moving to is one 691 00:33:24,671 --> 00:33:26,003 more we are moving to is one that will involve uh the 692 00:33:26,003 --> 00:33:29,405 that will involve uh the reduction of the nomination um 693 00:33:29,405 --> 00:33:31,071 reduction of the nomination um economies and to present in a 694 00:33:31,071 --> 00:33:33,004 economies and to present in a bigger and the congregation. so 695 00:33:33,004 --> 00:33:33,871 bigger and the congregation. so I think that the biggest 696 00:33:33,871 --> 00:33:35,471 I think that the biggest attraction of the centers will 697 00:33:35,471 --> 00:33:37,471 attraction of the centers will always be there and uh we’re 698 00:33:37,471 --> 00:33:39,037 always be there and uh we’re gonna the engine of growth will 699 00:33:39,037 --> 00:33:40,771 gonna the engine of growth will still be there. Um I don’t 700 00:33:40,771 --> 00:33:42,771 still be there. Um I don’t think that we will live in the 701 00:33:42,771 --> 00:33:45,937 think that we will live in the future. 702 00:34:16,604 --> 00:34:17,871 Generation you uh so we really 703 00:34:17,871 --> 00:34:20,003 Generation you uh so we really have to think about that I 704 00:34:20,003 --> 00:34:22,137 have to think about that I think that the type of policies 705 00:34:22,137 --> 00:34:24,637 think that the type of policies that have been carried out 706 00:34:24,637 --> 00:34:28,638 that have been carried out today to deal with That’s right 707 00:34:28,638 --> 00:34:31,171 today to deal with That’s right all is for the emergence very 708 00:34:31,171 --> 00:34:32,771 all is for the emergence very strict emergency, but now we’re 709 00:34:32,771 --> 00:34:35,004 strict emergency, but now we’re think more about allowing young 710 00:34:35,004 --> 00:34:37,403 think more about allowing young people to enter the market to 711 00:34:37,403 --> 00:34:39,871 people to enter the market to the market is safe jobs. Uh 712 00:34:39,871 --> 00:34:43,270 the market is safe jobs. Uh that’s extremely important so 713 00:34:43,270 --> 00:34:46,838 that’s extremely important so we have A. 714 00:35:15,038 --> 00:35:16,871 Um on the regional disparities, 715 00:35:16,871 --> 00:35:19,038 Um on the regional disparities, if you can spend a bit more 716 00:35:19,038 --> 00:35:21,670 if you can spend a bit more time uh sort of uh uh walking 717 00:35:21,670 --> 00:35:23,038 time uh sort of uh uh walking us through your resides and and 718 00:35:23,038 --> 00:35:24,704 us through your resides and and also thinking about a bit the 719 00:35:24,704 --> 00:35:26,138 also thinking about a bit the future. I mean how do you see 720 00:35:26,138 --> 00:35:27,438 future. I mean how do you see this evolving in the future? I 721 00:35:27,438 --> 00:35:29,504 this evolving in the future? I mean in the sense one reads now 722 00:35:29,504 --> 00:35:32,537 mean in the sense one reads now a lot of pieces that suggest 723 00:35:32,537 --> 00:35:33,904 a lot of pieces that suggest well now we’ve all learned how 724 00:35:33,904 --> 00:35:36,503 well now we’ve all learned how we can uh dole working isn’t 725 00:35:36,503 --> 00:35:38,137 we can uh dole working isn’t that the right moment to our go 726 00:35:38,137 --> 00:35:39,171 that the right moment to our go live on the country side, and 727 00:35:39,171 --> 00:35:40,737 live on the country side, and you know basically work from 728 00:35:40,737 --> 00:35:42,537 you know basically work from the countryside and oo oo 729 00:35:42,537 --> 00:35:46,038 the countryside and oo oo occasionally go. For um you 730 00:35:46,038 --> 00:35:48,470 occasionally go. For um you know uh uh networking but 731 00:35:48,470 --> 00:35:50,903 know uh uh networking but basically uh move out of the 732 00:35:50,903 --> 00:35:52,571 basically uh move out of the equations and is that an 733 00:35:52,571 --> 00:35:54,071 equations and is that an opportunity I mean it’s covered 734 00:35:54,071 --> 00:35:55,770 opportunity I mean it’s covered here, perhaps even an 735 00:35:55,770 --> 00:35:57,204 here, perhaps even an opportunity for this one-third 736 00:35:57,204 --> 00:36:00,504 opportunity for this one-third of workers uh regions that are 737 00:36:00,504 --> 00:36:03,671 of workers uh regions that are that I think you could um uh uh 738 00:36:03,671 --> 00:36:05,171 that I think you could um uh uh you know lagging behind regions 739 00:36:05,171 --> 00:36:07,138 you know lagging behind regions or something like this. So can 740 00:36:07,138 --> 00:36:08,503 or something like this. So can you talk a little bit about how 741 00:36:08,503 --> 00:36:10,038 you talk a little bit about how you see this evolving this 742 00:36:10,038 --> 00:36:15,538 you see this evolving this regional disparities? 743 00:36:43,605 --> 00:36:44,971 Productivity and efficiency 744 00:36:44,971 --> 00:36:47,804 Productivity and efficiency benefits for firms to develop 745 00:36:47,804 --> 00:36:50,437 benefits for firms to develop to economic cluster, and this 746 00:36:50,437 --> 00:36:52,237 to economic cluster, and this is why we see them around the 747 00:36:52,237 --> 00:36:55,471 is why we see them around the world and it’s what has driven 748 00:36:55,471 --> 00:36:58,070 world and it’s what has driven isolation of forty-eight 749 00:36:58,070 --> 00:37:00,137 isolation of forty-eight dynamic cities across Europe 750 00:37:00,137 --> 00:37:01,905 dynamic cities across Europe that attract companies and then 751 00:37:01,905 --> 00:37:04,237 that attract companies and then that begets the people that the 752 00:37:04,237 --> 00:37:08,005 that begets the people that the university graduates and more 753 00:37:08,005 --> 00:37:11,771 university graduates and more companies now will change that 754 00:37:11,771 --> 00:37:15,004 companies now will change that maybe. II, Of course, I don’t 755 00:37:15,004 --> 00:37:17,937 maybe. II, Of course, I don’t have a crystal ball but me 756 00:37:17,937 --> 00:37:20,003 have a crystal ball but me decelerate the trend of it 757 00:37:20,003 --> 00:37:21,471 decelerate the trend of it because of remote work, but I 758 00:37:21,471 --> 00:37:23,005 because of remote work, but I think it’s important to 759 00:37:23,005 --> 00:37:26,071 think it’s important to remember that only thirty to 760 00:37:26,071 --> 00:37:28,804 remember that only thirty to 40% of jobs in the economy can 761 00:37:28,804 --> 00:37:31,171 40% of jobs in the economy can be done remotely the majority 762 00:37:31,171 --> 00:37:33,537 be done remotely the majority of work in every country needs 763 00:37:33,537 --> 00:37:35,970 of work in every country needs to be done in person. so you’re 764 00:37:35,970 --> 00:37:37,937 to be done in person. so you’re talking about those of us on 765 00:37:37,937 --> 00:37:40,404 talking about those of us on this uh uh at the broil meeting 766 00:37:40,404 --> 00:37:41,670 this uh uh at the broil meeting right now who can work 767 00:37:41,670 --> 00:37:43,838 right now who can work remotely, but we are the 768 00:37:43,838 --> 00:37:46,171 remotely, but we are the minority. Secondly I. She has 769 00:37:46,171 --> 00:37:47,438 minority. Secondly I. She has pointed out and as you have 770 00:37:47,438 --> 00:37:50,370 pointed out and as you have started to point out when it’s 771 00:37:50,370 --> 00:37:53,171 started to point out when it’s we’ve all adjusted to 100% 772 00:37:53,171 --> 00:37:54,338 we’ve all adjusted to 100% remote work during the pandemic 773 00:37:54,338 --> 00:37:55,703 remote work during the pandemic because there was no choice, we 774 00:37:55,703 --> 00:37:58,404 because there was no choice, we couldn’t leave our homes but as 775 00:37:58,404 --> 00:38:00,638 couldn’t leave our homes but as companies start to think about 776 00:38:00,638 --> 00:38:02,303 companies start to think about the next phase, most you’re 777 00:38:02,303 --> 00:38:04,471 the next phase, most you’re thinking about a hybrid way of 778 00:38:04,471 --> 00:38:06,070 thinking about a hybrid way of working in which some people 779 00:38:06,070 --> 00:38:07,571 working in which some people will go to the office and the 780 00:38:07,571 --> 00:38:08,903 will go to the office and the companies are thinking very 781 00:38:08,903 --> 00:38:10,704 companies are thinking very hard about what needs to be 782 00:38:10,704 --> 00:38:12,638 hard about what needs to be done in person versus not in 783 00:38:12,638 --> 00:38:15,504 done in person versus not in person and it’s very likely. 784 00:38:15,504 --> 00:38:18,003 person and it’s very likely. Any job, there are some 785 00:38:18,003 --> 00:38:18,870 Any job, there are some activities that you can do 786 00:38:18,870 --> 00:38:20,070 activities that you can do perfectly efficiently and fine 787 00:38:20,070 --> 00:38:22,304 perfectly efficiently and fine working from home online, but 788 00:38:22,304 --> 00:38:23,637 working from home online, but there will be some that you 789 00:38:23,637 --> 00:38:25,138 there will be some that you need to go and be in the office 790 00:38:25,138 --> 00:38:26,804 need to go and be in the office and those might be training and 791 00:38:26,804 --> 00:38:28,871 and those might be training and on boarding it might be 792 00:38:28,871 --> 00:38:30,605 on boarding it might be brainstorming sessions and 793 00:38:30,605 --> 00:38:31,738 brainstorming sessions and collaboration. So what this 794 00:38:31,738 --> 00:38:32,803 collaboration. So what this means is that it’s unlikely 795 00:38:32,803 --> 00:38:35,371 means is that it’s unlikely that workers are going to be 796 00:38:35,371 --> 00:38:36,204 that workers are going to be living in the mountains of the 797 00:38:36,204 --> 00:38:38,470 living in the mountains of the Alps and you know dialing into 798 00:38:38,470 --> 00:38:40,138 Alps and you know dialing into their job in London, Most of 799 00:38:40,138 --> 00:38:41,538 their job in London, Most of course they can afford to fly 800 00:38:41,538 --> 00:38:42,304 course they can afford to fly to London and get there when 801 00:38:42,304 --> 00:38:45,471 to London and get there when they need to. It may take some 802 00:38:45,471 --> 00:38:48,271 they need to. It may take some pressure off of a and there may 803 00:38:48,271 --> 00:38:50,870 pressure off of a and there may be some departments, so we’ve 804 00:38:50,870 --> 00:38:53,038 be some departments, so we’ve seen it in customer service 805 00:38:53,038 --> 00:38:54,771 seen it in customer service call centers This might start 806 00:38:54,771 --> 00:38:57,437 call centers This might start to move out to other regions 807 00:38:57,437 --> 00:39:00,104 to move out to other regions where people work from home 808 00:39:00,104 --> 00:39:03,871 where people work from home around a small city or town I 809 00:39:03,871 --> 00:39:05,671 around a small city or town I can go in once in a while, so 810 00:39:05,671 --> 00:39:07,903 can go in once in a while, so there may be some potential for 811 00:39:07,903 --> 00:39:11,103 there may be some potential for remote work to bring jobs to 812 00:39:11,103 --> 00:39:12,271 remote work to bring jobs to thinking regions and regions 813 00:39:12,271 --> 00:39:14,704 thinking regions and regions that are being left. But by and 814 00:39:14,704 --> 00:39:17,704 that are being left. But by and large, I think that this trend 815 00:39:17,704 --> 00:39:18,804 large, I think that this trend will continue in the long run 816 00:39:18,804 --> 00:39:20,304 will continue in the long run just because of the economics 817 00:39:20,304 --> 00:39:21,603 just because of the economics of the higher productivity and 818 00:39:21,603 --> 00:39:23,871 of the higher productivity and efficiency So then that raises 819 00:39:23,871 --> 00:39:27,137 efficiency So then that raises the question of what do we do 820 00:39:27,137 --> 00:39:28,870 the question of what do we do uh with the shrinking regions? 821 00:39:28,870 --> 00:39:30,971 uh with the shrinking regions? I think that you brought out 822 00:39:30,971 --> 00:39:33,337 I think that you brought out young people are migrating um 823 00:39:33,337 --> 00:39:34,638 young people are migrating um and indeed you see that in the 824 00:39:34,638 --> 00:39:36,837 and indeed you see that in the data. so there’s a very strong 825 00:39:36,837 --> 00:39:39,104 data. so there’s a very strong net in migration to those 826 00:39:39,104 --> 00:39:41,137 net in migration to those forty-eight dynamic cities from 827 00:39:41,137 --> 00:39:42,804 forty-eight dynamic cities from across the EU, but one problem 828 00:39:42,804 --> 00:39:46,004 across the EU, but one problem is. Um a lot of the migraines 829 00:39:46,004 --> 00:39:49,004 is. Um a lot of the migraines are not getting the career path 830 00:39:49,004 --> 00:39:50,937 are not getting the career path high skilled jobs, they’re 831 00:39:50,937 --> 00:39:52,870 high skilled jobs, they’re taking the low skill service 832 00:39:52,870 --> 00:39:55,404 taking the low skill service jobs. um we did some 833 00:39:55,404 --> 00:39:56,571 jobs. um we did some interesting work with LinkedIn 834 00:39:56,571 --> 00:39:59,171 interesting work with LinkedIn looking at their data and what 835 00:39:59,171 --> 00:40:00,937 looking at their data and what we find is that people don’t 836 00:40:00,937 --> 00:40:03,303 we find is that people don’t change jobs and you’re quite 837 00:40:03,303 --> 00:40:05,938 change jobs and you’re quite often but people in a declining 838 00:40:05,938 --> 00:40:08,438 often but people in a declining occupation like a retail 839 00:40:08,438 --> 00:40:12,238 occupation like a retail cashier or a bank teller or a 840 00:40:12,238 --> 00:40:13,770 cashier or a bank teller or a food service worker when they 841 00:40:13,770 --> 00:40:16,338 food service worker when they change. They tend to go to 842 00:40:16,338 --> 00:40:18,437 change. They tend to go to another occupation that’s in 843 00:40:18,437 --> 00:40:21,171 another occupation that’s in declining demand situation. 844 00:40:21,171 --> 00:40:24,005 declining demand situation. Likewise, the people who have 845 00:40:24,005 --> 00:40:26,238 Likewise, the people who have uh occupations for what they’re 846 00:40:26,238 --> 00:40:28,237 uh occupations for what they’re growing demand tend to move to 847 00:40:28,237 --> 00:40:30,038 growing demand tend to move to other occupations with be in 848 00:40:30,038 --> 00:40:31,537 other occupations with be in demand. So what we need to 849 00:40:31,537 --> 00:40:34,138 demand. So what we need to think about is training for 850 00:40:34,138 --> 00:40:35,904 think about is training for young people or middle-aged 851 00:40:35,904 --> 00:40:38,537 young people or middle-aged people who are in occupations, 852 00:40:38,537 --> 00:40:40,071 people who are in occupations, we know over time are shrinking 853 00:40:40,071 --> 00:40:42,270 we know over time are shrinking and how can we help them move 854 00:40:42,270 --> 00:40:43,738 and how can we help them move into those growing occupations? 855 00:40:43,738 --> 00:40:46,137 into those growing occupations? So what? Gateway moves they 856 00:40:46,137 --> 00:40:48,671 So what? Gateway moves they could make with a little bit of 857 00:40:48,671 --> 00:40:50,137 could make with a little bit of training to get them onto a 858 00:40:50,137 --> 00:40:52,471 training to get them onto a career path that’s moving 859 00:40:52,471 --> 00:40:54,104 career path that’s moving upwards towards a better 860 00:40:54,104 --> 00:40:56,071 upwards towards a better standard of living as opposed 861 00:40:56,071 --> 00:40:56,870 standard of living as opposed to dead-end jobs if they’re 862 00:40:56,870 --> 00:41:00,171 to dead-end jobs if they’re just churning through low-wage 863 00:41:00,171 --> 00:41:01,537 just churning through low-wage low skill jobs uh because 864 00:41:01,537 --> 00:41:03,171 low skill jobs uh because that’s the recipe for 865 00:41:03,171 --> 00:41:05,937 that’s the recipe for inequality. So uh thank you 866 00:41:05,937 --> 00:41:08,037 inequality. So uh thank you Susan so we are seeing now the 867 00:41:08,037 --> 00:41:10,004 Susan so we are seeing now the results of the poll um 868 00:41:10,004 --> 00:41:11,903 results of the poll um thirty-four people voted. I 869 00:41:11,903 --> 00:41:13,770 thirty-four people voted. I mean that’s not. I guess not a 870 00:41:13,770 --> 00:41:14,337 mean that’s not. I guess not a representative sample, but 871 00:41:14,337 --> 00:41:17,838 representative sample, but still it’s it’s a pretty strong 872 00:41:17,838 --> 00:41:19,303 still it’s it’s a pretty strong result um so the question was 873 00:41:19,303 --> 00:41:21,170 result um so the question was what will have the most impact 874 00:41:21,170 --> 00:41:24,703 what will have the most impact on the future of work and uh 875 00:41:24,703 --> 00:41:27,204 on the future of work and uh 74% of the respondents actually 876 00:41:27,204 --> 00:41:29,803 74% of the respondents actually say it’s digitalization and AI 877 00:41:29,803 --> 00:41:31,538 say it’s digitalization and AI and perhaps let me let me spend 878 00:41:31,538 --> 00:41:33,737 and perhaps let me let me spend a moment uh turning to you um 879 00:41:33,737 --> 00:41:36,103 a moment uh turning to you um uh I think. Of all, I think 880 00:41:36,103 --> 00:41:38,771 uh I think. Of all, I think this poll nicely confirms I 881 00:41:38,771 --> 00:41:39,971 this poll nicely confirms I think that uh you know we are 882 00:41:39,971 --> 00:41:42,571 think that uh you know we are really focusing. I think on the 883 00:41:42,571 --> 00:41:44,070 really focusing. I think on the right issue, which is really I 884 00:41:44,070 --> 00:41:45,470 right issue, which is really I mean the long-term trend is 885 00:41:45,470 --> 00:41:47,138 mean the long-term trend is really this digitalization and 886 00:41:47,138 --> 00:41:48,571 really this digitalization and artificial intelligence and how 887 00:41:48,571 --> 00:41:51,104 artificial intelligence and how it impacts. I mean the Cot is a 888 00:41:51,104 --> 00:41:52,703 it impacts. I mean the Cot is a temporary thing. Hopefully I 889 00:41:52,703 --> 00:41:54,571 temporary thing. Hopefully I mean II think we all hope. it’s 890 00:41:54,571 --> 00:41:55,337 mean II think we all hope. it’s not gonna be a permanent issue 891 00:41:55,337 --> 00:41:57,604 not gonna be a permanent issue with us uh even though it may 892 00:41:57,604 --> 00:41:58,938 with us uh even though it may still be some with us, but I 893 00:41:58,938 --> 00:42:00,171 still be some with us, but I think we will have it under 894 00:42:00,171 --> 00:42:02,171 think we will have it under control. hopefully at some 895 00:42:02,171 --> 00:42:03,737 control. hopefully at some stage so the big trend here is 896 00:42:03,737 --> 00:42:06,204 stage so the big trend here is really. Visualization and 897 00:42:06,204 --> 00:42:09,638 really. Visualization and artificial intelligence and um 898 00:42:09,638 --> 00:42:11,171 artificial intelligence and um anti Tito was mentioning quite 899 00:42:11,171 --> 00:42:13,970 anti Tito was mentioning quite a bit um this issue of training 900 00:42:13,970 --> 00:42:16,404 a bit um this issue of training and you know um digital 901 00:42:16,404 --> 00:42:17,738 and you know um digital training, digital empowerment 902 00:42:17,738 --> 00:42:18,971 training, digital empowerment um, and I think that’s 903 00:42:18,971 --> 00:42:20,471 um, and I think that’s something that um you and the 904 00:42:20,471 --> 00:42:22,271 something that um you and the center you are very passionate 905 00:42:22,271 --> 00:42:24,537 center you are very passionate about that. so so perhaps you 906 00:42:24,537 --> 00:42:25,438 about that. so so perhaps you can share with us a little bit 907 00:42:25,438 --> 00:42:26,903 can share with us a little bit you’re thinking on you know 908 00:42:26,903 --> 00:42:28,704 you’re thinking on you know where you see the most training 909 00:42:28,704 --> 00:42:30,237 where you see the most training needs how to do them. What? 910 00:42:30,237 --> 00:42:31,870 needs how to do them. What? what is what is your thinking 911 00:42:31,870 --> 00:42:33,170 what is what is your thinking about this training digital 912 00:42:33,170 --> 00:42:36,071 about this training digital training? Preps, especially for 913 00:42:36,071 --> 00:42:38,537 training? Preps, especially for those that are left behind. 914 00:42:38,537 --> 00:42:40,371 those that are left behind. Yes, thanks, I think the 915 00:42:40,371 --> 00:42:42,071 Yes, thanks, I think the comments are uh that we’ve 916 00:42:42,071 --> 00:42:44,337 comments are uh that we’ve heard so far are actually right 917 00:42:44,337 --> 00:42:46,604 heard so far are actually right on in terms of what we have 918 00:42:46,604 --> 00:42:47,903 on in terms of what we have seen in our research over the 919 00:42:47,903 --> 00:42:50,804 seen in our research over the last many years, I think Cot 920 00:42:50,804 --> 00:42:52,238 last many years, I think Cot has acted as the accelerator. 921 00:42:52,238 --> 00:42:54,004 has acted as the accelerator. It’s sort of like the gas on 922 00:42:54,004 --> 00:42:55,505 It’s sort of like the gas on the fire of what we knew was 923 00:42:55,505 --> 00:42:56,871 the fire of what we knew was already coming around 924 00:42:56,871 --> 00:43:00,038 already coming around digitization um uh and so as 925 00:43:00,038 --> 00:43:02,470 digitization um uh and so as we’ve been thinking about 926 00:43:02,470 --> 00:43:04,870 we’ve been thinking about trying to incorporate inclusive 927 00:43:04,870 --> 00:43:06,703 trying to incorporate inclusive growth strategies into what we 928 00:43:06,703 --> 00:43:08,738 growth strategies into what we know has been coming around 929 00:43:08,738 --> 00:43:09,771 know has been coming around digitization a large focus of 930 00:43:09,771 --> 00:43:13,971 digitization a large focus of our. Has been on preparing 931 00:43:13,971 --> 00:43:16,005 our. Has been on preparing workers um for the digital 932 00:43:16,005 --> 00:43:18,471 workers um for the digital economy um and that I also 933 00:43:18,471 --> 00:43:20,338 economy um and that I also obviously relies a lot on the 934 00:43:20,338 --> 00:43:22,505 obviously relies a lot on the training component. um what 935 00:43:22,505 --> 00:43:24,037 training component. um what we’re seeing in um you know 936 00:43:24,037 --> 00:43:25,904 we’re seeing in um you know there. I’m sure there are many 937 00:43:25,904 --> 00:43:27,504 there. I’m sure there are many countries that maybe Susan can 938 00:43:27,504 --> 00:43:28,471 countries that maybe Susan can speak to. but what we’ve we’ve 939 00:43:28,471 --> 00:43:30,604 speak to. but what we’ve we’ve we’ve centered in on what’s 940 00:43:30,604 --> 00:43:32,937 we’ve centered in on what’s happening in France around the 941 00:43:32,937 --> 00:43:34,204 happening in France around the training um wallets the 942 00:43:34,204 --> 00:43:36,171 training um wallets the training programs and and their 943 00:43:36,171 --> 00:43:38,171 training programs and and their program that really 944 00:43:38,171 --> 00:43:39,204 program that really decentralized uh the training 945 00:43:39,204 --> 00:43:42,470 decentralized uh the training to. Um to sort of create a 946 00:43:42,470 --> 00:43:44,004 to. Um to sort of create a marketplace for digital 947 00:43:44,004 --> 00:43:46,537 marketplace for digital training that is based on the 948 00:43:46,537 --> 00:43:47,670 training that is based on the worker deciding where they 949 00:43:47,670 --> 00:43:50,437 worker deciding where they would like to spend the dollars 950 00:43:50,437 --> 00:43:51,738 would like to spend the dollars coming in from the government 951 00:43:51,738 --> 00:43:53,038 coming in from the government and the employers on the 952 00:43:53,038 --> 00:43:54,704 and the employers on the training places that make the 953 00:43:54,704 --> 00:43:57,538 training places that make the most sense to them um and so I 954 00:43:57,538 --> 00:43:59,471 most sense to them um and so I think more to come there. but 955 00:43:59,471 --> 00:44:02,337 think more to come there. but this idea that you centered the 956 00:44:02,337 --> 00:44:03,471 this idea that you centered the training dollars and the 957 00:44:03,471 --> 00:44:05,537 training dollars and the training decisions with the 958 00:44:05,537 --> 00:44:08,037 training decisions with the worker um with extensive 959 00:44:08,037 --> 00:44:10,238 worker um with extensive coaching um and competitive. 960 00:44:10,238 --> 00:44:12,503 coaching um and competitive. competitive marketplace. Um 961 00:44:12,503 --> 00:44:14,037 competitive marketplace. Um incentives from training 962 00:44:14,037 --> 00:44:15,671 incentives from training institutions, I think we’ll 963 00:44:15,671 --> 00:44:17,171 institutions, I think we’ll start to do what Susan has 964 00:44:17,171 --> 00:44:20,670 start to do what Susan has said, which is um create the 965 00:44:20,670 --> 00:44:23,704 said, which is um create the pool of people that are there, 966 00:44:23,704 --> 00:44:26,104 pool of people that are there, but now can be ready for the 967 00:44:26,104 --> 00:44:27,471 but now can be ready for the jobs that are here in the jobs 968 00:44:27,471 --> 00:44:28,670 jobs that are here in the jobs that are coming and I think 969 00:44:28,670 --> 00:44:30,438 that are coming and I think this is especially significant 970 00:44:30,438 --> 00:44:32,538 this is especially significant for young people um who we know 971 00:44:32,538 --> 00:44:34,304 for young people um who we know with our research and a lot of 972 00:44:34,304 --> 00:44:35,604 with our research and a lot of the work of frugal done has 973 00:44:35,604 --> 00:44:37,137 the work of frugal done has done around if you look at 974 00:44:37,137 --> 00:44:38,604 done around if you look at Spain if you look at any of 975 00:44:38,604 --> 00:44:40,204 Spain if you look at any of these markets and unless we 976 00:44:40,204 --> 00:44:44,638 these markets and unless we really. Our focus on um young 977 00:44:44,638 --> 00:44:45,371 really. Our focus on um young people, we’re gonna be in a in 978 00:44:45,371 --> 00:44:46,671 people, we’re gonna be in a in a in a world of hurt when it 979 00:44:46,671 --> 00:44:48,670 a in a world of hurt when it comes to unemployment. if we’re 980 00:44:48,670 --> 00:44:49,237 comes to unemployment. if we’re not figuring this thing out and 981 00:44:49,237 --> 00:44:51,871 not figuring this thing out and so um our work is really 982 00:44:51,871 --> 00:44:54,338 so um our work is really focused on one capitalizing on 983 00:44:54,338 --> 00:44:56,638 focused on one capitalizing on what Tito said about young 984 00:44:56,638 --> 00:44:57,971 what Tito said about young people already sort of being 985 00:44:57,971 --> 00:45:00,538 people already sort of being native digitally literate uh 986 00:45:00,538 --> 00:45:02,604 native digitally literate uh making sure that we create the 987 00:45:02,604 --> 00:45:05,871 making sure that we create the um economic incentives for 988 00:45:05,871 --> 00:45:07,304 um economic incentives for training organizations to 989 00:45:07,304 --> 00:45:09,138 training organizations to compete uh for workers by 990 00:45:09,138 --> 00:45:11,537 compete uh for workers by making by hopefully. Sure that 991 00:45:11,537 --> 00:45:12,937 making by hopefully. Sure that government put governments put 992 00:45:12,937 --> 00:45:14,604 government put governments put the dollars the training 993 00:45:14,604 --> 00:45:15,870 the dollars the training dollars in the hands of workers 994 00:45:15,870 --> 00:45:18,138 dollars in the hands of workers and that indeed they start to 995 00:45:18,138 --> 00:45:19,637 and that indeed they start to form the basis of what we call 996 00:45:19,637 --> 00:45:21,937 form the basis of what we call a portable benefits um 997 00:45:21,937 --> 00:45:23,671 a portable benefits um ecosystem where not only 998 00:45:23,671 --> 00:45:25,270 ecosystem where not only training dollars but all sorts 999 00:45:25,270 --> 00:45:28,003 training dollars but all sorts of benefit dollars um and then 1000 00:45:28,003 --> 00:45:30,104 of benefit dollars um and then uh move with the worker uh 1001 00:45:30,104 --> 00:45:32,070 uh move with the worker uh through their job life cycles 1002 00:45:32,070 --> 00:45:34,437 through their job life cycles so lots to think about but the 1003 00:45:34,437 --> 00:45:36,237 so lots to think about but the purpose of AI and all of this, 1004 00:45:36,237 --> 00:45:39,604 purpose of AI and all of this, I think is that um it creates 1005 00:45:39,604 --> 00:45:41,004 I think is that um it creates the efficiency it creates the 1006 00:45:41,004 --> 00:45:43,638 the efficiency it creates the speed it creates the um the 1007 00:45:43,638 --> 00:45:44,937 speed it creates the um the opportunities that I think even 1008 00:45:44,937 --> 00:45:47,471 opportunities that I think even 2 years ago. Didn’t see with 1009 00:45:47,471 --> 00:45:49,204 2 years ago. Didn’t see with the digital economy. I think 1010 00:45:49,204 --> 00:45:51,504 the digital economy. I think things like AI if done well if 1011 00:45:51,504 --> 00:45:54,304 things like AI if done well if done in partnership between 1012 00:45:54,304 --> 00:45:56,905 done in partnership between public sector private sector uh 1013 00:45:56,905 --> 00:45:59,337 public sector private sector uh ethical leaders uh training 1014 00:45:59,337 --> 00:46:01,104 ethical leaders uh training programs we we uh accelerate or 1015 00:46:01,104 --> 00:46:03,838 programs we we uh accelerate or we sort of create an incentive 1016 00:46:03,838 --> 00:46:05,004 we sort of create an incentive environment for a race to the 1017 00:46:05,004 --> 00:46:06,770 environment for a race to the top uh rather than a race to 1018 00:46:06,770 --> 00:46:08,337 top uh rather than a race to the bottom. So we’re excited 1019 00:46:08,337 --> 00:46:10,138 the bottom. So we’re excited about what’s what’s here and 1020 00:46:10,138 --> 00:46:11,870 about what’s what’s here and what’s coming um but certainly 1021 00:46:11,870 --> 00:46:13,737 what’s coming um but certainly the comments of the speaker’s 1022 00:46:13,737 --> 00:46:14,771 the comments of the speaker’s resonate with researcher 1023 00:46:14,771 --> 00:46:17,004 resonate with researcher showing as well. Thank you. 1024 00:46:17,004 --> 00:46:19,838 showing as well. Thank you. thank you sham. So let me start 1025 00:46:19,838 --> 00:46:21,171 thank you sham. So let me start taking a few questions from uh 1026 00:46:21,171 --> 00:46:23,371 taking a few questions from uh from our audience and actually 1027 00:46:23,371 --> 00:46:25,171 from our audience and actually the top rated uh question and 1028 00:46:25,171 --> 00:46:27,471 the top rated uh question and to all of our listeners if you 1029 00:46:27,471 --> 00:46:29,038 to all of our listeners if you if you want to have a question 1030 00:46:29,038 --> 00:46:31,537 if you want to have a question that you like um me being asked 1031 00:46:31,537 --> 00:46:32,937 that you like um me being asked please vote for it because then 1032 00:46:32,937 --> 00:46:34,737 please vote for it because then it moves up in my feet but the 1033 00:46:34,737 --> 00:46:35,671 it moves up in my feet but the top question currently is 1034 00:46:35,671 --> 00:46:37,038 top question currently is actually by my colleague uh 1035 00:46:37,038 --> 00:46:39,671 actually by my colleague uh scarlet uh Varga uh who’s 1036 00:46:39,671 --> 00:46:42,470 scarlet uh Varga uh who’s asking about um uh the debates 1037 00:46:42,470 --> 00:46:43,838 asking about um uh the debates um and the thinking around the 1038 00:46:43,838 --> 00:46:45,504 um and the thinking around the introduction of a universal 1039 00:46:45,504 --> 00:46:47,903 introduction of a universal basic income uh to deal with um 1040 00:46:47,903 --> 00:46:49,638 basic income uh to deal with um automation and artificial 1041 00:46:49,638 --> 00:46:53,137 automation and artificial intelligence. Um and um and the 1042 00:46:53,137 --> 00:46:58,204 intelligence. Um and um and the impact it has on on um now um I 1043 00:46:58,204 --> 00:47:00,204 impact it has on on um now um I would love to hear uh trips 1044 00:47:00,204 --> 00:47:02,037 would love to hear uh trips short comment from you on that, 1045 00:47:02,037 --> 00:47:04,038 short comment from you on that, but then really um I would love 1046 00:47:04,038 --> 00:47:06,071 but then really um I would love to hear. Also answer from you 1047 00:47:06,071 --> 00:47:07,637 to hear. Also answer from you because you’ve been working in 1048 00:47:07,637 --> 00:47:09,138 because you’ve been working in the social security system in 1049 00:47:09,138 --> 00:47:11,004 the social security system in Italy and I think it would be 1050 00:47:11,004 --> 00:47:12,204 Italy and I think it would be really I think a very 1051 00:47:12,204 --> 00:47:14,038 really I think a very interesting reality. Check to 1052 00:47:14,038 --> 00:47:15,438 interesting reality. Check to hear from you uh whether it’s 1053 00:47:15,438 --> 00:47:17,104 hear from you uh whether it’s such a move would even be 1054 00:47:17,104 --> 00:47:18,404 such a move would even be possible. I mean lots of 1055 00:47:18,404 --> 00:47:19,171 possible. I mean lots of Silicon Valley uh people of 1056 00:47:19,171 --> 00:47:22,204 Silicon Valley uh people of course. 1057 00:47:56,004 --> 00:47:58,470 A basic income in terms of 1058 00:47:58,470 --> 00:48:01,171 A basic income in terms of injecting capital um directly 1059 00:48:01,171 --> 00:48:03,538 injecting capital um directly into the accounts of um 1060 00:48:03,538 --> 00:48:05,171 into the accounts of um consumers across the country 1061 00:48:05,171 --> 00:48:06,438 consumers across the country regardless of their economic 1062 00:48:06,438 --> 00:48:08,370 regardless of their economic status or their employment 1063 00:48:08,370 --> 00:48:11,637 status or their employment status. And so I think uh maybe 1064 00:48:11,637 --> 00:48:13,003 status. And so I think uh maybe from people like Tito and Susan 1065 00:48:13,003 --> 00:48:15,771 from people like Tito and Susan will tell us um what the impact 1066 00:48:15,771 --> 00:48:17,003 will tell us um what the impact of that kind of injection of 1067 00:48:17,003 --> 00:48:19,504 of that kind of injection of capital means uh the benefits 1068 00:48:19,504 --> 00:48:22,503 capital means uh the benefits and the challenges. Thank you a 1069 00:48:22,503 --> 00:48:24,171 and the challenges. Thank you a Tito well. if you support, I 1070 00:48:24,171 --> 00:48:25,603 Tito well. if you support, I think we should agree on what 1071 00:48:25,603 --> 00:48:27,605 think we should agree on what we mean exactly by universal 1072 00:48:27,605 --> 00:48:29,471 we mean exactly by universal basic income because we are the 1073 00:48:29,471 --> 00:48:30,238 basic income because we are the definitions of the war and we 1074 00:48:30,238 --> 00:48:33,005 definitions of the war and we have to be very precise. 1075 00:48:33,005 --> 00:48:34,537 have to be very precise. Generally speaking, you know 1076 00:48:34,537 --> 00:48:35,838 Generally speaking, you know the idea of universal Basic 1077 00:48:35,838 --> 00:48:38,337 the idea of universal Basic income is one of unconditional, 1078 00:48:38,337 --> 00:48:41,171 income is one of unconditional, which is provided to every uh 1079 00:48:41,171 --> 00:48:43,438 which is provided to every uh the only requirement keep the 1080 00:48:43,438 --> 00:48:47,104 the only requirement keep the citizens so even the the very 1081 00:48:47,104 --> 00:48:50,204 citizens so even the the very rich people will get uh. Nice 1082 00:48:50,204 --> 00:48:51,804 rich people will get uh. Nice feature of this and one that 1083 00:48:51,804 --> 00:48:53,204 feature of this and one that could make it so appealing for 1084 00:48:53,204 --> 00:48:55,737 could make it so appealing for an academic standpoint is that 1085 00:48:55,737 --> 00:48:57,171 an academic standpoint is that it doesn’t carry any business 1086 00:48:57,171 --> 00:48:59,503 it doesn’t carry any business and two because whatever you do 1087 00:48:59,503 --> 00:49:02,537 and two because whatever you do if you if you don’t work, you 1088 00:49:02,537 --> 00:49:04,771 if you if you don’t work, you do get the answers so there is 1089 00:49:04,771 --> 00:49:06,605 do get the answers so there is not the type of issues that are 1090 00:49:06,605 --> 00:49:10,005 not the type of issues that are related to uh work at this and 1091 00:49:10,005 --> 00:49:11,670 related to uh work at this and give us associated to receiving 1092 00:49:11,670 --> 00:49:13,004 give us associated to receiving the answers. Have you ever been 1093 00:49:13,004 --> 00:49:16,004 the answers. Have you ever been there? It’s an activity costly 1094 00:49:16,004 --> 00:49:19,870 there? It’s an activity costly effort and uh it’s clearly. 1095 00:49:19,870 --> 00:49:22,337 effort and uh it’s clearly. Countries are struggling to 1096 00:49:22,337 --> 00:49:25,004 Countries are struggling to reduce uh and certainly that 1097 00:49:25,004 --> 00:49:26,304 reduce uh and certainly that the public that’s for good 1098 00:49:26,304 --> 00:49:28,003 the public that’s for good reason has increased during the 1099 00:49:28,003 --> 00:49:31,570 reason has increased during the day and uh and we still rising 1100 00:49:31,570 --> 00:49:34,003 day and uh and we still rising in the months to come uh but 1101 00:49:34,003 --> 00:49:35,637 in the months to come uh but the public that is not 1102 00:49:35,637 --> 00:49:36,504 the public that is not something good that we are 1103 00:49:36,504 --> 00:49:38,037 something good that we are talking before about the young 1104 00:49:38,037 --> 00:49:39,570 talking before about the young people certainly having such a 1105 00:49:39,570 --> 00:49:41,004 people certainly having such a high debt burden is not a good 1106 00:49:41,004 --> 00:49:43,637 high debt burden is not a good idea. The good thing for a new 1107 00:49:43,637 --> 00:49:45,337 idea. The good thing for a new generation so um I think you 1108 00:49:45,337 --> 00:49:47,171 generation so um I think you should be very careful of that 1109 00:49:47,171 --> 00:49:48,970 should be very careful of that and uh there is a reason why 1110 00:49:48,970 --> 00:49:50,870 and uh there is a reason why it’s not counting the world 1111 00:49:50,870 --> 00:49:52,470 it’s not counting the world that the pure idea of universal 1112 00:49:52,470 --> 00:49:55,703 that the pure idea of universal basic income has been applied. 1113 00:49:55,703 --> 00:49:59,038 basic income has been applied. Just du co 1114 00:50:12,171 --> 00:50:15,171 eh 1115 00:50:18,437 --> 00:50:21,437 targeting 1116 00:50:21,437 --> 00:50:21,504 targeting out est 1117 00:50:21,504 --> 00:50:26,071 out est five people di un 1118 00:50:26,071 --> 00:50:29,170 out est five people di un inituario 1119 00:50:29,404 --> 00:50:32,871 very good infrastruttura 1120 00:50:42,371 --> 00:50:45,504 e 1121 00:50:47,904 --> 00:50:53,637 a libreria clienti, bel 1122 00:50:54,203 --> 00:51:00,203 people web, face eh, margine 1123 00:51:02,504 --> 00:51:05,537 eh 1124 00:51:16,670 --> 00:51:19,970 il tipo 1125 00:51:21,070 --> 00:51:28,170 design e il e no 1126 00:51:29,170 --> 00:51:30,871 The transfer I would call them 1127 00:51:30,871 --> 00:51:34,103 The transfer I would call them a minimum income skills are 1128 00:51:34,103 --> 00:51:35,538 a minimum income skills are important for the most 1129 00:51:35,538 --> 00:51:39,038 important for the most countries uh they need to be uh 1130 00:51:39,038 --> 00:51:40,504 countries uh they need to be uh the strength to we like to be 1131 00:51:40,504 --> 00:51:42,005 the strength to we like to be we need to create an 1132 00:51:42,005 --> 00:51:44,670 we need to create an infrastructure that allow the 1133 00:51:44,670 --> 00:51:46,104 infrastructure that allow the government to reach these 1134 00:51:46,104 --> 00:51:47,737 government to reach these people and at the same time we 1135 00:51:47,737 --> 00:51:50,271 people and at the same time we need to improve uh integration 1136 00:51:50,271 --> 00:51:52,638 need to improve uh integration with the rest of the social 1137 00:51:52,638 --> 00:51:53,404 with the rest of the social security system in such a way 1138 00:51:53,404 --> 00:51:55,671 security system in such a way as we use to work at business 1139 00:51:55,671 --> 00:51:57,170 as we use to work at business and associated to them. no 1140 00:51:57,170 --> 00:52:00,304 and associated to them. no doubt. 1141 00:53:04,137 --> 00:53:05,637 Right back to be taken into 1142 00:53:05,637 --> 00:53:07,737 Right back to be taken into account and possibly the safety 1143 00:53:07,737 --> 00:53:10,138 account and possibly the safety net should be brought in such a 1144 00:53:10,138 --> 00:53:11,904 net should be brought in such a way as to each of these people. 1145 00:53:11,904 --> 00:53:13,204 way as to each of these people. But no doubt I think there 1146 00:53:13,204 --> 00:53:15,438 But no doubt I think there should be targeting more 1147 00:53:15,438 --> 00:53:16,937 should be targeting more targeting the one in business 1148 00:53:16,937 --> 00:53:18,471 targeting the one in business in the idea of the University 1149 00:53:18,471 --> 00:53:20,903 in the idea of the University of Michigan. Thank you. Thank 1150 00:53:20,903 --> 00:53:22,671 of Michigan. Thank you. Thank you Tito uh that that was very 1151 00:53:22,671 --> 00:53:24,404 you Tito uh that that was very comprehensive and of course, I 1152 00:53:24,404 --> 00:53:26,504 comprehensive and of course, I think it’s very clear that um 1153 00:53:26,504 --> 00:53:28,270 think it’s very clear that um the design really matters and 1154 00:53:28,270 --> 00:53:29,737 the design really matters and the way you design. it 1155 00:53:29,737 --> 00:53:31,471 the way you design. it precisely really makes a huge 1156 00:53:31,471 --> 00:53:32,604 precisely really makes a huge difference and there’s still a 1157 00:53:32,604 --> 00:53:36,037 difference and there’s still a lot of. Of course, ongoing also 1158 00:53:36,037 --> 00:53:38,571 lot of. Of course, ongoing also on the behavioral effects of of 1159 00:53:38,571 --> 00:53:41,771 on the behavioral effects of of such a scheme um they have been 1160 00:53:41,771 --> 00:53:42,504 such a scheme um they have been experiments. I think in 1161 00:53:42,504 --> 00:53:44,071 experiments. I think in Finland, there’s no new 1162 00:53:44,071 --> 00:53:46,771 Finland, there’s no new experiment uh starting in 1163 00:53:46,771 --> 00:53:48,237 experiment uh starting in Germany uh so many places 1164 00:53:48,237 --> 00:53:50,504 Germany uh so many places actually try this kind of 1165 00:53:50,504 --> 00:53:53,270 actually try this kind of instruments uh to see um how 1166 00:53:53,270 --> 00:53:54,605 instruments uh to see um how they would change actually 1167 00:53:54,605 --> 00:53:55,905 they would change actually behavior and what is a good 1168 00:53:55,905 --> 00:53:58,671 behavior and what is a good design um but uh uh perhaps I 1169 00:53:58,671 --> 00:54:01,004 design um but uh uh perhaps I can ask you. I mean how worried 1170 00:54:01,004 --> 00:54:02,270 can ask you. I mean how worried are you really about um this 1171 00:54:02,270 --> 00:54:05,504 are you really about um this issue? Um the impact of 1172 00:54:05,504 --> 00:54:06,905 issue? Um the impact of digitalization and artificial 1173 00:54:06,905 --> 00:54:09,703 digitalization and artificial intelligence on inequality um 1174 00:54:09,703 --> 00:54:13,605 intelligence on inequality um on the future of work um and uh 1175 00:54:13,605 --> 00:54:15,103 on the future of work um and uh to what extent do you think um 1176 00:54:15,103 --> 00:54:16,671 to what extent do you think um the policy solution is uh 1177 00:54:16,671 --> 00:54:18,671 the policy solution is uh something like a universal 1178 00:54:18,671 --> 00:54:22,204 something like a universal basic income. 1179 00:54:55,604 --> 00:54:57,104 Service you’re gonna see more 1180 00:54:57,104 --> 00:55:00,704 Service you’re gonna see more ordering on apps or iPads or 1181 00:55:00,704 --> 00:55:02,938 ordering on apps or iPads or kiosks in hotels you’re going 1182 00:55:02,938 --> 00:55:05,038 kiosks in hotels you’re going to get um robots delivering 1183 00:55:05,038 --> 00:55:08,971 to get um robots delivering goods to your room um and 1184 00:55:08,971 --> 00:55:10,304 goods to your room um and retail you’re gonna see more 1185 00:55:10,304 --> 00:55:12,504 retail you’re gonna see more self checkout and this is 1186 00:55:12,504 --> 00:55:15,037 self checkout and this is driven not so much by 1187 00:55:15,037 --> 00:55:15,837 driven not so much by productivity, but because of 1188 00:55:15,837 --> 00:55:18,904 productivity, but because of the health concerns so there 1189 00:55:18,904 --> 00:55:19,804 the health concerns so there are many classes of 1190 00:55:19,804 --> 00:55:20,871 are many classes of technologies that we do think 1191 00:55:20,871 --> 00:55:23,438 technologies that we do think are gonna be adopted faster. Um 1192 00:55:23,438 --> 00:55:25,204 are gonna be adopted faster. Um that’s gonna create an 1193 00:55:25,204 --> 00:55:28,171 that’s gonna create an accelerated need for this um 1194 00:55:28,171 --> 00:55:31,437 accelerated need for this um training. Positioning workers 1195 00:55:31,437 --> 00:55:34,470 training. Positioning workers to do the work available over 1196 00:55:34,470 --> 00:55:36,904 to do the work available over the next five to 10 years. I 1197 00:55:36,904 --> 00:55:38,437 the next five to 10 years. I don’t think we’re in a position 1198 00:55:38,437 --> 00:55:39,503 don’t think we’re in a position where technology is gonna do 1199 00:55:39,503 --> 00:55:40,971 where technology is gonna do all our work and we’re gonna 1200 00:55:40,971 --> 00:55:43,604 all our work and we’re gonna work 15 hours a week. It’s our 1201 00:55:43,604 --> 00:55:46,338 work 15 hours a week. It’s our team’s predicted 90 years ago. 1202 00:55:46,338 --> 00:55:49,171 team’s predicted 90 years ago. That would be lovely but um I 1203 00:55:49,171 --> 00:55:50,304 That would be lovely but um I don’t think we’re in that 1204 00:55:50,304 --> 00:55:53,004 don’t think we’re in that world. so I think that the 1205 00:55:53,004 --> 00:55:56,405 world. so I think that the critical um uh policy measures 1206 00:55:56,405 --> 00:55:58,504 critical um uh policy measures are to expand training 1207 00:55:58,504 --> 00:55:59,604 are to expand training opportunities. It starts with 1208 00:55:59,604 --> 00:56:00,903 opportunities. It starts with the young people as we’ve been 1209 00:56:00,903 --> 00:56:02,637 the young people as we’ve been talking about so that as they 1210 00:56:02,637 --> 00:56:05,937 talking about so that as they leave second. Do they have an 1211 00:56:05,937 --> 00:56:07,438 leave second. Do they have an idea of how they’re going to 1212 00:56:07,438 --> 00:56:09,170 idea of how they’re going to get skills they need and it can 1213 00:56:09,170 --> 00:56:11,171 get skills they need and it can be let’s not forget about some 1214 00:56:11,171 --> 00:56:13,104 be let’s not forget about some of the skilled trades like 1215 00:56:13,104 --> 00:56:15,070 of the skilled trades like plumbers, electricians and 1216 00:56:15,070 --> 00:56:16,871 plumbers, electricians and mechanics um that work is not 1217 00:56:16,871 --> 00:56:19,637 mechanics um that work is not easily automated um and in some 1218 00:56:19,637 --> 00:56:21,038 easily automated um and in some countries where the focus has 1219 00:56:21,038 --> 00:56:22,271 countries where the focus has been so heavily on everyone 1220 00:56:22,271 --> 00:56:24,004 been so heavily on everyone going to college, they are now 1221 00:56:24,004 --> 00:56:26,103 going to college, they are now a shortage of welders and 1222 00:56:26,103 --> 00:56:28,970 a shortage of welders and people doing that type of work 1223 00:56:28,970 --> 00:56:30,704 people doing that type of work um, but I think it’s an 1224 00:56:30,704 --> 00:56:31,538 um, but I think it’s an information problem and I think 1225 00:56:31,538 --> 00:56:32,937 information problem and I think we need to expand the school. 1226 00:56:32,937 --> 00:56:34,637 we need to expand the school. So that there are training 1227 00:56:34,637 --> 00:56:37,171 So that there are training programs that are matter of 1228 00:56:37,171 --> 00:56:38,503 programs that are matter of months not years because once 1229 00:56:38,503 --> 00:56:40,604 months not years because once you’re mid career and you may 1230 00:56:40,604 --> 00:56:42,138 you’re mid career and you may have children um and you have 1231 00:56:42,138 --> 00:56:43,505 have children um and you have other financial commitments, 1232 00:56:43,505 --> 00:56:45,904 other financial commitments, you can’t take years to learn 1233 00:56:45,904 --> 00:56:47,670 you can’t take years to learn new skills so um I think 1234 00:56:47,670 --> 00:56:49,137 new skills so um I think there’s been a lot of movement 1235 00:56:49,137 --> 00:56:53,004 there’s been a lot of movement to short-term very rapid boot 1236 00:56:53,004 --> 00:56:54,637 to short-term very rapid boot camp like training programs 1237 00:56:54,637 --> 00:56:57,003 camp like training programs that give you minimum skills 1238 00:56:57,003 --> 00:56:59,371 that give you minimum skills you need to get on the job. um 1239 00:56:59,371 --> 00:57:00,437 you need to get on the job. um we’ve seen it in a computer 1240 00:57:00,437 --> 00:57:03,604 we’ve seen it in a computer coding, but it’s now being. To 1241 00:57:03,604 --> 00:57:04,504 coding, but it’s now being. To things like for the lowest 1242 00:57:04,504 --> 00:57:07,505 things like for the lowest level of nurses for a graphic 1243 00:57:07,505 --> 00:57:08,204 level of nurses for a graphic designer and the rest, you can 1244 00:57:08,204 --> 00:57:09,171 designer and the rest, you can learn on the job. so I think 1245 00:57:09,171 --> 00:57:10,638 learn on the job. so I think those types of programs are 1246 00:57:10,638 --> 00:57:13,970 those types of programs are gonna be incredibly important 1247 00:57:13,970 --> 00:57:16,070 gonna be incredibly important in helping people adapt to the 1248 00:57:16,070 --> 00:57:18,238 in helping people adapt to the changing nature of work. there 1249 00:57:18,238 --> 00:57:19,704 changing nature of work. there will be jobs out there, but 1250 00:57:19,704 --> 00:57:21,204 will be jobs out there, but it’s gonna be different in how 1251 00:57:21,204 --> 00:57:22,638 it’s gonna be different in how you get them and I think a lot 1252 00:57:22,638 --> 00:57:23,638 you get them and I think a lot of people are gonna need help 1253 00:57:23,638 --> 00:57:26,004 of people are gonna need help to realize what opportunities 1254 00:57:26,004 --> 00:57:27,671 to realize what opportunities are there and then build that 1255 00:57:27,671 --> 00:57:30,538 are there and then build that skill base um very quickly. 1256 00:57:30,538 --> 00:57:33,638 skill base um very quickly. Thank you. A few minutes left, 1257 00:57:33,638 --> 00:57:37,438 Thank you. A few minutes left, but I do wanna turn to for the 1258 00:57:37,438 --> 00:57:39,638 but I do wanna turn to for the last question, which is really 1259 00:57:39,638 --> 00:57:41,404 last question, which is really about um the question of uh 1260 00:57:41,404 --> 00:57:43,971 about um the question of uh remote and um whether or not it 1261 00:57:43,971 --> 00:57:45,604 remote and um whether or not it is here to stay and what are 1262 00:57:45,604 --> 00:57:47,904 is here to stay and what are the effects of remote work um 1263 00:57:47,904 --> 00:57:50,671 the effects of remote work um on inequality um in in your 1264 00:57:50,671 --> 00:57:52,937 on inequality um in in your view and perhaps also in the 1265 00:57:52,937 --> 00:57:53,870 view and perhaps also in the view uh from the point of view 1266 00:57:53,870 --> 00:57:56,138 view uh from the point of view of uh of an organization, a big 1267 00:57:56,138 --> 00:57:57,404 of uh of an organization, a big organization like yours, I mean 1268 00:57:57,404 --> 00:57:59,437 organization like yours, I mean how how do you experience this 1269 00:57:59,437 --> 00:58:02,638 how how do you experience this and another person here? On the 1270 00:58:02,638 --> 00:58:04,971 and another person here? On the on the chat, um it’s actually 1271 00:58:04,971 --> 00:58:07,938 on the chat, um it’s actually asking um uh you know whether 1272 00:58:07,938 --> 00:58:10,804 asking um uh you know whether um some companies apparently um 1273 00:58:10,804 --> 00:58:13,604 um some companies apparently um are trying to get work back to 1274 00:58:13,604 --> 00:58:14,871 are trying to get work back to back to back to the office 1275 00:58:14,871 --> 00:58:17,005 back to back to the office again and I sort of suspicious 1276 00:58:17,005 --> 00:58:20,137 again and I sort of suspicious of progressive forms of remote 1277 00:58:20,137 --> 00:58:21,737 of progressive forms of remote work and so if you can just 1278 00:58:21,737 --> 00:58:23,038 work and so if you can just share with us a little bit of 1279 00:58:23,038 --> 00:58:25,804 share with us a little bit of your experience on how remote 1280 00:58:25,804 --> 00:58:27,971 your experience on how remote remote work is is shaping up 1281 00:58:27,971 --> 00:58:29,737 remote work is is shaping up and um you know whether there’s 1282 00:58:29,737 --> 00:58:31,171 and um you know whether there’s inequality effects whether you 1283 00:58:31,171 --> 00:58:33,171 inequality effects whether you see already that it leads to to 1284 00:58:33,171 --> 00:58:34,671 see already that it leads to to not inclusion of sun breaks 1285 00:58:34,671 --> 00:58:35,437 not inclusion of sun breaks that work remotely while others 1286 00:58:35,437 --> 00:58:39,871 that work remotely while others get more included. 1287 00:59:08,537 --> 00:59:11,204 It’s very difficult to sort of 1288 00:59:11,204 --> 00:59:12,938 It’s very difficult to sort of um require I think people to 1289 00:59:12,938 --> 00:59:14,471 um require I think people to come back to work uh in an 1290 00:59:14,471 --> 00:59:16,337 come back to work uh in an office setting, but I do think 1291 00:59:16,337 --> 00:59:18,070 office setting, but I do think that um for all of the 1292 00:59:18,070 --> 00:59:20,071 that um for all of the advantages of sort of working 1293 00:59:20,071 --> 00:59:22,104 advantages of sort of working remotely from anywhere in terms 1294 00:59:22,104 --> 00:59:24,604 remotely from anywhere in terms of flexibility and 1295 00:59:24,604 --> 00:59:26,171 of flexibility and productivity, I also think that 1296 00:59:26,171 --> 00:59:28,571 productivity, I also think that um we certainly have been 1297 00:59:28,571 --> 00:59:30,171 um we certainly have been missing um what happens when 1298 00:59:30,171 --> 00:59:33,538 missing um what happens when people come together and the um 1299 00:59:33,538 --> 00:59:36,171 people come together and the um uh contemporary work uh and the 1300 00:59:36,171 --> 00:59:39,637 uh contemporary work uh and the ideation and um. The 1301 00:59:39,637 --> 00:59:41,570 ideation and um. The collaboration that comes uh for 1302 00:59:41,570 --> 00:59:42,304 collaboration that comes uh for an organization like ours, 1303 00:59:42,304 --> 00:59:45,770 an organization like ours, which is very dependent on 1304 00:59:45,770 --> 00:59:47,804 which is very dependent on technology and innovation um to 1305 00:59:47,804 --> 00:59:48,737 technology and innovation um to accelerate the digitization. 1306 00:59:48,737 --> 00:59:50,971 accelerate the digitization. and so I think that these are 1307 00:59:50,971 --> 00:59:51,637 and so I think that these are all the things that we’re 1308 00:59:51,637 --> 00:59:53,937 all the things that we’re seeing both as a global 1309 00:59:53,937 --> 00:59:55,904 seeing both as a global company, but also as one that’s 1310 00:59:55,904 --> 00:59:57,438 company, but also as one that’s trying to balance, obviously 1311 00:59:57,438 --> 00:59:58,638 trying to balance, obviously the health and safety of our 1312 00:59:58,638 --> 01:00:01,471 the health and safety of our colleagues um with the 1313 01:00:01,471 --> 01:00:03,138 colleagues um with the innovation and productivity and 1314 01:00:03,138 --> 01:00:05,471 innovation and productivity and um the efficiency of what 1315 01:00:05,471 --> 01:00:06,404 um the efficiency of what happens when you come together 1316 01:00:06,404 --> 01:00:08,504 happens when you come together as an organization. so I think 1317 01:00:08,504 --> 01:00:09,904 as an organization. so I think again until there’s a vaccine 1318 01:00:09,904 --> 01:00:14,004 again until there’s a vaccine uh we sort of. This this gray 1319 01:00:14,004 --> 01:00:16,437 uh we sort of. This this gray area, but uh definitely lots of 1320 01:00:16,437 --> 01:00:18,070 area, but uh definitely lots of good things have come from it 1321 01:00:18,070 --> 01:00:19,537 good things have come from it for sure um in terms of 1322 01:00:19,537 --> 01:00:21,170 for sure um in terms of MasterCard, but I think we’re 1323 01:00:21,170 --> 01:00:22,504 MasterCard, but I think we’re all anxious to get back to the 1324 01:00:22,504 --> 01:00:23,671 all anxious to get back to the office and sort of roll up our 1325 01:00:23,671 --> 01:00:25,204 office and sort of roll up our sleeves together in a 1326 01:00:25,204 --> 01:00:27,204 sleeves together in a collaborative setting. Thank 1327 01:00:27,204 --> 01:00:30,104 collaborative setting. Thank you Shaina and indeed I think I 1328 01:00:30,104 --> 01:00:32,437 you Shaina and indeed I think I can very much confirmed that um 1329 01:00:32,437 --> 01:00:34,204 can very much confirmed that um while there’s been lots of 1330 01:00:34,204 --> 01:00:35,471 while there’s been lots of benefits um there’s also a lot 1331 01:00:35,471 --> 01:00:37,171 benefits um there’s also a lot of things that I missed and 1332 01:00:37,171 --> 01:00:39,637 of things that I missed and many of my colleagues we 1333 01:00:39,637 --> 01:00:41,937 many of my colleagues we definitely miss seeing you all 1334 01:00:41,937 --> 01:00:43,637 definitely miss seeing you all here on a panel in the same 1335 01:00:43,637 --> 01:00:44,804 here on a panel in the same room. I mean it’s still would 1336 01:00:44,804 --> 01:00:46,004 room. I mean it’s still would have been different than just a 1337 01:00:46,004 --> 01:00:48,737 have been different than just a tale conference. We did it um 1338 01:00:48,737 --> 01:00:50,571 tale conference. We did it um unfortunately, our time is 1339 01:00:50,571 --> 01:00:52,671 unfortunately, our time is already up um so um let me 1340 01:00:52,671 --> 01:00:54,871 already up um so um let me thank to thank all of our 1341 01:00:54,871 --> 01:00:57,838 thank to thank all of our panelists for their wives and 1342 01:00:57,838 --> 01:01:00,037 panelists for their wives and they are very interesting 1343 01:01:00,037 --> 01:01:02,537 they are very interesting contributions and uh thank you 1344 01:01:02,537 --> 01:01:04,537 contributions and uh thank you for the great collaboration. I 1345 01:01:04,537 --> 01:01:07,004 for the great collaboration. I mean there’s gonna be many more 1346 01:01:07,004 --> 01:01:08,737 mean there’s gonna be many more um conferences real conferences 1347 01:01:08,737 --> 01:01:11,171 um conferences real conferences video conferences debates on 1348 01:01:11,171 --> 01:01:12,737 video conferences debates on this and related to the issues 1349 01:01:12,737 --> 01:01:14,471 this and related to the issues in the years to come so uh 1350 01:01:14,471 --> 01:01:17,537 in the years to come so uh watch out on our website. And 1351 01:01:17,537 --> 01:01:20,204 watch out on our website. And you’ll see more of that coming. 1352 01:01:20,204 --> 01:01:21,604 you’ll see more of that coming. Thank you all for joining and 1353 01:01:21,604 --> 01:01:22,903 Thank you all for joining and it’s been a pleasure to host 1354 01:01:22,903 --> 01:01:25,204 it’s been a pleasure to host this panel and thank you again. 1355 01:01:25,204 --> 01:01:28,338 this panel and thank you again. Bye.