WEBVTT X-TIMESTAMP-MAP=LOCAL:00:00:00.000,MPEGTS:0 00:03.360 --> 00:07.060 Hello and welcome to this series of interviews on the future of cities. 00:08.100 --> 00:14.780 In the next hour or, or so, we will discuss what we can expect from the urban centers in 00:14.820 --> 00:17.380 the upcoming years. Joining us today is Sandy Carter. 00:17.420 --> 00:22.000 Sandy is the vice president of worldwide public sector partners and programs at Amazon 00:22.060 --> 00:24.800 Web Services. It is my pleasure to have you here. 00:25.120 --> 00:29.820 AWS has been an ally to governance, g- governments, public sector, private sector, 00:29.950 --> 00:34.660 and cities that want to take the next step into digitalizing their 00:34.720 --> 00:36.560 management and services. 00:37.520 --> 00:43.640 as it stands now, based on some numbers I've just seen, over 6,500 government agencies are 00:43.740 --> 00:46.260 using AWS, which is a remarkable number. 00:46.520 --> 00:52.500 My idea would be to talk a bit, with you about, IoT, data, 00:52.920 --> 00:59.510 cloud, and, how they are going to be used in the cities, and societies, 01:00.040 --> 01:02.380 of tomorrow. So welcome, Sandy. 01:03.200 --> 01:10.100 Let's, let's start, with I would say with a, with a topic that touches, touches, all, 01:10.110 --> 01:14.120 all of us. I, I would say COVID has been very severe. 01:15.200 --> 01:21.760 it's unco- I would say it uncovered several, urban challenges to our urban 01:21.780 --> 01:25.340 ecosystems, but also opens, some opportunities. 01:26.020 --> 01:32.360 How, how do you see the pandemic affecting cities and aff- affecting cities now and the 01:32.420 --> 01:35.440 way they will be planned in the years to come? 01:35.740 --> 01:37.920 Well, thank you, Miguel. First of all, I just want to say thanks for 01:37.960 --> 01:41.220 having me on. This is one of my very favorite topics. 01:42.020 --> 01:46.880 So to your question, how do I see the pandemic affecting states and cities and other urban 01:46.940 --> 01:52.800 development globally, we really see three major impacts today. 01:53.220 --> 01:56.920 first is efficiency that we've seen gained in the cloud. 01:57.840 --> 02:02.920 Second is around data, and third is around optimization. 02:02.980 --> 02:09.840 We saw states and cities around the world need expertise, and in order to be able to 02:09.940 --> 02:14.400 scale up and scale down very quickly, they needed to have a solution 02:14.420 --> 02:15.420 that was in the cloud. 02:16.040 --> 02:18.220 One example of that is a call center. 02:18.560 --> 02:24.860 Partnering with Deloitte, we were able to deploy a call center solution in the cloud in 02:24.920 --> 02:31.880 less than 10 days, which I love, with, with the ability to have 2,000 concurrent users 02:31.980 --> 02:35.680 at a time. The other thing that we really saw happening 02:35.760 --> 02:40.460 is that everybody was seeing the need for more data. 02:40.800 --> 02:44.340 Countries around the world, cities around the world needed to get masks 02:44.380 --> 02:45.400 to the right location. 02:45.420 --> 02:48.580 Well, how do you do that? Well, you have to have data about where the 02:48.600 --> 02:53.180 masks are, and they discovered very quickly that data really matters. 02:53.740 --> 03:00.720 And one of the big trends we saw is that IoT, using sensors or sensor-based apparatuses to 03:00.780 --> 03:06.060 gather that data, especially during COVID, when people had to stay six feet apart, IDC 03:06.120 --> 03:12.360 said that, the use of IoT to gather data to make better decisions went up by 400% 03:12.920 --> 03:14.240 since March to now. 03:14.300 --> 03:15.360 That's, like, in a year. 03:15.460 --> 03:16.720 That's pretty incredible. 03:16.860 --> 03:20.820 And then the third thing I would say is, we talked about optimization. 03:20.920 --> 03:26.340 Everybody looked at optimizing what they were doing, especially cities, but I would say the 03:26.380 --> 03:30.440 cities really looked to optimize their healthcare system. 03:30.580 --> 03:35.880 I love the platform that Deloitte has here because we've leveraged it across states and 03:35.920 --> 03:37.020 across countries. 03:37.040 --> 03:39.440 So for me, those were the three big impacts. 03:39.540 --> 03:41.520 Movement to the cloud that was accelerated. 03:42.580 --> 03:48.660 People, cities, states, countries, understanding the value and the significance 03:48.720 --> 03:53.520 of data like never before, and then the impact of optimization, especially 03:53.600 --> 03:55.180 on our healthcare systems. 03:55.720 --> 03:57.900 What do you think It's, it's a bit connected to what you say. 03:58.760 --> 04:00.920 even so, maybe you, you want to elaborate a bit further. 04:01.000 --> 04:06.520 What do you think are the main drivers shaping, I would say, the future of cities, and, and 04:06.580 --> 04:10.680 what's the role of, that, that you see, of technology in that? 04:10.760 --> 04:15.680 What do you think, is really shaping the, the future of the way we live, and what's the role 04:15.720 --> 04:19.160 of technology on that? Citizens now are demanding more. 04:19.880 --> 04:25.260 Because of the pandemic, there was much more reliance of, of citizens on their city 04:25.340 --> 04:26.940 government, city services. 04:27.080 --> 04:32.400 And so as citizens demand more, I think that one of the major drivers that will impact the 04:32.460 --> 04:38.820 future of cities will be how they will impact the demands and the requirements that are 04:38.840 --> 04:40.040 levied on things. 04:40.640 --> 04:45.540 I also think that a main driver of the future of cities will be clean energy. 04:45.960 --> 04:49.800 You know, it's a big, There's a big climate push right now. 04:50.190 --> 04:52.380 Yeah. I'm a member of the World Economic Forum. 04:52.540 --> 04:53.840 Climate is top of the chart. 04:53.880 --> 04:59.940 So as we enter 2021, clean tech companies no longer have to push their technologies on a 05:00.000 --> 05:04.380 city, but rather, cities are now pulling those in, in-house. 05:04.960 --> 05:11.780 And the rapid adoption of clean tech innovation, I believe, is, one of the 05:11.820 --> 05:15.440 investment areas. And then the other area that I think is really 05:15.480 --> 05:20.940 important is what we call IDE, inclusion, diversity, and equity. 05:22.020 --> 05:27.380 ensuring that we've got an inclusive culture in a city. 05:28.000 --> 05:31.320 one group that we work with is called the African Leadership Group. Mm-hmm. 05:31.700 --> 05:37.700 And, they have worked really hard to ensure that they're training up people around the 05:37.740 --> 05:39.500 world, and in particular in Africa. 05:39.940 --> 05:46.260 By 2035, Africa will have the largest and youngest workforce in the world, and how we 05:46.300 --> 05:50.200 train them will also be shaping the demand of the future of cities. 05:50.340 --> 05:54.380 And of course, in each of those, you know, there are technology implications, mobile, 05:54.480 --> 05:57.000 compute, network improvements that are needed. 05:57.580 --> 06:03.640 But I do believe that some of these areas that are gonna drive the future of cities will be a 06:03.700 --> 06:10.680 combination of, societal issues along with technology.One of the trends that we, 06:10.720 --> 06:17.720 that we envision and that we see, is, the need to orchestrate the data in the 06:17.760 --> 06:20.460 city and also to orchestrate the operations in the cities. 06:20.510 --> 06:23.700 And then they are all, of course, enabled by artificial intelligence. 06:25.120 --> 06:30.600 H- how can we, assess- how can we leverage more on AI, machine learning, and IoT, as you 06:30.640 --> 06:36.800 were describing in your introduction, and hub and platforms to deliver a better fu- future 06:37.020 --> 06:40.940 for us? How, how will these technologies be useful for 06:41.060 --> 06:42.360 us as citizens? 06:43.220 --> 06:48.400 I think that, the first step before we get to AI or machine learning is that data. 06:48.460 --> 06:51.990 So I'm gonna start with IoT- Yeah and then move to AI and machine learning. 06:53.060 --> 06:58.440 everybody who comes into one of our EBCs, our executive briefing centers, we always talk to 06:58.460 --> 07:00.200 them about having a data strategy. 07:00.400 --> 07:05.200 They really need to focus on their data sources, their data quality, their data 07:05.260 --> 07:12.180 quantity, and a lot of that can be solved by IoT sensors, whether it's sensors for traffic 07:12.240 --> 07:14.920 in their healthcare areas, in their arenas. 07:15.480 --> 07:20.500 I think gathering that data and being able to use that data will be critical. 07:20.540 --> 07:24.420 The second piece will be basically where your question started, which is how do we leverage 07:24.440 --> 07:26.610 then artificial intelligence and machine learning? 07:28.260 --> 07:32.680 I love the saying that data is the soil and everything else grows from the soil. 07:33.140 --> 07:38.060 We need all that data in order to accurately train our machine learning modules. 07:38.140 --> 07:40.320 I love the Deloitte platform. 07:40.480 --> 07:47.250 City synergy, for me, supports that city command center- Yeah in that cities can 07:47.360 --> 07:51.520 manage their responses, they have access to predictive impacts, they can monitor their 07:51.560 --> 07:57.780 KPIs, whether it's, you know, power management or waste collection or, you know, 07:57.920 --> 08:04.360 clean energy, and it's all because of the data that's coming in that enables those analytics 08:04.420 --> 08:05.840 to, to really happen. 08:06.380 --> 08:12.640 Regarding city synergy, we are now using the And it's powered by AWS, so we are using it 08:12.720 --> 08:19.280 now for, It was for COVID testing management, and now for vaccination, for the 08:19.300 --> 08:22.500 management of the vaccination process in, in Portugal. 08:22.580 --> 08:27.000 It's, and it's fully powered by AWS, as you know, so it's, it's really interesting. 08:27.760 --> 08:33.120 regarding data, and, and now, and now we're going to rephrase one, one, one phrase I heard 08:33.200 --> 08:39.220 from the mayor of Oporto, one of the, one of the mayors we interviewed, is that, w- where 08:39.240 --> 08:41.700 he was stressing the importance of data for city leaders. 08:43.120 --> 08:47.920 and he, and he said he, he came from educated guess- guesses in the past to having the 08:47.960 --> 08:53.040 ability to greatly improve the management and transparency of the city governance. 08:54.020 --> 09:00.900 W- what do you think the, the, the relevance of data is to, to, to the, to make sure 09:00.940 --> 09:03.820 that our governments are more inclusive and more transparent? 09:04.580 --> 09:08.460 The, the role of data- in inclusiveness and on transparency, what's your view on that? 09:10.040 --> 09:11.340 Well, it's essential, right? 09:11.380 --> 09:16.980 I mean, this is a big discussion point right now because, you know, if you have the right 09:17.100 --> 09:22.780 data source and the right data quality and quantity that is unbiased, you'll get the 09:22.860 --> 09:24.300 right information out. 09:24.620 --> 09:29.580 The problem is today that there's 1.7 megabytes of data that's created every second 09:29.660 --> 09:31.600 for every person on Earth. 09:32.040 --> 09:36.300 So how do you make sure that that data source you have has no bias in it? 09:36.380 --> 09:42.579 And it comes down to having diverse teams that you leverage to source the data. 09:42.660 --> 09:48.260 So I really do think that data, has an impact on 09:49.640 --> 09:52.020 the inclusive nature of what we're doing. 09:52.840 --> 09:58.360 the other area I think is really important around data is it's not just the ind- 09:58.740 --> 10:03.580 individual pieces of data, it's how that data is integrated as well, right? 10:03.660 --> 10:08.460 So if you think back to city synergy, we're looking at data that's collected from parking, 10:08.520 --> 10:11.520 traffic, lighting, utilities, purchases. 10:11.600 --> 10:15.180 Integrating that data makes that data more intelligent. 10:15.240 --> 10:21.140 That integration of data will be also important to making cities and governments 10:21.220 --> 10:25.700 more accessible, more reliable, and more transparent as well. 10:26.239 --> 10:32.560 Moving to, to another topic that also in your introduction, of course you, you described, is 10:32.880 --> 10:38.640 you, you describe, AWS describes cloud technology as the ultimate 10:39.040 --> 10:40.440 public sector upgrade. 10:41.240 --> 10:43.460 And I really very, I really agree with you of course. 10:44.080 --> 10:47.790 How, how do you see that the rate of transition to cloud in public sector, what 10:47.820 --> 10:51.770 kind of challenges you see, what kind of opportunities do you see in, in, in this 10:51.800 --> 10:53.360 transition less like like, like that? 10:54.060 --> 10:59.620 I say that, the pandemic made every city, state, local government a startup. 10:59.760 --> 11:03.390 They all started innovating more rapidly than they ever thought. Yeah. 11:03.420 --> 11:10.000 Trilia, which is one of our partners, they did a survey and, they found that the time period 11:10.040 --> 11:15.220 between March, when COVID kind of officially started, to now, so about a year, 11:16.200 --> 11:21.480 it accelerated digital transformation in one year what we had previously done in the 11:21.540 --> 11:23.030 previous six years. Yeah. 11:23.080 --> 11:28.540 Public sector really accelerated during the pandemic, and cloud helped 11:28.940 --> 11:30.420 because it reduced cost. 11:30.660 --> 11:37.000 So I think that, the impact here is wide, and I do believe it is the ultimate public sector 11:37.060 --> 11:41.730 upgrade, for sure. Another topic, that we have already touched is 11:41.780 --> 11:44.280 of course climate change and the, the issue of sustainability. 11:44.320 --> 11:50.908 As you said-I would say s- m- that b- based on a survey we have just done to 2,000, 11:51.248 --> 11:56.708 CXOs, around, around the world, it is very recent, it comes, it's the first priority in 11:56.748 --> 11:58.028 the agendas of the CXOs. 11:58.308 --> 12:05.248 What are the biggest contributions you see you as a, a global organization giving, for the 12:05.288 --> 12:09.318 environmental sustainability of kind of what kind of solutions you have been developing? 12:09.408 --> 12:10.458 Can you give some examples? 12:10.968 --> 12:14.898 I think that on sustainability there are multiple a- a- areas that 12:14.988 --> 12:16.348 Amazon is helping for. 12:16.508 --> 12:22.948 We have, an AWS sustainability perspective, an Amazon sustainability perspective. 12:23.008 --> 12:26.508 We're working to create an economy around clean water. 12:27.968 --> 12:34.528 for example, we worked with, SI, which is a partner, and, and they were looking at water 12:34.588 --> 12:35.968 management across Africa. 12:35.998 --> 12:41.228 So they created a pre-payment water dispenser solution that we helped them build an economy 12:41.308 --> 12:43.548 around their cities or their villages. 12:44.108 --> 12:50.728 And, what it, what enabled was use of IoT and AI to ensure 24 by seven accessibility. 12:50.888 --> 12:55.618 So there are many different ways that we're working with that, but this is for me one of 12:55.628 --> 13:01.788 the, one of the biggest impacts, is around the climate change and the climate change issues. 13:02.408 --> 13:08.608 One topic of, of, of, of this era is everything around security and privacy, 13:09.348 --> 13:13.628 data, data privacy, data security, cyber security, all this topic. 13:13.688 --> 13:20.328 W- w- in, in your view, what can be d- done to, to generate 13:20.908 --> 13:24.168 more trust and to make us feel more secure? 13:25.248 --> 13:28.128 I know there are several aspects of these, but what's your view on this? 13:28.748 --> 13:32.627 I think there are kind of three levels of, being secure. 13:32.728 --> 13:36.248 One is, you know, is the data available when I need it? 13:36.838 --> 13:38.068 Is it confidential? 13:38.788 --> 13:40.388 And is, does it have integrity? 13:40.508 --> 13:41.708 Can I rely on the data? 13:41.868 --> 13:46.548 Deloitte is actually, and one of those with us today, Miguel, it's called 13:46.608 --> 13:49.548 ATO, Authority to Operate. 13:49.628 --> 13:55.908 So if you know, governments and states and cities have requirements for 13:55.927 --> 13:59.268 security regulations or, or compliance. 13:59.808 --> 14:05.308 And so what we do is we train our partners, and we help their solutions to meet those 14:05.348 --> 14:06.588 security guidelines. 14:06.808 --> 14:12.628 Because security is such an important one for us to really be focused on as well. 14:13.308 --> 14:19.768 What do you think or th- what do you want, to be the role of AWS in urban ecosystems? 14:19.828 --> 14:21.588 What's your vision, what's your vision for that? 14:21.648 --> 14:23.608 What's the strategy for that? What's your objectives? 14:23.888 --> 14:28.748 And what's the role of, of, of partnerships, I would say, on that, on that strategy? 14:28.828 --> 14:30.168 What's the role of partners like Deloitte? 14:30.228 --> 14:34.148 Doesn't need to be just Deloitte, of course, as we live in an ecosystem perspective. 14:34.188 --> 14:35.828 But what's the strategy for urban? 14:36.308 --> 14:37.368 What's the role of partnerships? 14:37.728 --> 14:44.588 AWS always follows its, its principles, and one of those is always working backwards 14:44.608 --> 14:48.288 from the customer. So when we do that, Miguel, we see the role of 14:48.508 --> 14:49.788 many ecosystems. 14:50.248 --> 14:51.408 One, of course, is Deloitte. 14:51.568 --> 14:56.368 You know, partners like Deloitte are essential as we work backwards for the customer, 14:56.557 --> 15:00.828 figuring out how to meet their needs, whether that be figuring out how the data goes, the 15:00.888 --> 15:04.958 traffic, you know, vaccines that you gave an example of. 15:04.988 --> 15:09.088 We also know that startups are essential in ecosystems. 15:09.168 --> 15:13.648 So we have a set of programs that are set up to help startups, from providing them credits 15:13.708 --> 15:20.008 to get going, to advice and counsel, to help connecting them with VCs, private equity to 15:20.048 --> 15:23.328 get their funding. And when you do urban development, you want to 15:23.428 --> 15:27.588 use your local partners, small and medium businesses. 15:27.648 --> 15:32.008 So we just announced a new program called Think Big for Small Business. 15:32.388 --> 15:38.708 So for us, the ecosystems are important from system integrators like you to ISVs or tech 15:38.788 --> 15:43.848 providers, to startups, to small and medium diverse businesses. 15:43.908 --> 15:48.318 The, the role of that ecosystem is critical as we move forward. 15:48.988 --> 15:54.328 I just have one more question for you, but bef- before I pose it, I would like to ask you 15:54.368 --> 15:58.088 if there's, there's something you, else you would like to say or you would like to comment. 15:58.488 --> 16:00.568 I'm very passionate about smart cities. 16:00.628 --> 16:02.788 I do see this as the way of the future. 16:03.088 --> 16:08.848 We're really committed to having our partners in our, in our ecosystem participate in that. 16:08.908 --> 16:12.028 Deloitte is a very important partner for us. 16:12.068 --> 16:18.228 You guys have actually participated in our AI and ML rapid adoption assistance, both on 16:18.248 --> 16:21.808 healthcare, on image recognition, on distributed financial data. 16:22.168 --> 16:24.108 Of course, Sandy. One last, last question for 16:24.208 --> 16:25.908 you, a bit more personal. 16:27.548 --> 16:32.048 what i- w- how would it look like your dream city 10 years from now? 16:34.868 --> 16:38.068 so my dream city, first of all, it would be secure, right? 16:38.088 --> 16:42.448 Because security is job zero, as Andy Jassy likes to say. 16:42.508 --> 16:48.548 We would have more sensors to provide data, but it would be completely secure. 16:48.608 --> 16:52.368 The right compliance, the right governance would be in place everywhere. 16:53.288 --> 16:58.568 It would be a city that has a vibrant ecosystem of all partners that are 16:58.608 --> 17:05.498 participating, diversity partners for sure, startups, small businesses, all leveraging 17:05.528 --> 17:09.108 data to provide better and personalized service. 17:09.188 --> 17:15.508 So I imagine kind of a public/private partnership, you know, driven to 17:15.548 --> 17:18.958 include everything in the city, not just what's city-owned. 17:19.488 --> 17:26.248 But imagine, you know, a sporting arena supporting a city with a, an Amazon Go 17:26.258 --> 17:31.308 store, so you could just kind of walk in and walk out, that's connected that data to help 17:31.328 --> 17:33.148 you then get transportation home. 17:33.848 --> 17:39.528 I love that citizen experience that would be very simple, very intuitive with that public 17:39.608 --> 17:41.168 and private partnership. 17:41.268 --> 17:43.428 Great, Sandy. Thank you. 17:44.668 --> 17:47.668 thank you for your time. It was my pleasure talking to you, and for 17:47.708 --> 17:50.088 sure we'll have many opportunities to partner and to connect. 17:50.588 --> 17:52.328 Thank you. Thanks, Miguel.