- il y a 5 semaines
Digital Inclusion Bridging Gaps, Mapping (In)Equality
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00:00Hi, everyone, and I hope your Viva Tech is getting off to a great start.
00:06My name is Victoria Turk.
00:08I am an editor at Rest of World,
00:12a non-profit publication covering technology outside of the West.
00:17And it's my honor to be hosting the session today.
00:22We're going to be talking about digital inclusion
00:26and bridging inequalities that remain in innovation.
00:31I know there's a lot of excitement at Viva Tech this year,
00:34especially around the kind of recent boom in generative AI.
00:37But we're going to be asking, are we developing the right technologies?
00:41Are we developing the right applications for those technologies?
00:44Are those technologies reaching the people that they need to?
00:47And what can we do to bridge any remaining gaps?
00:50We're going to be taking a really global perspective on this.
00:54And I am joined by panelists from really diverse backgrounds
00:58in terms of geography, in terms of sector and experience.
01:04So we're going to dive right in.
01:05And rather than me continue talking,
01:07I'm going to ask each of our panelists if they can introduce themselves quickly.
01:12Tell us who you are, where you're from, what you do,
01:15starting with yourself, Minister.
01:17Thank you.
01:17Thank you very much, Victoria, for having me here.
01:20I would like to introduce myself.
01:21This is Zunaid Ahmed Pollock, Minister of State for Post-Telecommunication and IT from Bangladesh.
01:30My initial responsibility to provide reliable and affordable internet
01:36to all of our 170 million people.
01:39And we are developing our 50 million students
01:42with basic digital literacy and basic ICT skill set.
01:46And also, I promote ICT industry.
01:49I take care of our cyber security.
01:51At the same time, we are developing our telecom sector.
01:56So these are the primary role of my portfolio.
02:01At the same time, we are developing innovation ecosystem
02:05and introducing entrepreneurial supply chain.
02:10and at the same time, developing startup culture in Bangladesh.
02:13Thank you.
02:14Thank you.
02:15Felicitas.
02:16Yeah, hi.
02:16Super nice to be here.
02:18Thank you for having me.
02:19I am Felicitas.
02:20I am the Global Head of Diversity and Inclusion at SumUp,
02:23the fintech company.
02:24You might know the small, wide little devices, the card reader.
02:28And I also lead on sustainability initiatives,
02:31focusing on entrepreneurship, education and the environment,
02:34and also mental health.
02:36So super nice to be here.
02:37Thank you for having me.
02:39Okay.
02:41Thank you, Victoria.
02:43Good afternoon.
02:44My name is Charlotte Nguesson.
02:46I'm originally from the Ivory Coast.
02:47But most of my work, I've been from Africa.
02:50So I'm currently the lead of data solution and ecosystem at Amini.
02:54We are a digital company.
02:55We are based in Nairobi, Kenya.
02:57So we are currently solving the data scars here in Africa.
03:00So we have built a data infrastructure that is able to give access
03:05to reliable environmental data to organizations.
03:08Thank you for having me too.
03:11And Maria Grazia Scuicciarini, UNESCO.
03:14I'm the chief of the executive office of the social human sciences sector.
03:18I'm sorry, there is nothing short about me, nor the name, not the surname, nothing.
03:22And what I do is actually not only to steer the work of the sector.
03:26Actually, this is the S in UNESCO.
03:28So UNESCO is not only about cultural heritage that everybody knows.
03:32And it's one of the things we do.
03:34We do also education that is the E in the UNESCO and the S is for science.
03:39And we are responsible within the United Nations system for the ethics of new science and technologies.
03:45Hence the work we do in relation to artificial intelligence.
03:48Thank you very much.
03:49It's a pleasure to have everyone here for what I am convinced is going to be a very lively discussion.
03:55We may have questions at the end if we've got time.
03:58So if you've got questions for any of our panelists or all of them, please hold on to those.
04:02And we'll try and get to you before the session finishes.
04:05I'm going to dive right in with sort of the first question posed by this session title about digital inclusion,
04:11which is access, access to technology, particularly against the kind of context here at Viva Tech.
04:18I'm sure there's lots of people working on kind of the cutting edge of technology, pushing forward with what new
04:24is possible.
04:25But against that backdrop, there's still many people globally who are struggling with very basic connectivity issues,
04:31who may not have access to the Internet.
04:34And so how do we kind of square that circle, as it were, and bring those two things together?
04:40Are we prioritising the right innovations or are we just leaving people further behind?
04:46Minister, can I come to you first?
04:48What is the situation with access currently in Bangladesh?
04:51Is this a real priority for you?
04:53Tell us your position.
04:55Thank you for raising this very important issue, not only for Bangladesh, but also for the whole world.
05:01And if you talk about 15 years back in Bangladesh, our access to Internet penetration was very low.
05:10And from that position, now we have able to provide 130 million subscribers who are using Internet for their daily
05:20education,
05:21health services, and also for their employment issues.
05:26But I would say that a lot of discussions are happening on AI, quantum computing, all these cutting edge frontier
05:36technologies.
05:37But we need to also consider that if we are not able to provide reliable Internet access to this 2
05:46.5 billion people
05:47who are not getting access to Internet, that is going to be a really big issue for breaching the gap
05:56between the developed nation and the less developed countries.
06:00So in Bangladesh, Honourable Prime Minister Sheikha Sina, she declared her vision to build digital Bangladesh back in 2008.
06:09And since then, she decided to introduce all these digital technology-based government solutions could be provided by the digital
06:19service delivery centers at the village level.
06:21And she decided to employ one man and another woman entrepreneur who is going to provide digital services from those
06:32digital service delivery centers.
06:33By this way, we have actually able to set up 9,000 digital delivery centers.
06:39We introduced 52,000 websites.
06:43And near about 16,000 digital service entrepreneurs are providing 10 million services each every month.
06:52So these are the very, I would say, inclusive decision made by Honourable Prime Minister Sheikha Sina to reduce the
07:00gap between urban and rural areas, between men and women.
07:05At the same time, we have set up 13,000 computer labs in secondary, higher secondary levels.
07:11We introduced ICT as a mandatory subject from grade six.
07:16So this is how we are introducing all these inclusive technology-based solutions for the people.
07:22And now we are actually thinking to introduce generative AI for government service delivery.
07:29So we have decided to introduce our government brain, which is generative, pre-active and predictive adapters on education, health,
07:40investment, constitution.
07:42And we have involved our young entrepreneurs, innovators, to come up with this kind of innovative solutions.
07:51But I would suggest that all of our international organizations should come up with their resources.
07:58And technology should be universal to all of the countries and nations to the world.
08:04Because talent is universal, but opportunities are not.
08:08So our duty from the government side and the international organization to give that opportunities to all of our future
08:15generations.
08:16Great. So it sounds like you're sort of pointing to a need there to work at both ends.
08:20Like working on access and connectivity, but also working on generative AI and the latest tech trends.
08:26And Mario Grazia, we were talking earlier and you took issue with the framing of this question.
08:31And pointed out that it's maybe coming from a bit of a Western bias of how we in Europe or
08:36the US view the rest of the world.
08:39Actually, what was my point before we were discussing is really that continues to be very often the case that
08:45we have a vision that progress has steps.
08:47So unless you have accomplished the previous one, you cannot do the rest.
08:51Whereas what AI actually can do is help countries, especially developing countries, leapfrog.
08:57Because let me do a parallel. If you think about another of the big technologies that were discussed before is
09:03biotech, right?
09:04There has been a part in the last few years whereby there has been a massive investment in biotech.
09:10Now, biotechs are very expensive. I mean, a lab costs a lot of money.
09:14And then the materials and the safety protocols and all the rest of it.
09:17Think about how you can generate AI.
09:19You need basically a decent computer, decent access to data, decent access to the network, and people that are able
09:26to program.
09:26So in terms of entry costs, it's much lower.
09:29And in terms of the payoff this might give, it's actually very high because it's very pervasive.
09:34And I can do it in Bangladesh.
09:35And then we sell it everywhere in the world with very little transaction costs.
09:39So I think we have to change the narrative and think about these technologies as an opportunity.
09:45And, I mean, at UNESCO, one of our priority areas, for instance, is Africa.
09:49And by the time countries were discussing whether to adopt, that then was adopted in 2021, our recommendation on the
09:57ethics of artificial intelligence,
09:58there were other countries that, by the time we were saying, look, and this is fundamental also for Africa,
10:03they said, well, but, you know, Africa first needs, you know, to feed their people and they need this, that,
10:07and the other.
10:08And we were so proud to see African countries stand out and say, look, Africa knows what Africa needs, and
10:13Africa needs AI because AI can help us address a number of challenges,
10:18including, for instance, from the health to the food supply to actually the environment and taking care of the environment.
10:25So this is the way I would suggest to reframe in the conversation of what is needed and what for.
10:30And I think that's a great segue into, Charlotte, what you're doing with Amini.
10:34You're based in Nairobi, Kenya, and you're looking specifically at sort of environmental applications for AI.
10:39Is that right?
10:40What have you found and how does being based in Africa and Kenya maybe influence your decision making?
10:47Yes, so I think you said this right because you understand quite well the African market.
10:52Africa is really complex, especially when you're not familiar to this market.
10:57So for us, it was like we're going to change the narrative, we know the value of AI for Africa,
11:03we know how we can bring our AI solution in this space.
11:06So right now, we started focusing on the climate because climate is an odd topic, not just in Africa, but
11:11in the global world.
11:12But we have a lot of, let's say, worst cases happening in Africa right now.
11:17So there is a need, there is an urge to use data to have some actionable insight.
11:23That's why we're like, okay, let's build that solution from Africa and work with the people on that market.
11:28Because what sometimes the Western they miss is the fact that they built a lot of product based on assumption,
11:35right?
11:35With the way the line, what is happening.
11:37But there's a difference when you are on ground and you have to get access to data.
11:41It's quite hard.
11:42Not because you don't have data.
11:43We have data because people generate data, even if you go to see a farmer, whatever is doing, generate data.
11:49It's just like it's not maybe in the format that we can understand or even here we can understand, you
11:55know?
11:55So as now, I mean, what we do, we use our satellite data plus, let's say, data for something like
12:02IoT, drones, and we calibrate this data with ground data.
12:05We work with people on ground, startups, innovators, even like cooperatives, and we get this data and we calibrate.
12:12We ensure that this data is high quality and it can generate some insight because there is no need if
12:19you have a lot of data, but you can see the use, right?
12:22So we need to make sure that this data has some application.
12:24That's when we talk about the fact that we generate insight for farmers to improve their productivity.
12:30They know what is happening on the land, on the soil.
12:33At the same time, we also work with food and beverage companies because they source a lot of commodities from
12:39Africa, and they need to ensure that this commodity complying with, like, for instance, EODR for Cocoa Cafe.
12:45We help them to have that transparency.
12:47If maybe you are sourcing from a land that's devastated or not, you can have that understanding.
12:52And we have other large companies like insurance and banking that need to fill that financial exclusion.
12:59They need to be able to provide financial services for farmers.
13:02But for that, they need to have a better understanding about what is happening at the farm.
13:06And that's where we play because you have the right data that can help them as well build, let's say,
13:11a product prediction and create a scoring model for that farmers.
13:16So, where we stand is basically on the middle of the ecosystem.
13:20So, getting and ensuring that we have that data is available, is useful for any kind of third party that
13:27needs to process and generate some potential UKs for the African market.
13:31Thank you.
13:32That's great.
13:32And so, I think that shows, you know, it's not just about the technology.
13:35It's also about the applications that this tech is developed for.
13:38You know, we're hearing a lot about AI text generators, image generators, voice assistants.
13:44Are we perhaps prioritizing the wrong things?
13:48What should we be building?
13:50Does anyone have thoughts on that?
13:51Felicitas.
13:53Well, what should we be building?
13:55I think, to your question before, right?
13:57I mean, cutting-edge technology, of course, is super crucial and fundamental.
14:01And we cannot forget those communities that are underserved, especially those that are in rural areas and also the minoritized
14:10groups, right?
14:10If we think about our world population, according to the World Bank, about 40% of our world population cannot
14:17afford internet, right?
14:19About 850 million don't have a legal ID and about 1.4 billion are unbanked.
14:27So, there's a tremendous opportunity to serve those people from, especially, yeah, underserved communities and also our social responsibility.
14:36There's great, of course, economic opportunity behind that, but again, also social responsibility.
14:42And I think some of the innovations that have happened, but even a long time ago, Kenya is a great
14:46example, M-Pesa, you will know it better than me, where, you know, Safaricom and Vodafone use this mobile phone
14:53-based payment system for microfinancing and transferring money.
14:57I think that is groundbreaking.
14:582007, right, where developed countries like Germany are so behind, right, not even using cards in some shops, we have
15:08to pay cash.
15:09So, I think also our mindset needs to shift because I think innovation really comes from countries where the need
15:15is so high or from, yeah, various countries, right?
15:19That in various African countries, Asian countries has shown us already the way to go, also using, of course, in
15:26various Asian countries, QR codes as, you know, already established tool to transfer of instant money across borders also.
15:34So, I think that is something and I think some things at SumUp, of course, we try to do, I
15:39mean, 12 years ago, we were founded with a strong vision to help merchants thrive, right?
15:45So, to empower those and creating a business that they want to, but with giving them easy tools, so just
15:53a card reader that is, yeah, easy and affordable for them and not, you know, having massive financial backgrounds, right?
16:01So, building a world where everybody can build a thriving business.
16:04And, but of course, also, you mentioned there are many biases in our world that exist, especially looking at gender,
16:11looking at ethnic groups, age, disabilities and so on and so forth that I think we need to get right
16:18first because, yeah, it's a tremendous pool of talent and a tremendous economic opportunity there.
16:25May I make a comment?
16:26And, I think we should change the conversations, you put the question of, are we doing the right thing?
16:33And, this conversation is typically based on the type of technology we are discussing about.
16:37I think we have to change the conversation and switch it from which technology for what for?
16:44Putting humans at the centre.
16:45So, what do we want to achieve?
16:47What is the need we are trying to address?
16:49And, that will tell us immediately which perspective, I mean, which kind of thing to prefer.
16:54And, also, there has been this jargon all the time about responsible.
16:59Responsible is very good.
17:00Being responsible is a good thing.
17:01We all know.
17:02But, at UNESCO, we believe it's not sufficient.
17:05Let me do a parallel to another type of production.
17:08That is, for instance, shirts, right?
17:10Countries differ in the legislation they have in terms of the age, the entry age into the labour market.
17:16So, there are countries where younger people, younger kids, can work compared to other countries.
17:22Put the parallel back into the AI.
17:24So, what are we after?
17:26Are we after responsible?
17:28That means, insofar as I comply with the law, I'm fine.
17:30Or, are we after leveraging the bar because the effect that AI use, development, and deployment might have on our
17:38life is pervasive.
17:39And so, are we happy with knowing that a kid 10 years in another country is doing a shirt?
17:45Or, are we happy knowing that we can ensure that everybody around the world doesn't work in a sweatshop before
17:53a certain age, which is higher than that?
17:54That is what we typically have, for instance, in a country like this one.
17:58So, this is the switch between responsible and ethical.
18:01Ethical means also inclusive.
18:04Responsible doesn't necessarily mean that.
18:07It means no harm.
18:08But, it doesn't mean actively pursuing the decreasing of the inequalities.
18:14I think that's a really important point to make.
18:16And, speaking of inclusivity, who are we actually talking about when we're talking about underserved communities?
18:23Minister, you mentioned kind of there's a difference between urban and rural communities.
18:27Felicitas, you mentioned gender.
18:29Who is not being reached currently either as users of technology or as developers of technology that we need to
18:37bring more into this conversation?
18:40Minister, which communities are you prioritising on that front?
18:45I think there are huge investments that are coming into the frontier technologies.
18:53But, you know, billions of dollars are investing in AI, quantum computing, and different frontier technologies.
19:04But, I would consider those communities who are underprivileged, who live in remote areas like islands, river islands, hilly areas,
19:17some ethnic groups.
19:18So, those people should be considered as our target people.
19:25Maybe, with very small amount of money, we could give them access to internet.
19:32We can give them all the digital infrastructures.
19:36And, where we need to have a global consensus and where United Nations, UNESCO, they should come forward with the
19:47global AI governance or global universal access to internet.
19:52This kind of major primary requirements for all of the communities, for all of the citizens of the world.
20:00Because, I'm talking about this, because in Bangladesh, we took a very, very progressive initiative and strategies like bottom-up
20:11approach.
20:12We started digitising from the rural areas.
20:15Last year, we proposed before United Nations for zero digital divide by 2041,
20:20considering what are the basic technologies and tools you need to provide for the next generations,
20:28no matter which religious you are, from which religion you are, or from where, from which region you are.
20:38The main thing is to provide them the basic internet, because I consider access to internet as the basic needs.
20:47This is not a luxury service.
20:50This is a very necessary thing.
20:53And, also, I would like to share with you that we invested a huge amount of money from the government
21:02side
21:02and also created the business opportunities for the private sector.
21:06Like, we partnered with private entity and internet service providers to take fibre optical cable down to the village level.
21:14So, if there is a global fund or there is a global consensus, like how we are investing in environment
21:21and climate change issues,
21:23we should also consider AI as opportunity and also, at the same time, as a threat,
21:29like nuclear technologies and weapons actually created that huge vulnerability for the humanity.
21:38So, I think this is the right time to introduce AI global guidelines and also laws and strategies for each
21:48and every country.
21:48So, we are preparing our AI guidelines and laws for Bangladesh, what actually discussed here also,
21:55how we could create the opportunities for using data properly,
22:01and we should also focus on data privacy, security, localisation and data sovereignty.
22:07So, in Bangladesh, we have decided to introduce Personal Data Protection Act to also secure our citizens' data,
22:15at the same time, how we could utilise data for improving the decision-making process inside the government
22:22and also give the opportunity to the start-ups and private sector to introduce more and more business opportunities.
22:29I think these are the basic areas we should focus on from the government and international perspective.
22:34Sounds like you and Mario Grazia are on a similar page thinking about the global framing needed here,
22:39so maybe you two should talk after.
22:41What about from kind of an individual company perspective or organisation perspective?
22:46You know, what can you do at Amini or at SumUp to try and address some of these inequalities and
22:53include more people?
22:55Yes, so, let's start from in Africa, actually, in terms of underserved people.
23:00The group is quite well-defined.
23:01We have women, because there's a cultural norm, and right now, when you want to have even some kind of
23:07developing solution for women,
23:09it's hard because there is no historical data, there is not enough historical data about women.
23:13Because for a long time, there's been a screen there, there's a lot of stuff that we're doing, so it's
23:17hard to get access to that.
23:18And we have also a lot of people living in remote areas, so real people, and it's quite hard to
23:24even rush out to them.
23:26If you build a solution, how are you going to rush to make sure that they have access to your
23:30product?
23:30That's quite one of the challenges.
23:32And so far, we have been thinking about, you know, how to ensure that they get some kind of standard,
23:39I mean, let's say low devices, power internet kind of,
23:43because it's not everywhere you see that we have internet coverage, and these people are excluded.
23:49It's not even up to the company, it's excluded based on society, right?
23:53They are living far.
23:53And we have as well people that live in urban areas, there is internet coverage, but they can't afford any
24:00internet bond, but they can't pay for that.
24:02So in terms of, let's say, financial accessibility, it's quite hard for them to pay for what we provide.
24:08And we have other people where it's basically in terms of tech, let's say tech literacy, they're not really tech
24:15savvy.
24:15So even if you build a tech driving data product, it's quite hard for them to use.
24:20So for us as a company, when we are building our solution, we need to ensure that we're able to
24:24make sure that these people, they can get access to what we provide.
24:27One example is farmers.
24:29We are working with farmers, right?
24:31We know that a lot of farmers, sometimes they're not tech savvy, right?
24:34So we use cooperatives, because they are grouped into cooperatives, and we use some kind of partnership with telco companies
24:41to rush out to them with USD, IVF.
24:44So it's dependent on what we are looking at, to make sure that they're able to get the information.
24:48What they need is the information.
24:50They need to know what they do tomorrow.
24:51They don't need to know what is happening on the, let's say, in your code, in your model.
24:55They don't care about that.
24:56What they need is like, tomorrow is going to rain?
24:59Tomorrow, I'm thinking about when I'm going to invest, right?
25:02When I'm going to be sure that I can bring my product on the market and be paid.
25:05They're looking for information.
25:06And when we work, we generate that information, and we look for the easy way, traditional way, to share this
25:12information to them.
25:13And they get access, they apply, and actually monitor this over time.
25:16Yeah.
25:17That's one of the examples.
25:18Well, at SumUp, we have two approaches, right?
25:21One within SumUp, and one looking at the societies that we live in globally.
25:26Let me start maybe with the SumUp perspective.
25:29So, we definitely try to focus or focus on women, because we see there is the biggest back gap between
25:35the representation globally and our representation and leadership positions.
25:38Having said that, we, of course, also speak about topics like neurodiversity, autism, ADHD, because it's often stigmatized and unspoken,
25:49right?
25:49We speak about domestic violence and views, which can also impact women in their career progression.
25:54We speak about racism at work, super important, very untouched topic as well.
26:00But also, in our inclusive leadership workshops, we speak about privilege that many people don't like to speak about, but
26:05it's about recognizing it and using the privilege.
26:07And also, microaggressions that happen daily, for example, right?
26:12And what you can do to be a better leader.
26:16And today, actually, later on, we will speak for the first time about religion.
26:20That's also a very sensitive topic, right?
26:21So, we try to include everybody in the conversation, from disability, gender, and mental health also, right?
26:28We offer our people psychological support, because people are also traumatized from their upbringing partially.
26:34And one dimension that we haven't really spoke about, because it's also the smallest community, I believe, and in some
26:40countries, I'm aware of it, it's illegal to identify as transgender, for example.
26:45But this is actually the most vulnerable group, so we have about 2% representation.
26:51And why it's so important to focus on that, because they are the most vulnerable ones, right?
26:56Once outed, they lose often family, friends, jobs, and they have nothing left, but either living on the street, being
27:04homeless, or needing to enter the prostitution industry.
27:08So, we also touch on that topic.
27:10So, we look at embedding D&I throughout the whole life cycle, from hiring, where we're looking for talents, how
27:16can we diversify that,
27:17and how can we really embed D&I also in the recruiting process, in educating our people, why it's so
27:24important, why it matters, and then also, yeah, to compensation, and so on and so forth.
27:29That's internally, I'd sum up.
27:31And then, externally, we focus a lot on education, tech education for unemployed and underemployed youth.
27:37In Brazil, Chile, Colombia, for example, we collaborate with an NGO that gives tech education, Java, full stack, and 80
27:46% then will find employment.
27:47And we make it very clear that we want to double down on girls, because we see that also globally
27:52still, it's only 26 or so percent that graduate in those computer science courses.
27:59So, we know there's a massive gap, so we double down on that, but also on different dimensions, like LGBTQ
28:06+, migrants, black community, so we always look at the census.
28:10And one thing I'm super happy also about, we collaborate with Dharma Life, for example, an NGO in India, that
28:17focuses on tech education for kids, with, you know, English, math, basic coding.
28:22And we reach 10,000 kids per year, and also empower female entrepreneurs, reaching about 500 entrepreneurs a year.
28:30I think the program has reached over 23,000 or so women, who have created 11,000 businesses.
28:38So, really empowering them, right, with giving them the skills, digital literacy, entrepreneurship skills that is sustainable also, and, yeah,
28:48that can create a better world for the future.
28:51If I may just respond to the request by the minister, I mean, I cannot left that at intended.
28:56Actually, minister, if I were the genius of the lamp, you would have two desires left, because we do have
29:01a normative instrument that is the recommendation on the ethics of artificial intelligence,
29:05which is an instrument that actually aims to set, to level the playing field.
29:10So, it has been adopted by 193 member states at that point, now it's 194 member states.
29:15So, it can really represent the basis with its 12 areas of policy, exactly what you were mentioning, from privacy
29:22to data, to education, to inclusion.
29:25And actually, very proudly, the member states of UNESCO asked us to put separately, and very well highlighted, the gender
29:33component and the ecosystem flourishing.
29:35And in response to that, so in addition to propose and foster a number of policies in that direction, UNESCO
29:42has created a group of women, which is called Women for Ethical AI.
29:45They are experts in AI on many fields, ranging from, you know, the techies, to the lawyers, to the business
29:52people.
29:52The idea being, not only to foster better inclusion and better accounting for the need of basically half of the
29:59world population, that is women, in AI and for AI,
30:05but actually to leverage what women can contribute to the rest of the world, any other gender, you put it
30:09perfectly, it's really about any gender whatsoever.
30:12The reason is as following, and I think too often we underestimate what diversity, also linguistic, for instance,
30:19the preservation of the languages, avoiding that the internet and AI are actually dominated by only a few languages.
30:26It's because any of you, I'm sure, talking more than one language, know what it takes to speak correctly another
30:32language.
30:33That is, you can't simply translate. It's a mindset. It's a framing that kicks in.
30:38Now, imagine the wealth of abilities that having those different mindsets can bring into AI.
30:45that this is not programmed only, I'm Italian, according to an Italian mindset.
30:49It's programmed according to any of the thousand languages that exist in the world with their mindset.
30:55So, this is wealth that goes into the system, which then can create more powerful application for the good of
31:01society.
31:02I would like to add to this, because if you have inclusive initiatives in the government process,
31:12and you have the mindset to include all the gender and the races and all these places,
31:20places, so that you can do really amazing things, I would like to share a few projects and initiatives already
31:28executed and done by the government of Bangladesh.
31:31So, we introduced Harpower project, exclusively for the women, and it was five months' training on different IT fields,
31:41like website development, digital marketing, e-commerce, call center agent.
31:46A very low and primary level training for five months, and one month's internship and mentorship.
31:53Then we give them one laptop, one computer.
31:55And under this Harpower project, we have successfully done 25,000 trainings.
32:01And after having this success example, now we are taking a new project that is smart entrepreneurship and employment development
32:10project, SEED.
32:12So, under that project, we have a target to also create 200,000 employment for the young generation.
32:19And you would be very happy to know that within just 10 years of time, we have been able to
32:24develop 700,000 IT individual freelancers
32:28who are earning more than a billion dollars from different online marketplaces.
32:32And in IT and ITS sector, we have been able to provide 2 million jobs, and we are exporting 2
32:39billion dollars.
32:41And I think including telecom and ICT sector, we have been able to provide 3 million jobs.
32:49And now we are planning to reskill and upskill all of our university students because we are having 100,000
32:58IT ITS engineers every year from 150 universities.
33:03So, under that age project, we are developing our human resources, we are getting them ready for the industry on
33:13AI, blockchain, and machine learning, data analytics,
33:17because these are the basic things.
33:20If you are not actually able to provide this kind of training for the students, they will be irrelevant for
33:25the industry.
33:26So, I think this is the right time to talk about the policy from the government sector.
33:31At the same time, we need to focus about how we could create the knowledge ecosystem so that our future
33:37generation should be more creative, innovative, and problem-solving generation.
33:44So, Honorable Prime Minister Sheikh Hasina declared her new vision to build Smart Bangladesh under four pillars.
33:50I would like to just share that four pillars are smart citizen, economy, government, and society.
33:57So, under these four pillars, we have considered all those inclusive strategies so that no one should be left behind.
34:07And I 100% agree, Honorable Minister, with the approach of really investing in the future generation and the youth.
34:14Having said that, I would love to encourage all of us to also think about the aging population, right?
34:19And even 45 plus is not so far away from myself personally, because I would think many biases do play
34:26out.
34:27We believe that the older generation, which is not so old anymore, are not so tech-savvy and so on,
34:34which is, of course, there are many biases that also play out there.
34:36And there is, I mean, I think some research shows that about 40% of the people in the most
34:43developed countries will become 105 or 100 plus years old.
34:47And the global pension aid virus is about between 55 or 70 years old.
34:52The question I have is here, who covers for the 30, 40 years that people then don't work, right?
34:58So, there's a tremendous financial exclusion challenge that is approaching up.
35:05And I think also countries, companies, societies don't really speak about this yet,
35:09because it is a tremendous problem that we are facing, including also with the inflation and so on.
35:16So, I think also, yeah, we need to really educate also and give people that are like 50 plus, let's
35:21say, right?
35:22A chance to enter or re-enter the job market.
35:26Sometimes we're even targeted with voluntary levers program of companies, right?
35:31Because they're getting too expensive.
35:32So, that's really our responsibility as well here.
35:35I think that's a great point.
35:36And ageism often gets left out of discussions on diversity and inclusion.
35:40It's sort of invisibilized or forgotten about.
35:43So, I'm really glad you brought that up.
35:45Rio, Gracia, I wanted to dig into what you were saying earlier about the importance of mindset.
35:51And we were speaking just before this session, and you were saying, you know,
35:54the problem is companies develop their products, they develop their technologies,
35:58and then they start thinking about inclusion.
36:01And it's kind of too late then.
36:04It might be too late in the sense that, I mean, very often there is a bit of a false
36:08myth in my mind
36:09that is like once the AI is out, we can't do very much.
36:11This is not true.
36:12So, you can actually create a system, brother, call it as you want,
36:16algorithm that checks on the first algorithm, so things can be done.
36:18And by the time you program, you can indeed embed in the program some checkpoints.
36:24So, a first, you know, golden rule should be really to try to check on the data you're using for
36:29the purpose.
36:29But unfortunately, that is not often the case.
36:32And this is not done for a bad reason.
36:34It's just because it hasn't been part of the mindset of the programmers, for instance.
36:39By the time you go to university and you're taught how to code,
36:42very often what they tell you is how to have the run perform in a certain way,
36:47the amount of data you need, and having it done faster is better.
36:52Nobody ever tells you, have you checked the data you're using for the purpose?
36:56Now, this is really the basic thing that everybody in computing should learn
36:59in order to ensure that it doesn't lead to inequalities, to discrimination.
37:05because, for instance, because then it really leads to very, very bad results.
37:11Think about the health applications, right?
37:13If the sample underneath is not representative of the population you're targeting
37:17in terms of delivering your support system, decision support system,
37:22what might happen is that what you're suggesting is completely wrong.
37:26So, whatever illness might be undetected or you may create alarm.
37:31The other thing is really awareness about the systems and the fact that we can't always think
37:37to fix things as possible.
37:39Let's think about all the typical literature about economic growth and development.
37:45The mantra has been, let's first create the wealth, right?
37:48And then we will think how to redistribute that.
37:50Well, why don't we shift the conversation in such a way as to discuss it and put the seeds
37:57so that it is automatically redistributed and you hinted at a very, very important issue
38:02that we have just marginally touched upon now, that is the labor market.
38:06That is, like, very often I'm asked, aren't you afraid of generative AI that will take your job?
38:11Frankly, no.
38:12Not because I think I'm too cool, but because I think I wouldn't mind working less.
38:16The question is instead, by the time there are the gains from this technology,
38:22who does benefit from them?
38:25So it cannot accrue to the owner of the technology, it should accrue also to the workers.
38:29So I have no problem in seeing myself in a few years from now only working two hours a day
38:34on average
38:34and the rest of the machines doing it for me insofar as the redistribution of what comes out of that
38:40two-hour contribution to the production system is redistributed with the workers.
38:45And then we can do a lot of societal activities and increase our arts, our culture,
38:51because this is actually the fundamentals of what enables a good development of a technology.
38:56Yes.
38:57Yeah, I really like what you said because it's a mindset.
39:00And I'm sure that we all know right now that basically all these biases we're mentioning
39:06is a reflect on our societal bias, right?
39:08As you remember, what we think, that's how we build the solution.
39:11And there is a need to encourage, like, developer, builders to think problem-solving first,
39:17then find a way to make sure that people are really included.
39:20For instance, at Amini, if you check the team, we are really from Africa, right?
39:24We, or most of us, we have been working on the African market, we understand the market.
39:28So because Africa has been one of the first targets in terms of biases, not voluntarily, but it's happened,
39:34so we can't miss that point.
39:36So there is a need for us to ensure that even the data even is really diverse, right?
39:42When I'm speaking about data, right now we focus on environmental data,
39:45but in terms of variety of data we have, we're not just focused on collecting soil data from farmers.
39:50No, we have soil, we have weather, we have forests, we have different data from different markets
39:55because what we then notice while working is, like, in Africa and the other part of the global south,
40:01we face similar challenges, and what we are building in Africa can be also used for somewhere else
40:05because we learn from the market, right?
40:07So right now we have some ongoing work at Barbados for climate change as well,
40:11and we notice a lot of learning that we are planning for Africa.
40:14So there is a need to understand the market we are working on,
40:17and also put some standards, internal standards in terms of ethical and sustainability,
40:21also outside what is happening.
40:23What are my solutions facing the user, right?
40:26Who is the user?
40:26Who is the target?
40:27Is the solution accessible enough?
40:30So there are so many questions we have to ask ourselves,
40:32and ensure that we don't fail, you know,
40:34as African solver, we don't fail on that because we can't keep being beyond
40:39because we allow Western people or Western organizations to build solutions that are not representative enough.
40:46So we have to stand for ourselves, we have to build solutions, we have the resources,
40:49and we are still, you know, the market is still quite, let's say, complex,
40:54but there is a lot of ongoing work,
40:56and if we put different stakeholders involved, it's going to change.
40:59And for instance, our work as well of the African Union EU Continental Strategy,
41:04and it was basically around that, how to ensure that in terms of AI,
41:08how AI is deployed on different African countries, how can we learn from different countries?
41:12Because in Africa, we have a lot of countries, right?
41:14So if maybe we look at South Africa, we look at Indonesia, for instance,
41:19there is a different gap in terms of progress of development,
41:21but we can learn from each other, we can support each other.
41:23So there is a need, there is a way to collaborate,
41:25and to make sure that whatever we are building for our people is actually solving a problem we are facing,
41:33but it also can be extended on different markets, yeah.
41:36So that's what we have been doing at Amini, and hopefully in the next, let's say, five years,
41:41we see a lot of solutions being developed for the African market,
41:44because we have data, we have data, we have quality data, comprehensive data,
41:49so people could use that and solve the real problem we are facing.
41:53Thank you.
41:54A bit of a call to arms there for anyone thinking about developing similar AI initiatives, I think.
41:59We have literally one minute, just over one minute left,
42:02so does anyone have a really quick question?
42:04I did say I'd open it up, so I'm giving you a chance.
42:06We have one down the front here.
42:08Do we have a microphone for this gentleman?
42:14Thank you very much for this attack.
42:15Thank you.
42:16So my name is Shah Rukh, I'm the managing director of Bondstein.
42:19So I had a question regarding digital inclusion in the context of misinformation.
42:23So we have recently seen that in different parts of the world,
42:26there are a lot of riots and activities going on regarding the spread of misinformation, right?
42:32So how do you think the digital inclusion is going to handle the context of misinformation spreading out in the
42:38world?
42:38So that was one particular question.
42:40Thank you.
42:40Great question.
42:42Thank you, Shah Rukh, for your very timely and important question.
42:47I just last week, one of our startups from Bangladesh, they actually presented me, my digital avatar to me,
42:57and who could actually speak like me, who could look like me, but it's not me.
43:02So this is how actually deep tech companies are creating more opportunities for AI developers,
43:10at the same time creating really serious threat.
43:15So I would say that we should focus security by design, any of our products.
43:21We should have a general universal guidelines on AI or machine learning or data analytics.
43:30Otherwise, it's really difficult to differentiate between real and the fake.
43:37So I would suggest to all of the government and the international organizations to consider it's a security threat
43:48for the global security perspective.
43:53At the same time, beside training and regulatory framework and investing in access to internet,
44:03we should also focus on research and innovation in the educational field.
44:09So I have seen in the young startups and innovators, they are coming with really fantastic solutions.
44:18If we could actually accommodate them, if we could actually give them proper funding and proper financing support,
44:27then they could actually resolve all the problems.
44:29But we should promote and encourage and focus security by design so that whatever we are creating,
44:38like digital public infrastructures or verification authentication systems or creating AI tools,
44:46we should focus and be serious about the security threat.
44:50Thank you.
44:51Thank you very much.
44:52I'm afraid I am going to have to end us there because we are over time.
44:55But thank you, everyone, so much for joining us.
44:57There will be another session starting very soon.
45:00Thank you to all of our panelists.
45:02Thanks so much for your comments.
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