




Laurent: So I’ll start with this quote. I don’t know if you all know who Jeffrey Sachs is but he’s probably one of the top three development economists in the world. And he said this about three or four years ago. That the mobile phone really is, according to him, the most transformative technology for development. Now to a certain extent, some people would agree with him, some people don’t. But my interest is in looking a little bit about at whether this is actually the case and what we’ve found out about how ICTs and notably the mobile phone have transformed developing countries and how it’s made a difference to people in the developing worlds in terms of their health, their education, their livelihoods, whatever.

This stuff, I assume you all know already. You may have already actually had a presentation or something that was broader, that explained the extent to which the mobile revolution has been absolutely incredible. It has surpassed any other kind of technology in…globally, in terms of how fast it has reached such a large amount of people. You’ve probably already seen something like this. Mobile phones actually reach about 6 billion people, around 75% of the population. For sticklers on stats around these things, you know, these are debatable numbers. But we don’t have to get into that here but I’m happy to get into that debate. The key numbers that could be of interest to you are that essentially in 2000, developing countries were the minority. Twenty-nine percent of people had access to mobile phones. Then 2010, by far the majority. Seventy-seven percent of mobile phone owners were from the developing worlds.

So what have we learned about the socioeconomic impacts of ICTs? That’s essentially the title of the overall conference, so I’m quite happy that we get to share some of our findings. So let’s look at who uses these technologies, why, then we’ll look at the evidence of impact in various development areas, what are some current issues we’re focused on, and then maybe some conclusions if I have time.

So we’ve funded a lot of surveys, household surveys, on the way in which, especially the poor, the people at the bottom of the pyramid, use ICTs or use mobile phones. In Asia, this is some of the results. If you look at the BOP, the bottom of the pyramid–so these are people who, depending on the definition but generally they make less than a $1 to a $1.25 a day–these are the percentages of access to mobile phones. Pretty incredible. That means that they have reached all segments of society. This is not just the middle class, this is not just the upper class. It now reaches every segment of society.

That’s extremely important for people who, maybe amongst you, are trying to create applications or thinking about who they could reach and what segments of the population they might be able to reach. Second, here is some data on how much they spend. So again, this is the poor. These are people who usually make less than a $1, a $1.50 a day. This is how much they’re spending. But it’s 3 to 6% of their income on this technology. That’s enormous. That’s way more than what we spend on it. Way more. There’s obviously a reason for that. That’s extremely important. That means they feel a need and a desire to be spending this much on this technology. Again, that’s extremely important. They have found interesting uses, important uses for that technology.

And I know I don’t have figures for Africa here but they’re quite comparable. They’re actually higher. In Africa, they’re closer to 10% of people’s income. Why do they use it? So basically five is the highest, zero is the lowest. This is why they’re using it. Essentially the top reason, interestingly enough, is the ability to act in an emergency. This shows the importance for these people of the mobile phone–or the technology in general, information technology–the importance of that tool as a tool to be a lifeline. As a tool that helps you when you’re in need, as a tool that helps you when you are geographically displaced, as a tool that helps you keep in touch with family and friends when it’s very difficult to keep in touch with family and friends. So that’s their top reason. Acting in an emergency.

After that, no surprise, family, and social relations. Basically talking to your friends and family. The lowest, interestingly, is the ability to earn and save. Which…I mean, for people who work in development that’s a bit problematic because we keep on having this hypothesis that says the reason that people use this technology is because they have an instrumental need to use it, i.e. they make more money or something like that. And yet the data says something different.

However, there’s a lot of debate about that as to whether actually the family and social relations element and ability to earn and save are actually pretty much intertwined. That they’re the same, essentially. Because in developing countries quite often your social network is also your earning network and it’s also your saving network. It’s a financial network as well. So those things are actually probably, should be, disabrogated.

So what’s the impact on economic growth in general? This is a map that we produced that basically shows GDP per capita. So the darker the image, the poorer the region. And the lighter the image, the richer the region. And then you’ll see these bigger circles or smaller circles. And that’s an indicator of ICT access that we came up with, us and a few partners, that essentially says the bigger the circle, the more access they have, okay? So you’ll notice–it may be hard to tell–but you’ll notice that essentially very small circles here and very big circles there. So essentially it looks like there’s a correlation between the countries where you have, that are poorer have less access and vice versa.

That seems fairly self-evident but I can assure you there are tomes and tomes of research written on why that is and how that is. The most interesting thing is to think about whether or not–and I’ll have to go back there in a second–whether it’s because you, country is poor that it doesn’t have much access or whether it’s because they don’t have much access that they’re poor. It’s a causal relationship thing that people are really interested in. And because if we’re able to demonstrate that people who get access become less poor, i.e. get richer, then all of a sudden the power and the importance of the technology is that much greater. And here’s what some of the research says.

In Kenya, ICTs and mobiles were responsible for 25% of the GDP in the last 10 years. That’s quite impressive. In Peru, a control group study, so this is a study where you take one community with access to the internet in this case and another community that didn’t have access to the internet, they found that the community that had access to the internet was 19% richer after three, four years. More importantly, a study that we did in East Africa, [inaudible 00:08:26] support in East Africa showed that same thing. Control group study with a community that had access to, at that time, mobile phones, another that did not. We went there in 2007, went back in 2010, studied their economic situation.

And they found that they spent, the community that had access to the ICTs spent $21 more. Might not seem like much but for those communities that’s huge. But second, why is spending important? Because the assumption is that that is an indicator telling you that they actually earned more. They’re able to spend more, it’s because they have more. So essentially that is a very good finding in terms of understanding the power or the influence and importance of this technology for reducing poverty and getting people out of poverty.

Now, what about agriculture? This is…these are actually friends in Senegal who are looking at a mobile phone. And they’re looking at the agricultural, the price, sorry, of tomatoes and…I think it was cucumbers. And so those two other people are farmers. And essentially they are part of a project that looked at whether access to the price of, at that time, tomatoes and cucumbers in a market, the direct access to that pricing, helped the farmers’ situation.

What they found…so here, in a nutshell, is how it worked. You had…so this guy was part of an NGO that hired somebody to go to the market and three times a day put the price of tomatoes and cucumbers into an online database. Then anytime those farmers were out in rural regions could get access to that pricing. Seems pretty self-evident to us now, that kind of thing should exist, right?

The incredible thing is that up until then, there was only one person who actually had access to that price information. It was the intermediary. Is anybody Senegalese here? Ah. So with, [foreign language 00:10:51] who would go and of course go to the farmer and he had access to that price information. So he would go to the farmer and he would negotiate the price of tomatoes and cucumbers. And so he had that power of information. The farmer did not. So he could negotiate, the intermediary could negotiate how he wanted.

So with this system, all of the sudden, the intermediary is not the only one with that information. The farmer does too. So as you would expect, the amount of income and revenue that the farmer could make went up astronomically, actually. On average, they made about $200 more a month, the farmers that used this system. Now what I love telling about this story is…well one, the other interesting thing is that some of these farmers for the first time in their life after having used this system made enough money that they could go on holiday. They had never been on holiday before. But second, when do you think this happened?

Woman: 2008?

Laurent: 1998. It was a system that we supported in 1998. So these are not new systems. These have been going on for a while. So as some of you might be interested in these apps and creating these kinds of apps, realize that actually these kinds of apps have been around for a very long time. There’s a lot you can learn from what’s been going on.

So this essentially, for those who are interested in kind of understanding this whole issue of price information, agricultural price information, this is actually something that I might skip. But if you’re interested, I’d be quite happy to talk to you about it. But essentially it’s about how much money can be saved on an agricultural value chain, regarding any kind of product. If you say tomatoes or whatever, you could save up to 15% because they’ve measured…sorry, up to 12% because they’ve measured that 70% of the cost, transaction cost of any good, is linked to information. So if you improve the information value chain in any kind of good, you actually can play with about 70%, sorry, 12% of the cost of that good. Which is pretty important when you think about things like tomatoes, cucumbers, which have very small margins.

So that’s just saying what I said. Health. Health is probably the area where ICTs have made the most positive difference. It’s really quite impressive. Most, not most but a lot of the projects that we’ve supported have shown quite impressive impacts in the area of health, mostly in the area of what you call demographic surveillance. So what is that, demographic surveillance? That’s essentially where the government of say, Benin, is able to go to the rural areas and know how many people in a village has malaria, how many people have TB, and how many have AIDS. Why is that important? Because they need to send them the appropriate amount of medicine.

Pre-internet or pre-ICTs, this was all done through paper. They would send somebody out to a village and start counting people and put it all on paper. It would take weeks if not months. Huge errors. Huge errors. So villages would get way too much antimalarials and not enough AIDS antiretrovirals. That’s a huge, for…all of us know, these are governments that don’t have big health budgets. So those kinds of errors are enormous.

So what kind of projects were done? Well essentially, digitizing that whole process. You get somebody who is able to come into a village, transcribe that information in real time, on a mobile or whatever. But generally with mobiles have been most effective. Government gets the information right away. Error rates were reduced by about 10 to 20% percent. But on top of that, the main kind of interesting outcome was that government saved millions of dollars. And we were able to prove that. We did a cost-benefit study that helped us see that in the case of Uganda the government saved almost $50 million by using the system. Or could save up to $50 million.

Education. We talked a little bit about this in the other one. But the weird thing is that the last presentation talked about education like from a formal internet side of things. What about mobiles? I mean most people are using mobiles. Is there any role for a mobile in the education system. Are there any apps that could help out? Yeah. Incredibly, yes.

We did a study in the Philippines where students, two groups of students, students who just went to a class normally and another group of students that had access to their course and tests through their mobile phones. Incredibly, the ones who used the mobile phones, their test scores were five points higher than the ones who didn’t. And on top of that when asked–because there was a cost associated. They had to pay for the text messages, they had to pay for those things–when asked whether that cost, they would bear that cost, they said, “Yes. We think it’s worth it.”

So a pretty incredible kind of study. I definitely did not think we would come up with that kind of research finding. I thought it was pretty far-fetched to think mobiles would have any kind of importance in the education sector but it seems that it does. Governance and digital activism. I could talk about this for hours but I won’t because my time is running out. But if you’re interested, please talk to me.

New issues. Open data. I don’t know if any of the talks are actually about open data and openness but this is definitely something that everybody is talking about. I assume you all know what it is. It’s basically the release of information through open, reusable means. And generally, it’s seen as a very positive thing. Definitely, the World Bank is very interested in this issue. Some of you may have been involved in Hackathons or Codefests or what kind of thing. It has been the flavor of the month for the past say three to five years, so those are a lot of months. And there’s some exciting things that can be done with that. But, few words of warning. They’re not always as good as we hope they’ll be.

Some of the research that we supported in India showed that actually when you digitize something like land records, what happens? Well all of the sudden, rich people, real estate tycoons, bought up land that was not owned. And why was it not owned? Because squatters were there. And so what happened is that they bought up this land and then they kicked out the squatters. From a development perspective, that’s not exactly the outcome we’re looking for necessarily. So whenever thinking about these apps, always think about the other potential, unintended consequences.

Second, crowdsourcing. I assume you’ve all heard about Ushahidi. It is probably one of the most impressive innovations in Africa in this space. Kenya is now one of the global leaders in the technology industry, in large part because of iHub, which is linked to Shahidi, but also because of Ushahidi. Because they made crowdsourcing a very African thing. And that’s quite impressive. The only thing is, we don’t know much about what the impact of crowdsourcing is on development. Right? We don’t know how it’s actually making a difference from a research point of view. And I’ll have to speed through some of these things. So to finish up, I mean, I’ve told you a lot about the positive impact. But it’s not all good news, definitely not.

The internet, which of course is, you could say is of more interest to us than mobiles, especially coming from Canada, some of you are interested in this, the app ecosystem or open data or crowdsourcing, the internet is a pretty fundamental part of that. And yet, the internet is largely unaffordable to most people in Africa. Even though access rates have gone up tremendously, you’re still talking about 5 to 10% of the population having access. Second, amongst the poor, so the vast majority of the population, they have no idea what the internet is. All right? So you still have a long way to go when it comes to that.

Second, as I said, there are a lot of [inaudible 00:20:32] projects and there are a lot of apps for development type activities. There are a couple of thousand, I think, Ushahidi deployments, so crowdsourcing platforms for various things. The vast, vast, vast majority never get used. Never. They’re just created by people and they don’t get used. Now that’s fine in a context where most of those apps are actually created by people who just are in their garage or living room and want to make something fun and that might help, that’s fine. But if this funded by a government or the private sector or something like that, then that’s more problematic. And as I said, there’s a lot to learn about how to do this type of technology project well and how to do it badly. There are a lot of negative examples of doing this. So I’ll end with that and I’d be happy to answer any other questions.