One of the key features of the African digital renaissance is that it is increasingly home grown. In other sectors of the African economy, such as mining or agribusiness, much of the know-how is imported and the wealth extracted. But Africa’s 700 million or so mobile subscribers use services that are provided locally, and they are also downloading more applications that are developed locally.
The sharing economy has been around for a long time. But recent technological advances like the development of real-time transactions through smartphones and credit cards have taken the potential of the shared economy to a whole new level, and opened the door for substantial changes in the way we think about urban mobility.
Recently, I was invited to join a panel on the sharing economy moderated by Prof. Susan Shaheen at UC Berkeley, focusing more specifically on shared mobility.
The panel acknowledged that shared mobility is already transforming the mobility landscape globally, but could go a lot further in increasing the sustainability of urban mobility systems. The panel identified a number of key research gaps that we need to pay close attention to if we want to create a policy environment that is conducive to mobility innovations. Three that I want to highlight are:
Supporting open data and open-source ecosystems is critical considering the tremendous potential of open-source software and data-sharing for improving transport planning, facilitating management and providing a better experience for transport users (for more detail, please see my previous blog on how the transport sector in Mexico is being transformed by open data)
Looking into shared-economy solutions for those at the bottom of the pyramid – solutions that don’t require credit cards and smartphones as prerequisites (see this blog on the bike-share system in Buenos Aires for a good example)
The world of driverless cars is coming – which, depending on how policy responds to it, could spell really good or really bad news for the environment: if such technology is used primarily in shared mobility scenarios, it could greatly reduce the environmental cost of motorized transport; on the other hand, the possibility of “empty trips” with zero-occupancy cars could exacerbate the worst elements of automobility (see Robin Chase’s blog in The Atlantic Cities for a great discussion on this). That is why it is critical to create a policy environment that appropriately prices the ‘bads’ of congestion, accidents and emissions while steering the world of driverless cars towards sharing and resource conservation.
As part of my job at the World Bank helping to advise governments on what works, and what doesn't, related to the use of new technologies in education around the world, especially in middle- and low-income countries, I spend a fair amount of time trying to track down information about projects -- sometimes quite large in scale and invariably described as 'innovative' in some way -- that were announced with much fanfare which received a great deal of press attention, but about which very little information is subsequently made widely available.
Most of these projects prominently featured some new type of technology gear, whether low cost laptops for students or new ways to connect people in remote places to the Internet or low-power e-reader devices. Other projects featured new software (English learning apps for phones! Free science curricula for teachers! A learning management system that enables personalized learning!). A sub-set of these projects -- the really ambitious and 'visionary' ones -- combined both hardware and software, and a variety of services to support their introduction and use.
I do this follow up for two very basic reasons:
(1) I am generally interested in learning from these sorts of projects, wherever they may be happening; and
(2) I am asked about them a lot.
These conversations generally go one of two ways:
"Whatever happened to that project in [fill in country name] -- how are things going there these days?"
"Things are proceeding [well / not so well], and a bit more slowly than originally envisioned. Here's what you need to know ..."
"Can you give me an update on the exciting stuff that is happening with computers in schools in ___?"
"You mean the ___ project? Actually, that never actually happened." "No, that's not true, I read that ---"
"Yes, you probably did read that. You may well have heard about it during a presentation by [insert name of vendor] as well. But I assure you: I talk regularly with [the ministry of education / companies / NGOs / researchers] there: Nothing actually happened there related to this stuff in the past, and nothing is happening there related to this stuff now. Will something happen there in the future? Undoubtedly something will ... perhaps even something as potentially 'transformative' as was promised ... although whether it happens in the way it was originally marketed or advertised: Your guess is as good as mine."
In retrospect, the rather short half-life of an unfortunate number of such aborted projects can largely be measured not by things actually implemented 'on the ground', but rather by PowerPoint presentations and press releases. (A rather charitable characterization of what happened in some such cases, but one that is not always or necessarily more accurate, might be that people were 'overly optimistic' or that someone or some group 'was simply ahead of her/their time'. Technology folks sometimes just dismiss such efforts as 'vaporware'.)
When it comes to educational technology projects, most of the press attention tends to come when new initiatives of these sorts are announced, with some momentum continuing on for awhile in the early days of a project, especially when, for example, kids get new tablets for the first time, an occasion that presents a nice, and ready-made, photo opportunity (not that such things are ever conceived of as photo opportunities, of course!). Then, often: Silence.
Projects that do get implemented, and last for awhile, tend eventually to be crowded out of the popular consciousness by the latest and greatest new (new!) thing -- and, when it comes to the use of technology in education, one thing can be certain:
There is always a next new (new!) thing.
(In addition to lots of press attention, the well-known One Laptop Per Child project was the subject of many papers and presentations from academics in the early days that were largely speculative -- e.g. here's what could happen -- and theoretical -- e.g. here's a pedagogical approach whose time has come. Only recently have we started to see more deliberative, rigorous academic work looking at actual implementation models, and what has happened as a result.)
For me, the most interesting part of the use of technology in education isn't the planning for it (although I spend a lot of time helping people who do that sort of thing) nor the evaluation of the impact of such use (I spend a lot of time on that stuff as well).
The most interesting part is implementation -- because it's so messy; because a fidelity to certain theoretical constructs and models often comes into rude collision with reality; because that's where you really *learn* about what works, and what doesn't, and what impact the whole enterprise may be having. How are kids, and teachers, actually using the stuff? What unexpected problems are people having -- and how are they being addressed? What is changing or happening that is interesting or surprising that wasn't part of the original plan, but which is potentially quite exciting?
One place where things have actually happened related to technology use in education, and where they continue to happen, at a rather large scale, is Portugal.
Back in 2012, we had a small event here at the World Bank that attempted to share some of the lessons learned from recent Portuguese experiences in introducing new technologies into the education sector (seeAround the World with Portugal's eEscola Project and Magellan Initiative). The U.S.-based Consortium for School Networking (CoSN) released a report last month as a follow-up to a study visit to Portugal in late 2013. While written from a North American perspective and for a North American audience, "Reinventing Learning in Portugal: An Ecosystem Approach" provides a useful lens through which an outsider, regardless which continent she calls home, can start to take stock of some of the high level lessons from the ongoing Portuguese experience.
(Side note: I would also be quite interested to read a companion report at some point that focuses on what went wrong in Portugal, and what changed as a result; I am a big believer in the power and value of learning from failure.)
Countries interested in learning about the 'impact' of efforts to introduce and sustain the use of technologies to benefit education in Portugal might do well to understand the context of what has happened in Portugal, and the circumstances that may make it either unique, or a good comparator, to their own national circumstances.
We traveled down a bumpy, dirt road in the rural areas of West Bengal towards a village called Bolpur. Three hours after leaving Kolkata, the car pulled up to an unassuming concrete building. The health care worker who accompanied us for this ride jumped out enthusiastically and immediately spoke into her megaphone. “Not feeling well?” she called out to the village, “Need a quick check up? Come and visit us for the next hour and a half.” Here, in a small village, at an unassuming building, we had found ourselves at an iKure spot camp.
iKure - a Kolkata-based social enterprise dedicated to bringing affordable health care to India’s poorest populations - has created these spot camps as an integral part of their inventive model for a network of health clinics in India’s rural areas. In addition to providing access to doctors and medicine prescriptions, they provide the necessary outreach to tell villagers about where and when the clinics are and how they can access medical consultations and medicine.
Even where there is common agreement on the potential utility of deploying mobile phones as part of a particular data collection effort, as well as a consensus understanding about relevant challenges that may complicate such an effort, decision makers may still be unsure about how to start their related planning efforts – or how best to change course once such efforts are underway.
In many instances, an intriguing proposal by a vendor of a particular product or service may help instigate initial considerations to use mobile phones as part of data collection efforts; news reports and information sharing between key practitioner groups may as well. Whatever catalyzes consideration of the use of mobile phones as aids in data collection efforts – in some cases it may simply be a general dissatisfaction with the status quo – here are some general questions that may be worth asking:
At a recent lunchtime presentation, World Bank staff had the opportunity to hear about the progress of the Government of India’s Aadhaar program. Aadhaar, which means ‘foundation’ in English, is a 12 digit individual identification number issued to each resident in India by the Unique Identification Authority of India (UIDAI). The program aims to provide a unique ID to 1.2 billion residents and is, as such, the largest ID project of its kind currently in the world. Beyond registration of citizens, it will allow identifying and finding citizens who qualify for social benefits and social protection services but have been excluded until now for a variety of reasons including lack of documentation, cast system and gender. Aadhaar is seen by many as one of key means to enable social and financial inclusion in India.
Much has been made of the potential use of mobile phones to help collect, verify and disseminate information quickly, widely and cheaply in support of activities in the education sector.
What do we know about how such use looks in practice,
and what are we learning from emerging efforts in this area?
At an event last month at the World Bank, my colleagues Sukhdeep Brar and Gaurav Relhan shared some lessons from a few recent and on-going education activities in Uganda, providing some potentially quite useful insights for those seeking answers this question. The full video for this event, as well as the PowerPoint file presented, is available online. For those of you who are pressed for time, or are just not sure if clicking those links is worth the effort, here is a quick synopsis of what was shared and discussed.
The explosive growth in the availability of mobile phones in societies around the world – even in some of the poorest, most remote communities – is increasingly leading many groups to explore how these devices might be used effectively as part of large scale data collection efforts in many sectors, including education. Utilizing small, portable electronic computing devices to help collect data is not new, of course. For over two decades, laptop computers and personal digital assistants (PDAs) have featured in initiatives to (e.g.) collect census information, interview consumers of various goods and services and poll potential voters. That said, such efforts often faced constraints related to, among other things: costs; the relative novelty of such devices among key segments of the population; the need to provide device-specific user training; and difficulties in exchanging data between these devices and other components of a larger system for data collection. If, as it has been argued, the best technology is often the one you already have, know how to use, can maintain and can afford, for most of the world, the mobile phone fits these criteria quite well. As of late 2013, rates of mobile phone penetration stood at 96% globally (128% in developed countries and 89% in developing countries). According to the International Telecommunications Union, “today there are almost as many almost as many mobile-cellular subscriptions as there are people in the world.”
Given their ubiquity, increasing functionalities, and decreasing related acquisition and operating costs, it is not surprising that mobile phones have been employed in a variety of ways to aid data collection efforts around the world. While many people may believe that such efforts require the use of a high-end (and expensive) smart phones, phones of all sorts have been deployed successful to different ends in different contexts.
Very simple, low-end ‘dumb phones’, for example, can utilize simple text messaging (or SMS) or voice to (e.g.) send out short queries by phone to a bank of phone numbers, prompting users to reply with a short response, which can be either predefined (‘text 1 for yes, 2 for no’) or open-ended. Smartphones can be used in much more sophisticated ways by presenting rich media survey questions directly to respondents or to help guide the actions of an ‘enumerator’ (someone who administers a survey in person) by presenting a user-friendly interface to help an enumerator input and transmit data in structured ways. Such phones may also contain help files and training aids for the enumerators. In between the high and low end, ‘feature phones’ (a catch-all category of sorts for phones which can do more than make basic voice calls and send and received text messages, but do not have the advanced functionality of smart phones) can make use of simple graphical forms (e.g) on screen as prompts for questions, and can store/transmit structured data as a result of responses.
Data input or captured into phones may be transmitted or shared in many ways (including SMS, MMS, USSD, Bluetooth, wireless Internet, or the exchange of physical memory cards). Where mobile connectivity is not available, data can be stored on the phone and transmitted later once a phone is within sufficient range of a cell tower.
How and why might mobile phones
be useful in large-scale data collection efforts,
and what comparative advantages might their use have when compared to other options?
A number of attributes and characteristics of mobile phone use in such activities (as well as the use of other small, low-cost portable devices such as tablets, especially where such devices can be connected to mobile and wireless networks) may lead them to be considered, especially when compared with the use of more traditional, paper-based survey instruments:
These are some of the views and reports relevant to our readers that caught our attention this week.
The Transformative Impact of Data and Communication on Governance: Part 3
How do digital technologies affect governance in areas of limited statehood – places and circumstances characterized by the absence of state provisioning of public goods and the enforcement of binding rules with a monopoly of legitimate force? In the first post in this series I introduced the limited statehood concept and then described the tremendous growth in mobile telephony, GIS, and other technologies in the developing world. In the second post I offered examples of the use of ICT in initiatives intended to fill at least some of the governance vacuum created by limited statehood. With mobile phones, for example, farmers are informed of market conditions, have access to liquidity through M-Pesa and similar mobile money platforms.
Cashing in: why mobile banking is good for people and profit
Using digital finance to tackle development problems can improves lives, and offer innovative companies handsome rewards. Whether it is lack of access to water, energy or education, development professionals are well versed in the plethora of challenges facing billions of people. The traditional approach to solving these problems has been to think big – in terms of the millennium development goals, government aid programmes, or huge fundraising campaigns. But there are dozens of startups and larger companies with innovative ideas who are approaching these challenges in new ways using digital finance.
The epic battle of man against machine has been fought on many occasions. One of the most memorable encounters was the chess game between IBM’s Deep Blue and Gary Kasparov. Deep Blue was the first computer to beat a reigning chess champion in 1996 (the machine still lost 2 to 4 after six games). A year later, at their “rematch”, the machine won on the overall score: 3.5 to 2.5.
However, it is surprising that, 18 years later, we still have not figured out the ultimate winning strategy in chess. Any game with limited combinations and full disclosure of information must have ‘safe strategies’ and can be ‘solved’ (as has happened with the game checkers in 2007). The solution, in chess, would from what we know today involve strategies whereby the white player would win or the black player would force a draw. Yet no human or super computer to date has managed to solve chess’ mathematical puzzle. How much more computing power do we need to succeed?