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Disruptive Technologies

Leveraging technology to close gaps between men and women

Mirai Maruo's picture


Technology serves as a key driver of change and opens new avenues to address the world’s most complex challenges. It is changing the nature of work and challenging traditional production patterns. And it is changing the skills that employers seek, how people work and the terms on which they work.
 
This month, the World Bank Group Advisory Council on Gender and Development will meet for its twice-yearly meeting to discuss the World Bank Group (WBG)’s recent developments and initiatives to close key gaps between men and women. Chaired by Kristalina Georgieva and comprising senior government representatives from client and donor countries, private sector and civil society, the Council is the main external consultative body helping the WBG consider frontier issues and accelerate progress towards gender equality.
 
Earlier this year, the Council undertook a learning session on the role of technology in promoting gender equality. The discussion mapped out some key challenges in this area.

Why Disruptive Technologies Matter for Affordable Housing: The Case of Indonesia

Dao Harrison's picture

  The Case of Indonesia

Big Data. Blockchain. Drones. E-Wallets. Artificial Intelligence.
These are words that one would expect to hear at the latest conference in Silicon Valley, not during a discussion of Indonesia’s affordable housing challenges. Yet they were buzzing through the captive crowd in Jakarta at the Disruptive Technologies Workshop for Affordable Housing on September 17, 2018. The event, hosted by Indonesia’s Ministry of Public Works and Housing with support from the World Bank’s National Affordable Housing Program (NAHP), was attended by 150 participants from local public agencies, developers, lenders, and community organizations. The workshop’s goal was to explore one big question: How might Indonesia harness the power of disruptive technologies to transform its housing ecosystem?   

In Africa, technology and human capital go hand in hand

Sheila Jagannathan's picture
Photo: eLearning Africa
Rwanda’s progress from the devastating civil war two decades ago to one of the most rapidly developing African countries is a remarkable narrative on development.

Twenty-four years ago, the country was torn apart by civil war and one of the worst genocides human history has known; one in which more than a million people were killed in only three months.

Now, with years of sustained economic growth—predicted to be around 6.5% this year, the country is well on the way to achieving many of the ambitious development goals set out in the Rwandan Government’s ‘Vision 2020.’ This strategy seeks to move away from agriculture and rely instead on services and knowledge as the new engines of economic growth, with the objective of achieving middle-income status in the near term.

I had the privilege of getting a snapshot view of Rwanda’s success during the few days I spent in the country last month attending elearning Africa 2018, the continent’s largest conference on technology-assisted learning and training. The choice of Kigali as the location for this year’s conference is highly symbolic: Rwanda has put education and skills at the heart of its national strategy, and can send a powerful message to other African countries about the importance of investing in human capital to support overall development.

How can digital technology help transform Africa’s food system?

Simeon Ehui's picture
Also available in: Français 
Photo: Arne Hoel/World Bank
There’s no question that agriculture is critical to Africa’s biggest development goals. It is fundamental for poverty reduction, economic growth and environment sustainability. African food market continues to grow. It is estimated that African food markets will triple to US$1 trillion from its current US$300 billion value. Farming accounts for 60% of total employment in Sub-Saharan Africa—and food system jobs account for even more. In Ethiopia, Malawi, Mozambique, Tanzania, Uganda and Zambia, the food system is projected to add more jobs than the rest of the economy between 2010 and 2025.

And yet, Africa’s agriculture sector is facing serious challenges. Agricultural productivity in Africa lags behind other regions. One in four people in Sub-Saharan Africa are chronically undernourished. Africa’s food system is further strained by rapid population growth and climate change. The food security challenge will only grow as climate change intensifies, threatening crop and livestock production. If no adaptation occurs, production of maize—which is one of Africa’s staple crops—could decline by up to 40% by 2050. Clearly, business as usual approaches to agriculture in Africa aren’t fit for transforming the sector to meet its full potential.

Digital technology could be part of the solution. But how can digital technology help transform Africa’s food system?

It’s instructive to look at startups, which are an emerging force in Africa’s agriculture sector.

Data analytics for transport planning: five lessons from the field

Tatiana Peralta Quiros's picture
Photo: Justin De La Ornellas/Flickr
When we think about what transport will look like in the future, one of the key things we know is that it will be filled and underpinned by data.

We constantly hear about the unlimited opportunities coming from the use of data. However, a looming question is yet to be answered: How do we sustainably go from data to planning? The goal of governments should not be to amass the largest amount of data, but rather “to turn data into information, and information into insight.” Those insights will help drive better planning and policy making.

Last year, as part of the Word Bank’s longstanding engagement on urban transport in Argentina, we started working with the Ministry of Transport’s Planning Department to tap the potential of data analytics for transport planning. The goal was to create a set of tools that could be deployed to collect and use data for improved transport planning.

In that context, we lead the development of a tool that derives origin-destination matrices from public transport smartcards, giving us new insight into the mobility patterns of Buenos Aires residents. The project also supported the creation of a smartphone application that collects high-resolution mobility data and can be used for citizen engagement through dynamic mobility surveys. This has helped to update the transport model in Buenos Aires city metropolitan area (AMBA).

Here are some of the lessons we learnt from that experience.

Can disruptive business models and technologies be the key to unlocking trillions in climate finance?

Alzbeta Klein's picture



It is no secret that disruptive “technologies of tomorrow” are now regularly touted as a keystone to addressing a changing climate.  A recent study by IFC shows that building on technological innovation, global markets for climate-smart business already exceed US $1 trillion in size in key industries ranging from energy storage and electric vehicles to green buildings and supply chain logistics. By scaling up business models relying on these technologies, developing countries can unlock trillions more in investment opportunities while promoting shared and sustainable economic prosperity.

Completing the storytelling ‘circle’: a VR project goes home

Tom Perry's picture
Development organizations & NGOs need powerful stories to help people connect with their work. Yet how do communities feel after their stories have been shared?

After leading the production of a climate change Virtual Reality production in Fiji and returning it to communities, Tom Perry, the World Bank's Team Leader for Pacific Communications, shares his thoughts.

Beyond Proof of Concept: do we have the right structure to take disruptive technologies to production?

Michael M. Lokshin's picture
Figure 1: Azure Cognitive Services Algorithm compliments authors’
youthful appearances

“Every company is a technology company”. This idea, popularized by Gartner, can be seen unfolding in every sector of the economy as firms and governments adopt increasingly sophisticated technologies to achieve their goals. The development sector is no exception, and like others, we’re learning a lot about what it takes to apply new technologies to our work at scale.

Last week we published a blog about our experience in using Machine Learning (ML) to reduce the cost of survey data collection. This exercise highlighted some challenges that teams working on innovative projects might face in bringing their innovative ideas to useful implementations. In this post, we argue that:

  1. Disruptive technologies can make things look easy. The cost of experimentation, especially in the software domain, is often low. But quickly developed prototypes belie the complexity of creating robust systems that work at scale. There’s a lot more investment needed to get a prototype into production that you’d think.

  2. Organizations should monitor and invest in many proofs of concept because they can relatively inexpensively learn about their potential, quickly kill the ones that aren’t going anywhere, and identify the narrower pool of promising approaches to continue monitoring and investing resources in.

  3. But organizations should also recognize that the skills needed to make a proof of concept are very different to the skills needed to scale an idea to production. Without a structure or environment to support promising initiatives, even the best projects will die. And without an appetite for long-term investment, applications of disruptive technologies in international development will not reach any meaningful level of scale or usefulness.

Technology holds great promise for transport, but…

Nancy Vandycke's picture
Photo: Automobile Italia/Flickr
Not a day goes by without a new story on how technology is redefining what is possible for transport. A futuristic world of self-driving, automated cars seems closer than ever.  While the ongoing wave of innovation certainly opens up a range of exciting new possibilities, I see three enduring challenges that we need to address if we want to make sure technology can indeed help the transport sector move in the right direction:      

The focus is still on car-centric development

The race towards incredibly sophisticated and fully automated cars is well underway: companies like Google, Uber, Delphi Automotive, Bosche, Tesla, Nissan Mercedes-Benz, and Audi have already begun testing self-driving cars in real conditions.  Even those who express concern about the safety and reliability of autonomous vehicles still agree that this innovative technology is the way of the future.

But where is the true disruption? Whether you’re looking at driverless cars, electric vehicles, or car-sharing, all these breakthroughs tend to reinforce a car-centric ecosystem that came out of the industrial revolution over a hundred years ago.

Toward a linked and inclusive economy

Jim Yong Kim's picture
The arrival of broadband internet is set to significantly improve medical services in Tonga. © Tom Perry/World Bank.
The arrival of broadband internet is set to significantly improve medical services in Tonga. © Tom Perry/World Bank.

While some studies predict automation to eliminate jobs at a dizzying rate, disruptive technologies can also create new lines of work. Our working draft of the forthcoming 2019 World Development Report, The Changing Nature of Work, notes that in the past century robots have created more jobs than they have displaced. The capacity of technology to exponentially change how we live, work, and organize leaves us at the World Bank Group constantly asking: How can we adapt the skills and knowledge of today to match the jobs of tomorrow?
 
One answer is to harness the data revolution to support new pathways to development. Some 2.5 quintillion bytes of data are generated every day from cell phones, sensors, online platforms, and other sources. When data is used to help individuals adapt to the technology-led economy, it can make a huge contribution toward ending extreme poverty and inequality. Technology companies, however well intended, cannot do this alone.


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