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Big Data

To the Data Day skeptics

Pinelopi Goldberg's picture

As I wondered which of the many fascinating ideas from the World Bank’s inaugural annual Data Day to recap in a blog, it occurred to me that there was likely selection bias in those who chose to attend.  Presumably, some skeptics of big data chose to skip the day entirely. So this blog is aimed first and foremost at the skeptical.

A fair data marketplace for all

Siddhartha Raja's picture
Credit: Kentoh/Shutterstock
Billions of people around the world are barely aware of their participation in a trillion-dollar data market. Its growth and impact has been accelerated by the easier flow, storage, and analysis of data—thanks to rapid advances in digital technology combined with falling costs of computing. The global data economy is estimated to be worth more than US$3 trillion; the European Commission believes that personalized data was worth over EUR 300 billion by 2016. The application of personal data for online advertising is also skyrocketing with the internet surpassing television as the leading advertising channel. Two internet giants—Facebook and Google—have combined digital advertising revenues on par with the gross domestic product (GDP) of Morocco.
 
This marketplace is reshaping how people interact with and use information, leading to new opportunities. Yet, it confronts these people and policymakers alike with new questions of the trade-offs between privacy, convenience, and access to information.
 
In chapter 4 of our latest Information and Communications for Development report, we started to frame what this marketplace (or places) might look like. We sought to understand what the costs and benefits were for people—the producers of much the data, the most valued commodity in this new economy. We tried to abstract from the now almost (worryingly regular) news of leaks and hacks to get a better sense of what might be ways to think about public policies that lead to a more balanced and fair data marketplace. We thought about the opportunities and the risks that are emerging, but also about what might be ways to make data marketplaces fairer in their functioning.

Artificial intelligence, big data: Opportunities for enhancing human development in Thailand and beyond

Sutayut Osornprasop's picture

The use of artificial intelligence (AI) and big data can offer untapped opportunities for Thailand. Particularly, it has enormous potential to contribute to Thailand 4.0, a new value-based economic model driven by innovation, technology and creativity that is expected to unlock the country from several economic challenges resulting from past economic development models (agriculture – Thailand 1.0, light industry – Thailand 2.0, and heavy industry – Thailand 3.0), the “middle income trap” and “inequality trap”. One core aspect of Thailand 4.0 puts emphasis on developing new S-curve industries, which includes investing in digital, robotics, and the regional medical hub.

Improving public procurement in Georgia – what’s the magic recipe?

Sandro Nozadze's picture
Procurement Georgia

What exactly is procurement, you may ask? If you google the word, you’ll likely find several different definitions.
 
Essentially, procurement is about buying things. That sounds quite simple, of course, but it becomes much more complicated at the level of government buying, especially when complex risks and variables must also be considered. So, is there a way to simplify government procurement?

From Discovery to Scale: Leveraging big data to improve development outcomes

Michael M. Lokshin's picture

In the last few years, the World Bank has expanded use of big data in more than 150 development projects globally, spanning a wide range of sectors and geographies. Solutions have ranged from using big data to monitor, evaluate, and improve projects—in energy, transport, and agriculture—to poverty diagnostics and understanding how well urban residents are connected to jobs. But, as Haishan Fu, Director of the Development Data Group at the World Bank, has said, “we are just beginning to realize the potential of the data revolution.”

These pilots have taught us that moving from discovery, to incubation, to scale requires a more coordinated and systematic approach. At the World Bank, we found it important to go beyond internal dialogue and assessments. We wanted to listen to and understand the perspectives of our partners in the development and data ecosystems—on current gaps, opportunities, as well as on the role(s) the World Bank should play in order to foster collective action.

Socio-Emotional Skills Wanted! – New Big Data Evidence from India

Saori Imaizumi's picture


We all hear about the importance of “socio-emotional skills” when looking for a job. Employers are said to be looking for individuals who are hardworking, meet deadlines, are reliable, creative, collaborative … the list goes on depending on the occupation. In recent years, it seems, these skills have become equally important as technical skills. But do employers really care about these soft skills when hiring? If so, what type of personality do they favor?

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 psychometrics help bridge the gap?

Claudia Ruiz's picture
Traditional credit scores are fairly accurate in predicting future loan performance, which is why lenders have tended to concentrate on clients with already a solid credit history, as screening them is less costly. However, interest in alternative ways to identify potential good borrowers that lack credit history is growing, particularly in countries where a non-trivial fraction of the population remains unbanked.

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.

Leveraging technology to achieve the Sustainable Development Goals

Mahmoud Mohieldin's picture
A drone delivery project made Rwanda the first country in the world to use the drone technology at the service of saving lives. © Sarah Farhat/World Bank
A drone delivery project made Rwanda the first country in the world to use the drone technology at the service of saving lives. © Sarah Farhat/World Bank


Billions of people are connected by mobile devices, with unprecedented processing power, storage capacity, and access to knowledge -- foreshadowing stunning possibilities.  This potential is multiplied by technologies such as artificial intelligence, robotics, big data processing, the internet of things, autonomous vehicles, 3-D printing, blockchain, etc.
 
This so called 4th industrial revolution can help accelerate progress towards the Sustainable Development Goals (SDGs). Indeed, Science, Technology and Innovation, together with Financing for Development, were identified by the UN as one of the two main “means of implementation” to achieve the SDGs by 2030 as it cuts across all SDGs as highlighted by International Telecommunication Union’s Fast Forward Progress Report – Leveraging Tech to Achieve the SDGs.


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