Syndicate content

data

Thanksgiving Woes? IBM and Big Data May Help.

Tanya Gupta's picture

In just about a week, on Thursday November 28, people all over the United States will kick off the "holiday season" with the celebration of Thanksgiving Day. While the day's significance is both historical and profound, in modern times it consists of a lot of shopping and a big meal with family and friends gathered around the dinner table. Pre-thanksgiving is a time to be on the lookout for creative new recipes.  Sure, we can get recipes from magazines, websites and friends and while they may be special, they will not be unique.  Wouldn’t it be nice to have an app that would create a special unique recipe just for you? A delightful recipe that has never been executed before.  Well the idea is not as futuristic as it sounds. It may be here sooner than you think.  IBM and big data have a lot to do with this particular innovation.
 
Can computers be creative?  IBM thinks they can.  IBM scientists Lav R. Varshney and other members of an IBM team, have used data sets and proprietary algorithms in the daunting field of the culinary arts to develop a computational creativity system. The data sets they have used are recipes, molecular level food related data and data about the compounds, ingredients and dishes that people like and dislike.  They then developed an algorithm that produces thousands or millions of new ideas from the recipes.  The recipes are then evaluated to select the best ones that combine ingredients in a way that has never been attempted before.  Humans can interact with the system by choosing a key ingredient and the kind of cuisine.

Media (R)evolutions: China is an Internet Sleeping Giant

Kalliope Kokolis's picture

New developments and curiosities from a changing global media landscape: People, Spaces, Deliberation brings trends and events to your attention that illustrate that tomorrow's media environment will look very different from today's, and will have little resemblance to yesterday's.

This week's Media (R)evolutions: China is an Internet Sleeping Giant.


 

Visualizing Global Remittances – Big Data Mapping of Bilateral Flows

Dan Ewing's picture

Global flows of cross-border remittances exceed $500 billion in money transfers across a dizzying array of bilateral corridors. With over 200 countries, send-receive combinations exceed forty thousand. Moreover, the variables that drive these cross-border flows hinge on a multitude of factors from migration flows, economic growth, historical connections and more. In short, it’s an explosion of diversity that can be hard to fully comprehend and envision.

You Need Beautiful Art to Understand Data. Really, You Do.

Susan Moeller's picture

It’s tempting for those who work with numbers and spreadsheets, for those who live by the bottom line and whose minds run along quantitative paths to think that art exists for its own sake. It’s tempting to think of art as something nice for the wall, pleasant to look at, maybe even restorative or inspiring in its impact, but ultimately not essential to the running of the world.

Yet consider the work of University of Maryland Computer Science Prof. Ben Shneiderman. Shneiderman is the inventor of treemaps — those graphics that chart often vast quantities of hierarchical data, such as electronic health records.  He’s also famous for the eponymous “Shneiderman’s Mantra” of visual data analysis: look at an overview of the data first, then zoom and filter it, then, on demand, consider the details. 

Worth the wait in Zanzibar

Raka Banerjee's picture

My experiences with field work thus far have been nothing if not adventurous. I seem to attract broken glass – a rock the size of a small coconut crashing through my 3rd floor window in Zanzibar, for instance, or the windows of my taxi being broken with baseball bats by an armed mob in Mali. Just the other day, my boss and I came within inches of dying in a fiery plane crash – we were on our way back to the main island of Zanzibar from Pemba island in a tiny 12-seater Soviet-era plane, and were just about to land in a strong crosswind when the engine on my side failed.  We managed to land, somehow, and taxied to a stop right there on the runway to wait for a vehicle (ironically, it ended up being an ambulance) to take us to the terminal.

Social and online media for social change: examples from Thailand

Anne Elicaño's picture


In Bangkok, a campaign to save land from being turned into another mega mall
brings people together online--and offline. Photo credit: Makkasan Hope

As a web editor and as a digital media enthusiast I’ve seen all sorts of content online: a close-up photo of someone’s lunch, a video of singing cats, selfies (for the blissfully uninitiated- these are self-portraits taken from mobile devices), and more.

Can such content change the world for the better? What if these were more substantial or inspiring, would it spur change more effectively? While messaging is important, I think the real power of social and online media is in its convening power.  The changing the world for the better bit happens when the communities formed by social media take things offline and act.

Learning from Data-Driven Delivery

Aleem Walji's picture

Given confusion around the phrase “science of delivery,” it’s important to state that delivery science is not a “one-size-fits-all” prescription based on the premise that what works somewhere can work anywhere. And it does not profess that research and evidence ensure a certain outcome.
 
A few weeks ago, the World Bank and the Korea Development Institute convened a global conference on the science of delivery. Several development institutions assembled including the Gates Foundation, the Grameen Foundation, UNICEF, the Dartmouth Center for Health Care Delivery Science, and the mHealth Alliance. We discussed development opportunities and challenges when focusing on the extremely poor, including experiments in health care, how technology is reducing costs and increasing effectiveness, and the difficulty of moving from successful pilots to delivery at scale.
 
The consensus in Seoul was that a science of delivery underscores the importance of a data-driven and rigorous process to understand what works, under what conditions, why, and how. Too often in international development, we jump to conclusions without understanding counterfactuals and assume we can replicate success without understanding its constituent elements.

Democracy and Crime: An Old Question Awaiting New Answers

José Cuesta's picture

The recent political unrest and violence occurring across the world have revived an old question, one that is so straightforward that it rarely gets a straightforward and convincing answer: Does democracy fuel or quench violence? For decades, sociologists, historians, political scientists, criminologists, and economists have hypothesized numerous associations, predicting just about any result.

Let’s focus on democracy’s relationship with crime. Democracies have been predicted to fuel crime (conflict theory); decrease crime (civilization theory); initially raise and then decrease crime (modernization perspective); have no impact at all (null hypothesis); or have an unpredictable impact depending on the development of their political institutions (comparative advantage theory).

In a recently published paper, I argue that the many existing explanations relating crime and democracy suffer from what I describe as an “identification” problem. The different explanations are not necessarily exclusionary in terms of their determinants, mechanisms, and predictions, which makes testing those explanations a rather difficult business. Furthermore, predictions are imprecise. This is unsurprising when dealing with concepts as fluid as democratization, political transitions, and democratic maturity. Arguments talk vaguely of early and late stages and of short or medium terms to describe the processes’ dynamics. The result is a broad range of predictions consistent with various hypotheses simultaneously. 

Moneyballing Development: A Challenge to our Collective Wisdom of Project Funding

Tanya Gupta's picture
The biggest promise of technology in development is, perhaps, that it can provide us access to consistent, actionable and reliable data on investments and results.  However, somewhat shockingly, we in development have not fully capitalized on this promise as compared to the private sector.  Would you invest your precious pension hoping you will get something back but without having any reliable data on the rate of return or how risky your investment is?  If you have two job applicants, one who is a methamphetamine addict and the other is one who has a solid work history and great references, would you give equal preference to both?  If your answer to either is no, then take a look at the field of international development and consider the following:
  • Surprising lack of consistent, reliable data on development effectiveness: Among the various sectoral interventions, we have no uniformly reliable data on the effectiveness of every dollar spent.  For example of every dollar spent in infrastructure programs in sub-Saharan Africa, how many cents are effective? Based on the same assumptions, do we have a comparable number for South East Asia? In other words why don’t we have more data on possible development investments and the associated costs, benefits/returns and risks?
  • Failure to look at development effectiveness evidence at the planning stage: Very few development programs look at the effectiveness evidence before the selection of a particular intervention.  Say, a sectoral intervention A in a particular region has a history of positive outcomes (due to attributable factors such as well performing implementation agencies) as opposed to another intervention B where chances of improved outcomes are foggy.  Given the same needs (roughly) why shouldn’t we route funds to A instead of B in the planning stage? Why should we give equal preference to both based purely on need?

Pages