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Stanford’s Poverty and Technology Lab

Poverty and Technology
Stanford University launched its Poverty and Technology Lab in 2016, promoting the collaboration of students and Silicon Valley experts to use their knowledge of the technology world in order to provide practical solutions to poverty.

Reversing the Roles of Technology

Stanford initiated its Poverty and Technology Lab as a project within the university’s Center for Technology and Inequality (CPI). Its goal with this initiative is to redefine the various uses of technology. Experts and students at the university recognize the possible dangers of technology, as it has the potential to decrease employment opportunities and perpetuate global inequalities. This Lab aims to switch this role by applying technology to benefit low-income people, rather than prioritizing the improvement of middle-class lives.

The Technology and Poverty Lab fostered collaboration among students, professors and Silicon Valley technology experts. In addition, the Lab incorporates the voices and opinions of people living in low-income communities into these conversations. This inclusion ensures that the tools being innovated are truly geared toward issues that the impoverished are enduring.

A Unique Approach in the Classroom

Stanford also launched a course series that parallels the goals of this lab. Professor David Grusky, Director of Stanford’s Center on Poverty and Inequality, teaches the first course—Ending Poverty with Technology—as well as the remaining courses.

Grusky explained the unique approach of both his classes and the lab in an interview, stating that “[Stanford’s Poverty and Technology Lab] is an opportunity to not take on problems at their root sources, which is our instinct. …  Sometimes the best way forward is to not take on problems at their causes, at their sources, but rather to approach them less directly and instead opt for approaches that proceed in a different way. It’s kind of a more pragmatic approach.”

Grusky said his classes are largely geared toward teaching students to think in a manner that enables them to create solutions using this unique method: “One of the outputs [of my class] is just training students in how you would think through problems in this way. So it’s not that they actually make headway on the problems themselves, but they learned how to approach problems of this type, and hopefully, in the future, we’ll make headway.”

Forming Projects

Many of the projects that have formed through Stanford’s Poverty and Technology Lab are information-oriented. Examples include services that aid employment, boost access to educational opportunities and enable low-income communities to rate preexisting assistance programs. These projects primarily focus on the process of linking data to evaluate current programs related to these processes.

“We have a lot of work underway in which we negotiate data-sharing agreements and use them to put together linked administrative data sets that then allow us to carry out evaluations,” Grusky reported.

From the United States to Abroad

Stanford created the Poverty and Technology Lab to find poverty solutions in the Bay Area and the United States. However, much of the work by this lab is applicable to impoverished communities across the globe. Acknowledging this global relevance, some students have even begun the process of testing their innovations abroad.

“Although we used the U.S. as a kind of a testbed in trying to understand the problems, some of [the students] actually went on and worked on their projects in other areas,” Grusky revealed.

Experimentation with one such project occurred in Peru, where a female student devised an entrepreneurship app. She proposed this application to include a convenient toolkit for those struggling to secure employment opportunities. This app would help these impoverished individuals to avoid this challenge by learning to start their own business.

At the surface, this project engages students at Stanford University. But it also urges technology experts across the country to examine the impact of their products more broadly. Students and scholars nationwide are collaborating with community members to find practical technological solutions to poverty.

– Hannah Carroll
Photo: Flickr

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AI and Satellites Improve Poverty Mapping Techniques

Poverty Mapping TechniquesHow many people live in poverty? The answer a search engine might give overlooks the complexity of the issue. A great deal of poverty data comes from the World Bank, which still relies on household surveys. These household surveys can be very inaccurate, and statistics like these are critical in the fight against poverty. Thankfully, many organizations are working on creating better poverty mapping techniques to help fight global poverty.

The Need for Poverty Mapping Techniques

Governments, private companies and NGOs must know who needs help, what works and how much they need in order to fight poverty. With more accurate data, aid programs can be rolled out more effectively, directly targeting populations who need it the most. Accurate data also determines the effectiveness of aid or other interventions, which helps agencies discover what works. It is important for the missions of many agencies to have accurate data on poverty, but methods for collecting this data are flawed.

One issue with current data collection is the amount of data available. The World Bank is a leader in the fight against global poverty, and it compiles many official statistics on poverty rates. Historically, the main way the World Bank typically measures poverty is through household surveys. However, these surveys do not reach as many people as they should. For lower-income countries, an annual investment of $1 billion would be required to expand these surveys to generate consistent, accurate data.

Not only are these surveys too narrow, but they are also not frequent enough. Surveys typically happen every few years and even every decade in some countries with lower capacities. Between 2002 and 2012, no poverty data was collected from 29 countries.

The Problems with Current Poverty Mapping Techniques

The most common surveying method employed by the World Bank is the household survey. Unfortunately, household surveys have built-in inaccuracies and miss many people, usually some of the poorest. This method tries to measure poverty by sending surveys to households, but these surveys are ill-suited to measure an atypical home environment. Many people trying to avoid poverty live in open households, whose membership is usually in flux. These households operate to reduce poverty collectively in ways that a typical survey cannot easily measure. When data from these households is not interpreted differently from other household data, overall data on poverty can be skewed.

Satellites Mapping Poverty

This dearth of accurate data was the inspiration for a team of Stanford researchers. Marchall Burke, David Lobell and Stefano Ermon have spent the better half of the last decade creating better poverty mapping techniques. The solution they are working on now is satellite mapping.

The team has used artificial intelligence to map poverty using publicly available satellite imagery. The system examines poverty by analyzing the wealth of assets in a given area as seen from space. By indexing images of wealthy areas and poor areas, the program can identify levels of poverty in other areas. It uses a variety of factors like lighting at night, roofing, infrastructure, roads and other easily recognizable traits to do so. Utilizing deep learning, the program is able to correlate factors and create an idea of poverty in an area with fairly high accuracy. The model explains about 70% of asset wealth variation at the village level. This means the model can predict more accurately than other attempts at mapping poverty using higher resolution imagery and mobile phone mapping. The ability to distinguish poverty at a village level also means that the program can identify levels of poverty in places that surveys never go, with much less cost and time required.

Household surveys have become obsolete compared to more modern and effective methods. Better poverty mapping techniques like the Stanford researchers’ will enable organizations to fight poverty with a greater level of accuracy, which will make this decade of poverty-fighting more efficient than the last.

– Brett Muni
Photo: Flickr

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Satellite Technology Can Combat Poverty in Africa

Satellite Technology Can Help Combat Poverty
Over the last two decades, there has been an observed decrease in poverty levels in the eastern and southeastern regions of Asia. Unfortunately, 42% of people in sub-Saharan Africa are still living in absolute poverty conditions. To aid developmental efforts on the continent, scientists and engineers are exploring how satellite technology can combat poverty across the entire continent.

Identifying Poverty 

It is well-known in the academic community that research relating to poverty in comparatively poor regions is hard to come by. Surveys and censuses are not frequent enough to provide an accurate understanding of poverty in Africa. This lack of data makes strategizing and taking action to alleviate poverty in some areas particularly difficult. Luckily, some are conducting new research to explore the possibility of using satellite imagery to identify poverty-stricken areas. In fact, Stanford researchers Marshall Burke, David Lobell and Stefano Ermon spent the last 5 years studying the use of available images to assess poverty conditions in Africa over time.

Satellite imagery and machine learning can work together to identify poverty and development hot-spots. Images that satellites take during the night could expose the absence of lights in an area that may lack electricity. Images from the day may also show the status of general infrastructures like housing, waterways, agricultural techniques and roads. These features are components of development and identifying their status should be able to help efforts to provide communities with the resources they lack. Neural networks, which are a component of machine learning, use these satellite images to find patterns in communities. The Stanford researchers tested this technology on 20,000 different African villages and created models for the conditions they observed. While machine learning is a new tool for the fight against poverty, it is a promising source of information and understanding that can enhance our response. 

Famine and Natural Disasters

In its response to conditions in Africa, USAID has long known that satellite technology can help combat poverty. In 1986, NASA began working with the U.S. Geological Survey (USGS) to detect and prevent famine through the famine early warning system (FEWS). Using remote sensing and existing satellite data that NASA collected, USAID has been able to predict famine conditions in sub-Saharan Africa. 

In 2000, NASA and USGS also collaborated to establish more effective response-planning mechanisms through an updated FEWS Network. They have used this network to predict floods, landslides, fires and other natural threats to development. In 2017, the network was able to make a credible appeal for food aid in a war-torn Somalia, which reduced deaths from starvation. Researchers have also concluded that the early warning system lowered mortality rates in Kenya, where the number of “severely hungry” Kenyans was 1.75 million in 2017, versus 2.8 million in 2011. Good disaster response can better inform developmental projects in poorer countries, which makes the network a crucial component of a greater effort to alleviate poverty. 

The Long-term

Many are now looking at how satellite technology can combat poverty. The technology can no doubt open more doors to understanding economic development. Experts suggest that satellite intel on land usage could aid non-governmental organizations in crafting policies for better resource allocation in the region and the possibilities do not stop there. Although there is still work to do to alleviate poverty in Africa, viewing this advancing technology as an enabler for further research and action is incredibly exciting.

– Arshita Sandhiparthi
Photo: Flickr

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Poverty Reduction May Begin in the Classroom

Classroom
The Stanford Center on Poverty and Inequality (CPI), a nonpartisan research center, is monitoring trends in poverty and inequality, developing policy and explaining the root causes of poverty. This education begins in the classroom and finishes in the field, such as rural villages in Africa. The Center supports research students and established scholars in the field. All research is published in CPI’s magazine Pathways, which will likely become the new fact-based journal on poverty, inequality, income, discrimination and more.

Since CPI’s beginning in 2006, the Center has received support from the US Department of Health and Human Services, Stanford University, Office of the Assistant Secretary for Planning and Evaluation, Pew Charitable Trusts and others. This type of intellectual approach and curiosity might be the next step needed for a meaningful change in poverty reduction.

Ending Poverty with Technology is just one of many courses within the Center. Stanford students have the opportunity to pick an issue and use the semester to determine how they would better the situation. Sarukkai, a Stanford student majoring in symbolic systems stated, “In the land of opportunity it only makes sense that every human being has access to the same resources and pathways to success—an ideal we are far from achieving.”

As an undergraduate capstone project, one CPI team proposed a web platform and mobile app called “CareSwap.” This app is designed to help low-income families trade childcare within their respected network of friends and family. Although the course has ended, the “CareSwap” team plans to continue to develop and execute its website and app. The ending of a course does not mean the work ends.

The course is simply a place where the inspiration begins—the work ethic and dreams of the Center’s students cannot be diminished by the end of a semester. Poverty reduction begins in the classroom but is carried out during the long hours of the student’s personal time.

“Our idea evolved so much in the last few months after our interviews and conversations with parents and childcare experts,” the students said. “We are excited to develop it further next year. This project has become far more than a class assignment for each of us.” An idea that began in the classroom later developed into an app and website, making thousands of children’s lives easier and safer.

Some of the proposed projects may even be adopted for further development by the Stanford Poverty & Technology Lab, an initiative dedicated to developing technology-based solutions to rising inequality in the United States. Currently, the lab is developing an app, under Bill Behrman, director of the Stanford Data Lab, for “mapping” poverty in California. The app has the potential to help government agencies and nonprofits better target certain demographics by delivering estimates of poverty, unemployment, income and other indicators for very small geographic areas of the state.

Innovative and creative thinking are both necessary to tackle any complex topic, particularly poverty. In the classroom, both attributes are present, as well as the ability to look at the situation from various perspectives. The communal feel and global mindset of Stanford are felt in every classroom of the Center on Poverty and Inequality. “It’s not about a professor teaching and the students learning,” one student said. “We’re all just part of the same team trying to build products that work to reduce poverty.”

Reducing poverty encompasses so many different aspects of society. However, like anything truly successful it should begin in the classroom. Poverty reduction can better the quality and longevity for millions of people worldwide, as academics and students studying to better the world—it only makes sense to tackle poverty from inside the classroom through innovation and creative thinking.

– Danielle Preskitt
Photo: Flickr

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Toy Inspires Low-Cost Lab Aid to Detect Malaria

Toy Inspires Low-Cost Lab Aid to Detect Malaria
Malaria is a life-threatening disease caused by parasites that are transmitted through the bite of an infected mosquito. In 2015 alone, there were 212 million cases of malaria and 429 thousand deaths. Suffice it to say that malaria is a global health problem.

Even worse is that Sub-Saharan Africa continues to carry a disproportionately high share of the global malaria burden. In 2015, the region was home to 90 percent of malaria cases and 92 percent of malaria deaths.

The good thing is that malaria is preventable and curable, given the proper tools to do so. A device called a centrifuge that spins a blood sample very quickly and separates different cells can detect malaria. Centrifuges, though, are expensive, bulky and require electricity – which makes it inefficient in regions such as Sub-Saharan Africa.

A low-cost lab aid to detect malaria is in dire demand, which is exactly what Manu Prakash, a professor of bioengineering at Stanford University, realized on a trip to Uganda. On his trip, Prakash says he found centrifuges used as doorstops because there was no electricity.

Back in California, Prakash experimented with spinning toys in his search for a model for a low-cost lab aid to detect malaria. Though toys are not the conventional approach to developing a lab aid, Prakesh argues that toys hide profound physical phenomena we take for granted.

After experimenting with several spinning toys, including a yo-yo, they stumbled upon the children’s toy known as the whirligig or buzzer. The toy is made of a disk that spins when the strings that go through it are pulled.

This new low-cost lab aid to detect malaria dubbed the paperfuse, can separate pure plasma from whole blood in less than 1.5 minutes, and isolate malaria parasites in 15 minutes. The paperfuse has an ultra-low-cost of fewer than 20 cents, weighs only two grams and is, therefore, field-portable. The paper fuse could be the tool that helps detect and end malaria in low-income countries in the near future.

– Mayan Derhy

Photo: Flickr

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Solar-Powered Water Purifier Has Potential to Save Lives

solar-powered water purifier
Recently, scientists at Stanford University and the Department of Energy’s SLAC National Accelerator Laboratory have developed a tiny, solar-powered water purifier resembling a rectangular bit of black glass. The new device does not have a name yet, but is being referred to as a “tablet.”

Access to safe drinking water is a problem for 663 million people in the world. The World Health Organization reports that unsafe water supplies, sanitation and hygiene are responsible for 842,000 deaths every year, 361,000 of which are children under the age of 5.

What sets this device apart from other water purifying gadgets on the market is its use of a wider range of light. According to the Global Citizen Organization, the device absorbs 50 percent of incoming sunlight energy, while other purifiers only absorb 4 percent.

According to project leader Chong Liu, “This can greatly enhance the speed of water disinfection. It does not need any additional energy or effort for treating water.” In an experiment, the tablet took only 20 minutes to function. In contrast, other purifying systems that use only UV rays can take up to almost 48 hours.

On the surface of the tablet is a layer of nanoflakes and a small amount of copper. The nanoflakes’ exposure to sunlight and water excites electrons in the device and results in the release of hydrogen peroxide. This chemical kills bacteria in the water, making it safe to drink. As of now, however, the tablet is only capable of killing E. coli and lactic acid bacteria.

In an experiment published in the Nature Nanotechnology journal, researchers placed the solar-powered water purifier in a container with 25 milliliters of water for 20 minutes. It killed 99.99 percent of the bacteria in the water, an impressive amount for such a short amount of time. Even Liu said, “We didn’t expect it to work that well at first.”

Since the device is new and not ready for the market yet, it has no fixed price. But according to Liu, “The material itself is cheap and the synthesis process is facile. So we assume that the device would be of low-cost.”

More experiments and field tests must be done before the tablet can be distributed. Nonetheless, this solar-powered water purifier has the potential to cheaply and quickly help people who struggle to obtain clean drinking water.

– Karla Umanzor

Photo: Flickr

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Poverty Mapping with Help of Artificial Intelligence

Poverty Mapping with the Help of Artificial Intelligence
Poverty mapping has proven to be a difficult task in past years. Poor countries are often reluctant to account for poverty due to corruption or the inability to do so because of ongoing conflicts. The World Bank reports that only 20 African countries conducted two or more population surveys on poverty from 2000 to 2010.

A new study from Stanford University hopes to improve poverty mapping by combining high-resolution satellite imagery with artificial intelligence.

According to a feature article published by online tech magazine Motherboard, Neal Jean, a Ph.D. engineering student at Stanford, has designed a machine learning algorithm that can predict poverty in Malawi, Nigeria, Rwanda, Tanzania, and Uganda.

Using satellite imagery to determine “nightlights” and levels of economic activity as a method of poverty mapping is nothing new. What’s different about the algorithm designed by Jean and his team is that it looks at daylight images of infrastructure, such as roads and metropolitan areas, which it then uses to identify nighttime patterns.

“Our basic approach involved a machine learning technique called ‘transfer learning,’ which is the idea that you can solve a hard problem – in our case, predicting poverty from satellite images – by trying to solve an easier one,” Jean said.

According to Motherboard, the algorithm may prove to be a very effective method of poverty mapping, especially given the cost of traditional household surveys and the lack of viable alternatives. Another advantage of the machine learning model is its transparency, as it doesn’t rely on private or protected information.

Jean told Motherboard that he hopes to make the technology open-source and cooperate with NGOs to put the algorithm to use. “If we could provide them with high-resolution poverty maps, they could overlay them on regions where operations already exist, and ultimately inform where they distribute funding,” he argued.

Jean’s machine learning algorithm is not the only artificial intelligence tool that is providing better data for poverty alleviation efforts. South African computer scientist Muthoni Masinde developed a solution that can forecast droughts with 98 percent accuracy, combining traditional knowledge with new technologies. In recognition of her achievements, she received a Distinguished Young Women Researcher award at the 2016 South African Women in Science Awards.

Technological advance has been the greatest impetus for poverty reduction throughout history, and artificial intelligence is the future of poverty mapping. It provides economists and scientists with better data in order to pinpoint and resolve problems that are holding developing countries back.

– Philip Katz

Photo: Flickr

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Rosenkranz Prize Winners Dedicated to Improving Healthcare in Developing Countries

Rosenkranz Prize
The Rosenkranz Prize aims to fund the work of Stanford University’s rising research stars who have the desire to improve healthcare in developing countries but who lack the necessary resources.

Most grants in the scientific field are awarded to established researchers. But because the Rosenkranz Prize is awarded to rising researchers, it is able to split funds between two young researchers.

Marcella Alsan, MD, PhD, is investigating how the division of labor among men and women begins at a young age in the developing world. Alsan theorizes that this is because young girls are responsible for taking care of younger siblings, missing endless days of school.

Alsan states, “Anecdotally, girls must sacrifice their education to help out with domestic tasks, including taking care of children, a job that becomes more onerous if their youngest siblings are ill.”

More than 100 million girls worldwide do not complete secondary school. Alsan will be analyzing whether medical interventions in children under the age of 5 show an increasing trend in schooling for their older sisters.

By analyzing this data, Alsan will be able to prove or disprove if sick siblings affect their older sister’s school participation. If this thesis proves true, implementing medical interventions in younger children will increase the number of girls in school. By completing school, girls will be able to not only take care of family and their own children but also have a strong background in education.

The second Rosenkranz Prize winner, Jason Andrews, an infectious disease specialist, is focusing his funds on the development of cheap, effective diagnostic tools for infectious diseases.

Andrews recalls working in rural Nepal as an undergraduate student and “founded a nonprofit organization that provides free medical services in one of the most remote and impoverished parts of the country . . . one of the consistent and critical challenges I encountered in this setting was routine diagnosis of infectious disease.”

Andrews realizes that the diagnoses are hindered by lack of electricity, limited laboratory resources and lack of trained personnel. To eliminate these obstacles, Andrews is developing “an electricity-free, culture-based incubation and identification for typhoid; low-cost portable microscopes to detect parasitic worm infections; and most recently an easy-to-use molecular diagnostic tool that does not require electricity.”

Andrews does not want to develop new diagnostic approaches. Rather, Andrews believes he can develop the diagnostic approaches already in place to function in an affordable and accessible manner.

With the Rosenkranz Prize, Andrews is also able to develop a simple, rapid, molecular diagnostic or cholera that is 10 times more sensitive than the tests currently available. Andrews plans to test this new technology in Nepal.

The Rosenkranz Prize has allowed two individuals dedicated to helping healthcare in developing countries by providing the necessary funding. With the help of Alsan, girls may be able to attend school without worrying about ill siblings, and Andrews has shed light on the problems facing many developing countries when providing medical help. But by further developing the diagnostic approaches available, healthcare will change for the better.

– Kerri Szulak

Sources: Scope, Stanford
Photo: PickPik

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How Carbon Can Power Solar Energy

carbon
According to the World Bank, renewable and efficient energy are key to overcoming global poverty. Researchers have recently found that carbon-based materials can offer some of the most effective sources of renewable solar energy.

The first source is an all-carbon solar cell developed by researchers at Stanford University. As the name suggests, the cell uses carbon to replace traditional silver and indium tin oxide, which are far more expensive.

What proves most beneficial about the cell is the consistency. The prototype is a thin film, and because of this, it can be placed on top of existing equipment to gather energy. This means new windows or panes do not need to be retrofitted to the new design. Instead the film can simply be placed on top and the energy will generate.

The product is still in the developmental stages, thus not yet reaching the levels of silicon solar panels. This is partially because the carbon-based material needs infrared light to function. While this is problematic, researchers are confident that they can adjust the material to make it a potent form of energy that can be used around the world.

Another carbon-based material has also been found as an excellent steam generator. Solar-powered steam is effective for electricity, but there are other uses that make it ideal for areas of the world whose only natural resource is sunlight. These include refrigeration, sterilization, chemical purification and waste treatment.

Despite its many beneficial uses, it will be hard to pass these on at a commercial level. While it might take a while, it seems that the researchers at MIT are confident about solar energy.

The verdict on both of these carbon-based materials seems to be similar: they can be quite effective but are still in nascent stages. However, the research that has happened up to this point has proven to be very promising. Researchers have looked into several different solutions to each of the unique problems posed.  The big incentive backing it should be enough cause to act.

– Andrew Rywak

Sources: The Economist, Scientific American, Gizmag
Photo: Gizmag

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Design for Extreme Affordability

design for extreme affordability
Design for Extreme Affordability, a graduate course offered by Stanford University, aims to give students the tools needed to “design products and services that will change the lives of the world’s poorest citizens.”

Offered by the university’s Institute of Design, 40 students from a variety of different disciplines complete the course each year, producing ten final projects that aim to achieve cheap solutions to serious global problems.

They are taught design and marketing principles, form student teams, collaborate with local partner organizations, travel to their project sites, prototype and test their products and present their final projects product proposals. According to the Stanford course website, emphasis is placed on “design for the developing world, including economic, technological and cultural considerations.”

When the course is completed, many students actually fulfill their proposal and see their idea through to completion. In fact, a considerable number of Design for Extreme Affordability projects have found global success.

For example, Embrace, an international nonprofit maternal and child health organization, was created as a result of the course. The Embrace Warmer, the organization’s central product, is a low-cost innovation to help care for premature infants in developing countries.

Usually, the solution for premature infants is to place them in an incubator until they are able to regulate their own body temperature. However, incubators are expensive and require electricity, training to use and maintenance. Consequently, mothers in less-developed countries must find different methods to save premature infants from hypothermia. They often resort to using fire, light bulbs or hot water bottles, all of which are dangerous and ineffectual. There was a clear need for an affordable, non-electric and safe method to keep infants warm.

This was the challenged posed to one team of graduate students taking the Design for Extreme Affordability course, and the Embrace Warmer was its result. The price tag is under 1 percent of the cost of a standard incubator, and its wraparound design is durable, portable, safe, hygienic and very effective.

The Embrace team’s idea has blossomed into an international organization that has reached over 50,000 infants across the world and made a real impact.

Stanford’s Design for Extreme Affordability is not just another school project. It is an intensive year where dedicated and motivated students–with support from expert staff–create practical solutions to life-threatening global problems.

With the courses direction, students have been able to consistently create innovative products that are making a difference in the world today. Hopefully the course will continue to inspire the university’s gifted students to direct their talents toward the global community.

– Emily Jablonski 

Sources: Embrace Global, Huffington Post, Stanford
Photo: Stanford Daily

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