Famine Action Mechanism
The World Bank has discovered a new approach to helping the 124 million people currently affected by crisis-levels of food insecurity: artificial intelligence.

Three international organizations: the World Bank, the U.N. and the International Committee of the Red Cross, have partnered with three of the world’s largest tech giants: Microsoft, Google and Amazon, in a joint initiative to preemptively address world hunger. The result? It’s called the Famine Action Mechanism (FAM).

What is Famine Action Mechanism?

Launched by U.N. Secretary-General António Guterres on September 23, 2018, in New York, the Famine Action Mechanism seeks to improve international food aid through famine prevention, preparedness and early action. FAM is being created to augment the capability of existing warning systems to effectively distribute aid prior to the emergence of famine. This is being done through the establishment of official procedures that connect early warnings with financing and implementation.

With the cooperation of humanitarian development organizations, tech companies, academia, the insurance sector and, of course, international organizations, this collaborative effort hopes to see success through the investment of a wide variety of stakeholders.

While other forms of famine prediction, like Famine Early Warning Systems Network started by USAID in 1985, already exist, it lacks the ability to give real-time data and requires the hard work of hundreds of employees.

If successful, the Famine Action Mechanism will be the first quantitative modeling process using an algorithm to calculate food security in real time.

Hope is high for executives at Google and Microsoft who have seen the humanitarian power of technology firsthand. Advanced technologies have already proven effective in helping farmers to identify the disease in cassava plants as well as keeping cows healthier and more productive. President of Microsoft, Brad Smith, has expressed that artificial intelligence holds huge promise in forecasting early signs of food shortages.

How is FAM going to be implemented?

Famine Action will be implemented through four steps:

  1. Early warning systems. Microsoft, Google and Amazon web services are coming together to develop a set of analytical models known as “Artemis” to predict cases of famine using artificial intelligence and machine learning that detect correlations between different risks. With more powerful early warnings and information in real time, this will allow aid agencies to create a faster response and preemptively halt escalating insecurity.
  2. Pre-arranged financing. Syncing the early warning system with pre-determined finances helps to prevent food insecurity because it secures funding before a situation devolves into a crisis. The financing for this program is not only set to tackle the immediate symptoms of poverty and famine but also help the community to build safety nets and coping skills to encourage local development in hopes of preventing repetition in the future.
  3. Increasing resource efficiency. The Famine Action Mechanism plans to partner its resources with existing systems to reinforce the most effective and efficient efforts that are already working on the ground. This way, it will be producing a joint response system with the organizations involved with the program.
  4. Stressing preventative and preparedness approach to global famine crises. International Organizations like the U.N. and World Bank are redefining their approach to food insecurity, poverty and famine, making a proactive system of action rather than reactive aid a top priority of their efforts.

Isn’t Famine Pretty Easy to Predict?

While seemingly slow to take place, the cause of famine, defined as a daily hunger-related death rate that exceeds 2 per 10,000 people, is extremely complex.

The usual suspects of food insecurity like drought and crop production aren’t always the forces that bring a community to famine. Other factors like political instability, inflation or a natural disaster have the potential to significantly alter a community’s food supply. Additionally, nine of the last 10 major famines were triggered by conflict and war.

The uncertainty around when and how an undernourished community shifts into a crisis of famine adds to the importance of preemptive action for food insecurity and the demonstrated need for the Famine Action Mechanism.

Hunger in the World Today

After years of progress on decreasing hunger in the world, we have backtracked on those advancements with more than 820 million undernourished people in 2017. Approximately 155 million children will see the effects of stunting for their entire lives due to chronic malnourishment as well as a reduction of up to 13 percent of their lifetime income. Additionally, last year in Nigeria, Somalia, Yemen and South Sudan, more than 20 million people faced famine or near crisis levels of food insecurity.

One in nine people in the world today do not have enough to eat, but that does not mean we cannot get back on track. Not only can early response to famine result in saved lives and decreased suffering, but it is also cost effective. The World Bank predicts that an earlier response rate can reduce humanitarian costs up to 30 percent.

In 2017, the World Bank President Jim Yong Kim and U.N. Secretary-General Antonio Guterres pledged to have zero tolerance toward famine, and in the declaration of this program that pledge has been renewed. In the eyes of the United Nations, the success of the 2030 Agenda for Sustainable Development means ending hunger everywhere for everyone.

To conclude, in the words of Mr. Guterres: “Crisis prevention saves lives. We need to put cutting-edge technology to full use, in the service of all humankind in order to feed everyone in our world and to leave no one behind.”

– Sara Andresen
Photo: Flickr

The Accomplishments of Artificial Intelligence in Alleviating Poverty
In the first half of the twentieth century, Artificial Intelligence (AI) revolved around just science fiction movies but it has come a long way since then. From presenting targeted ads based on one’s Google search history to SIRI and self-driving cars, AI has made progress in various socioeconomic issues as well.

Medical Accomplishments of Artificial Intelligence

One of the most remarkable breakthroughs of AI and machine learning is in healthcare applications. People are using various apps to learn more about themselves and lead a happier and healthier life.

  1. Autism & Beyond App: Recent research shows autism can be detected as early as 18 months old using AI, while previously the disease could not be detected before five years of age. The app Autism & Beyond can study a child’s emotions and behavior from their expressions and understand a child much better to provide early effective treatment.
  2. EpiWatch: This app has been very helpful for patients with epilepsy as it accurately helps measure the body’s vitals during the onset and duration of a seizure in real time. EpiWatch then learns from this data and can predict whether such seizures are imminent. Once the accelerometer and heart rate sensors are triggered, the caregiver or a family member is alerted so there is enough time for the patient to receive immediate help.
  3. Concussion Tracker: This app helps monitor a head injury for a consecutive six weeks by tracking the heart rate and recording other physiological and cognitive functions. It helps to figure out how fatal the concussion is and its possible consequences.
  4. Tumor Detection: Doctors can easily detect a tumor in the brain but quantifying exactly how big it has long been difficult. Microsoft’s Inner Eye has made this possible and has helped accelerate the time of the treatment.

Advancements in AI for Agriculture

Apart from Medical Science, accomplishments of Artificial Intelligence in the fields of agriculture have become widespread. Agriculture is not just old school farming anymore. High tech agriculture starts with variable rate planting equipment that helps identify where a seed will grow best and in what soil conditions it will grow better, thus making farming more efficient than it has ever been. Various AI-based robotic harvesting equipment has also been invented which helps to harvest crops like fruits and berries.

Global Fishing Watch is also one of the many accomplishments of Artificial Intelligence, which has helped stopped illegal fishing across the ocean. Over three billion people depend on seafood for protein in their diets. The global economy loses $83 billion every year to illegal fishing and poor fishery management.

Global Fishing Watch has brought more transparency on the fishing location and behaviors of commercial fishing fleets from every corner of the ocean through processed data sets and fishing activity maps with 95 percent accuracy. Indonesia is the first nation to show its results and, already, multibillion-dollar fines have been charged from the evidence gathered.

AI Combating Global Poverty

Artificial Intelligence has also been a game changer to help predict poverty and fight hunger. Tracking poverty in various places through household survey-based data collection was expensive so AI came to the rescue. In recent years, scientists have tried to identify rich or poor regions by studying nighttime satellite photos on the basis of which places glow brightly.

However, this approach came with a limitation: it could not differentiate between places suffering from near-poverty and those with absolute poverty. A research group at Stanford University recently fed the computer both nighttime and high-resolution daytime satellite images of five countries in Africa along with the household survey data. The device found features like concrete buildings, well-developed roads, agricultural regions and urban areas which helped predict poor places with 81 to 99 percent accuracy. United Nations claims this to be one of the biggest accomplishments of Artificial Intelligence.

Many times, the media focuses on the negative sides of AI but scientists are hopeful that the accomplishments of Artificial Intelligence will do more good than bad. With many more advancements to come, the socioeconomic status of the world is sure to change for the better.

– Shweta Roy
Photo: Google

Technology out of India

India’s reputation for outsourcing has grown over the last 30 years. However, India’s market has dropped due to the recent change in the U.S. political climate and the development of artificial intelligence and automation systems. While things look uncertain now, there is still a strong case for the technology out of India.

Opportunity for Growth

India has been called the “new China” for many companies looking to expand consumer bases. Corporations like Google, Facebook and Twitter have largely been banned from China’s market, which is why India provides an important opportunity. The technology out of India would have been unheard of ten years ago, but now with the ballooning smartphone users (hitting 168 million Indian users in 2015) and internet users (around 277 million Indian users as of 2017), an environment for phone applications, mobile payments, social media sites and more are growing.

The big corporations have moved in despite challenges. One such hurdle was the Indian government requesting more than any other country that Facebook remove information (10,792 times in 2014). This change in technological circumstances has opened channels for local Indian companies to develop as well. A 2016 National Association of Software and Services Companies reported India ranked 3rd largest for startups. While there is still some gender inequality with less than 10 percent of Indian entrepreneurs and engineers being women, there is an awareness of the inequality, thus creating an opportunity for change.

Replacing IT Jobs

The IT sector brings in almost 10 percent of India’s gross domestic product (GDP) and all trajectories showed growth, but recent layoffs in the industry have caused some question of India’s ability to create a job market and grow. The wave of recent layoffs, estimated to be around 56,000 over the last year, is assumed to be due to automation in a lot of the industry along with U.S. President Trump’s campaign of focussing jobs in the U.S. and cutting back H-1B visas.

Around 60 to 70 percent of jobs in the IT and call center industry are expected to be replaced by automation systems. The layoffs are expected to hit a high of 480,000 by 2021. This makes it difficult as 12 million Indians enter the workforce every year, but only about 135,000 jobs were created by India’s eight biggest sectors, including IT, in 2015. Pankaj Bansal, a chief executive with People Strong, believes the IT sector will hit a net of zero hires in the future unless something changes.

Returning Home

Even with layoffs, many Indian engineers and entrepreneurs are leaving the U.S. to return home and pursue careers in India. Experts estimate the migration home to be in the tens of thousands. Indians are returning home to pursue opportunities closer to family and where their salaries will go farther than in the U.S. The migration back to India shows the job market is still open and available for more technology out of India. Although India’s average GDP has slowed recently, it has still grown tremendously in the past compared to other countries, like the U.S. India’s GDP grew 7.3 percent from 2010 to 2014 while the U.S. GDP only saw a 2.2 percent increase. 

Electronic Payment

A particular segment of the IT sector worth noting is electronic payments. The use of electronic payment is growing in Asia as a whole and many are trying to bring India to a place of acceptance for mobile payment applications. Paytm (an Indian mobile payment technology out of India) in particular plans to invest $1.9 billion over the next two years to make this the electronic payment method the future of India. Only about one-third of citizens have access to the internet, and of those who do, only about 14 percent are making an average of one electronic payment a week. Plus, there is a trust issue from reports of hackers stealing money from Paytm accounts.

Two years ago India was all over the news for being the next China, but many have decreased their expectations and predictions after recently reduced job opportunities. While India is currently facing challenges, if it can find growth prospects, particularly locally, there should be no reason to be unable to turn layoffs into job possibilities.

– Natasha Komen

Photo: Flickr

Using AI to Fight Against PovertyDiscussions about artificial intelligence (AI) often center around one of two ideas: the first looks at the exciting prospect of driverless cars and other advanced technology. The second investigates the irreversible rise of AI and how it could leave an entire socioeconomic class jobless. But it is time to initiate a third discussion around AI: specifically, using AI to fight poverty and helping 3 billion people around the world.

AI is on the Rise

Deputy Secretary-General of the U.N. Amina Mohammed said the greatest global challenge today is eradicating poverty. The elimination of poverty worldwide is the main U.N. Sustainable Development goal, and AI is making this problem easier to solve. So pressing is this issue that the XPRIZE Foundation announced a $5 million prize for projects that are using AI to fight poverty and tackle socio-economic challenges.

Stanford Poverty & Technology Lab is a prime example of the recent proliferation of companies and incubators dedicated to finding technology-based solutions to poverty and gross inequality. “Poverty and economic immobility is clearly a huge problem in the U.S.,” said Elisabeth Mason, founding director of the Stanford Poverty & Technology Lab. “It’s time that we get serious about designing 21st-century solutions.”

AI is Adaptable

While the expansion of AI may threaten blue-collar jobs, the data-mining abilities of AI could also be used to speed up job searches and predict which skills and training will be needed for them. Using AI to fight poverty extends beyond curbing unemployment levels.

AI could also provide the poor with a quality education that responds and adapts to the users’ specific needs. “Access to information has always been a big differentiator with poverty,” Mason said. “If we can use the right tools and develop the right programs, we’re looking at a different world.”

AI could help address or predict some of the primary causes of poverty, including food shortages, epidemics, illiteracy and natural disasters. In times of natural disaster, AI is widely used to determine the location of casualties by analyzing social-media communication and parsing satellite and drone imagery. Scientists at Stanford are using AI and satellite remote-sensing data to anticipate food shortages by accurately predicting crop yields months in advance.

AI is Helpful in Agriculture

Predicting crop yields is not enough, though. Data provided by the World Bank shows that 65 percent of poor working adults make a living through agriculture.

Technology companies such as FarmView are working to solve the global food crisis by improving the agricultural yield of various stable crops. Sorghum is a valuable cereal crop in developing countries, India, Nigeria and Ethiopia in particular, that could be cultivated more efficiently with the help of AI. The highly sophisticated and selective crop breeding that exists in the U.S., with valuable foods like corn, does not exist in developing countries.

FarmView utilizes AI and four-wheeled robots to drive through fields to measure everything from potential signs of disease to plant color, shape and size in order to give poor farmers the “information they need to cultivate the most nutritionally-packed crop of sorghum possible for their environment —at the highest possible yield.”

These are some examples of the ways AI is making the world a better place not just for the affluent but for those in need, too. While advancements in AI technology will no doubt present us with moral, ethical and socio-economic challenges, it is also one of the most promising tools to end extreme poverty and stimulate economic growth. Using AI to fight poverty can once and for all help bring an end to what is widely considered the greatest challenge facing mankind.

– Johnny Harounoff

Photo: Pixabay

Indian farmers use AIIndia is an agrarian economy and over 58 percent of the rural households depend on agriculture as their principal means of livelihood. With the recent help of tech giant Microsoft, Indian farmers have begun to use AI to increase efficiency, further encouraging them to harvest a good crop.

Every year since 2013, more than 12,000 suicides have been reported in the agricultural sector with 10 percent accounting for farmer suicides. Collectively, seven states (Maharashtra, Karnataka, Telangana, Madhya Pradesh, Chhattisgarh, Andhra Pradesh and Tamil Naidu) accounted for 87.5 percent of the total suicides in the farming sector. Additionally, the reasons for farmers’ suicides have varied widely including high input costs, low yields, disintegration with markets, mounting loans, water crisis and urban consumer-driven economic policies.

In partnership with the International Crop Research Institute for the Semi-Arid Tropics (ICRISAT), Microsoft developed an AI-sowing app. With the app, Indian farmers use AI to increase their agricultural income, giving them greater price control over their crop yields.

On his two-day visit to India in 2017, Microsoft CEO Satya Nadella highlighted the benefits of AI in agriculture. In an interaction with Microsoft engineers in India, Nadella said, “Taking AI to the oldest industry on our planet, agriculture, is something we have already been doing in collaboration with local stakeholders like ICRISAT, which just at a little distance away from the campus. If you can increase the yield [with the help of AI] in agriculture, the kind of impact it will have on economies like India will be huge.”

The beta version of the new sowing application was tested in June 2016 in Kurnool district of the Indian state Andhra Pradesh and was applied only to the groundnut crop. The results showed a 30 percent higher average in yield per hectare. The pilot also confirmed that the advisories received through the app via SMS were relevant and accurate. The sowing app provides the best times to sow depending on weather conditions, soil and other indicators, relieving Indian farmers from inaccurate forecasts.

The app relies on business intelligence tools that give clear insights on the soil health, fertilizer recommendations and seven-day weather forecasts powered by the world’s best available weather observation systems and global forecast models.  So far, Indian farmers use AI-powered apps in a few dozen villages in Telangana, Maharashtra and Madhya Pradesh.

Powered by Microsoft Cortana Intelligence Suite, the app provides updates to Indian farmers. Indian farmers use AI for sowing recommendation, seed treatment, optimum sowing depth, preventive weed management, land preparation, farmyard manure application, recommendation on harvesting, shade drying of harvested pods and storage. The SMSs can also be delivered in regional languages like Telugu and Kannada. Through a basic phone capable of receiving text messages, farmers can use AI with no capital expenditure.

Microsoft’s next collaboration could help farmers fight pest risk. In collaboration with India’s largest producer of agrochemicals, United Phosphorous (UPL), Microsoft aims at leveraging AI and machine learning to calculate the risk of pest attack.

But interestingly, Indian farmers are not oblivious to digital farming. In the past, Tata Consultancy Services (TCS) Innovation Labs introduced mKrishi, which allowed farmers to receive advice on pest information, crop prices, weather conditions and more in their local languages.

Tech innovations and partnerships like that of Microsoft and TCS could help Indian farmers with information that is more data-driven and based on pure analytics. Whether such efforts lower the suicidal rates of Indian farmers or not is yet to be seen. But if the results are positive, it will be a boon to many agriculturally reliant Indian households that have faced huge losses.

– Deena Zaidi

Photo: Flickr

Artificial Intelligence and PovertyArtificial intelligence (AI) has forever changed the way society interacts with technology. It has provided limitless opportunities for problem-solving in the last decade, and the relationship between artificial intelligence and poverty reduction may be one worth fostering.

In 2007, the iPhone had first made its appearance on the world stage. Since its release, phone-based computer programs (apps) have evolved from simple games like Space Invaders: Infinite Gene, to industry-upsetting business models like Uber.

Since apps began to use algorithms to create relatively simple artificial intelligence (AI), computation has become vital to leading businesses and organization. Ten years ago, AI was almost entirely task-based, but a new form of AI—known as deep learning—has garnered more attention in the past few years.

Instead of a programmer telling how a certain machine should do a task, deep learning AI uses neural networks which actually teach the computer (or other deep learning AI) how to complete tasks in the most efficient manner. What makes it so special is that deep learning is faultless, and, with enough computation resources, can learn things faster than humans.

Does this finally mean that the age of robots is upon us? The easy answer is yes. Deep learning machines have now outplayed people in chess, Go (widely considered to be the most complex game in the world) and are possibly are going to try to beat humans at StarCraft, a multiplayer video game. But AI can disrupt the world’s economy in significant ways. Corporations use it to trade in the financial sector; write articles for newspapers; diagnose health disorders and diseases and do manual office work. It has even recreated a Nobel prize-winning physics experiment.

In the last decade, we have discovered that deep learning AI and AI has infinite potential. So, the question goes, how will artificial intelligence and poverty correlate? Can AI reduce poverty? In general, it should. Never in the history of mankind have we let machines do this type of work for us, so we have no precedents to build off of. Additionally, because deep learning machines are only just coming onto the marketplace, new obstacles may appear as we continue AI research.

However, people are beginning to harness this extremely powerful tool for the poor, and the work sounds promising. At the moment, AI is especially useful for data mining simple statistics: which areas need more development, which people require more education and how they can receive it, etc. Having to collect this data manually would be a time-intensive task that would also be incredibly expensive.

However, there are also more complex uses for AI, such as agricultural research for poor farmers. Tech giant IBM is working on an operations research robot that will optimize transporting food aid around the globe. Improvement of artificial intelligence and poverty reduction are thus parallel goals for these major corporations.

In addition, IBM is also working on a novel illiteracy project. If eventually implemented, it will allow people to learn how to read without the assistance of a teacher by having a computer analyze something that a student of any age might find in their daily life (such as a flower). The computer would then display the written word while playing the sound for it. This would allow people to learn how to read wherever they are, whenever they have time.

Of course, these are all leading edge uses when talking about artificial intelligence and poverty. While engineers continue to work on the technical aspects of the technology, the U.N. is preparing for the change in methodology in battling poverty by holding AI summits. Twenty U.N. agencies have and will continue to discuss issues pertaining to the Millennium Goals and the Sustainable Development Goals in relation to AI.

The potential to significantly diminish poverty with these new technologies is very high. It might take humanity decades before AI is actively fighting poverty, but when it does, it will most likely help eradicate it.

One main challenge of AI is to make sure that we can control it. Futurologist Elon Musk, along with world renowned physicist Stephen Hawking and many AI experts have signed an open letter warning the U.N. against the use of AI-powered weapons, as they can potentially develop their own ethics standards and kill humans ceaselessly, regardless of their affiliation. Even though this warning specifically targets militarized robots, it is a cautionary tale: we need to tread carefully when using new technology, which is why AI will only truly take off several years into the future.

Michal Burgunder

Photo: Flickr

AI Solutions
The Artificial Intelligence (AI) for Good Global Summit occurred on June 7, 2017. The International Telecommunication Union (ITU) and XPRIZE hosted the event. Utilizing the Summit’s neutral platform, professionals of all sorts came together to discuss AI solutions. Twenty United Nations Agencies who believe that AI may be essential to ending global poverty backed the summit.

Currently, there are three main AI solutions to global poverty, although there is immense potential for more. These solutions include utilizing AI to point out nations in need, improve agriculture and increase access to education.

A recent development in AI solutions uses satellite images to find areas that require aid. The current methods for discerning this information include household surveys and census data. Although this has been effective in some developing nations, the process is slow and difficult to manage.

Thus, researchers at Stanford University are developing and improving upon “machine-learning” AI that utilizes an algorithm to identify poverty. The algorithm can predict poverty rates with 81 percent to 99 percent more accuracy. With this technology, researchers plan to create a worldwide poverty map that anyone can access online. Consequently, government agencies around the world could monitor poverty and “evaluate the effectiveness of anti-poverty solutions.”

AI solutions also include improving agricultural methods. Up to 65% of poor working adults make their living through agriculture, making its improvement key to reducing poverty. One of the biggest challenges that developing nations face pertains to the identification of and information about their crops. To address this issue, they launched a project called Farmview. Farmview combines AI and robotics to increase the yield of staple crops by collecting relevant information. With this information, scientists could then predict yield and find sustainable crops for any region.

An ongoing project in AI solutions has been towards the improvement of global education. Many open-access computer learning programs are available worldwide, but there is needed improvement as to individualizing education.

Future AI may improve online education programs by learning how to adapt to the user and their specific needs. This includes the improvement of translation programs so that users have access to education in their language. One related project is the Science for Social Good Initiative, which the International Business Machines (IBM) launched. The initiative aims to reduce worldwide illiteracy by using AI to decode texts and convey them through visuals and simple speech.

Global Poverty is a large issue to address, but AI solutions may be able to simplify the process. Through the advancement of AI development and democratization, meeting all Sustainable Development Goals may become more attainable.

Haley Hurtt

Photo: Pixabay

AI to fight poverty
On September 25, 2015, United Nations member countries adopted a set of goals “to end poverty, protect the planet and ensure prosperity for all.” The number one goal to be achieved by 2030 is to eradicate extreme poverty.

Fighting global poverty is a huge battle, and many countries don’t keep data on the frequency and distribution of poverty, which makes it hard to track.

The lack of clear, representative data is what drove students and professors at Stanford University to create the Sustainability and Artificial Intelligence Lab. The lab focuses on many different projects that use artificial intelligence to fight poverty.

Neal Jean, Marshall Burke, Michael Xie, W. Matthew Davis, David B. Lobell and Stefano Ermon started the Predicting Poverty project 18 months ago. The project combines the forces of satellite imagery and machine-learning algorithms to detect places in the world that put off more light at night than others. The Borgen Project had the opportunity to speak with Burke about the work the team is doing.

The logic is that the brighter the lights in an area, the more developed that country is likely to be. Over time, the tracking of “night lights” can give information about where and how extreme poverty is. Using artificial intelligence to fight poverty can also recognize where there are roads, urban areas, waterways, and farmland.

“We are still in the stage of making sure the satellite-based approach works,” Burke said. “We have had great results in five African countries, but still need to know how it works in other countries and whether it can make decent predictions of changes in poverty over time.”

The group has tracked poverty in Uganda, Tanzania, Nigeria, Malawi and Rwanda. The methods used in these countries are inexpensive. By mapping where poverty is most significant, aid organizations can properly distribute help and materials.

Once they have figured out whether the technology can predict changes in poverty, the team hopes to track all of Africa and monitor many other Sustainable Development Goals using technology.

“I think AI could provide some large benefits in regions of the world where we currently have little on-the-ground data about economic well-being — which includes a lot of the developing world,” Burke said. “AI-based approaches can help us measure livelihoods on the ground in these places, and also help us understand which sorts of anti-poverty programs are particularly successful in reducing poverty. “

Madeline Boeding

Photo: Flickr

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

Free Legal AidNot everyone has the option to hire a professional lawyer when they need one. However, Joshua Browder, a student at Stanford University, is helping to make legal advice more accessible than ever through his website DoNotPay, which runs an artificial intelligence (AI) platform to provide free legal aid.

Initially, Browder created the program to contest parking tickets. Because appealing parking tickets is a defined and relatively straightforward process, artificial intelligence is capable of navigating the appeals procedure. People who want to use the program go the DoNotPay website, where the AI asks them a series of questions and then creates a claim letter if appropriate. After launching in London and New York, DoNotPay managed to successfully appeal 160,000 parking tickets, saving a combined $4 million for its clients.

Despite the success of his program, Browder has expanded his ambitions beyond just overturning parking tickets. Earlier this August, he updated his program to provide legal assistance to those recently evicted from their homes in the U.K. His updates are especially relevant considering eviction rates increased by 53% between 2010 and 2015 in the U.K. and are at an all time high currently.

Similarly to the way it approaches parking tickets, DoNotPay starts off by asking recently evicted clients a series of questions. In the U.K., government housing is guaranteed to the recently evicted, but the actual application process for government housing can be complicated, especially if someone is trying to do it on his or her own. DoNotPay helps people craft claim letters for the government housing that they deserve.

Browder hopes to expand the housing services to New York and San Francisco. However, he acknowledges that there are some obstacles to his aspirations. He would have to account for a different set of housing laws in each city; and in places where government housing is not guaranteed, helping the evicted is not as simple as crafting a claim letter to housing that the government is obligated to give someone. Additionally, the massive homeless population of 60,000 in New York might be too large for the AI to handle in its current form.

Critics are also wary of the AI’s ability to handle non-standard scenarios and pick up subtle legal nuances. Of course, a real life lawyer will provide better and more specific advice than an AI. However, Browder still believes that his program can be of use to those who cannot afford a real lawyer.

He also continues to seek other legal possibilities for his program. For example, he wants to update the AI to provide advice to HIV-positive people on their legal rights. Additionally, he hopes to release another update in September to help Syrian asylum seekers.

Despite some of the questions being raised about the efficacy of the AI in dealing with more complex legal situations, Browder’s work could still be an important first step in providing universal legal aid. This use of AI is still in its early stages of development, and as the technology improves, so too should the quality of legal advice.

Edmond Kim

Photo: Flickr