Artificial Intelligence and Disaster ResponseNatural disasters are a phenomenon that affects countries around the world. The World Health Organization reports that more than 160 million people are affected by natural disasters annually. Estimates from the World Bank also suggest that 26 million people are forced below the poverty line annually due to natural disasters. Technological advancements with artificial intelligence (AI) aiding natural disasters may help countries with their response to such catastrophic events and help reduce these detrimental effects.

Natural Disasters Contributing to Poverty

Across the globe, poorer communities are more negatively affected by natural disasters than wealthier communities. Natural disasters have the potential to cause a major loss of income due to damage to infrastructure, crops, or a decrease in demand and tourism. This loss of income is more significant for those in the low-income category as they have fewer resources to begin the rebuilding process, potentially causing long-term poverty.

History shows that major natural disasters widen income inequalities. After the 2011 floods in Australia, low-income individuals lost an average of $3,100 AUD ($2,141 USD) per year. This lower income was typically maintained for five years after the natural disaster. Contrastingly, middle and high-income individuals gained over $3,300 AUD ($2,280 USD) annually for those five years. This was because emergency aid was more oriented to businesses rather than households, and the wealthy are more likely to own businesses. This example illustrates how low-income individuals are more vulnerable to being pushed into poverty due to a natural disaster.

The U.N. reports that, globally, the largest loss of life due to natural disasters occurs in poor communities. This may be a result of the fact that low-income individuals tend to live in geographical areas that are more prone to natural disasters. Additionally, those who are low-income tend to live in poorly constructed, fragile housing. This was observed in 2010 when an earthquake hit Haiti, where the largest loss of life was in a fragile and over-crowded housing facility, located in a poor community.

Artificial Intelligence Improving Disaster Response

AI is skilled at analyzing and tracking weather patterns to help predict the course and severity of natural disasters. However, technology has previously struggled to accurately predict earthquakes. Geophysicist Paul Johnson has assembled a team to use machine learning to predict these natural disasters. Machine learning uses technology to track data and identify similarities and patterns that occur prior to an earthquake. AI technology will then be able to analyze these characteristics to preemptively detect earthquakes. Johnson’s team has successfully used AI to predict earthquakes in a controlled laboratory setting. This technology would allow the opportunity for civilians to evacuate prior to an earthquake, decreasing injury and loss of life.

The application of this technology will resultingly allow for improved personnel and resource management once the natural disaster is detected. AI technology can now use geospatial observations to identify locations where people may move to during the natural disaster. This will allow officials to accurately complete rescue missions and send supplies to people who have relocated.

This technology will also help model which areas will be most affected by a natural disaster. AI can predict which buildings and roads will sustain the most damage throughout the disaster. This knowledge allows officials to re-route resources and response personnel to more appropriate areas. AI modeling will result in faster response times and more strategic access to affected areas.

McKinsey and Co. is an organization that uses technology to aid disaster relief efforts as a part of its Change That Matters initiative. McKinsey and Company’s AI uses satellite data and an algorithm to assess the damages sustained to a certain area. This allows for the responsible distribution of resources to help rebuild vital community services such as schools and medical facilities.

AI and Poverty Relief

AI is a tool that can be applied to many areas of life. The use of technology and AI is crucial in predicting natural disasters and improving aid responses after the disaster. These abilities and their effects lead AI to have the potential to play a major role in decreasing the number of people who are forced into poverty due to natural disasters.

– Laura Embry
Photo: Pixabay 

AI Improves FarmingOnce a far-fetched, abstract idea, artificial intelligence is now proving to be a valuable asset in solving world hunger. Although AI is still in its earlier stage of development, progress is being made by corporations and university programs such as Google and Stanford University’s Sustainability and Artificial Intelligence Lab. No longer merely science fiction, now AI improves farming, helps identify disease, predicts crop yields and locates areas prone to scarcity.

FarmView Increases Sorghum Yields

Researchers from Carnegie Mellon University created FarmView to help solve the issue of a rapidly increasing population. By 2050, over 9.8 billion people will live on the planet, making food scarcity a topic of increasing importance. Additionally, CMU wants to help current farmers grow more food using the same amount of crops. And as AI improves farming methods, CMU believes it’s a possibility.

CMU is working with plant scientists and agricultural leaders to develop and deploy a system of AI, sensing and robotics technologies to improve plant breeding and crop management. One aim is to increase yields of drought and heat resistant sorghum–a crop that can thrive in famine-stricken countries. Researchers first collect data with drones, robots and stationary sensors. Then, machine learning technologies analyze the data to determine what factors yield more sorghum.

Agricultural Improvement with Google’s TensorFlow

Another AI technology created to help the agriculture industry is PlantMD. Created by high school students Shaza Mehdi and Nile Ravanell, PlantMD is an app that allows a farmer to detect plant diseases.  Mehdi and Ravanell built the app using Google’s TensorFlow, an open-source machine learning library.

Inspiration for PlantMD came from Nuru, an app built by a research team at Penn State University called PlantVillage in tandem with the International Institute of Tropical Agriculture.

Nuru was created as a solution to disease and pest susceptibility in cassava, a crop that feeds half a billion Africans daily. Because it is difficult for farmers to inspect and manage every crop, machine learning is being used to increase efficiency. First, a machine learning model was trained using thousands of classified cassava images. The model was then turned into an app where farmers can send images of their crop and receive information not only identifying diseases but also giving options to manage them. With this information, vital African agriculture can be better sustained to feed people.

Stanford University’s Research

Similar to PlantVillage and the IITA, Stanford University is utilizing machine learning in order to understand and predict crop yields in soybeans. But these models may be expanded to help underdeveloped countries.

Marshall Burke, an assistant professor of earth system science at Stanford, said: “If we have a model that works for U.S. soybeans, maybe we can train that model for areas with less data.”

Machine learning can also identify areas in underdeveloped countries suffering from food scarcity. Because these countries often lack reliable agricultural data, machine learning technology is extracting information from satellite images to discover areas where agriculture is suffering.

Solving the World’s Problems with AI

Google’s open-source TensorFlow allows machine learning technologies to be applied to agriculture. Moustapha Cisse, lead of the new Google AI center in Accra, Ghana, mentioned how farmers use TensorFlow-based apps like PlantMD and Nuru to diagnose plant diseases. Cisse said: “This wasn’t done by us but by people who use the tools we built.” Although not everyone owns a phone, it’s an excellent step in demonstrating the possibilities of AI in reducing poverty. And as AI improves farming, it brings us another step closer to reducing world hunger.

Lucas Schmidt
Photo: Flickr

No technology is inherently good or bad; rather, it is humanity’s use of that technology that can be evil or virtuous.  Certain modern tools seem only capable of carrying out despicable or ultimately evil deeds as controversy surrounds them, and their names evoke fear. Artificial intelligence (AI) and drones are two of the most widely commented on and feared applications of modern science. Despite the prevailing negative perceptions, AI and drones are also used for a good cause: combatting poverty.

Unequal Scenes

Although drones, or UAVs (unmanned aerial vehicles), are often used in violent attacks and warfare, they and their human operators are doing wonderful things across the world. Photographer Jonny Miller used drones to capture cityscapes and the line dividing the rich and the poor. He captured images of lush, green golf courses directly up against dirt roads and shack neighborhoods. Giant mansions can be seen with trees and acres of grass next door to brown areas with buildings packed into a small plot. Miller’s project “Unequal Scenes” is raising awareness about poverty and inequality which would be impossible without drone photography.

The Problem of Land Ownership

More than half of the world’s population, usually women, cannot prove that they own their land. This is especially problematic in the country of Kosovo, where most of the men and boys were murdered during the Balkan wars of the 1990s. The women who remained have worked tirelessly to rebuild their homes and communities, but they face an enormous roadblock: the inability to use their vast land resources to provide for themselves economically. These women do not have any sort of documentation for their lands once owned by their husbands. One woman explained that she had applied for loans to build her business but was repeatedly turned down because she lacked what the government called “property documents to put down as a guarantee.”

These communities do not have the means to hire land surveyors necessary for official registration. Property owners with potentially good, profitable land are powerless without official documentation. However, drones are helping these women. The World Bank Group’s Global Land and Geospatial unit dispatches drones to map out land plots. Drones survey and map for a fraction of the cost of traditional means, giving the Kosovan women the ability to register their lands and ultimately invest in their own property.

The Positive Impacts of AI

Artificial intelligence (AI, also referred to as “machine learning”) refers to a machine’s ability to imitate intelligent human behavior. AI is often associated with 1980s movies about robots destroying humanity based on a real fear that one day the machines will become self-aware and grow tired of serving humanity; “the development of full artificial intelligence could spell the end of the human race,” warned Stephen Hawking in 2014. Despite this apparent destructive potential of AI, it is currently transforming agriculture and changing the African business environment in the real world.

One writer argues that Africa is amid the “fourth industrial revolution … ushered in by the power of AI.” Many innovative African business leaders have embraced AI to improve productivity and efficiency. One example is a Moroccan company which uses AI to perform analytics on data sent from devices on motorcycle helmets. This improves riding habits and provides more accurate insurance premiums, reducing costs and improving safety for riders. Another instance involves an Egyptian manufacturer using AI to automate certain processes and reduce overall error while improving quality of service, which ultimately reduces the cost to the consumer. Finally, one Algerian firm helps local doctors provide cancer detection and treatment for their patients. The firm uses AI to create models that can diagnose those who are unable to visit hospitals for formal examinations. This has the potential to save the lives of many who don’t have the means to get regular checkups and screenings.

In addition to previous models, AI is also reducing overall costs for farmers and helping to improve their yields in India. Certain Indian dairy cows are given radio-frequency identification tags that transmit important information about the cows’ diets and overall health to cloud storage where it is “AI-analyzed.” The farmers receive alerts about any potential issues of the cows that require their attention. This can reduce costs and increase efficiency for the farmers.

These are just some of the ways that technology often labeled as “bad” is being used for good, especially in the fight against poverty. Cases like these prove that technology cannot be inherently evil and that there are good uses for AI and drones. While some individuals use modern equipment to destroy the world, there are plenty of men and women using the same tools to improve it.

– Sarah Stanley

Photo: Flickr

Artificial Intelligence and Poverty

Artificial 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