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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 

Artificial Intelligence Helps the Impoverished
Artificial intelligence has evolved from a futuristic fantasy to our living reality. The possibilities for artificial intelligence-based solutions are continuously developing. Therefore, the potential to expand the reach of various initiatives to help those in poverty is increasing. Recently, companies have recognized that artificial intelligence helps the impoverished by contributing to various sustainability initiatives in impoverished countries. The globally impoverished disproportionately suffer from the negative impacts of environmental issues. Artificial intelligence can help those in poverty restore a sense of empowerment in struggling communities.

How Artificial Intelligence Helps the Impoverished with Sustainability Goals

  • Wadhwani AI – The focus at Wadhwani AI is to bring artificial intelligence to communities in need (and thus that are the least likely to have access to artificial intelligence). One of their current projects focuses on cotton farming. Cotton is the third-largest crop in India with 75 percent grown by small farmers who struggle to have a stable income. Pests are a huge problem for small farmers for both economic and mental health reasons. After 40 percent of cotton crops were destroyed by a pink bollworm attack between 2017-2018, 100,000 cotton farmers committed suicide. As many pesticides have proven unreliable over time, Wadhwani AI is developing technology to detect pests, reducing crop losses and pesticide use.
  • GringgoRecycling collection is incredibly limited in impoverished areas. Generally, only 40 percent of trash is collected in South East Asia. Gringgo, based in Indonesia, uses an app to help collect plastic waste. The app connects waste collectors to uncollected recyclables in their area that can be sold for a profit, increasing income for waste workers and cleaning up waste simultaneously. Recycling facilities purchase these recyclables and convert them into various commodities. For example, plastics can be converted into fuel for the cement industry. Selling waste back to recycling industries (effectively taking it out of the waste stream) reduces ocean pollution, as many landfills are located near rivers, causing much of the collected waste to end up in oceans. Gringgo aims to increase recycling rates by 50 percent by 2022 and reduce the plastic in oceans by 25 percent by 2020 in South East Asia.
  • Makerere University – Air pollution causes more than 700,000 deaths in Africa yearly. Additionally, 98 percent of cities in low and middle-income areas do not meet air quality guidelines. Finding solutions to reduce air pollution is imperative. Based in Uganda, Makerere University demonstrates how artificial intelligence helps the impoverished by aiming to improve air quality. By using low-cost technology, Makerere University hopes to obtain more data on air pollution and the communities most at risk. Sensors attached to taxis around Uganda track pollution and will ultimately forecast future air pollution rates. Policymakers will use this data to make informed decisions regarding industrial changes to reduce air pollution. As data on air pollution rates in specific communities is currently lacking. However, this study could raise awareness among citizens about the unhealthy pollution rates in their own communities.

AI expansion is inevitable; it is already happening. While there are many possibilities for how artificial intelligence can help the impoverished, companies may also question the ethics of new technologies and possible impacts. That being said, it is clear that artificial intelligence can help those in poverty when paired with an open dialogue with those involved in terms of how to help.

– Amy Dickens
Photo: Flickr