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AI to help studentsIn Ecuador, a country where poverty is a prominent social issue, education stands as an essential pathway out of impoverishment. In a modern world where technology is thriving, combining technology and education is beneficial to the population. Starting January 2021, Ecuador has been using AI to help students understand math to a greater extent.

Higher Education in Ecuador

According to CEIC Data, in 2015, the percentage of adults aged 25 and older with a bachelor’s degree or an equivalent qualification stood at just 12%. Due to the impacts of the COVID-19 pandemic, many higher education students in Ecuador faced learning losses or gaps.

With the help of funding from the World Bank, the Ministry of Higher Education, Science, Technology and Innovation (SENESCYT) in Ecuador started offering “artificial intelligence (AI) assisted academic support in math” to new students starting their higher education. According to the World Bank, “using AI [has] enabled access to large-scale, low-cost academic remediation programs.”

The program has improved math results for students, which will, in turn, increase skills and job opportunities. This is changing the face of Ecuadorian remedial education. The use of AI to help students will help solve any recurring problem of lowered access to face-to-face classes due to weather, lack of transportation or sickness.

Implementation

The conventional method for a school to provide extra courses to pupils with learning gaps was to hire a private tutor after school hours. Most parents had the same issues with their children — the children faced difficulty understanding course work. However, not everyone could afford the privilege of hiring a tutor. But, for those who could, parents found it difficult to ensure that each student would be helped in a customized way that caters to their individual pace of learning.

Now, with the help of technology, students are able to access academic support to improve their performance in math. The new AI-powered learning platform is able to tailor tutoring to students’ strengths and weaknesses and prior learning.

According to a February 2022 article by the World Bank, the portal has provided assistance to “more than 14,000 students in the technical and technological higher education system” since January 2021. With the support and involvement of more than 300 educators, more than 400 technical and technological higher education courses implemented the AI tutoring program.

The Importance

According to the World Bank, as of 2020, 33% of Ecuadorians are living under the national poverty line. Access to education can help to combat poverty. According to UNESCO, “if all students in low-income countries had just basic reading skills (nothing else), an estimated 171 million people could escape extreme poverty. If all adults completed secondary education, we could cut the global poverty rate by more than half.”

In this case, providing students with AI-powered academic support to improve their critical skills will help to lay a foundation that paves the path to greater job opportunities. There is a correlation between education and poverty as education provides the skills and knowledge essential for accessing well-paying, skilled employment opportunities to break cycles of poverty. Because of this, access to good quality education is an antidote to poverty. Ecuador’s use of AI to address gaps in learning stands as a step toward the nation’s future economic prosperity.

– Frema Mensah
Photo: WikiCommons

AI Increases Food SecurityArtificial Intelligence seems like a far-off concept reserved for science fiction. In truth, AI is present in modern life and the advancements in this technology are being used to combat global poverty. Most prominently, computer scientists and engineers are improving the ways that AI increases food security globally. The need for utilizing technology in food security is essential to protect more than 800 million people suffering from hunger worldwide.

Predicting Threats to Food Security

A vital step to protect food security is looking ahead and responding proactively to potential problems. The Nutrition Early Warning System (NEWS) works by gathering massive amounts of data from vast sources to forecast developing situations affecting food supply. NEWS is a perfect example of how AI increases food security with constant improvements in its system to enhance response times to price changes, poor weather conditions for food development and other global crop issues.

The effectiveness of machine learning far surpasses human data collection and these types of technology have already seen success. Through the algorithms created by AI technology, a forecasted drought prevented many Colombian farmers from planting crops that would not have been fruitful. This prediction saved the farmers millions of dollars by avoiding crop loss during the dry spell. Preserving large amounts of money to spend during opportune times is another way AI increases food security and stabilizes supply.

AI Optimizes Agricultural Procedures and Production

People living in rural areas that work in farming communities are usually the most susceptible to extreme poverty. AI can improve working conditions and modernize agriculture to protect vulnerable populations and provide them with upward economic mobility through technology education and increased crop production.

AI robotics is revolutionizing agriculture and crop harvesting robots as well as AI-enhanced drones are increasing production and keeping workers safe. Robotic weed control allows for the proper and safe distribution of herbicides that can be harmful to humans. This also prevents herbicide resistance. In Argentina, drones inspect wheat crops for harmful infections and pests. AI increases food security by diagnosing soil conditions as well. This technology allows workers to implement the necessary strategies for correcting nutrient deficiencies.

The most important aspect of these technologies is that they provide benefits but will not reduce the need for actual workers. Though education in these fields can be expensive, the skills learned will add value and mobilize people out of extreme poverty.

The FAO AI Systems Used for Food Security

The Food and Agriculture Organization (FAO) has implemented two programs in which AI increases food security and improves agriculture sustainability; the FAO’s WaPOR portal and the Agriculture Stress Index System (ASIS). Both systems monitor water usage in agriculture in different ways.

  • The FAO’s WaPOR portal monitors water in the Near East and African regions. It does this through open-source technology that gathers massive amounts of data. Simultaneously, the AI analyzes the data to determine the best water use for different crops and regions and uploads the information in real-time.
  • ASIS works similarly to NEWS. It is a satellite system that works as an early detection system for droughts or other water shortages. ASIS breaks down the information from a global standpoint to each country and region. Doing this allows people to be proactive in their preparation for impending droughts by improving water usage and shoring up logistics of moving aid to an area troubled by food shortages, thereby preventing hunger.

The Future of Food Security

As time progresses, AI will improve and become more common, eventually becoming cheaper and more accessible worldwide. With the rapid advancement in this technology and what is already in place to sustain food security using AI, a hunger-free world is a closer reality.

– Zachary Kunze
Photo: Flickr

AI fights against COVID-19 COVID-19 has endangered the lives of millions of people around the world. Worse, the disease incites greater implications beyond itself. Its impact is threatening to turn back the World Poverty Clock for the first time this century. This would backtrack on the progress made in the past 20 years toward eliminating global poverty. However, artificial intelligence (AI) fights against COVID-19 in two very important ways.

A Basic Overview of AI

Originating in the 1950s, the field of artificial intelligence has become ubiquitous in our everyday lives: from determining our shopping habits to facial recognition to helping doctors diagnose patients before symptoms manifest. The computer performing tasks that we thought needed human intelligence is a very broad understanding of AI. Using a combination of programming, training and data, researchers who work with AI teach computers how to solve complex problems more quickly and efficiently than humans. In a similar process, AI fights against COVID-19.

The World Poverty Clock

The World Poverty Clock is a real-time estimate of the number of people living in poverty across the globe. Its interactive website provides a variety of statistics and demographics about those who are living in extreme poverty, including geographic locations and age ranges. Calculations are made using publicly available data to estimate the number of people living in extreme poverty and the rate at which that number is changing.

According to the World Bank, in a worst-case scenario, COVID-19 could push 100 million people into poverty. However, scientists are working hard to contain and eliminate the virus, AI being one of their strategies. AI fights against COVID-19 by predicting, detecting and eliminating the coronavirus in many parts of the world. In turn, protection from COVID-19 impacts lessens global poverty.

How AI Fights Against COVID-19

AI fights against COVID-19 in a two-pronged approach. It focuses on both detection of the virus and the development of vaccine options.

In late December 2019, the program BlueDot detected a cluster of pneumonia-like illnesses in Wuhan, China. This was the beginning of the COVID-19 outbreak. The program detected the virus nine days before the World Health Organization announced the emergence of a novel coronavirus. BlueDot software has the ability to sift through massive amounts of data to find patterns in the location and movement of a virus. Further developments in virus detection have been made by Alibaba Cloud with the creation of analytical software for computerized tomography (CT) scans. The software can detect coronavirus pneumonia in seconds with approximately 96% accuracy.

AI systems, like Google’s AlphaFold, are aiding researchers by creating predictive models of the protein structure of coronavirus. Models like these can then be used by researchers to design novel vaccine prospects. Overall, these systems enable scientists to reduce the time needed to begin clinical trials and find viable vaccines.

Under human oversight, AI systems can potentially control the spread of the coronavirus. The longer it takes to control and eradicate coronavirus the greater the number of people pushed into poverty. The use of swift and efficient AI applications could not only help curb the spread of COVID-19 but, in turn, fight global poverty as well.

Hannah Daniel
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

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

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