Artificial Intelligence and Global Challenges — No Poverty
Goal nº 1. “No Poverty: End poverty in all its forms everywhere.”
How Artificial Intelligence technologies can play a central role in the achievement of the Sustainable Development Goals one by one.
Artificial Intelligence technologies can play a central role in the achievement of the Sustainable Development Goals. This article starts with goal nº1 “No poverty” in an effort to explore its physiognomies and potential course of actions through an AI perspective. In a series of 17 articles, we will go through all of the goals one by one.
In September 2000, the Millennium Summit gathered at the United Nations Headquarters the largest number of world leaders in the history of humankind. On this crucial date, representatives of 189 member states came together to reflect on a common destiny for humanity. In that context, the acceleration of the globalization process promised faster growth, as well as raising living standards and new opportunities. Notwithstanding, the end of the twentieth century was also a time of poverty and conflict where about 1.1 billion people were forced to survive on less than $ 1 a day.
From this occasion, was born the commitment that by 2015, the world would make measurable progress in the most critical areas of human development. This commitment would be known as the Millennium Development Goals (MDGs), a series of 8 objectives for:
- Eradicate extreme poverty and hunger;
- Achieve universal primary education;
- Promote gender equality and empower women;
- Reduce child mortality;
- Improve maternal health,
- Combat HIV/AIDS, malaria and other diseases;
- Ensure environmental sustainability; and
- Develop a global partnership for development.
The establishment of those goals produced remarkable achievements, but fifteen years later, there was still much to be done. In 2015 a new series of negotiations in the United Nations culminated in the adoption of the Sustainable Development Goals (SDGs). Through a ‘2030 Agenda’, 17 new objectives are supposed to be reached in what comes to global challenges such as poverty, inequality, climate change, environmental degradation, prosperity, and peace and justice. These new objectives should guide national policies and international cooperation activities over the next 12 years from now, succeeding and updating the Millennium Development Goals.
Among all the results achieved and the failures, all those conferences and goals left us with an important lesson: success can only be achieved through cooperation with governments, business and the civil society altogether. Artificial Intelligence here can play a central role in the achievement of the Sustainable Development Goals. In a decentralized Alliance, it can foster cooperation to put together efforts to potentialize and disseminate innovative solutions in healthcare, agriculture, food security, poverty, education and more. From an AI point of view, we invite you to reflect with us on what comparisons and analysis can be done to reach the most complex and ambitious of all of the SDGs by the year 2030: End poverty.
Goal nº 1 — No Poverty: End poverty in all its forms everywhere
“Perhaps with the tools of this new technological revolution, we will be able to undo some of the damage done to the natural world by the last one, industrialization. We will aim to finally eradicate disease and poverty.” — Stephen Hawking (2016) —
The first Sustainable Development Goal set out to eliminate extreme poverty and decrease in half the numbers of people living in all aspects of poverty. It aims to ensure equal rights to economic resources and social protection coverage to all people. With more than 1 billion people lifted out of extreme poverty by 2015, the MDGs proved that this aim is within reach. Notwithstanding, with over 700 million people still battling extreme poverty and the continued growth of the world population, this reach is quite a challenge even to Artificial Intelligence.
According to the World Bank report “Poverty and Shared Prosperity 2016: Taking on Inequality”, the poorest people in the world are predominantly rural (80%), young (44% are under 14), have low schooling (39% do not have formal schooling), mostly employed in agriculture (64%) and are living in families that have more than two children. A table of absolute numbers of poverty in the world shows us a number of 766 million people living at up to $1.90 a day. The highest number of people in this condition is in sub-Saharan Africa (388 million). Numbers in the southern part of Asia point us to 256 million, the next is Latin America with 33 million. The numbers in central and northern Africa were not collected because of problems such as the difficulty of accessing households and the impossibility of comparing their gains against the dollar.
Poverty Map — Data Collection
The impossibility to collect data is a consequence of poverty itself but in what comes to “end poverty in all its forms everywhere”, location is a fundamental variable. Countries do not collect much data and scaling up traditional household surveys is very expensive, Artificial Intelligence can help change that. In fact, a recent study by a team at Stanford University is using satellite images to provide an alternative to map poverty. The social scientists and computer experts’ team came up with the idea of using high-power satellites to detect poverty by analyzing their images. The study focused on five African countries (Nigeria, Tanzania, Uganda, Malawi and Rwanda) and use an accurate survey of data to corroborate the predictions.
To map poverty efficiently, Artificial Intelligence can combine high-resolution satellite imagery with powerful machine learning algorithms and predict how rich or poor specific locations around the world are (providing information such as the distance from the nearest water sources, the nearest urban market or where the agricultural fields are for example). If standard machine learning approaches to interpreting imagery work best with a huge amount of data, a Decentralized AI Alliance could be a great environment to amplify the mapping solution, making it widely available and precise to help aid organizations and policymakers in a more efficient distribution of funds and evaluation of policies.
Rural Areas — Agriculture
Poverty is a multifaceted phenomenon; it is a combined condition of lack of income, education and social assistance. The strongest combination of these three conditions are in rural areas as it concentrates 80% of the world’s most poor population. In the areas where poverty is prevalent, many people make their living through agriculture. Therefore, another way in which AI could tackle poverty is through its potential in improving farming, soil cultivation for growing crops and the rearing of animals to provide food, wool, and other products. In fact, we already have some applications for that, from AI-based robots helping to harvest crops to machine learning in an AI model that can predict the best ways for farmers to grow this crop.
Using robotics and artificial intelligence to improve the sustainability of main food crops in developing countries, the project FarmView can explore the best way in which to increase the growth of crops like the “sorghum”, used for food, drink production and biofuels. The potential of AI in agriculture can significantly benefit poverty-stricken areas, and we expect to dive deeper into this on the second article of this series concerning objective number 2 “Zero Hunger”. In a decentralized AI environment, farmers can go from being reliant on the information provided by intermediaries to being independent negotiators and dealmakers through accessing timely and reliable information.
Education
When 39% of the world’s most poor do not have formal schooling, another front of action is clearly education. AI can help increase education levels in poor areas through adapted learning. It can help identify students learning necessities and optimize the process through different methods of learning. In an additional scenario, we could see intelligent chatbots standing in as educators for pupils without access to other forms of schooling in a way that it can help alleviate the money-barrier and inequality that come up alongside education.
AI tech-enabled teaching is just a start and is good to mention here the partnership between SingularityNet and UNESCO to preparing the youth to deal with new technologies that will shape the coming years. The social enterprise Eneza Education is another project with AI potential that is already tutoring millions of rural students in Kenya, Ghana and Côte d’Ivoire. We will explore more about the possibilities and implications of Artificial Intelligence in education in a separate article about AI and goal number 4: “Quality Education: Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all”.
Role of AI
Despite electoral promises and political ideologies, poverty remains a structural problem that affects all of humanity and undermines the stability of societies and the world itself. Over recent years, mobile telephony improved the lives of many poor people living in rural areas. With mobile phones, people who previously were socially and economically excluded are now actively participating in the economy. AI has the potential to expand the socioeconomic benefits of currently existing technologies; it can lead different alternatives to reach remote areas that lack education, social assistance and productive capacities and be a decisive instrument to eradicate poverty.
AI can help to identify regions most in need of help. It can tackle poverty in particular areas through the improvement of farming and agriculture, increasing education and helping citizens learn new skills to support communities. It can help implement applications for a more effective social assistance with unbiased assessments to make sure they met the needs of those who needs most. It can also help with the distribution of aid in conflict areas or those facing natural disasters and devastation. In a decentralized environment, artificial intelligence could take these benefits to the whole world.
Of the 766 million people living in these poverty conditions, 385 million are children and more than one fifth of them are under five. Sub-Saharan Africa has the highest number of children in this condition, almost 50%. Second comes South Asia with 36% and India with 30%. Affected by hunger and misery many of them die before they reach adulthood, and if they manage to survive, their physical and mental development are greatly impaired. Harnessing the power of AI to help the most desperate in our society is a commitment of DAIA. It represents another indication of the promising aspect of AI in the service of the general good. Before discarding new technologies as only agents of chaos and rupture, we must evaluate their work power for the benefit of our society. This is just the beginning!
Text by Camila Froede
How can you get involved?
The vision of DAIA is to foster a world where AI technologies and associated data are made open with decentralized, democratic control for the benefit of all sentient beings.
The immense potential of AI means that it can either increase the inequalities of our societies or liberate us from numerous sufferings. We believe the best way forward is to come together and work practically toward creating a better future. We see a massive potential for evolution in the established centralized corporations.
DAIA welcomes the participation of those corporations that are sincere about their aim and goal of democratizing AI. The AI enthusiasts whom have come together to join DAIA, such as SingularityNET, and partners such as Dbrain, are the enabling layer for such a democratization process.
