How to leverage ‘Prosocial AI’ in the fight against global poverty

The persistent challenge of global poverty: Despite significant progress in reducing extreme poverty rates over the past few decades, millions of people worldwide still struggle to meet their basic needs, living on less than $2.15 per day.

• According to recent World Bank estimates, around 719 million people live in extreme poverty, a figure that represents a substantial portion of the global population.
• To put this number into perspective, it is equivalent to about half of Africa’s total population or more than twice the population of the United States.
• The $2.15 per day threshold is considered inadequate to ensure a life of dignity, as it falls short of covering actual living costs.

Multifaceted nature of poverty: The persistence of poverty is attributed to a complex interplay of individual and institutional factors, requiring a holistic and systematic approach to eradication.

• This year’s International Day for the Eradication of Poverty theme, “Ending Social and Institutional Maltreatment,” highlights the intricate nature of poverty and its root causes.
• Addressing poverty effectively necessitates involvement from various sectors, including public, private, academic, and artistic stakeholders.
• The challenge of poverty eradication has been described as a transdisciplinary and multigenerational endeavor that has remained largely unresolved.

AI as a potential game-changer: Artificial intelligence, particularly through the framework of ProSocial AI, offers promising avenues for fostering human dignity, social inclusion, and equitable growth in the fight against poverty.

• ProSocial AI integrates fairness, transparency, and inclusivity into AI systems to address poverty in innovative ways.
• By leveraging AI’s capabilities, it may be possible to tackle root causes of poverty more effectively, from improving access to education and healthcare to creating new job opportunities.

Data-driven targeted assistance: AI’s ability to analyze vast amounts of data can significantly enhance the identification and support of underserved regions and communities.

• AI can process satellite imagery and geospatial data to pinpoint areas lacking basic infrastructure such as water, sanitation, and electricity.
• AI-driven analytics can provide real-time insights into poverty distribution, inequality patterns, and future needs, enabling more informed decision-making by governments and NGOs.
• Collaborating with local authorities, AI tools can optimize resource distribution and improve the effectiveness of social protection programs.

Democratizing education: AI has the potential to bridge educational disparities between rural and urban areas by providing personalized learning experiences to underserved communities.

• AI-powered platforms can deliver tailored, world-class content to children in impoverished areas via mobile phones or low-cost devices.
• Adaptive learning systems can assess individual knowledge gaps and strengths, offering personalized learning paths that adjust in real-time.
• AI-powered chatbots and virtual tutors can provide guidance and support, mimicking one-on-one instruction in areas facing teacher shortages.

Economic empowerment through AI: Contrary to fears of job losses, ProSocial AI focuses on augmenting human work and creating new economic opportunities.

• AI-driven platforms can connect impoverished individuals to gig economies, micro-entrepreneurial activities, and flexible work opportunities.
• Real-time job market data and predictive analytics can help workers in poverty-stricken regions develop in-demand skills and transition to more stable, higher-paying jobs.
• AI can facilitate connections between local artisans and global e-commerce markets, helping small businesses scale and increase income.

Improving healthcare accessibility: AI can provide low-cost, scalable, and personalized healthcare solutions to underserved populations.

• AI-powered telemedicine platforms can offer remote medical consultations, diagnostic services, and follow-up care without expensive infrastructure.
• AI models can predict disease outbreaks and optimize resource allocation, improving overall healthcare outcomes in impoverished areas.
• By identifying high-risk communities based on environmental and social factors, AI can enable preemptive distribution of medical supplies and preventive interventions.

Promoting financial inclusion: ProSocial AI has the potential to revolutionize financial services for those traditionally excluded from the formal banking sector.

• AI-driven financial tools can assess creditworthiness using alternative data sources, enabling microloans for individuals without formal credit histories.
• In regions lacking formal identification documents, AI-powered biometric systems can create secure and verifiable identities, granting access to essential services like banking, education, and healthcare.

The path forward: While ProSocial AI offers significant promise in addressing systemic issues perpetuating poverty, its success depends on collaborative efforts across various sectors.

• The effective implementation of AI-driven solutions requires voluntary cooperation between governments, businesses, academia, and civil society.
• Moving beyond abstract commitments celebrated annually on October 17th, ending poverty necessitates sustained human desire and action.
• AI can serve as a powerful tool to accelerate progress towards poverty eradication, but it requires human initiative and guidance to realize its full potential.

Broader implications: As we consider the role of AI in poverty eradication, it’s crucial to recognize that technology alone cannot solve deeply rooted socioeconomic issues.

• While AI offers innovative solutions, its effectiveness ultimately depends on addressing underlying structural inequalities and power imbalances in society.
• Ethical considerations, such as data privacy and algorithmic bias, must be carefully addressed to ensure AI-driven poverty reduction efforts do not inadvertently exacerbate existing disparities.
• The success of AI in combating poverty will likely hinge on its integration with broader policy reforms, community-driven initiatives, and a genuine commitment to social justice on a global scale.