AI for Social Good

The field of AI for Social Good is expanding, with its focus on utilizing artificial intelligence (AI) to tackle a variety of social, humanitarian, and environmental issues. Entities like Google AI and the AI for Good Foundation are at the forefront of advocating for the positive societal impact of AI. The initiative by Google’s AI for Social Good involves collaborations with innovators and organizations to create data-centric, user-oriented tools and technologies aimed at addressing societal problems. The McKinsey Global Institute has pinpointed approximately 160 use cases where AI can have a social impact, from cancer diagnosis to assistance in disaster relief efforts. These applications could potentially benefit hundreds of millions of individuals across developed and developing nations. There are also academic programs and corporate funding initiatives designed to bolster the use of AI for societal benefits.

Moreover, resources such as Google AI’s ‘AI for Social Good Guide’ exist to assist nonprofits and social enterprises in understanding how to leverage AI and machine learning to tackle societal challenges. The mission of the AI for Good Foundation is to utilize economic strategies and technological innovation to address major human challenges and positively affect people’s lives. While the potential of using AI for societal good is immense, it does come with hurdles like data accessibility, lack of sufficient AI expertise, and effective risk management requirements. Despite these obstacles, various stakeholders including researchers, organizations, governments are committed towards exploiting the potentialities of AI for broader benefits.

Artificial Intelligence (AI) has demonstrated substantial promise in tackling a range of societal issues and enhancing the welfare of communities. Here are some key insights from research on the application of AI for societal benefit:

AI Applications for Societal Benefit

• Areas of Societal Benefit: AI has diverse applications across multiple sectors such as healthcare (cancer diagnosis), assisting in disaster relief operations, identifying victims of online abuse, and aiding visually impaired individuals to navigate their environment.
• Alignment with UN Sustainable Development Goals The use cases of AI correspond with all 17 UN Sustainable Development Goals, bolstering various facets of each goal.
• Illustrations
  • Cancer Detection: Deep-learning algorithms powered by AI are utilized for cancer detection and screening, enhancing healthcare results.
  • Wildlife Preservation: AI is used to analyze sound data to safeguard endangered species and monitor wildlife populations.
  • Tackling Global Hunger: AI scrutinizes data to maximize crop yield, create seeds, and forecast food scarcities, thereby helping reduce global hunger.
  • Addressing Inequality and Poverty: By simulating scenarios to find the best solutions and minimize biases in decision-making processes, AI can help tackle inequalities.

Obstacles and Considerations

• Data Access Data access for AI applications can pose challenges due to privacy issues and insufficient technology investments in certain organizations.
• Shortage of Skilled Personnel A lack of skilled AI professionals restricts the broad application of AI for societal benefit, necessitating high-level expertise for complex problem-solving.

Future Trajectories

• Cross-disciplinary Partnerships The movement towards using AI for societal good aims to encourage partnerships between AI researchers and application domains to stimulate positive societal change.
• Sustainable Collaborations For successful social-good-oriented applications of AI, long-term collaborations involving stakeholders from different sectors are crucial.

In summary, harnessing the power of Artificial Intelligence for societal good offers a promising pathway to tackle intricate societal challenges across various domains, align with global sustainability objectives, and foster positive impacts on communities globally.

Here are some further reports worth reading:

• Gen-AI: Artificial Intelligence and the Future of Work" by Mauro Cazzaniga, Florence Jaumotte, Longji Li, Giovanni Melina, Augustus J. Panton, Carlo Pizzinelli, Emma Rockall, and Marina M. Tavares, and published by the International Monetary Fund (IMF) in January 2024,

• Artificial Intelligence for Social Good: The Way Forward by Nuria Oliver, from the Institute of Humanity-centric AI (ELLIS Unit Alicante Foundation), July 2022