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AI for Humanitarianism: Fostering Social Change Through Emerging Technologies

A Volume in Chapman & Hall/CRC Artificial Intelligence and Robotics Series.


This book will offer a comprehensive coverage of the intersection between AI and humanitarian work. This book will serve as a one-stop resource for readers interested in this unique and important intersection. The book will bridge the gap between AI practitioners and humanitarian professionals. This book will bring together these two fields and fosters mutual understanding and collaboration by making technical concepts accessible to non-technical readers and highlighting the real-world implications of AI in humanitarian work. This book will address the ethical considerations that come with using AI in humanitarian work, such as data privacy, algorithmic bias, and the potential for unintended consequences. This book will meet the need for thoughtful discussions on the responsible and ethical use of technology by tackling these important topics. This book will adopt an interdisciplinary approach allowing it to explore the technological, social, political, and ethical dimensions of AI in humanitarian work. This wide-ranging scope of this book will satisfy the need for resources that consider the complexities and nuances of using emerging technologies for social impact.

The research questions guiding this proposed book project include:

  1. How are AI technologies currently being used in humanitarian contexts, and what are the most successful applications and outcomes to date?

  2. What are the main challenges and obstacles that practitioners face when trying to integrate AI into humanitarian work, and how can they be addressed?

  3. How can AI technologies be designed and deployed ethically in humanitarian contexts, particularly when working with vulnerable populations?

  4. What role do local communities and beneficiaries play in the development and deployment of AI technologies for humanitarian work, and how can their input and agency be prioritized?

  5. What tools, strategies, and best practices can be developed to support the effective and responsible integration of AI into humanitarian efforts?

  6. How does the use of AI in humanitarian work relate to broader trends and debates in AI, technology, and social impact, and what can be learned from these intersections?

The proposed tentative content for this book is given below:

  1. Relevance of AI in Humanitarian Contexts

  2. Potential of AI for Social Impact

  3. Addressing the SDGs with AI

  4. Opportunities in Health, Education, and Poverty Reduction

  5. Creating a Sustainable Ecosystem for AI-Driven Humanitarian Efforts

  6. Collaborations between AI Practitioners and Humanitarian Organizations

  7. The Role of Government and International Organizations

  8. Building Partnerships for AI in Humanitarian Efforts

  9. Financial and Funding Models

  10. Traditional Funding in Humanitarian Work: An overview and its limitations.

  11. Emerging Financial Models for AI-Humanitarian Initiatives: From impact investing to tech philanthropy.

  12. Public-Private Partnerships: Merging the best of both worlds for social impact.

  13. Crowdfunding and Grassroots Funding: Mobilizing the masses for tech-driven social change.

  14. Economic and Social ROI: Measuring the returns on AI-humanitarian investments.

  15. Open-source Tools and Collaborative Development

  16. The Power of Open-Source: Why collaborative development accelerates impact.

  17. Leading Open-Source Platforms for Humanitarian AI

  18. Building and Sustaining a Collaborative AI Community

  19. Infrastructure and Implementation in Resource-Limited Settings

  20. Technologies for Off-Grid AI

  21. Edge Computing

  22. Solar-Powered Data Centers

  23. Low-Power AI Chips

  24. Connectivity Solutions

  25. Distributed Data Centers

  26. Hybrid Cloud Solutions

  27. Training and Capacity Building

  28. Local Tech Hubs and Innovation Centers

  29. Resilience and Maintenance

  30. Challenges of Using AI in Humanitarian Work

  31. Algorithmic Bias and Fairness Concerns

  32. Data Privacy and Security Issues

  33. Scalability and Generalization Challenges

  34. Case Studies:

  35. Real-world Case Studies of Successful AI Applications

  36. Lessons to be Learned from Failed Implementations

  37. AI Applications in Disease Prediction

  38. Improving Health Monitoring and Response

  39. Addressing Health Disparities with AI

  40. Tackling Educational Inequalities with AI

  41. AI for Poverty Reduction and Economic Growth

  42. Identifying Areas of Extreme Poverty with AI

  43. Optimizing Resource Allocation for Aid Programs

  44. Developing Solutions to Address Root Causes of Poverty

  45. AI for Climate Action and Environmental Sustainability

  46. AI Applications for Climate Modeling

  47. Predicting and Addressing Extreme Weather Events

  48. Optimizing Resource Use and Environmental Protection

  49. Ethical Considerations in AI for Humanitarian Context

  50. Ethical Principles for AI in Humanitarian Work

  51. Avoiding Harm and Ensuring Transparency

  52. Ethical Challenges and Potential Solutions

  53. Future Trends and Considerations

  54. Evolving Trends in AI and Humanitarian Work

  55. Preparing for Challenges and Leveraging Opportunities

  56. Nurturing a Culture of Innovation and Responsibility

  57. Conclusion and Call to Action


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