Humanitarian Frontiers in AI: Episode Summary – "Where to Start with Strategy?"

Release Date: January 7, 2025

In the second episode of "Humanitarian Frontiers in AI," hosts Chris Hoffman and Nassim Motalebi delve into the strategic integration of artificial intelligence (AI) within the humanitarian sector. Joining them are Yurian Lar, Director of Digital Transformation at the International Federation of Red Cross and Red Crescent Societies (IFRC), and Lindsey Moore, CEO and Founder of Develop Metrics. The conversation uncovers both the transformative potential and the multifaceted challenges of leveraging AI to enhance humanitarian efforts.

1. Introduction

Chris Hoffman opens the episode by highlighting the series' mission to explore how AI redefines humanitarian work, emphasizing its role in crisis response, intelligent delivery systems, and ethical considerations. The hosts set the stage for a deep dive into AI's strategic influence on humanitarian organizations.

2. AI’s Impact on IFRC’s Strategy

Yurian Lar discusses IFRC’s digital transformation strategy, outlining three primary pillars where AI is employed:

• Improving Productivity: Automating workplace tools, summarizing meetings, analyzing data, and enhancing translation services. For instance, AI assists in data analysis and report summarization, significantly reducing manual workload.

  "[00:48] Yurian Lar: ... AI has been around, but of course is becoming more prominent for us globally in our day to day work."

• Knowledge Management: Utilizing AI to process extensive reports, making knowledge access smoother through chatbot functionalities both internally and externally.

  "[03:51] Yurian Lar: ... knowledge management is going through big chunks of reports, make them available and easier, hopefully."

• Delivering Humanitarian Services: Implementing AI in social media listening, improving blood collection processes, and developing mental health chatbots to better serve communities.

  "[03:51] Yurian Lar: ... in areas of social media, listening, improving blood collection, but also very advanced and novel mental health chatbots."

3. Challenges in AI Adoption

The conversation shifts to the hurdles organizations face when adopting AI:

• Organizational and Process Challenges: Many organizations struggle with fragmented data systems and lack centralized data governance. Yurian Lar emphasizes the need for guidelines to ensure ethical AI use aligned with humanitarian principles.

  "[05:57] Yurian Lar: ... we need to develop these guidelines and giving guidance to colleagues how to use it and reflect against our fundamental principles."

• Ethical Considerations: Protecting the rights and data of affected populations is paramount. Yurian Lar shares experiences of AI bias, such as the inability to generate images with Red Crescent logos, highlighting inherent prejudices in AI models.

  "[08:48] Yurian Lar: ... it was no way we could get the red crescent logo on the picture... the bias is significant."

• Capacity Building: Organizations often lack the technical expertise required to implement and manage AI solutions effectively. Lindsey Moore points out the resource-intensive nature of experimenting with and validating AI tools.

  "[10:51] Lindsey Moore: ... experimentation being that research perspective ... it takes perhaps even a year or more to have a team with expertise."

4. Opportunities in AI Integration

Despite challenges, AI presents significant opportunities:

• Enhanced Decision-Making: AI enables evidence-based decisions by analyzing large datasets beyond human capacity, leading to more informed strategies in humanitarian efforts.

  "[03:59] Nassim Motalebi: ... evidence based decision making in the humanitarian field, which has been a huge advancement."

• Cost Reduction and Efficiency: Automating repetitive tasks allows humanitarian workers to focus on more impactful activities. Nassim Motalebi shares how AI has saved USAID substantial time and resources by automating document generation.

  "[38:12] Nassim Motalebi: ... they saved around 1200 hours and I think a million, just under a million dollars of staff time in auto generating documents."

• Improved Service Delivery: AI-driven tools enhance the quality and speed of humanitarian services, from predictive models for disaster response to streamlined blood donation processes.

  "[44:42] Yurian Lar: ... prioritize the assistance in the right place at the right time for the right people."

5. Capacity Building and Data Management

Building the necessary infrastructure and expertise is crucial for successful AI integration:

• Data Quality and Governance: Yurian Lar underscores the importance of consolidating fragmented data systems into a unified data platform, enhancing data management and governance across the organization.

  "[27:30] Yurian Lar: ... AI and data management go really hand in hand... we did not have one data governance for the entire organization."

• Internal Capabilities: Developing in-house expertise through hiring specialized roles such as data architects and engineers is essential. Yurian Lar details IFRC’s efforts to build a central data management team to oversee AI projects and partnerships.

  "[32:14] Yurian Lar: ... we are bringing the right skills in and the right people into the Organization."

• Collaborative Partnerships: Engaging with academia and tech industries fosters innovation and ensures that AI solutions are tailored to the specific needs of humanitarian organizations. Nassim Motalebi emphasizes the necessity of collaborative efforts to bridge technical gaps.

  "[13:10] Nassim Motalebi: ... it's a collaborative effort to get around these things, to be able to get it right."

6. Return on Investment (ROI) in AI

Assessing the financial benefits of AI implementation is vital for securing funding and justifying investments:

• Demonstrable Savings: AI applications can lead to significant cost savings and efficiency gains. Nassim Motalebi cites USAID’s use of AI to automate report generation, saving nearly a million dollars in staff time.

  "[38:12] Nassim Motalebi: ... they saved around 1200 hours and I think a million, just under a million dollars of staff time in auto generating documents."

• Challenges in Quantifying ROI: Measuring ROI in the humanitarian sector can be complex, as improvements in speed and quality of service may not always translate directly into financial terms. Yurian Lar highlights the difficulty in expressing certain benefits, such as faster response times, in monetary terms.

  "[43:52] Yurian Lar: ... what baseline data you need, that you gather that data before is really important decision making or being aware that it does add something that is not quantifiable."

7. Future Perspectives and Concerns

Looking ahead, the panel discusses both the excitement and apprehensions surrounding AI in humanitarian work:

• Excitement About Advancements: Both Nassim Motalebi and Yurian Lar express enthusiasm for AI’s potential to revolutionize data practices, improve response times, and enhance service delivery. Nassim is particularly excited about emerging AI models that mimic human intuition and causality.

  "[45:41] Nassim Motalebi: ... AI go more towards AGI and look at, like, more physical and social understanding... it's going to explode."

• Concerns Over Inequality and Bias: The panel voices worries about AI exacerbating existing inequalities, particularly if models are developed predominantly by Western entities, potentially marginalizing data from developing regions. Nassim fears the unequal distribution of AI benefits and the exploitation of data from vulnerable populations.

  "[45:41] Nassim Motalebi: ... the inequality that it will produce in terms of the people who are working with these models..."

• Data Divide: Yurian Lar underscores the risk of technological divides, emphasizing the need to ensure that AI advancements reach the most vulnerable communities and do not leave them further behind.

  "[48:43] Yurian Lar: ... the divide in all forms we can have is that we need to find ways to bring these technologies really to all the places that we work..."

8. Conclusion and Takeaways

The episode wraps up with Lindsey Moore reflecting on the duality of AI's potential to both advance equality through accessible knowledge and pose risks of inequality if not implemented thoughtfully. She emphasizes the importance of capacity building, data governance, and collaborative innovation to harness AI responsibly.

Lindsey Moore concludes:

"[50:27] Lindsey Moore: ... AI, to me, is a beautiful space where actually has brought people together. And I think this is the most valuable part of this journey."

Nassim Motalebi echoes the sentiment of cautious optimism, recognizing the transformative power of AI while advocating for ethical practices and inclusive development.

Notable Quotes:

1. Yurian Lar on AI's role in IFRC:

   "[00:48] ... AI has been around, but of course is becoming more prominent for us globally in our day to day work."

2. Yurian Lar on mitigating AI bias:

   "[08:48] ... the bias is significant."

3. Nassim Motalebi on proving ROI:

   "[38:12] ... saved around 1200 hours and ... a million dollars of staff time in auto generating documents."

4. Lindsey Moore on AI's potential for equality:

   "[50:27] ... AI is a beautiful space where actually has brought people together."

Final Thoughts:

This episode underscores the critical balance between leveraging AI’s vast potential to enhance humanitarian efforts and navigating the ethical, organizational, and technical challenges that accompany its adoption. The insights shared by Yurian Lar and Lindsey Moore offer a roadmap for organizations seeking to integrate AI thoughtfully and effectively, ensuring that technological advancements translate into meaningful, equitable benefits for communities in need.

Listeners are encouraged to consider the foundational steps of data management, capacity building, and ethical guidelines as they embark on their AI journey within the humanitarian sector. The collaborative spirit highlighted throughout the discussion reinforces the notion that meaningful AI integration is a collective effort, requiring shared knowledge and sustained commitment.

Stay tuned for future episodes of "Humanitarian Frontiers in AI," where leaders and innovators continue to explore the intersection of technology and humanitarian work, driving forward the mission to bring real change to communities worldwide.