Humanitarian Frontiers in AI (Chris Hoffman and Nasim Motalebi)

How should we think strategically about AI, address its emerging challenges, and approach solutions with realistic expectations? In the inaugural episode of Humanitarian Frontiers in AI, hosts Nasim Motalebi and Chris Hoffman are joined by Michael Tjalve from Humanitarian AI Advisory, Hovig Etyemezian from UNHCR, and Nick Thompson of The Atlantic. Together, they delve into the efficiencies and complexities of AI today and its profound implications for the humanitarian sector. Guests share insights on mitigating risks, the critical importance of involving intended audiences in the AI development process, and much more. The discussion navigates the delicate balance between the costs of error and efficiency, emphasizing the necessity of deeply understanding the tools you use—or collaborating with someone who does. Finally, the episode underscores the risks of rejecting AI adoption in humanitarian work, highlighting how such resistance can shift power to those perpetuating crises rather than those striving to resolve them. Join us for a pragmatic look at how AI strategy can be implemented to ethically and effectively support humanitarian efforts around the world. Thanks for listening. 

Key Points From This Episode:

• Welcoming listeners and guests, Nick Thompson, Michael Tjalve, and Hovig Etyemezian. 
• This episode’s topic: thinking strategically about AI and problem-solving using artificial general intelligence.
• Nick weighs in on what this might mean for the humanitarian sector. 
• Michael’s perspective on beneficiary-facing versus internal tools.
• Avoiding risks associated with AI by involving the client in the development process.
• What to take into account with regard to the cost of error.
• Understanding what is lost when the human element is extracted in favor of an algorithm.
• Balancing the efficiency that AI can create for humanitarian work with the challenges and the threat of inaccuracy it poses.
• Why it is so important to have an in-depth understanding of the AI tools that you choose to use.
• Hovig’s perspective on what is truly necessary to use AI effectively in the humanitarian world. 
• Unpacking the cost of error and efficiency.
• The relationship between objective and outcome in the context of AI. 
• Costs associated with AI and who is responsible for them. 
• Considering whether or not there is room to partner with other companies to deploy solutions.
• Capacity building through language models. 
• Understanding risk while developing strategies. 
• Rapid fire questions for each guest. 
• Nasim and Chris reflect on the pragmatism and expertise shared during the first episode. 
  
  

Links Mentioned in Today’s Episode:
 
Nicholas Thompson on LinkedIn
Nick Thompson

Nick Thompson on X
The Atlantic

Michael Tjalve on LinkedIn

Humanitarian AI Advisory

Hovig Etyemezian on LinkedIn
Hovig Etyemezian on X
UNHCR
Nasim Motalebi
Nasim Motalebi on LinkedIn
Chris Hoffman on LinkedIn

Implementing a successful AI strategy for your social enterprise may seem overwhelming, but with the right support, the results can be transformative. In today’s conversation, hosts Nasim Motalebi and Chris Hoffman sit down with Juriaan Lahr and Lindsey Moore to discuss how humanitarian organizations can implement and build a successful AI strategy. Juriaan is the Director of Digital Transformation at the International Federation of Red Cross (IFRC), the world’s largest humanitarian network, and Lindsey is the CEO and Founder at DevelopMetrics, a company leveraging ethical AI to revolutionize global development. Together, they unpack how organizations in the humanitarian sector can harness the power of AI to grow their impact while navigating the ethical questions and unique challenges of these emerging technologies. Discover how humanitarian organizations are adopting best practices in AI, building capacity, financing AI implementation, and much more. To hear the full scope of today’s fascinating conversation, be sure to tune in!
 

Key Points From This Episode:

• Unpacking the role of AI in the IFRC's Digital Transformation Strategy.
• The IFRC’s three pillars of AI implementation: improving productivity, knowledge management, and delivering humanitarian services.
• How USAID is using AI for strategy development and evidence-based decision-making.
• The IFRC’s approach to navigating the challenges and ethical questions that accompany AI.
• How Lindsey helps organizations adopt AI best practices and build capacity.
• Finding the optimal mix of collaboration when using AI in your organization and academia.
• The benefits and difficulties of local partnerships when using AI in the humanitarian sector.
• Taking on the challenge of trying to fill data gaps and the drawbacks of synthetic data.
• How AI can help advance data practices in a humanitarian organization.
• The importance of shared goals and organizational knowledge in AI adoption.
• Juriaan and Lindsey’s approach to building AI capacity for their teams and organizations.
• The investment requirements and expected ROI of implementing AI.
• Rapid-fire round, including what Lindsey and Juriaan are most excited and fearful about.

Links Mentioned in Today’s Episode:

Juriaan Lahr on LinkedIn
Lindsey Moore on Linkedin

IFRC
DevelopMetrics

World Food Program

Nasim Motalebi
Nasim Motalebi on LinkedIn
Chris Hoffman on LinkedIn

Are we ready to let AI drive humanitarian solutions or are we rushing toward an ethical disaster? In this episode of Humanitarian Frontiers in AI, host Chris Hoffman is joined by AI experts Emily Springer, Mala Kumar, and Suzy Madigan to tackle the pressing question of accountability when AI systems cause harm and how to ensure that AI truly serves those who need it most. Together, they discuss the difference between AI ethics and responsible AI, the dangers of rushing AI pilots, the importance of AI literacy, and the need for inclusive, participatory AI systems that prioritize community wellbeing over box-ticking for compliance. Emily, Mala, and Suzy also emphasize the importance of collaboration with the Global South and address the funding gaps that typically hinder progress. The panel argues that slowing down is crucial for building the infrastructure, governance, and ethical frameworks needed to ensure AI delivers a sustainable and equitable impact. Be sure to tune in for a thought-provoking conversation on balancing innovation with responsibility and shaping AI as a force for good in humanitarian action!

Key Points From This Episode:

• Responsible AI versus AI ethics and the importance of operationalizing ethical principles.
• The divide between AI for compliance (negative rights) and AI for social good (positive rights).
• CARE’s research advocating for “participatory AI” that centers voices from the Global South.
• Challenges in troubleshooting AI failures and insufficient readiness for technical demands.
• The need for AI literacy, funding for holistic builds, and a cultural shift in understanding AI.
• Avoiding “participation-washing” in AI and raising the standard for meaningful inclusion.
• Ensuring proper due diligence through collaborative design and authentic engagement.
• Why it’s essential to slow down and prioritize responsibility before rushing AI implementation.
• The question of who is responsible for halting AI deployment until systems are ready.
• Balancing global standards with localized needs: the value of a context-sensitive approach.
• Building infrastructure for the future: a focus on foundational technology, not one-off solutions.
• What goes into navigating AI in a geopolitically diverse and rapidly changing world.

Links Mentioned in Today’s Episode:

Emily Springer on LinkedIn

Emily Springer Advisory

The Inclusive AI Lab by Emily Springer

Mala Kumar

Mala Kumar on LinkedIn

ML Commons

Suzy Madigan on LinkedIn

Suzy Madigan on X

The Machine Race by Suzy Madigan

FCDO Call for Humanitarian Action and Responsible AI Research

ML Commons AI Safety Benchmark

‘Collective Constitutional AI: Aligning a Language Model with Public Input’

Nasim Motalebi
Nasim Motalebi on LinkedIn
Chris Hoffman on LinkedIn

How can humanitarian organizations harness the power of AI while safeguarding data and ensuring ethical use? In this episode, hosts Nasim Motalebi and Chris Hoffman are joined by experts Jeff Wagg and Matthew Harris to demystify the complexities of AI and data management in the humanitarian space. Jeff is an AI consultant for Relief International, where he focuses on deploying innovative AI solutions in fragile settings. Matthew brings his expertise from DataKind and the World Food Programme, specializing in data science and AI practices for scalable and equitable solutions. In today's conversation, they explore the role of data in AI-driven solutions and how these tools are reshaping global humanitarian efforts. Jeff and Matthew discuss the challenges of managing heterogeneous datasets, the importance of data governance, and practical tools to ensure data quality. They unpack using AI for predictive analytics in famine and disease management, and they discuss the ethical considerations surrounding privacy, data security, and AI’s broader societal implications. Join the conversation and discover the immense potential of AI to transform the humanitarian sector with Jeff Wagg and Matthew Harris! Tune in now!

Key Points From This Episode:

• Jeff and Matthew's professional expertise and what fascinates them about AI.
• The role of data in AI applications and its significance for humanitarian work.
• Unpack the challenges of managing and integrating heterogeneous datasets.
• Risks of incomplete or biased datasets and how they impact AI outcomes.
• Learn about approaches for overcoming unstructured and incomplete data sets. 
• Essential data governance practices and why protecting personal information is vital.
• Ethical considerations of using AI in humanitarian work and the 'Do No Harm' principle.
• Find out why a model's use case, biases, and technology stacks are significant.
• Matthew and Jeff explain the critical need for data engineers and cloud specialists.
• Hear examples of innovative AI use cases and what AI needs to be effective. 
• Their opinions of leveraging chatbots for engagement and support services.
• Why risk analysis and evaluation frameworks for deploying AI tools are important.
• Explore the current and future trends of AI in healthcare, agriculture, and humanitarian aid.

Links Mentioned in Today’s Episode:

Jeff Wagg on LinkedIn

Relief International

Matthew Harris on LinkedIn

Program Integrity Alliance

World Food Programme

'Generative AI for Humanitarians'

LangSmith

DataKind

Nasim Motalebi
Nasim Motalebi on LinkedIn
Chris Hoffman on LinkedIn

What does it actually take to use LLMs? We may see the prompt center and receive a beautiful answer or use a WhatsApp chatbot and have an informative conversation, but the reality is that there’s a lot that goes on in the background. There are also a lot of things that NGOs will need to consider as they move forward in a changing world. AWS AI specialist David Master and Tech Tavern founder Scott Turnbull join this conversation to discuss how evolving technology and AI are influencing the non-profit space today. We discuss responsible use, donor responses to AI needs, and how new technological solutions are influencing HR and education in the workplace. Touching on the impact of AI on environmental research and addressing misconceptions about the impact of AI, we discuss the efficiency and complexity of AI today. If there’s one key takeaway from this conversation, it is to understand that AI is an enabler, rather than a threat to employment or efficiency. Tune in as we explore AI’s potential to change lives! 

Key Points From This Episode:

• What large language models (LLMs) are and how to use them.
• Understanding machine learning (ML) and its uses.
• Where NGOs should begin to leverage AI and ML to meet humanitarian crises.
• Allocating financial and human resources to maximize these tools. 
• How donors are responding to new tech tools with safety in mind. 
• Assessing whether reticence towards AI interaction with users is warranted. 
• Using AI to mitigate risk and understanding the risk of failing to act.
• HR and educational resources that AI can provide. 
• How AI data sets are supporting environmental advocacy.
• Misconceptions about artificial intelligence in the non-profit space. 
• The efficiency and complexity that AI is creating today. 
• Sustaining AI beyond quick fixes with data, value-add insights, and lighter models.
• Customer concerns and why many of them stem from a lack of understanding. 
• Low-hanging fruit and long-term gain in the context of leveraging AI. 
• Extracting meaningful data from AI in the context of humanitarian response.

Links Mentioned in Today’s Episode:

David Master on LinkedIn

Scott Turnbull on LinkedIn

Scott Turnbull on X

Data Friendly Space

Innovation Norway

Twilio

Nasim Motalebi
Nasim Motalebi on LinkedIn
Chris Hoffman on LinkedIn

As the humanitarian sector navigates significant transformation, AI is emerging as an essential tool, but how do we ensure it is used effectively, ethically, and at scale? In this episode of Humanitarian Frontiers in AI, we welcome Nana Gamkrelidze, Planning, Monitoring, Evaluation, and Reporting Delegate at the International Federation of Red Cross and Red Crescent Societies (IFRC), and Karin Maasel, CEO at Data Friendly Space and Board Chair at H2H Network, to discuss the latest AI trends in humanitarian work, the challenges of adoption, and the evolving role of technology in crisis response. In our conversation, we delve into how Europe has positioned itself as a regulatory and innovation leader, why AI adoption in humanitarian organizations is vital, and how humanitarian efforts should change to leverage AI technology effectively. Explore how funding cuts have sparked the adoption of AI, what humanitarian organizations can gain from data analytics, and how the cost of building AI for humanitarian efforts has changed. We also uncover the common barriers to AI adoption, the benefits of multi-modal AI approaches for situational awareness, data protection policies, ethical concerns, and the power of AI agents. Join us to discover how AI is reshaping the humanitarian sector, the key to its successful integration, and how to navigate the ethical and operational challenges ahead. Tune in now!

Key Points From This Episode:

• Introduction and a warm welcome to Karin Maasel and Nana Gamkrelidze.
• Main takeaways from the recent AI Action Summit in Paris.
• Trends in AI humanitarian efforts between the Global North and Global South. 
• Learn about the impact of global funding cuts on humanitarian efforts. 
• Ways AI can help shift away from reactional responses by leveraging data analytics.
• Why humanitarian organizations need to embrace AI and data analytics.
• Find out what is preventing humanitarian organizations from implementing AI. 
• How multi-modal AI approaches can help organizations address inefficiencies. 
• Unpack the ethical concerns and risks surrounding AI in humanitarian work.
• Explore the pros and cons of open-source AI versus public-private partnerships.
• How AI agents could improve processes, reduce silos, and automate data collection.
• Uncover long-term adoption strategies and the future of AI in the humanitarian sector.

Links Mentioned in Today’s Episode:

• Karin Maasel on LinkedIn
• Data Friendly Space (DFS)
• H2H Network
• Nana Gamkrelidze on LinkedIn
• International Federation of Red Cross and Red Crescent Societies (IFRC)
• AI Action Summit
• UN World Food Programme (WFP)
• GANNET
• Hugging Face
• Nasim Motalebi
•  Nasim Motalebi on LinkedIn
•  Chris Hoffman on LinkedIn
• Humanity Link
• Chris Hoffman

How do donors balance risk, responsibility, and innovation in the evolving humanitarian sector? In this episode of Humanitarian Frontiers in AI, we welcome leading voices from the donor landscape Therese Marie Uppstrøm Pankratov, Special advisor at Innovation Norway, Sian White, Director of UK Humanitarian Innovation Hub, and Zainah Alsamman, Senior Progam Manager at Grand Challenges, to discuss shifting funding priorities and the role of AI in humanitarian work. In today’s conversation, we explore the challenges and opportunities in scaling AI-driven solutions, ethical data use, and how to foster partnerships to create impact. We delve into how the humanitarian sector should approach AI and innovation and learn why reducing competition and embracing collaboration of AI technologies is essential for the humanitarian sector. We also explore the importance of capacity building and systems innovation, the appetite for risk in the sector, and the need for locally-led AI solutions. Join us to gain insights into bridging the digital divide, how humanitarian organizations fit into the AI landscape, the future of humanitarian innovation, and more. Tune in now!

Key Points From This Episode:

• How drastic funding cuts are reshaping the donor landscape and impacting innovation.
• Why Sian thinks it is critical to challenge the assumed benefit of AI-based solutions.
• Duplication and competition in AI technologies and the problems they create. 
• Find out why donors must rethink how they allocate resources for AI and innovation.
• Navigating the humanitarian sector's capacity to innovate with the need for innovation. 
• Learn about the challenges of scaling AI technologies and the barriers to adoption.
• The lack of investment in local AI talent and why empowering local actors is crucial.
• Explore how funders can help drive the development of responsible and ethical AI.
• Unpack how to balance the need for innovation with the risk associated with innovation.
• Data ownership and the idea of compensating affected communities for the data. 
• Discover why ethical AI development and responsible data governance are essential.
• Uncover the hurdles that evolving regulations create and the role of global policies.
• How fostering collaboration and partnerships will aid in ethical and sustainable solutions.

Links Mentioned in Today’s Episode:

Therese Marie Uppstrøm Pankratov on LinkedIn

Innovation Norway

Sian White on LinkedIn

UK Humanitarian Innovation Hub (UKHIH)  

Zainah Alsamman on LinkedIn

Grand Challenges Canada

Creating Hope in Conflict: A Humanitarian Grand Challenge

UK Humanitarian Innovation Hub | Directory of AI-enabled humanitarian projects

UK Humanitarian Innovation Hub | Newsletter

Humanitarian Innovation Programme: Innovation Norway

Elrha

Nasim Motalebi
Nasim Motalebi on LinkedIn
Chris Hoffman on LinkedIn

Who sets the rules for AI and who gets left behind? In this episode of Humanitarian Frontiers in AI, we’re joined by Gabrielle Tran, Senior Analyst at the Institute for Security and Technology (IST), and Richard Mathenge, Co-founder of Techworker Community Africa (TCA), to explore the global landscape of AI regulation and its humanitarian impact. From the hidden labor behind AI models to the ethical and political tensions in governance, this conversation unpacks the fragmented policies shaping AI’s future, from the EU’s AI Act to the U.S.'s decentralized approach. Richard sheds light on the underpaid, invisible workforce behind AI moderation and training, while Gabrielle examines the geopolitical power struggles in AI governance and whether global policies can ever align. We also tackle AI’s high-risk deployment in humanitarian work, the responsibilities of NGOs using AI in the Global South, and potential solutions like data trusts to safeguard vulnerable populations. If you care about the future of AI in humanitarian efforts, this episode breaks down the challenges, risks, and urgent questions shaping the path forward. Tune in to understand what’s at stake (and why it matters)!

Key Points From This Episode:

• The hidden labor of AI: how AI models rely on underpaid human moderators.
• AI ethics versus the ethics of AI and how ethical concerns are framed as technical fixes.
• Insight into the sometimes murky origins of training datasets.
• Contrasting the EU’s AI Act with America’s decentralized approach.
• The risks of AI deployment in humanitarian work, particularly in crisis zones.
• Accountability in AI supply chains: how new EU policies may enforce transparency.
• Reasons that AI governance is a low priority in many African nations.
• Why tech giants typically only comply with AI policy when it benefits them.
• AI for surveillance versus humanitarian use: the double-edged sword of AI governance.
• An introduction to the concept of data trusts to safeguard humanitarian AI data.
• Ensuring informed consent for workers when building and monitoring AI tools.
• The role of humanitarian organizations like the UN in enforcing “digital rights."
• What goes into building an ethical future for AI in humanitarian work.

Links Mentioned in Today’s Episode:

 Richard Mathenge on LinkedIn

Techworker Community Africa (TCA)

Gabrielle Tran on LinkedIn

Gabrielle Tran on X

Institute for Security and Technology (IST)

EU AI Act

National Institute of Standards and Technology (NIST)

AI Risk Management Framework (RMF)

Occupational Safety and Health Administration (OSHA)

The Alignment Problem

Nasim Motalebi
Nasim Motalebi on LinkedIn
Chris Hoffman on LinkedIn

Innovation Norway