Humanitarian Frontiers – Détails, épisodes et analyse

In Episode 2, Chris Hoffman is joined by Sandra Uwantege Hart (Mercy Corps Ventures) and Doug Smith (Acting CEO, Data Friendly Space) for a clear-eyed conversation about open source, Digital Public Goods (DPGs), and what sustainability really looks like once the pilot funding runs out.

This episode cuts through the buzzwords and gets into the hard parts: why “everything must be open source” can unintentionally create abandoned codebases, how donor incentives shape what gets built (and what gets maintained), and why long-term ownership, governance, and security often matter more than ideology. Doug shares why AI adoption is accelerating faster than most humanitarian policies can keep up, and what that means for risk and accountability. Sandra adds the nuance on localization—how blanket requirements can undermine local tech start-ups and limit sustainable business models in the places where humanitarian response actually happens.

What we cover:

• Open source vs. DPGs (and when each makes sense)
• Sustainability beyond pilots: maintenance, governance, security
• Localization and market-shaping effects of funding requirements
• Responsible AI + data risk in humanitarian operations

Links:

• Data Friendly Space: https://www.datafriendlyspace.org/
• Doug Smith (DFS profile): https://www.datafriendlyspace.org/members/doug-smith
• Mercy Corps Ventures: https://www.mercycorps.org/what-we-do/ventures
• Mercy Corps Ventures: https://www.mercycorpsventures.com/

LinkedIn:

• Sandra Uwantege Hart: https://www.linkedin.com/in/sandra-uwantege-hart-862b5986/
• Doug Smith: https://www.linkedin.com/in/connectwithdoug/

keywords: digital public goods, open source sustainability, humanitarian innovation, responsible AI, localization, humanitarian technology, NGO digital transformation, data governance.

When connectivity drops, power is limited, and the stakes are life-and-death, “cool tech” isn’t enough. In Episode 1, Chris Hoffman is joined by Camille Crittenden (Executive Director, CITRIS & the Banatao Institute at UC Berkeley) and Carlos Pignataro (former CTO at Cisco, Founder/Principal, Blue Fern Consulting; tech-for-good inventor) to talk about what it really takes to build resilient, offline-first technology for humanitarian response.

You’ll hear why the best systems are designed for reality: messy environments, unreliable networks, frontline workflows, and rapid change. Camille breaks down practical principles for offline data collection, delayed sync, usability under pressure, and responsible deployment. Carlos adds hard-won lessons from field experience and the importance of co-design with the people who will actually use the tools—so solutions don’t fail at the last mile.

What we cover:

• Edge computing + offline-first design for humanitarian operations
• Co-design (top-down architecture + bottom-up user reality)
• Security, resilience, and trustworthy data in crisis settings
• Building tech that scales without breaking communities

Links:

• Camille (CITRIS bio): https://citris-uc.org/people/person/camille-crittenden/ (CITRIS and the Banatao Institute)
• Carlos (Blue Fern profile): https://bluefern.consulting/carlos (Blue Fern Consulting)
• Carlos (Cisco author page): https://blogs.cisco.com/author/carlospignataro (Cisco Blogs)
• Carlos LinkedIn: https://www.linkedin.com/in/cpignata/ (cednc.org)
• Camille LinkedIn : https://www.linkedin.com/in/camillecrittenden/

keywords: humanitarian innovation, edge computing, offline-first, crisis tech, resilient systems, co-design, digital transformation, humanitarian operations.

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

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

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

Get Ready!  New Season Launches in 2026!

During the tenth and final episode of Humanitarian Frontiers in AI, we discuss how the changes we have seen in the past year might influence the year to come. This broad conversation covers tech advancements and adoptions in the humanitarian sector, what is fuelling the need for partnerships, and how context-specific work can support the effective use of community-driven technologies. We also get into false perceptions about open source, the risk AI poses to open source, and why traditional ways of work are irrelevant to evolving tech. Next, we discuss what our sector can do to improve its relationship to technology and leverage it to achieve more, including shifting some of the perceptions that have informed its approach in the past. Join us as we wrap up a 101 in humanitarian AI relevant to listeners from all backgrounds. Thanks for listening! 

Key Points From This Episode:

• Welcome to the tenth and final episode of Humanitarian Frontiers in AI. 
• Why the conversation around AI and innovation in humanitarian work is so relevant.
• How Nasim’s experiences over the past year may lead to future advancements.
• Tech advancements and adoptions in the humanitarian sector.
• The missing lexicon that highlights the need for partnerships. 
• Context-specific work and supporting community-driven technologies.
• Why it’s important to distinguish between open source and zero cost.
• How risks from AI are threatening open source.
• The problem of applying traditional ways of working to AI. 
• How the humanitarian sector can improve its relationship to technology.
• Distinguishing between humanitarian and international mandates.
• The stumbling block posed by in-between spaces.
• How we will continue this podcast’s mission in the future. 

Links Mentioned in Today’s Episode:

AI Code Hallucinations Increase the Risk of ‘Package Confusion’ Attacks

Nasim Motalebi
Nasim Motalebi on LinkedIn
Chris Hoffman on LinkedIn

What happens when the worlds of policy, product development, and pragmatic decision-making collide in the race to create responsible AI? In this episode of Humanitarian Frontiers in AI, we are joined by a panel of experts, Sabrina Shih, Hadassah Drukarch, Gayatri Jayal, and Jigyasa Grover, for an in-depth discussion of responsible AI development in humanitarian contexts. Together, they unpack the realities of applying AI technologies in crisis-affected settings and grapple with issues around trust, speed, cultural adaptation, and ethical responsibility. They unpack how “human-in-the-loop” models must adapt depending on the context, how affected populations should be involved in AI design, and how to navigate scaling technologies quickly versus building them responsibly. They also explore the challenges of building context-specific tools, the evolving definitions of responsible AI, and how humanitarian organizations can stay rooted in people and processes, not just technology. Join us to discover insights into the crucial role of people and AI design in reshaping humanitarian work. Tune in now!

Key Points From This Episode:

• Introduction to today’s guests and their perspectives on the role of AI in humanitarianism.
• Learn about the risks and opportunities of using AI for decision-making in humanitarian work.
• Why AI is a “double-edged sword” and how organizations can set effective guardrails.
• What “human-in-the-loop” means and why it depends on autonomy, context, and design.
• Explore the role of affected populations in AI development, lifecycle, and implementation.
• Challenges of balancing speed, cost, and responsible AI deployment in humanitarian work.
• Unpack the colonial undercurrents of AI development and the power imbalances it causes.
• How to identify the needs of an affected population and the potential AI-based solutions. 
• Measuring the cost and return of humanitarian AI solutions versus private-sector models.
• Hear about the future of AI, how it will enable experts, and best practices for developing AI.

Links Mentioned in Today’s Episode:

Sabrina Shih on LinkedIn

Hadassah Drukarch on LinkedIn

Responsible AI Institute

Gayatri Jayal on LinkedIn

Dimagi

Jigyasa Grover

Jigyasa Grover on LinkedIn

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

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