Humanitarian Frontiers in AI

• 3Ps: Policy, Product, Pragmatism: You Only Know What You Know

  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 LinkedInHadassah Drukarch on LinkedInResponsible AI InstituteGayatri Jayal on LinkedInDimagiJigyasa GroverJigyasa Grover on LinkedInNasim Motalebi Nasim Motalebi on LinkedIn Chris Hoffman on LinkedIn

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• AI Regulations: Trickling up, Pouring Down, or Nowhere to Be Seen?

  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 LinkedInTechworker Community Africa (TCA)Gabrielle Tran on LinkedInGabrielle Tran on XInstitute for Security and Technology (IST)EU AI ActNational Institute of Standards and Technology (NIST)AI Risk Management Framework (RMF)Occupational Safety and Health Administration (OSHA)The Alignment ProblemNasim Motalebi Nasim Motalebi on LinkedIn Chris Hoffman on LinkedInInnovation Norway

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• The Donor Dilemma:  Risk Tolerance, Innovation and Responsibility

  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 LinkedInInnovation NorwaySian White on LinkedInUK Humanitarian Innovation Hub (UKHIH)  Zainah Alsamman on LinkedInGrand Challenges CanadaCreating Hope in Conflict: A Humanitarian Grand ChallengeUK Humanitarian Innovation Hub | Directory of AI-enabled humanitarian projectsUK Humanitarian Innovation Hub | NewsletterHumanitarian Innovation Programme: Innovation NorwayElrhaNasim Motalebi Nasim Motalebi on LinkedIn Chris Hoffman on LinkedIn

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• Nowhere To Go but Up: Future Trends of AI Use in the Humanitarian Sector

  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 LinkedInData Friendly Space (DFS)H2H NetworkNana Gamkrelidze on LinkedInInternational Federation of Red Cross and Red Crescent Societies (IFRC)AI Action SummitUN World Food Programme (WFP)GANNETHugging FaceNasim Motalebi Nasim Motalebi on LinkedIn Chris Hoffman on LinkedInHumanity LinkChris Hoffman

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  46:52
• Aid and Algorithms: Demystifying LLMs

  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 LinkedInScott Turnbull on LinkedInScott Turnbull on XData Friendly SpaceInnovation NorwayTwilioNasim Motalebi Nasim Motalebi on LinkedIn Chris Hoffman on LinkedIn

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