Humanitarian Frontiers in AI

• 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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  57:50
• Peering Through the Data Scope: Uncovering the Unknown

  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 LinkedInRelief InternationalMatthew Harris on LinkedInProgram Integrity AllianceWorld Food Programme'Generative AI for Humanitarians'LangSmithDataKindNasim Motalebi Nasim Motalebi on LinkedIn Chris Hoffman on LinkedIn

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  49:10
• Ethics and Responsibility from 30,000 Feet

  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 LinkedInEmily Springer AdvisoryThe Inclusive AI Lab by Emily SpringerMala KumarMala Kumar on LinkedInML CommonsSuzy Madigan on LinkedInSuzy Madigan on XThe Machine Race by Suzy MadiganFCDO Call for Humanitarian Action and Responsible AI ResearchML Commons AI Safety Benchmark‘Collective Constitutional AI: Aligning a Language Model with Public Input’Nasim Motalebi Nasim Motalebi on LinkedIn Chris Hoffman on LinkedIn

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  57:29

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