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How are AI-powered nonprofits moving beyond early experiments to deliver deep, lasting social impact? In this episode of Humanitarian AI Today, guest host Alexandra Pittman, Founder and CEO of ImpactMapper, speaks with Kevin Barenblat, Co-founder and President of Fast Forward and author of AI for Humanity on Substack. Kevin shares exclusive findings from Fast Forward’s 2026 AI for Humanity Report, a comprehensive study based on survey data from 119 AI-powered nonprofits across 20 countries and 20 in-depth leadership interviews. The conversation explores how mission-driven organizations are leveraging AI to personalize services and improve program outcomes, while confronting major sector challenges, including the "messy middle" of post-launch funding, rising infrastructure costs, human capacity constraints, and community-first risk mitigation. Humanitarian AI Today is proud to be part of the Devex Podcast Network, bringing listeners insider journalism and expert analysis across global development and humanitarian relief fields. For complete show notes, transcriptions, and further resources from this episode, visit the Humanitarian AI Today Substack at humanitarianaitoday.substack.com. This Week in Global Development is Devex’s podcast series covering the top stories from the global development sector: https://www.devex.com/focus/this_week_in_global_development

In this Humanitarian AI Today episode, Yemesrach Assefa Workie (Yemi), Executive Director of the International Aid Transparency Initiative (IATI), speaks with producer and guest host Brent Phillips about open data as a strategic infrastructure for artificial intelligence. As an open data sharing framework widely used across the humanitarian community, IATI tracks over $3.9 trillion in funding across more than one million development and relief activities reported by nearly 2,000 organizations. The conversation explores how rapid advances in machine learning are reigniting interest in large structured data sets, allowing AI applications to seamlessly traverse IATI’s vast corpus and convert decades of decentralized global aid data into real-time operational insights. The interview dives into practical use cases where AI tools are already unlocking the value of IATI's machine-readable XML standard alongside the 500,000 unstructured evaluation documents, audits, and reports linked within its database. Yemi highlights real-world implementations, such as the UK Government’s Development Explorer for portfolio analysis, Germany’s AI-driven data quality checks, and IATI’s deployment of AI help desk agents. However, she cautions that AI capabilities are only as good as their underlying inputs, urging humanitarians to manage critical risks including poor data quality, loss of local crisis context, representation bias from varying publishing volumes, and over-reliance on automation over human judgment. A key takeaway from the discussion focuses on how publishing open data acts as a vital visibility multiplier for aid organizations in the AI age. As autonomous agents, LLMs, and decision-support systems become the primary interfaces for analyzing crisis responses, unstandardized or unshared operational data effectively renders an organization invisible to automated discovery. By channeling standardized data through open frameworks like IATI, actors of all sizes, particularly small civil society organizations and local NGOs, ensure their ground-level contributions, delivery partnerships, and operational footprints are accurately represented and indexed by global AI systems. Looking ahead to major sector gatherings like the AI for Development Summit hosted by DevelopMetrics, the episode underscores why structured open data standards are experiencing a major revival. By providing a standardized, verified baseline, large datasets like IATI prevent model hallucinations, enable cross-domain interoperability with geospatial or climate data, and lay the groundwork for futuristic decision-support tools. Concluding with a clear call to action, Yemi encourages organizations of all sizes to publish their data, refine entry quality, and leverage free IATI tools to position themselves at the forefront of AI-driven humanitarian action. Humanitarian AI Today is a community-produced podcast and a proud member of the Devex Podcast Network, an initiative dedicated to expanding the visibility of coverage across global health, development, and relief sectors. The series brings together community partners like the International Aid Transparency Initiative (IATI) and enterprise technology leaders like Neo4j, providing an open channel for humanitarian actors and technical teams to share updates on AI projects, discuss advances in machine learning, and collaborate on data-driven solutions for the sector.

On this special Humanitarian AI Today episode recorded in Chinese and English, Lili Qiu, Co-founder and Chief Supervisor of the Peaceland Foundation speaks with guest host, Brent Phillips, and Ankang Song, Executive Director at Global Youth Philanthropy, about the Peaceland Foundation’s aid work around the world and experimentation with AI. As the global humanitarian community gathers for the AI for Good Summit in Geneva, this insightful interview offers Western organizations an exclusive window into how China's fast-evolving technology ecosystem is transforming disaster relief and healthcare. The discussion explores how Chinese non-profits are actively experimenting with cutting-edge AI, from deploying autonomous medical rescue ships to standardizing drones for wildfire and flood responses. The podcast episode highlights the dynamic partnerships driving these innovations, showcasing how Chinese organizations closely collaborate with universities and research institutions to test intelligent equipment in real-world disaster scenarios. It also addresses the operational agility required to keep pace with China's rapid tech advancements while keeping production and supply chain costs exceptionally low for underdeveloped regions. Most importantly, the interview serves as a bridge for international cooperation, offering practical advice on how Western and Chinese organizations can break through linguistic barriers, build mutual trust, and establish direct channels for meaningful cross-border collaboration.

In this Humanitarian AI Today episode, Michael Tjalve, Independent Humanitarian AI Advisor and co-author of the SAFE AI framework, speaks with guest host Jennifer Wilde, an AI strategy and social impact advisor, about AI governance, the SAFE AI initiative and the evolving security and operational landscapes. Against the backdrop of critical, sector-wide dialogues bringing together executive leadership and technical teams from organizations of all sizes, they explore the new safety and security topics of concern posed by advances in AI, compute distributed across agents, and the emergence of sophisticated models like Mithos that can expose and be used to exploit critical IT security vulnerabilities. Michael outlines his advisory work helping humanitarian organizations understand how they can confidently use AI in a way that is both effective and responsible, emphasizing the increasingly present role that artificial intelligence has in humanitarian action today. Jennifer and Michael discuss the SAFE AI framework next, the Standards and Assurance Framework for Ethical AI, which stands as the first operational, end-to-end AI governance framework tailored specifically for humanitarian actors. Developed through a vital collaboration between the CDAC Network, The Alan Turing Institute, and the Humanitarian AI Advisory, with critical funding from the UK Government’s Foreign, Commonwealth and Development Office (FCDO) and deep consultation with East African researchers and communities, the toolkit bridges the gap between high-level policy and grassroots implementation. They walk through how both large and small organizations can start utilizing the toolkit today, what is essential to know to begin, and exactly where to start. Pointing out how organizational governance is lagging behind organic, "shadow IT" AI experimentation, Michael and Jennifer discuss in detail why structured guardrails are vital for the sector. They address how crucial it is for team members and staff across entire organizations, whether at global headquarters or country offices, to have access to appropriate training and a centralized focus on AI policy and strategy, highlighting how the SAFE AI framework provides actionable guidance to achieve this. Touching on rapid technological leaps, Michael notes how the emergence of agentic AI introduces an additional layer of complexity for responsible governance. With semi-autonomous processes executing tasks on an organization's behalf, the potential for compounding errors increases while transparency declines, a distance that challenges traditional accountability models and complicates oversight. Together, Michael and Jennifer advocate for starting any AI adoption journey with a clear focus on the specific human need or use case rather than deploying the technology for its own sake. Drawing on the core tenets of the framework, co-authored by Michael alongside Suzy Madigan, Helen McElhinney, Sarah Spencer, and Anjali Mazumder, they emphasize that true accountability requires an operational commitment to "communities in the loop". This means ensuring that frontline staff can confidently explain AI-driven outcomes to affected populations, and that AI systems never silently or inequitably exclude the very people humanitarians are bound to protect. Ultimately, they agree that while the rapid expansion of AI is exciting, organizations must maintain a healthy balance of curiosity and caution, allowing their concerns to drive continuous learning and the proactive questioning necessary to confidently take responsible steps forward. Because there is absolutely no margin to get it wrong in a humanitarian crisis, this collective effort reminds listeners that stress-testing AI governance under extreme, high-stakes conditions does not just safeguard vulnerable populations; it creates a vital proof of concept with profound lessons for how responsible AI should be governed anywhere in the world.

In this Humanitarian AI Today Voices flashpod, Theodora Skeadas, Head of AI Red Teaming with Humane Intelligence, joins guest host Brent Phillips to unpack for staff from humanitarian organizations what AI red teaming is and how Humane Intelligence approaches carrying out AI evaluations. They also discuss the nonprofit’s mission to make AI systems more accountable, fair, and safe and the organization’s latest initiatives. The discussion traces the evolution of Humane Intelligence’s evaluation work, highlighting recent milestones such as the open-source release of their evaluation application and their expanded bias bounty programming in collaboration with platforms like Zindi. Theodora outlines the fundamentals of artificial intelligence evaluations and red teaming methodologies applied to humanitarian applications. The discussion offers a practical introduction to the testing and evaluation of generative AI models, specifically tailored to help staff from aid organizations understand how these systems operate and learn how to carry out effective risk assessments. For humanitarian actors looking to ethically integrate artificial intelligence into active crises workflows, the interview provides a grounded framework for identifying potential harms before and after applications deployment. Theodora outlines how organizations can proactively red team tools for systemic vectors of concern, including factuality, geographic bias, and public health misinformation using simple workplace tools like spreadsheets or through step-by-step guidance found in resources like The Playbook: Red Teaming Artificial Intelligence for Social Good. By demonstrating how humanitarian actors can systematically test language models for safe output boundaries, the conversation illustrates a critical pathway toward building more transparent, responsible, and localized AI implementations across the sector.

Priyank Hirani, Vice President of Programs at data.org discusses the India AI Impact Summit and India’s role as a development space and test bed for responsible and inclusive AI applications with Humanitarian AI Today Producer, Brent Phillips. In this insightful conversation, Hirani highlights how India is shifting the global narrative away from frontier model competition toward practical, population-scale AI deployment that addresses real-world challenges in health, agriculture, and finance. By building directly upon a decade of robust digital public infrastructure, the Indian ecosystem accelerates adoption through lean, cost-effective and context-aware innovation. Hirani emphasizes how this unique ecosystem serves as a powerful blueprint for the global majority, championing "South-South" collaborations and responsible and inclusive AI innovation. The episode underscores data.org’s mission as a global catalyst, capacity builder, and convener in the social impact sector. Hirani discusses the organization’s ambitious goal to cultivate one million purpose-driven data professionals by 2032 through its expanding Capacity Accelerator Network. Looking ahead to the future of technology, he shares a compelling vision for "Civic AI” and the creation of persistent, multilingual, and context-aware personal AI agents designed to help citizens frictionlessly navigate complex public systems. The conversation is packed with updates on data.org’s latest initiatives, including regional hackathons and the Finverse, a decision support tool and resource hub designed to help organizations in the Asia Pacific (APAC) region use data and AI to improve the financial health of the individuals and communities they serve. This episode is a must-listen for social impact professionals, researchers, and anyone invested in a more equitable and human-centered AI future.

In this Humanitarian AI Today Voices flashpod, Eric Talbert, Co-founder of MedCycle Network guest hosts an interview with Jarrod Goentzel, founder and director of the MIT Humanitarian Supply Chain Lab in the MIT Center for Transportation & Logistics. This interview dives into the evolution and modern practices of the MIT Humanitarian Supply Chain Lab for humanitarian professionals looking to optimize crisis response through system-level thinking and technology. The discussion traces the lab’s journey from its origins during the 2004 Indian Ocean tsunami to its needs-assessment work and market-resilience studies to it’s general shift away from reactive, event-specific planning toward building structural, "system-level" understandings of supply chains and how organizations can better anticipate bottlenecks and coordinate with the private sector. For humanitarian professionals, the interview offers a grounded, pragmatic perspective on integrating artificial intelligence into crisis response. Goentzel explicitly addresses the limitations of relying solely on automated systems, noting that AI inherently struggles with data gaps, as it is bounded by what is publicly available and cannot easily synthesize entirely unique disaster contexts on its own. To overcome this, the MIT Humanitarian Supply Chain Lab utilizes AI as an initial data-gathering and pattern-matching catalyst, which is then verified through a human-in-the-loop framework. The lab deploys a network of real-time ground-truthers who are trusted professionals embedded within the supply chain who validate the AI's outputs. This hybrid model ensures that automated data collection never compromises the absolute operational integrity required when delivering life-saving aid to vulnerable populations. The interview touches upon "polycentric governance," which is the concept of humans organically cooperating to manage common resources during crises. The lab models supply chains as complex adaptive systems and conducts "Blue Sky Studies”which are highly detailed structural mapping done when there is no active emergency to locate vulnerabilities before disaster strikes. A prime example of this is the lab’s SCAN (Supply Chain Analysis Network) mapping, which evaluated infrastructural bottlenecks in transportation and fuel pipelines. Looking toward the future of humanitarian tech, the conversation highlights cutting-edge applications of predictive modeling and advanced AI training. For AI developers, Goentzel offer’s a futuristic vision for disaster AI: rather than letting a machine application start from scratch during an active crisis, the lab is actively researching ways to pre-embed AI with complex supply chain network science and system dynamics. By providing the machine with a sophisticated baseline of structural interdependencies beforehand, the AI can immediately interpret real-time news and data influxes with extreme speed. This effectively frees up human humanitarian leaders to step away from the information onslaught and focus entirely on creating the rapid physical and collaborative connections needed to save lives. The MIT Humanitarian Supply Chain Lab offers resources and educational platforms to connect researchers, technology experts, and ground-level aid workers. Goentzel invites listeners to join the lab’s humanitarian supply chain community and take advantage of free online course developed by the lab, like the lab’s free Humanitarian Logistics course through MITx: https://www.edx.org/learn/business-administration/massachusetts-institute-of-technology-humanitarian-logistics An article on the Lab's supply chain resilience work can be found here: https://ctl.mit.edu/sites/default/files/documents/scmr-innovation-strategies-september-2025.pdf To learn more about Eric Talbert’s work and the MedCycle Network, check out his interview on the Grow Healthy, Help People Podcast: https://youtu.be/w495cOVVajw?si=EMZLr-zZXAWM93Oq

Rubén Lozano-Aguilera, Product Lead for Asta at the Allen Institute for AI (Ai2), explores the transformative potential of agentic AI in scientific research with Humanitarian AI Today guest host Lindsey Moore, Founder of DevelopMetrics. Rubén introduces AutoDiscovery, a powerful new tool developed by his team that moves beyond traditional query-based analysis to autonomously generate and test scientific hypotheses. This shift from manual data processing to autonomous discovery offers a powerful force multiplier for researchers, helping them surface blind spots and hidden patterns that traditional methods often overlook in fields ranging from melanoma research to marine ecology.   For humanitarian and development organizations, Ai2's work represents a vital new advancement in what Rubén calls "shared AI infrastructure." Ai2's deep commitment to the open-source movement, providing open models, checkpoints, code, and training data, ensures transparency and accessibility for all. This approach is particularly impactful for organizations operating in resource-constrained environments, as it allows them to leverage state-of-the-art predictive analytics without the high costs or "black box" risks associated with proprietary systems. By democratizing access to high-level research tools, Ai2 enables any researcher or developer to maintain data ownership while utilizing sophisticated AI to solve the world's most pressing problems.   The conversation next turned to the deeper philosophical stakes of automating scientific discovery itself. Drawing on his graduate research in AI ethics at Cambridge, Rubén separates what philosophers of science call the "context of discovery”, how a hypothesis is generated, from the "context of justification," how it is tested and validated. The worry is deskilling: as scientists offload hypothesis generation to AI, will they lose the instincts needed to catch when the machine is wrong? His answer centers on cultivating "meta-AI skills", the practiced ability to evaluate AI outputs critically. That raises its own problems: how do those skills get built, and are they really the same kind of skill as the hypothesis-generating instincts they would replace? Ai2 is actively studying this by examining how tools like AutoDiscovery affect students and early-career researchers. For humanitarian and development professionals navigating an era of shrinking research budgets and growing AI adoption, these added points raise essential questions about keeping human judgment at the center of discovery.

Ethna Ghosh, India Partnerships Lead with Renaissance Philanthropy, discusses the nonprofit organization’s operational strategy, her work and India’s role as a global hub for AI experimentation with Brent Phillips, Humanitarian AI Today podcast producer. Drawing on her deep roots in the Indian development sector, Ethna shares insights from her experience as a founding member of GivingPi, India's first family philanthropy network at Dasra, where she specialized in building strategic partnerships and advising families on high-impact giving. From this vantage point, she provides an insider’s perspective on India’s emergence as a science and technology pioneer and a premier real-world testing ground, where localized AI applications can be deployed across a diverse population of 1.4 billion people with immense cultural, geographic and linguistic diversity to address a myriad of social challenges. Elaborating on her role as Renaissance Philanthropy’s India Partnerships Lead, Ethna outlines how the organization accelerates scientific, technological and innovation breakthroughs by using a thesis-driven, time-bound fund model connecting donors with domain experts to tackle high-impact, underfunded projects. By empowering field leaders to identify and eliminate systemic bottlenecks to enable scalable change, the organizations acts as force multiplier to achieve large-scale, transformative impact rather than just deploying capital. By supporting a diverse portfolio of deep-science innovations, the organization seeks to spark a modern "Renaissance movement" where converging technologies like AI and space tech for example transform the global landscape. Offering insight into the keys to success in environments like India, Ethna emphasizes "bottom-up" approaches that prioritize deep collaboration between Samaj (society), Sarkar (government), and Bazar (market). Highlighting rural maternal health workers as a case study, Ethna points out that involving government entities is a non-negotiable in India for any initiative aiming to achieve true national scale and effectively engage the "last mile" of the population. Looking toward the future, Ghosh envisions a shift toward agentic and physical AI that moves beyond simple text prompts to become a voice-enabled "buddy" for those with limited digital literacy. She advocates for the development of inclusive models that strip away linguistic and gender biases to provide safe, life-changing access to justice, healthcare, and government services. This vision ensures that technology serves as a bridge for equality, providing every citizen with a reliable companion to navigate a rapidly changing world. She concludes with a powerful call for radical collaboration among foundations and NGOs, urging stakeholders to move past silos and genuinely partner to eliminate the bottlenecks holding back progress.

Co-produce by Humanitarian AI Today, this third pilot episode of The Inference Layer podcast bridges the technical complexities of AI deployment with the reality of humanitarian operations and dives into the transition from static models to autonomous agentic systems. On behalf of the Humanitarian AI Today podcast, guest host Patrick Hassan, an AI policy lead with a background in disaster response, interviews Federico Pierucci, Scientific Director of the Icaro Lab, to explore how the inference layer is becoming a site of significant systemic risk. The discussion provides a unique look at inference-time failures such as alignment drift and steganographic coordination that emerge only when multiple agents interact in production environments. For humanitarian actors, the episode raises concerns regarding operating in an era of assistance automated by layers of AI agents. The dialogue highlights how multi-agent chains used for beneficiary selection or resource allocation for example can degrade, develop invisible biases or be weaponized or politicized by parties to a conflict. Federico explains that these risks can be compounded by a lack of safety benchmarks for things like underrepresented languages and dialects, which can lead to unpredictable jailbreaks or administrative failures in the field. The episode provides an inside look at pioneering research being carried out by the Icaro Lab, a Rome-based laboratory specialized in AI safety in collaboration with the Sapienza University. The lab focuses on mechanistic interpretability, a technical field dedicated to understanding the internal attention heads and decision-making units of an AI to decipher how it truly processes information. The discussion introduces the concept of Institutional AI, a proposed framework to manage these emerging xeno-behaviors through a governance graph. Rather than relying solely on prompt engineering or model-level alignment, Federico argues for a protocol-level solution that can manage misbehaving agents during inference. The episode is informative for professionals seeking to understand why AI safety must evolve from a localized technical challenge into a global institutional design problem, particularly in regions where traditional governance has broken down. This particular episode moves beyond surface-level AI ethics and safety issues that the humanitarian community has been talking a lot about, to address inference-time vulnerabilities in agentic systems. This is an important topic because as the humanitarian community moves from developing and testing simple chatbots to incorporating autonomous multi-agent systems into humanitarian operations, we face new challenges that can have very serious consequences - making the 'inference layer' a new frontier for humanitarian risk.

Zineb Bhaby, AI Lead at the Norwegian Refugee Council, introduces NRC’s CLEAR (Crisis Learning, Early-warning, Anticipation, and Response) initiative and discusses the critical necessity of data collaboration in the humanitarian sector with Humanitarian AI Today producer Brent Phillips. The CLEAR initiative is a three-year project supported by Twilio that is designed to build a digital "backbone" for humanitarian cooperation that the humanitarian community can collectively maintain and evolve. Zineb stresses that CLEAR’s goal is bring together humanitarian, academic and private sector partners through a consortium to integrate diverse data sources into unified early warning and early action systems, leveraging artificial intelligence and predictive analytics to transform how humanitarian organizations detect, prepare for and respond to crises. Discussing CLEAR and challenges associated with the collection and use of data by aid organizations and the imperative to do better, Zineb nevertheless emphasizes that strict data governance remains a priority to protect the safety and sensitivity of information regarding vulnerable populations. By prioritizing an agile, safety preserving, open-source approach that bridges the gap between available information and field response, the initiative seeks to create a more resilient and unified technological foundation for the entire humanitarian ecosystem.

Voices is a new mini-series from Humanitarian AI Today. In short daily flashpods, Voices passes the mic to guests to learn about new projects, events and advances in artificial intelligence and discuss topics that are important to the humanitarian community. In this flashpod, Lukas Borkowski, Senior Director of Strategic Partnerships at Viamo shares how artificial intelligence can serve the billions of people who remain offline and rely on basic mobile phones. In a conversation with Humanitarian AI Today producer, Brent Phillips, Lukas spotlights the reality that most people in lower income countries live their lives largely offline and disconnected from the benefits of emerging AI applications while at the same time live under mobile network coverage. Lukas describes how Viamo works directly with mobile network operators to negotiate long-term partnerships that enable national-scale, toll‑free hotlines and behavior-change campaigns and he describes how Viamo is rapidly expanding voice-first gen‑AI experiences for use cases like rural health worker hotlines and disaster-preparedness campaigns. He outlines Viamo’s cloud and in‑country server architecture, their use of generative AI and speech technology in local languages, and their specialization in behavior-change communication design that is tailored to specific geographies and demographics. Offering examples from public-health collaborations, he illustrates how voice-based generative AI can support and provide both community members and frontline workers with accessible information, advice and decision support. Touching on broader ecosystem challenges, Lukas highlights the lack of high-quality speech technology for many African and Asian languages and calls for more investment, standardized tooling, and collaboration with aggregators like Viamo rather than fragmented pilots and one-off solutions. He calls for partners who bring clear behavioral objectives and a willingness to deploy imperfect but improving tools, arguing that waiting for perfect technology delays agency for people who urgently need trustworthy information. Looking ahead, he envisions seamless voice experiences where, in a single call, users can learn about services, ask personalized questions, and complete tasks.

Voices is a new mini-series from Humanitarian AI Today. In short daily flashpods, Voices passes the mic to guests to learn about new projects, events and advances in artificial intelligence and to discuss topics that are important to the humanitarian community. In this flashpod, Javan Van Gronigen, Founder and Creative Director of Fifty & Fifty, a digital agency that works with leading social-minded organizations, and Donately, a fundraising software provider for nonprofits and peer-to-peer fundraising platform, joins Humanitarian AI Today Producer, Brent Phillips, to discuss digital storytelling and the technical infrastructure required to sustain modern humanitarian missions. Javan points out that while many organizations have powerful missions, only a small fraction feel truly ready to adopt and execute their digital strategies. Drawing from his extensive background as a creative director for global campaigns, Javan emphasizes that for humanitarian organizations to remain competitive in a crowded digital attention economy, they must move beyond random acts of marketing and instead adopt a cohesive "Engagement OS" that treats brand identity and donor friction with the same rigor as top companies. The conversation primarily touches on digital transformation and how organizations can leverage AI to bridge the gap between small-scale manual engagement efforts and scalable, one-to-many engagement models. The interview serves as a strategic roadmap for humanitarian practitioners looking to navigate the complexities of AI and ensure that technology serves as an invisible operating layer that amplifies human impact rather than obscuring it. Javan argues that the solution lies not just in adopting more tools, but in ensuring that those tools are secondary to a primary, authentic narrative that builds long-term trust with a global audience.

Voices is a new mini-series from Humanitarian AI Today. In short daily flashpods, we pass the mic to guests to tell us about new projects, events and advances in artificial intelligence and to discuss topics that are important to the humanitarian community. In this flashpod, Golestan (Sally) Radwan, Chief Digital Officer with the United Nations Environment Program and a Board Member of the Allen Turing Institute speaks with Panagiotis Moutis, Assistant Professor at the City College of New York and a member of the Climate Change AI initiative about AI’s environmental “sustainability paradox” with Humanitarian AI Today Producer, Brent Phillips. Balancing technology’s potential to solve complex environmental problems against AI’s ecological costs, high energy consumption, water usage and e-waste, Sally and Panos emphasize that AI is not a magic solution but a complex equation where the new tools that we’ll use to save the environment are themselves taxing its resources, and suggest that AI’s value must be weighed against costs and resources that the technology draws away from other humanitarian and environmental needs. The participants explore the potential of on-device machine learning to reduce the environmental footprint of AI by shifting workloads from data centers to local hardware and discuss the critical role of data infrastructure and global cooperation in addressing climate change. Sally touches on the challenges of data interoperability, noting that too many different standards exist for environmental data, which complicates the "multivariable analysis" needed for accurate climate forecasting. Panos offers a somber closing perspective, likening the struggle against climate change to a war where key battles may already be lost. He argues that AI's greatest potential might lie in creating clear, uncurated narratives to help the public and politicians grasp the existential urgency of the crisis. To help address this need for reliable information, Sally highlights the launch of EnvironmentGPT, a new tool designed to make environmental science easier to access and understand. Humanitarian AI Today is a community-led initiative advised and co-produced by collaborating organizations and technology companies. Amidst a fragmented landscape, the podcast serves as a recognizable channel for organizations, donors, and innovators to collectively use to report AI projects, events and advances, turning raw insight into collective intelligence.

Yarissa Matos-Soto, Founder of The Curioux, speaks with Humanitarian AI Today producer, Brent Phillips about the critical need to effectively assess artificial intelligence for outcomes and risks within the humanitarian sector. Drawing from her background as a biochemist, data specialist and startup founder, Yarissa explains how her organization, The Curioux, provides advisory services to help for-profit organizations structure their data strategy and pipelines to make data more actionable. Beyond her corporate work, she discusses her passion for environmental science, specifically her efforts to create open-source intelligence for biodiversity that aggregates hyper-local data. She also highlights her leadership role with the Association for Latin American Professionals (ALFA), where she works to formalize the local economy in Puerto Rico through networking and AI training initiatives. The conversation explores the practical realities of deploying technology in challenging environments, emphasizing the "hidden costs" of connectivity in places like Puerto Rico and Ukraine. Yarissa shares insights on how local professionals navigate rolling blackouts and infrastructure hurdles to maintain digital livelihoods. Looking toward the future, she envisions AI becoming an invisible operating layer in daily life and encourages humanitarian workers to view AI as a tool for augmentation rather than a threat, urging them to find use cases that make practical sense for their missions.