Humanitarian AI Today

Humanitarian AI Today

Humanitarian AI Today is the leading AI for Good podcast series focusing on humanitarian applications of artificial intelligence. We interview leaders, developers and innovators advancing humanitarian applications of AI from across the tech and humanitarian communities. The series is produced by the Humanitarian AI meetup.com community, linking local groups in Cambridge, San Francisco, Seattle, New York City, Toronto, Montreal, London, Paris, Berlin, Oslo, Geneva, Zurich, Bangalore, Tel Aviv and Tokyo.

  1. Theodora Skeadas on Red Teaming Humanitarian AI Applications

    1 day ago

    Theodora Skeadas on Red Teaming Humanitarian AI Applications

    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.

    21 min
  2. Priyank Hirani from Data.org on Scaling Inclusive AI for Social Impact

    4 Jun

    Priyank Hirani from Data.org on Scaling Inclusive AI for Social Impact

    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.

    24 min
  3. Jarrod Goentzel on MIT’s Humanitarian Supply Chain Lab, AI and System Level Thinking

    29 May

    Jarrod Goentzel on MIT’s Humanitarian Supply Chain Lab, AI and System Level Thinking

    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

    33 min
  4. Ruben Lozano Aguilera from Ai2 on Asta's AutoDiscovery Tool for Scientific Discovery

    12 May

    Ruben Lozano Aguilera from Ai2 on Asta's AutoDiscovery Tool for Scientific Discovery

    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.

    25 min
  5. Renaissance Philanthropy’s Ethna Ghosh on Partnership Building in India, AI and Unlocking Scientific and Technological Advancement

    6 Apr

    Renaissance Philanthropy’s Ethna Ghosh on Partnership Building in India, AI and Unlocking Scientific and Technological Advancement

    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.

    33 min
  6. Federico Pierucci on Multi-Agent Risks in Humanitarian Aid at The Inference Layer

    19 Mar

    Federico Pierucci on Multi-Agent Risks in Humanitarian Aid at The Inference Layer

    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.

    42 min
  7. Zineb Bhaby on NRC's CLEAR Initiative and Building a Digital Backbone for Humanitarian AI

    10 Mar

    Zineb Bhaby on NRC's CLEAR Initiative and Building a Digital Backbone for Humanitarian AI

    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.

    23 min
  8. Lukas Borkowski on Building Voice-First Humanitarian AI on a National Scale

    4 Mar

    Lukas Borkowski on Building Voice-First Humanitarian AI on a National Scale

    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.

    23 min

About

Humanitarian AI Today is the leading AI for Good podcast series focusing on humanitarian applications of artificial intelligence. We interview leaders, developers and innovators advancing humanitarian applications of AI from across the tech and humanitarian communities. The series is produced by the Humanitarian AI meetup.com community, linking local groups in Cambridge, San Francisco, Seattle, New York City, Toronto, Montreal, London, Paris, Berlin, Oslo, Geneva, Zurich, Bangalore, Tel Aviv and Tokyo.

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