『Humanitarian AI Today』のカバーアート

Humanitarian AI Today

Humanitarian AI Today

著者： Humanitarian AI Today
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今ならプレミアムプランが3カ月 月額99円

2026年5月12日まで。4か月目以降は月額1,500円で自動更新します。

概要

 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.All rights reserved
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  • Renaissance Philanthropy’s Ethna Ghosh on Partnership Building in India, AI and Unlocking Scientific and Technological Advancement

    Renaissance Philanthropy’s Ethna Ghosh on Partnership Building in India, AI and Unlocking Scientific and Technological Advancement
    2026/04/06
    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.
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    33 分
  • Federico Pierucci on Multi-Agent Risks in Humanitarian Aid at The Inference Layer

    Federico Pierucci on Multi-Agent Risks in Humanitarian Aid at The Inference Layer
    2026/03/19
    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.
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    42 分
  • Zineb Bhaby on NRC's CLEAR Initiative and Building a Digital Backbone for Humanitarian AI

    Zineb Bhaby on NRC's CLEAR Initiative and Building a Digital Backbone for Humanitarian AI
    2026/03/10
    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.
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    23 分
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