Humanitarian AI Today

著者： Humanitarian AI Today
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  • 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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あらすじ・解説

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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エピソード
  • Affected Populations in Discussion: Vulnerable Populations and the Rollout of AI Applications

    Affected Populations in Discussion: Vulnerable Populations and the Rollout of AI Applications
    2024/12/17
    In this episode, the UK Humanitarian Innovation Hub (UKHIH), Elrha, and Humanitarian AI Today bring panelists together to critically examine the colonial approach in the rollout of AI applications, including the extraction of data from vulnerable groups without adequate representation or input. Shaza Alrihawi, Researcher, Human Rights Advocate, and Consultant specializing in working with refugees at the Leibniz Institute for Educational Trajectories; Shruti Viswanathan, an Independent Consultant, Data Governance and Digital Inclusion; Olubayo Adekanmbi, CEO and Co-founder of EqualyzAI and CEO and Founder of Data Science Nigeria; and Helen McElhinney, Executive Director with the CDAC Network, join Brent Phillips, Producer of the Humanitarian AI Today podcast, to discuss the rollout of AI applications, the extraction of data from vulnerable groups without adequate representation or input, key challenges in engaging affected populations and communities on the topic of AI and how we can roll out AI technologies in humanitarian work in an ethical and impactful manner. This episode is part of a six-part panel discussion series produced by Humanitarian AI Today in collaboration with the UK Humanitarian Innovation Hub and Elrha, with funding from UK International Development from the UK Government. More information about this episode and details about the rest of the series can be found by subscribing to the UK Humanitarian Innovation Hub and Elrha's new AI newsletter: http://ukhih.org/newsletter.
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    1 時間 14 分
  • Transparency in Discussion: Improving Transparency and Accountability in AI Implementations

    Transparency in Discussion: Improving Transparency and Accountability in AI Implementations
    2024/11/24
    The UK Humanitarian Innovation Hub (UKHIH), Elrha, and Humanitarian AI Today bring panelists together to discuss transparency and strategies for improving transparency and accountability in AI implementations. Michael Hind, Distinguished Research Staff Member at IBM Research; Shadrock Roberts, Director of Global Data Protection & Privacy at Mercy Corps; Scott Turnbull, Chief Technology Officer at Data Friendly Space; Liam Nicoll, Signpost Product Lead at Signpost AI Lab; and Sarah Spencer, a consultant who regularly speaks on humanitarian operations and applications of artificial intelligence, contribute their insights on transparency and ways of improving transparency and accountability in AI implementations. Touching on the existing landscape of AI initiatives within the humanitarian sector, key players, and what transparency means broadly and in practice, their views connect the humanitarian and technology communities and provide valuable insight into why transparency is crucial for building trust in AI systems and engaging stakeholders in developing and leveraging uses of AI for good. The panel discussion, guest hosted by Brent Phillips from Humanitarian AI Today, mixes input on AI systems, technical information disclosure, AI governance and regulation, and how humanitarian organizations are approaching developing, testing and deploying safe, responsible and trustworthy AI applications that are transparent and accountable to end users. Panelists each share their views on ways of improving transparency and offer ideas on directions to expand the transparency conversation. In closing, panelists provide a strong case for greater information sharing on AI use cases and greater inclusivity around transparency throughout the AI building and deployment process. This episode is part of a six-part panel discussion series sponsored and produced by Humanitarian AI Today in collaboration with the UK Humanitarian Innovation Hub (UKHIH) and Elrha, with funding from UK International Development from the UK government. More information about this episode, its focus and upcoming discussions can be found by subscribing to the UK Humanitarian Innovation Hub and Elrha's new AI newsletter: http://ukhih.org/newsletter.
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    1 時間 19 分
  • Sian White, Dan Amias and Daniela Weber Introduce Elrha and UKHIH's new AI Newsletter

    Sian White, Dan Amias and Daniela Weber Introduce Elrha and UKHIH's new AI Newsletter
    2024/10/26
    Sian White, Director of the UK Humanitarian Innovation Hub; Dan Amias, Senior Innovation Learning Advisor at Elrha; and Daniela Weber, Director of NetHope’s Center for the Digital Nonprofit, discuss the growing importance of AI in the humanitarian sector and introduce Elrha and UKHIH’s new AI newsletter. Joining Brent Phillips of Humanitarian AI Today, they highlight recent AI initiatives by UKHIH, Elrha, and NetHope, emphasizing their collaborative role in advancing humanitarian efforts. They also share insights from their AI learning journeys, key takeaways, and ongoing challenges in harnessing AI for humanitarian impact.
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    37 分

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