Humanitarian AI podcast series | Bridging implementation gaps: from AI literacy to localisation

How can humanitarian organisations bridge the gap between individual AI experimentation and organisational adoption?

In this second instalment of our six-part humanitarian AI podcast series, Ka Man Parkinson sits down with Michael Tjalve to explore how organisations can move from experimentation to the deployment of contextualised, fit-for-purpose AI solutions - if an organisation decides that this is the right pathway for them,

Michael brings over two decades of interdisciplinary expertise working at the intersection of technology, social impact and humanitarian action. As founder of Humanitarian AI Advisory, co-founder of the RootsAI Foundation, and former Chief AI Architect at Microsoft Philanthropies, and with roles in academia and the UN, he offers insider perspectives on these challenges.

In this deep dive conversation, Michael discusses implementation barriers, practical steps and possibilities, including:

• Why AI policy development should be every organisation's first step
• Looking beyond ChatGPT and large language models for contextualised humanitarian solutions
• Language barriers and broadening AI access
• Community Q&A

Visit the episode webpage for shownotes including speaker bios, episode transcript and supporting links:

https://www.humanitarianleadershipacademy.org/resources/humanitarian-ai-podcast-series-bridging-implementation-gaps-from-ai-literacy-to-localisation

Thanks for listening. Please help us to grow this podcast by subscribing and leaving a review on the platform you're listening from. Thank you! For more resources for the humanitarian community, visit humanitarianleadershipacademy.org/resources

The views and opinions expressed in our podcast are those of the speakers and do not necessarily reflect the views or positions of their organisations.

Chapters

• 0:00 Chapter 1: Introduction
• 2:55 Chapter 2: Tech and academia meets social impact: Michael’s transition into humanitarian AI
• 8:24 Chapter 3: Closing implementation gaps: moving beyond pilot projects through learning
• 17:35 Chapter 4: Overcoming infrastructure challenges: small language models and emerging technologies
• 24:32 Chapter 5: Contextualisation and localisation of AI solutions: addressing the language and cultural learning gaps
• 36:31 Chapter 6: Balancing commercial tools with purpose-built solutions and weighing up the cost of error
• 47:32 Chapter 7: Michael answers your questions: humanitarian community Q&A
• 1:01:32 Chapter 8: Blind spots to address to accelerate shared progress, and closing reflections