Code Green
Digital Futures Lab and Earth Venture Foundation
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09/05/24 • 63 min
The climate crisis has pushed parts of Asia past a tipping point, making urgent solutions critical. While tech solutions like AI-driven smart agriculture and energy management are emerging, there's little understanding of the extent of their adoption and impact. How will AI fare in contexts underscored by issues of digital divide, data challenges and financial gaps?
In episode zero of the Code Green podcast, we speak to leading experts on the intersection of AI and climate action in Asia from a policy, technology and finance lens. Our guests highlight the many opportunities for AI in climate adaptation, environmental costs and pathways needed to ensure climate justice in the long run.
Speakers
Elina Noor, Senior Fellow, Asia Program, Carnegie Endowment for International Peace
Elina's work focuses on developments in Southeast Asia, particularly the impact and implications of tech in reshaping power dynamics, governance and nation-building.
She's been the director of political-security affairs and deputy director of the Washington DC office at the Asia Society Policy Institute; and associate professor at the Daniel K. Inouye Asia-Pacific Center for Security Studies in Honolulu.
Elina has spent most of her career at the Institute of Strategic and International Studies Malaysia, last as director, foreign policy and security studies. She was also with the Brookings Institution’s Project on US Relations with the Islamic World, and currently serves on the UN Sec-Gen’s Advisory Board on Disarmament Matters.
Alpan Raval, Chief Scientist AI/ML, Wadhwani AI
Alpan is a theoretical physicist, in the applied AI space for the last 24 years, applying ML to problems in computational biology and chemistry, queuing, computational advertising, online newsfeed optimisation and content moderation, public health, and agriculture.
Alpan has led applied AI teams at LinkedIn and Amazon, worked as a researcher at D E Shaw Research; and taught mathematics and computational biology at the Claremont Colleges in California. He is the co-author of Introduction to Biological Networks (CRC Press).
Varad Pande, Partner, Boston Consulting Group
Varad is a leader in BCG’s Climate & Sustainability and Social Impact practices with a focus on emerging markets. He is part of BCG’s Asia leadership team for social impact, climate finance, and adaptation and resilience. He has over 20 years of global experience as a senior ministerial advisor, an impact investor, and strategy consultant.
Varad’s work has spanned UN Sustainable Development Goal domains such as financial inclusion, agriculture and livelihoods; and he has helped shape the global discourse on the role of digital public infrastructure (DPI) in accelerating the achievement of the SDGs.
Varad was formerly a Partner at Omidyar Network India, and a partner and Asia Leader at Dalberg.
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Find the transcript here and visit codegreen.asia
Credits
Audio Editing: Sharon Joseph
Production Support: Shivranjana Rathore
Attributions
Intro, Outro - Retro Sounds, Alban_Gogh
Transitions - Meditative Background Music, white_records
Show notes
Check out resources referenced in the episode:
IEEE portfolio of AIS technology and impact standards and standards projects
International Standard on information Technology-Artificial Intelligence-Management System
Nikshay Platform for Tuberculosis
E-Sanjeevini for doctor-patient consultation
10/01/24 • 45 min
Geospatial AI is the use of AI-based tools for analysing any type of geographic information derived from sources such as satellite imagery, aerial drones, and geographic information systems (GIS). These technologies can be employed in resource management, disaster response, and conservation efforts, offering real-time monitoring and analysis of ecosystems and natural resources.
In this episode, we explore the potential and limitations of using Geospatial AI for climate action. The conversation ranges from trends in democratisation of map-making with easy-to-use GIS tools to the risks and ethical concerns that are associated with the use of GIS data. Our guests discuss the need for community involvement, factoring in local knowledge systems, and ensuring equitable access when it comes to Geospatial AI. They discuss the potential environmental costs and the importance of funding and transparency in technology implementation.
You can read the transcript for this episode here.
Speakers
Cathy Richards
Cathy is the Associate for Digital Resilience and Emerging Technology at The Engine Room. Recently, as a Green Web Fellow, she investigated the benefits, ethical questions, and security risks associated with using GIS for environmental justice. Cathy holds a Bachelor's degree in International Relations from Boston University and an MPA from the Monterey Institute of International Studies. She is from Costa Rica.
Izni Zahidi
Izni is a Civil Engineering academic at Monash University, Malaysia and has over 16 years of academic and industry experience. Her primary research is in using remote sensing, GIS, and modelling to develop sustainable and climate-resilient communities. Her research team assesses environmental risks such as flooding, water pollution, vegetation degradation, and urban heat island effect to improve natural resources management. Her research work has won a Gold Award, Silver Award, and Special Award as selected by the Toronto International Society of Innovation and Advanced Skills in the international competition, Sustainability in Civil Engineering Exhibition and Competition.
Show Notes
Geospatial AI or Geo AI (glossary term)
ArcGIS, Esri’s enterprise geospatial platform
QGIS, a free and open-source platform
Felt Maps, a cloud-native platform
Artificial intelligence for predicting urban heat island effect and optimising land use/land cover for mitigation: Prospects and recent advancements, research paper co-authored by Izni Zahidi
Modelling public social values of flood-prone land use using GIS application SolVES, research article co-authored by Izni Zahidi
Internet of Things or IoT (glossary term)
Tracking Amazon: How Neighbors Are Monitoring Pollution From New Delivery Hub
Wireless Sensors Could be Less Effective in Muddy Soil
How the “Internet of Cows” is Transforming Livestock Farming in Europe
Northern Kenya leads the way in the world's largest IoT conservation network
01/07/25 • 51 min
In this episode, Eleanor Slade & VV Robin discuss how technologies like AI have the potential to support conservation practices, yet challenges (data availability & financing) remain to realise some of these aspirations.
On one hand, technology has facilitated public interest in nature. Using digital tools & apps, people can access info about diverse species & improve their understanding of their environments. On the other, the potential benefits of technology must not distract resources away from basic foundational research. AI can help in monitoring & processing large amounts of data, but investments are needed to ensure the next generation's familiarity with basic sciences & knowledge.
With years of data collection, we're also at the point where we need to approach biodiversity data more thoughtfully-how much data do we really need? Would smaller datasets captured over shorter durations lead to the same kind of results? How do we minimise resource wastage? Eleanor & Robin discuss some of these key issues, situated in their unique practice areas in Singapore, Malaysia & India.
You can read the transcript for this episode here.
Speakers
Eleanor Slade
Eleanor is an Associate Professor at the Tropical Ecology & Entomology Lab at the Asian School of the Environment at Nanyan Technological University. Her research focuses on the challenges & opportunities associated with conservation, management, & restoration of tropical forests & human-modified landscapes. She's worked in the rainforests & oil palm plantations of Singapore, Malaysia, Sumatra, Philippines, Belize, & Brazil, & the woodlands & agricultural systems of Finland & the UK.
She's currently also working on the AMBER project that's testing the use of automated camera & audio systems, combined with AI to deliver more standardised monitoring of insects, bats & birds; aiming to deploy a network of 40 biodiversity monitoring units over the next 2 years.
Social Media: @eleslade.bsky.social / @teelab.bsky.social
VV Robin
Robin is an Associate Professor at the Indian Institute of Science, Education, & Research (IISER) Tirupati. His work focuses on patterns & processes in ecology, behavioural ecology, biogeography & evolutionary ecology. He's interested in conservation initiatives involving multiple stakeholders & in collaborative research initiatives. He & his team use tools like bioacoustics, phylogenetics & population genetics, along with Remote Sensing & GIS to understand the relationship of birds with their habitats. Five years ago, he initiated a project to understand why birds found in some Western Ghats habitats didn't appear in others. It took him two years to analyse avian sound recordings collected over a year. He is of the opinion that AI could've helped him analyse this data in a year. His geography of work is the Western Ghats, Eastern Ghats & peninsular areas of India.
Show Notes
Warning of 'ecological Armageddon' after dramatic plunge in insect numbers
Centre for Ecology and Hydrology in the UK
AMBER: Unveiling AMBER: A Glimpse into Biodiversity Monitoring in Singapore using AI,
10/31/24 • 56 min
Climate change is disrupting agricultural practices, affecting food security and farmers' livelihoods. Technologies like AI-enabled precision agriculture are emerging as potential solutions to alleviate some of these problems. In Asia, where most farmers are smallholders and a digital divide persists, what are the implications of AI adoption for agriculture in the region? Can it help address the climate crisis or is it likely to exacerbate existing inequities?
In this episode, we deep-dive into the opportunities, challenges and risks of using AI for agriculture and how it might impact climate change. For the most part, our speakers are sceptical about the use of AI for agriculture, highlighting that it may not be what farmers need and ultimately serves narrow commercial interests. If we are to use AI for agriculture, we need to resist the fail-fast logic that dominates the start-up industry and invest the time and resources to engage with farming communities and understand their needs and social context.
You can read the episode transcript here.
Speakers
Anubha Singh
Anubha is a PhD candidate at the School of Information at the University of Michigan with a graduate certificate in Science, Technology, and Society. Through long-term ethnography of the onion supply chain in Western Maharashtra, she studies how data-driven technologies are restructuring farming and redefining the future of agriculture in India. Her work is informed by and contributes to the fields of Postcolonial and Feminist Science and Technology Studies, Ethnography of Computing and Agriculture, and Critical Cultural Studies.
Elenita ”Neth” Daño
Elenita, also known as Neth, is the Asia Director of the ETC Group that works to address the socioeconomic and ecological issues surrounding new technologies that could have an impact on marginalised communities. Neth is a researcher who has done in-depth analysis and published work on various issues in agriculture and climate change as well as technological divides, in developing countries, particularly in Southeast Asia. She has represented environmental non-governmental organisations in the Advisory Board to the Climate Technology Centre and Network (CTCN), the operational arm of the Technology Mechanism of the UNFCCC. She was appointed by the UN Secretary-General in the 10-member Group that supports the Technology Facilitation Mechanism (TFM) in 2016-2017.
Show Notes
A commentary on agricultural digitalisation for climate action in the Philippines. Page 17. Expert brief authored by Elenita Dano for the AI + Climate Futures in Asia Project.
The Green Revolution is a warning, not a blueprint for feeding a hungry planet
Digital Agriculture Mission: Tech for Transforming Farmers’ Lives Agristack and digital registry of farmers in India
Indian Government Seed Fund Scheme for Start-up Prototypes
The Politics of Manmohanomics 1991 Economic Liberalisation in India
Agriculture sector has done well, needs ‘re-orientation’
A commentary on agricultural digitalisation for climate action in the Philippines. Page 14. Expert brief authored by Elenita Dano for the AI + Climate Futures in Asia Project.
05: AI & Energy Transitions in Asia
Code Green
02/03/25 • 62 min
For many countries in Asia, pathways to clean energy transitions are complex with continued reliance on coal and legacy infrastructure, a rapidly urbanising economy, and a booming data centre industry. How can we ensure that AI adoption is both safe and sustainable while also fostering equitable energy transitions?
In this episode, we hear from John Cotton & Priya Donti on the enthusiasm of governments in Asia in using AI to improve the efficiency of energy systems & manage energy demand & supply. We discuss AI’s potential to help integrate renewable energy sources into the grid, challenges in the area, environmental impacts & ways to manage them, and the need to invest in capacity building & skill development.
You can read the transcript for this episode here.
Speakers
John Cotton
John Cotton is Senior Program Manager for the Southeast Asia Energy Transition Partnership, UNOPS with a demonstrated history of project development in energy transition, renewables, IT and mining industries. John is educated in the UK at Manchester and Sussex Universities with a B.Sc (Hons) in Mathematics, Software Engineering, and an M.Sc in Energy Policy, respectively.
John has been based in Southeast Asia for 20 years and has overseen projects ranging from EPC contracts for hydropower and solar projects, through policy analysis and recommendations for the multi-disciplinary energy transition challenges faced across the region. Before ETP, he was Climate Change Policy Officer at the British Embassy, Vientiane of Lao PDR, and draws on extensive experience from both the public and private sectors.
Priya Donti
Priya Donti is an Assistant Professor at MIT EECS and LIDS, whose research focuses on machine learning for forecasting, optimisation, and control in high-renewables power grids. Specifically, her work explores methods to incorporate the physics and hard constraints associated with electric power systems into deep learning workflows.
Priya is also the co-founder and Chair of Climate Change AI, a global non-profit initiative to catalyse impactful work at the intersection of climate change and machine learning. She received her Ph.D. in Computer Science and Public Policy from Carnegie Mellon University.
Show Notes
COP26: What Asia pledged, from China to Vietnam and Philippines
PT PLN Indonesia’s State Utility Company
Upgrading and Modernising the Java-Madura-Bali Electricity Control Centre
Renewable Integration - Energy System - IEA
Development of Vietnam Smart Grid Roadmap for period up to year 2030, with a vision to 2050
Review on Machine Learning for Sustainable Energy Systems
Aligning artificial intelligence with climate change mitigation (overview of the multi-faceted relationship between AI and climate)
Climate Change and AI: Recommendations for Government Action (Global Partnership on AI report)
Welcome to Code Green: Trailer
Code Green
09/04/24 • 1 min
Welcome to Code Green! Brought to you by Digital Futures Lab, in partnership with Earth Venture Foundation, Code Green is a podcast and newsletter series that deep dives into the intersection of AI and climate-tech in Asia.
Cutting through the hype and silos of knowledge, Code Green will foster interdisciplinary knowledge exchange and surface voices from the ground.
Through this season and an accompanying monthly newsletter, we will showcase emerging climate AI research and provide a socio-technical perspective on the implications of adopting AI for climate action.
Sign up for updates here.
Credits
Audio Editing: Sharon Joseph and Shivranjana Rathore
Attributions
Intro and Outro - Retro Sounds, Alban_Gogh
Transitions - Meditative Background Music, white_records
12/02/24 • 59 min
Leaders at COP29 in Baku endorsed a declaration to use digital technologies and AI to address climate action, while also acknowledging the need to minimise its environmental impacts. How do we find this balance? Is it achievable at all? What new narratives and policy directions are needed? What does it mean for countries in Asia that are already grappling with the environmental impacts of rapid industrialisation?
In this episode, Cindy Lin and Sherif Elsayed-Ali critique AI's scalability and environmental costs while urging interdisciplinary approaches to ensure meaningful impact. They advocate for realistic narratives, collective restraint, and context-specific innovations, highlighting the need to distinguish hype from scientifically proven use cases to achieve sustainable advancements.
You can read the transcript for this episode here.
Speakers
Cindy Lin
Cindy is an Assistant Professor at the School of Interactive Computing at Georgia Tech. An ethnographer and information scientist, her work centers on the data practices, exchanges, and expertise of climate change and their relationship to race and environmental governance in Indonesia and the United States.
Prior to her professorship at Georgia Tech, she was assistant professor at the College of Information Sciences and Technology at the Pennsylvania State University. She was also a visiting postdoctoral fellow at Cornell Tech's Digital Life Initiative as well as a postdoctoral fellow at Cornell Atkinson Centre for Sustainability and Cornell's Department of Information Science.
Sherif Elsayed-Ali
Sherif is Executive Director of the Future of Technology Institute, where he brings unique expertise at the intersection of technology policy, entrepreneurship and human rights. He previously co-founded and served as CEO of Carbon Re, a joint spin-out of Cambridge University and UCL using machine learning to accelerate the decarbonization of foundational materials such as cement.
Prior to this, he set up and led the AI for Climate practice at Canadian scale-up Element AI and was co-founder of Amnesty Tech. He was a World Economic Forum Global Future Council co-chair and a fellow at Harvard Kennedy School, both focusing on the intersection of technology and human rights.
Show Notes
Conference of Parties 29 (COP29)
COP29 Declaration on Green Digital Action
School of Interactive Computing, Georgia Tech
Josiah Hester on Battery-less Devices
Yale Program on Climate Change Communication - Climate Change in the Indonesian Mind
Post-growth Human Computer Interaction
This podcast series is accompanied by a monthly newsletter - sign up for updates here.
For more about this project, visit our website codegreen.asia
Credits
Audio Editing: Creator Studio Goa by Winfluence Media
Production Support: Shivranjana Rathore
Cover Design:
04/01/25 • 50 min
As population growth, motorisation, and climate change strain urban mobility in the Asian region, the design and delivery of transport services are becoming increasingly complex. Experts Huê-Tâm Jamme and Kris Villanueva-Libunao explore why cities need equitable, people-centred planning that accounts for existing mobility patterns and what barriers exist to implementing AI for mobility. Hue-Tam emphasises the role of political will in shaping new transport modes that should not only support networks of economic activity but also enhance urban vibrancy and local culture. Kris juxtaposes AI’s potential to improve traffic management, sustainability, and safety with the need for strong data governance and capacity building for equitable AI implementation in the region. Together, they advocate for stakeholders to view mobility infrastructure as systems that impact people’s economic, social and cultural lives.
You can read the transcript for this episode here.
Speakers
CEO, SmartCT
Kris R. Villanueva-Libunao is a leader in digital governance, AI policy, and smart cities including smart mobility. As Executive Director of SMARTCT-Philippines, she leads initiatives integrating AI and data-driven solutions into urban planning, leading projects such as the Smart LGU Assessment and Growth Map to optimise mobility and infrastructure in local governments. Her expertise in AI governance is underscored by her role as AI Country Lead Researcher for the United Nations International Telecommunication Union (ITU), where she advanced policies to enhance gender-sensitive AI adoption in Southeast Asia. Kris has authored publications, including “Artificial Intelligence Policies to Enhance Urban Mobility in Southeast Asia”, and co-developed the Philippine National Transportation Strategy.
Assistant Professor, Arizona State University
Huê-Tâm explores the effects of new technologies on space and society, especially on how people move, work, shop, and socialize in cities, asking how we can shape urban spaces that are more livable, accessible, and equitable? Jamme has led projects on car-free living in the US, automated food vending in France, and the platform economy in Southeast Asia. Her research interests span mobility, retail, transit-oriented development (TOD), and public space. Through her theory of "productive frictions", she explains how motorbike mobility in Vietnam produces high opportunities for commercial and social interactions on city streets; and why the rapid adoption of cars and mass transit will likely reduce the level of urban productive frictions..
Show Notes
Global status report on road safety 2023
JICA Philippines Annual Report 2023, JICA Roadmap for Transport Infrastructure for Metro Manila 2014
Mobility over Air Quality Index (MAQI)
Doing Urban Development Fieldwork: Motorbike Ethnography in Hanoi (2018)
03/06/25 • 54 min
AI is often framed as the future of progress, but what fuels this revolution? Behind every data centre, semiconductor, and AI model lies a hidden world of resource extraction, geopolitical power struggles, and environmental destruction. In this episode, we dig into the raw materials powering AI—from rare earth mining to data centres sucking up water in drought-prone regions. Experts Tom Özden-Schilling and Tamara Kneese reveal the true cost of AI’s rapid expansion—its human and ecological toll—and why the conversation on sustainability must move beyond carbon footprints to the messy realities of global supply chains.
You can read the transcript for this episode here.
Speakers
Dr. Tom Özden-Schilling
Tom Özden-Schilling is Presidential Young Professor of Sociology and Anthropology at the National University of Singapore. His first book, The Ends of Research: Indigenous and Settler Science after the War in the Woods, is an ethnography of environmental deregulation in western Canada, and its effects on Indigenous and settler researchers’ struggles to maintain long-term forestry experiments and sovereignty projects. Tom’s current project examines the social costs of green energy transitions through the emergence of new critical minerals research and development initiatives in the United States, Malaysia, and Australia. Before joining NUS, Tom was Assistant Professor of Anthropology at Johns Hopkins University.
Dr. Tamara Kneese
Dr. Tamara Kneese directs Data & Society Research Institute's Climate, Technology, and Justice programme. Previously, she led Data & Society's Algorithmic Impact Methods Lab (AIMLab). Before joining D&S, she was lead researcher at Green Software Foundation, director of developer engagement on the Green Software team at Intel, and assistant professor of Media Studies and director of Gender and Sexualities Studies at the University of San Francisco. She is the author of Death Glitch: How Techno-Solutionism Fails Us in This Life and Beyond (Yale University Press, 2023). Tamara holds a PhD in Media, Culture and Communication from NYU.
Check out the Code Green glossary for more terms.
This podcast series is accompanied by a monthly newsletter - sign up for updates here. For more about this project, visit our website codegreen.asia
Show Notes
Australia's first rare earths processing plant opens in Kalgoorlie
Nvidia: what’s so good about the tech firm’s new AI superchip?
Value creation in the metaverse
Crypto's Climate Impact: 8 Claims, Fact-Checked
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FAQ
How many episodes does Code Green have?
Code Green currently has 9 episodes available.
What topics does Code Green cover?
The podcast is about Podcasts and Technology.
What is the most popular episode on Code Green?
The episode title '00: Navigating AI’s role in Asia’s Climate Action Strategy' is the most popular.
What is the average episode length on Code Green?
The average episode length on Code Green is 50 minutes.
How often are episodes of Code Green released?
Episodes of Code Green are typically released every 30 days, 14 hours.
When was the first episode of Code Green?
The first episode of Code Green was released on Sep 4, 2024.
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