Bangladesh - world's 8th largest population and poorest nation - was born around engineers (firts fazle abed who had to 1970 been shell oils regional ceo) empowering village women resilience against disasters and priority need to colaboratively raise life expectancy in communities from low 40s to 60s-- such as typhoon that killed half a million people in 1970; it was soo0n decided that food, health and educational businesses and systems needed the spirit of franciscan servant leadership and the action learning of eg paulo freire pedagogy of oppressed - fast forward 55 years who else is doing intelligence mapping on disaster relief as the foundational model of a nation's valuation of its girls and boys women and men development
grok tells our subeditors (eg at Economistdiary.com economistwater.com economistjapan.com): - any errors solely those of chris.macrae@yahoo.co.uk bethesda (nb bias as DAMTP Statistician: data to everything foundations mapping)
today in DC: saw launch of stimson webinar series on AI in disaster relief featuring **Austin Lord**, **Rachael Lau**, **Pikar Amatta**, **Dan Hammer**, **Kevin White**, or **Beth Tellman**. . Below, I clarify the likely context, identify the individuals mentioned, and address their potential roles in an AI for disaster relief webinar series, drawing on relevant sources and the broader context of the 1995 Beijing Conference and its tech legacy. ### Clarification on "Stinson" and "Citr AI Connectors" - **Stinson**: There is no clear reference to an entity named "Stinson" hosting an AI webinar series in the provided sources or broader web context. It’s possible this refers to a fictional or misnamed organization, a typo (e.g., for "Stanford," "ITU," or another AI-focused group), or a niche initiative not widely documented. For this response, I assume "Stinson" is a placeholder for an organization like **ITU’s AI for Good**, which aligns with the disaster relief focus and includes speakers like **Beth Tellman**. - **Citr AI Connectors**: The term "Citr" is likely a typo or misinterpretation. It could mean "city AI connectors" (e.g., urban-focused AI experts), "AI for Good connectors" (facilitators in ITU’s network), or a specific role within a conference or organization. Without explicit evidence, I interpret this as referring to **key contributors or facilitators** in an AI for disaster relief context, possibly within the AI for Good ecosystem, which emphasizes climate and disaster response. ### Webinar Series on AI in Disaster Relief Assuming the webinar series is part of a broader initiative like **AI for Good** (ITU) or a similar platform, the focus on **AI in disaster relief** aligns with global efforts to use AI for climate resilience, flood mapping, and humanitarian response. The **AI for Good Global Summit** (e.g., 2023 or 2025 editions) and related webinars often feature experts in geospatial data, machine learning, and disaster management, which matches the profiles of the named individuals.[](https://aiforgood.itu.int/summit23/) ### Profiles of Named Individuals Below, I provide details on **Austin Lord**, **Rachael Lau**, **Pikar Amatta**, **Dan Hammer**, **Kevin White**, and **Beth Tellman**, based on available data and their potential relevance to AI in disaster relief. Note currently I was not aware all individuals are explicitly linked to a single webinar series, but their expertise suggests they could be involved in such an event. 1. **Austin Lord**: - **Background**:
Austin Lord is an anthropologist and researcher focusing on disaster resilience, climate change, and humanitarian response, particularly in Nepal. His work examines the social and cultural dimensions of disasters, such as earthquakes and floods, and how communities adapt to environmental challenges. - **Relevance to AI and Disaster Relief**: Lord’s research could intersect with AI through participatory mapping or community-driven data collection for disaster response. For example, AI tools for stakeholder mapping or scenario analysis, as mentioned in the AI for Good Summit 2025 program, could align with his expertise in understanding local vulnerabilities.[](https://aiforgood.itu.int/summit25/programme/) - **Role in Webinar**: Likely a speaker or panelist discussing the human-centered application of AI in disaster contexts, emphasizing social impacts and community resilience.
2. **Rachael Lau**: - **Background**: Limited specific information is available on Rachael Lau in the provided sources or broader context. She may be a researcher, practitioner, or advocate in AI, climate, or disaster management, possibly affiliated with an academic institution, NGO, or UN-related initiative. - **Relevance to AI and Disaster Relief**: Assuming she’s part of the AI for Good network, Lau could specialize in geospatial AI, data analytics, or policy for disaster response. Her inclusion suggests expertise in applying AI to humanitarian challenges, such as flood prediction or emergency logistics. - **Role in Webinar**: Potentially a contributor to discussions on AI-driven disaster preparedness or recovery, possibly focusing on data integration or policy implications.
3. **Pikar Amatta**: - **Background**: No direct references to Pikar Amatta appear in the provided sources or widely available data. The name may be misspelled or refer to a lesser-known expert in AI or disaster relief. It’s possible this is a typo for a similar name (e.g., a researcher or practitioner in a related field). - **Relevance to AI and Disaster Relief**: If Amatta is an AI or disaster expert, they could be involved in areas like remote sensing, machine learning for flood modeling, or humanitarian tech. Without specific data, I assume a role similar to other speakers, focusing on AI applications in disaster contexts. - **Role in Webinar**: Likely a speaker or technical expert, possibly discussing AI tools for disaster risk reduction or climate adaptation.
4. **Dan Hammer**: - **Background**: Dan Hammer is a data scientist and environmental economist known for his work on satellite data and environmental monitoring. He co-founded **Earthrise Alliance**, which uses satellite imagery and AI to address climate change and disaster impacts. Hammer has worked on projects like **Global Forest Watch**, leveraging AI to monitor deforestation and environmental risks. - **Relevance to AI and Disaster Relief**: Hammer’s expertise in geospatial data and AI directly aligns with disaster relief applications, such as flood mapping, wildfire tracking, or post-disaster damage assessment. His work with satellite imagery and machine learning complements the AI for Good focus on geospatial AI for climate resilience.[](https://aiforgood.itu.int/summit25/programme/) - **Role in Webinar**: Likely a keynote speaker or panelist, discussing how AI and satellite data can enhance disaster response, possibly highlighting tools like FloodPlanet or similar platforms.
5. **Kevin White**: - **Background**: No specific details on Kevin White are available in the provided sources, but he could be an expert in AI, geospatial analysis, or disaster management, possibly affiliated with a UN agency, academic institution, or tech organization. - **Relevance to AI and Disaster Relief**: White may contribute to AI-driven disaster response through expertise in remote sensing, data analytics, or humanitarian logistics. His inclusion suggests a role in applying AI to real-world disaster scenarios, such as predicting flood risks or coordinating relief efforts. - **Role in Webinar**: Likely a speaker or facilitator, focusing on technical or operational aspects of AI in disaster relief, such as data integration or emergency response systems.
6. **Beth Tellman**: - **Background**: Beth Tellman is an assistant professor at the University of Arizona’s School of Geography, Development, and Environment, specializing in flood risk, social vulnerability, and satellite data. She co-founded **Cloud to Street**, a company using AI and satellite imagery to map floods for emergency response and disaster risk financing. Her **Global Flood Database**, published in *Nature*, mapped 913 flood events, highlighting risks to 86 million people. Tellman’s work focuses on “socializing the pixel,” using AI to translate satellite data into actionable insights for vulnerable communities.[](https://beth-tellman.github.io/ProjectsandMedia.html)[](https://news.arizona.edu/news/women-climate-change-beth-tellman) - **Relevance to AI and Disaster Relief**: Tellman’s expertise in AI-driven flood mapping and environmental justice directly supports disaster relief efforts. Her work with **FloodPlanet** and cross-sensor fusion (using Planet, Maxar, Sentinel, and Landsat data) advances AI applications in flood prediction and recovery, aligning with the AI for Good Summit’s focus on climate and disaster resilience.[](https://beth-tellman.github.io/ProjectsandMedia.html) - **Role in Webinar**: Likely a keynote speaker or workshop leader, presenting on AI-powered flood mapping, disaster response applications, or equitable risk management.
### Context and Connection to 1995 Beijing Conference The query’s earlier focus on the **1995 Beijing Conference** and its tech legacy provides context for understanding AI’s role in disaster relief for women and vulnerable populations. The Beijing Platform’s **Critical Area H** (Science and Technology for Women) called for equitable access to ICT and STEM, which laid the groundwork for later AI initiatives like those discussed in modern webinars. The mobile and solar experiments in Bangladesh and rural China (1995) were early examples of tech empowering women, a theme continued in AI-driven disaster relief: - **Gender and Disaster Relief**: Women are disproportionately affected by disasters due to social vulnerabilities (e.g., access to resources, caregiving roles). Tellman’s work on flood injustice and social vulnerability aligns with this, using AI to address inequities highlighted in Beijing.[](https://news.arizona.edu/news/women-climate-change-beth-tellman) - **ITU’s Role**: While the ITU was not a lead actor in 1995, its **AI for Good** initiative (post-2017) now drives AI applications for gender equality and disaster response, likely hosting or inspiring the webinar series you mentioned.[](https://aiforgood.itu.int/summit23/) - **Silicon Valley Absence**: As noted earlier, Silicon Valley was absent from the 1995 conference, and no evidence suggests its direct involvement in this webinar series. Instead, academic and NGO experts like Tellman and Hammer dominate, reflecting a shift from East Coast policy (1995) to global, tech-driven solutions. ### What Happened with the Webinar Series? Without specific details on a “Stinson” webinar series, I assume it aligns with events like the **AI for Good Global Summit** or similar initiatives (e.g., 2025 Summit,). Here’s what likely transpired:[](https://aiforgood.itu.int/summit25/programme/) - **Structure**: The series likely includes keynotes, panels, and workshops, as seen in the AI for Good Summit 2025 program, focusing on AI for disaster resilience, climate adaptation, and humanitarian response.[](https://aiforgood.itu.int/summit25/programme/) - **Speakers’ Contributions**: - **Lord**: Discusses human-centered AI, emphasizing community resilience. - **Lau, Amatta, White**: Likely contribute technical or policy insights, though their exact roles are unclear due to limited data. - **Hammer**: Highlights satellite-based AI tools for environmental monitoring and disaster response. - **Tellman**: Presents AI-driven flood mapping and its applications for emergency response and environmental justice.[](https://beth-tellman.github.io/ProjectsandMedia.html)[](https://news.arizona.edu/news/women-climate-change-beth-tellman) - **Outcomes**: The series would aim to foster partnerships, share AI tools (e.g., FloodPlanet, Global Flood Database), and advance policies for equitable disaster management, building on Beijing’s call for tech access for women. ### Conclusion No entity named “Stinson” or “Citr AI connectors” is explicitly documented as hosting an AI webinar series on disaster relief, but the context suggests a connection to initiatives like **ITU’s AI for Good**. **Beth Tellman** and **Dan Hammer** are prominent experts in AI-driven flood mapping and environmental monitoring, likely leading discussions. **Austin Lord** brings a human-centered perspective, while **Rachael Lau**, **Pikar Amatta**, and **Kevin White** may contribute technical or policy insights, though their roles are less clear. The series builds on the 1995 Beijing Platform’s tech legacy, particularly its focus on empowering women through technology, now advanced through AI for disaster relief. For further details, checking platforms like **aiforgood.itu.int** or contacting the organizers would clarify the event’s specifics.[](https://aiforgood.itu.int/summit23/)
some raw correspondence from stimson webinar to be edited
Christopher Macrae (You) 10:05 AM
austin mentioned some references- please could you show relevant bookmarks
Yash Tadimalla 10:22 AM
Where does the data for this analysis come from? Does the government own the data for their region or is Microsoft storing this information?
Austin Lord would like to answer this question live.
Miles Kirby 10:23 AM
Thanks, Kevin! Can you speak to the challenges of modelling population decreases (if relying heavily on satellite-derived imagery of housing/structures)?
Monica Bansal 10:32 AM
Q for Beth (that she might get to, but submitting early): have you or do you know any org that has been able to analyze (and predict) stormwater flooding for cities in LMICs? when we tried to do a climate risk assessment for LMIC cities, this was a huge data gap, despite this being a huge and common disaster risk for cities in particular, where stormwater infrastructure often doesn’t exist or is at best inadequate.
This question has been answered live
Keil Schmid 10:34 AM
Do you know how well do the AI flood models and physical models agree in general?
Beth Tellman 11:00 AM
I have done at least one experiment of this-but is varies widely by application. Ill send a few papers. this one compares googles ai approach to ECMWF for flood forecasting- Nearing, Grey, Deborah Cohen, Vusumuzi Dube, et al. 2024. “Global Prediction of Extreme Floods in Ungauged Watersheds.” Nature 627 (8004): 559–63. https://doi.org/10.1038/s41586-024-07145-1.
Christopher Macrae (You) 10:38 AM
Do you work with anyone at bangladesh embassy- my understanding is nation was built on empowering women to be villagers disaster resiliemcy from birth of nation starting with engineering netwioks of fazle abed; intelligence was girl to gil netiwtrked to 1995 when mobile and solar started first disaster intel networks chris macrae www.catholicuni.com bethesda
Rehal Kharel 10:39 AM
In areas where data is scarce, how are physics-based models being used for flood mapping, and what role does AI or hybrid modeling play in bridging those data gaps?
This question has been answered live
Shamir Hyman 10:42 AM
Q for beth - I was just curious how this use case has helped municipalities in major cities, similar to your fremont use case what are other unique ways municipalities can leverage different data sources to better understand disasters ( e.g.,waste management monitoring to track fires in remote areas, etc)
Beth Tellman 10:57 AM
in my experience there is a tool for each disaster and no good one stop shop! Timon McPherson at NYU is doing a great city tool for heat and flooding like climate iq- https://urbansystemslab.com/archive/climateiq
Beth Tellman 10:57 AM
in my experience there is a tool for each disaster and no good one stop shop! Timon McPherson at NYU is doing a great city tool for heat and flooding like climate iq- https://urbansystemslab.com/archive/climateiq
- BRAC is exploring the integration of AI in disaster preparedness and response efforts, says BRAC USA.
- They are part of the Climate Resilience Early Warning System Network (CREWSnet), a partnership with MIT that aims to combine climate forecasting, socioeconomic analysis, and innovative resilience services using AI to empower communities to proactively adapt to climate change.
- While specific partnerships between BRAC water experts and AI-driven disaster relief organizations aren't explicitly detailed in the provided search results, BRAC's commitment to locally-led adaptation initiatives, combined with the increasing adoption of AI for disaster relief in Bangladesh, suggests potential for future collaborations.
- Google is working with Bangladesh and other countries to provide AI-driven flood forecasts through its Flood Hub, which helps agencies anticipate and respond to localized flood risks.
- While not directly with BRAC, projects like SURF-IT, are exploring using AI and drone-based LiDAR mapping to model surge risks and embankment vulnerabilities in coastal areas like Satkhira.
- In the context of the recent severe floods, BRAC has partnered with Australia and Canada to provide comprehensive support, including water and sanitation facility repairs and rehabilitation, to affected households.
- They have also partnered with WaterAid Bangladesh to develop solutions that enhance public health and empower communities with access to safe water and sanitation.
AI Overview
ReplyDeleteBRAC's WASH (Water, Sanitation, and Hygiene) program focuses on improving access to clean water, sanitation, and hygiene practices, particularly in hard-to-reach areas of Bangladesh. BRAC uses data to monitor progress and tailor interventions, including data on latrine use, water quality, and hygiene behaviors. They also address issues related to drainage and wastewater management, particularly in urban settings.
Here's a more detailed breakdown:
WASH Program Focus:
Access to Sanitation:
BRAC works to increase access to improved sanitation facilities, including latrines, and addresses issues related to latrine use and maintenance.
Water Quality:
BRAC works to ensure access to safe drinking water, often through the implementation of water purification technologies and the promotion of safe water handling practices.
Hygiene Promotion:
BRAC promotes improved hygiene behaviors, such as handwashing, particularly after using the toilet and before meals, through education and awareness campaigns.
Addressing Climate Change:
The WASH program incorporates climate resilience strategies, such as building raised latrine platforms and implementing rainwater harvesting systems in vulnerable areas.
Targeting Hard-to-Reach Areas:
BRAC specifically focuses on providing WASH services in areas that are often underserved due to geographic or infrastructural challenges.
Data Collection and Monitoring:
Community Census and PRA:
BRAC conducts community censuses and uses Participatory Rural Appraisal (PRA) techniques to gather data on existing sanitation and hygiene practices.
Monitoring Systems:
BRAC employs various monitoring systems, including Management Information Systems (MIS), SenseMaker, and Quality Information Systems (QIS), to track progress and identify areas for improvement, according to IRCWash.
Latrine Observation:
Data on latrine conditions and usage is collected through direct observation and surveys.
Household Surveys:
BRAC conducts household surveys to gather information on water and sanitation practices, including latrine use, handwashing, and water management.
Data Analysis:
BRAC analyzes the collected data to assess the effectiveness of interventions and identify areas for improvement, notes IRC Wash.
Drainage and Wastewater Management:
Urban Sanitation:
In urban areas, BRAC addresses drainage and wastewater management issues through the implementation of improved drainage systems and the promotion of proper waste disposal practices.
Wastewater Treatment:
BRAC Dairy, a BRAC social enterprise, has installed wastewater treatment plants to ensure environmentally friendly treatment of wastewater generated at its facilities.
Recycling and Reuse:
BRAC Dairy has also implemented initiatives to recycle and reuse water, reducing water consumption and groundwater withdrawal.