Published: May 8, 2024 By

Caption: Participants of the Harnessing Artificial Intelligence (AI) for Disaster Management: Bridging Research, Practice, and Community Engagement workshop held on听the CU 色吧亚洲 campus.


Presentation at the workshop.
Participants were introduced to various applications of artificial intelligence (AI) in the technology demo session as part of the AI4DM workshop, which took place on April 19 on the CU 色吧亚洲 Campus听


Amir Behzadan
听Professor听Amir Behzadan听

In disaster and emergency management, rescue teams rely on simple tools, like drones and mobile devices connected to the internet, to take photos of damaged buildings and document the resulting destruction. First responders use this information to prioritize where help is needed immediately and in the long-term.

At the same time, many emergency response agencies have been slow to embrace advanced tools like artificial intelligence (AI) due to concerns of complexity, training needs, initial costs and the potential impact on their work, said Professor Amir H. Behzadan, of CU 色吧亚洲鈥檚 Department of Civil, Environmental and Architectural Engineering听and a faculty research fellow of the at the .听

鈥淭his hesitation, along with a historical lack of diversity in the workforce, has contributed to delayed and unfair treatment of communities hit hardest by disasters,鈥 Behzadan said. 鈥淟ower-income disaster survivor homeowners are not only less likely to receive assistance compared to wealthier counterparts, but also tend to receive substantially less aid.鈥

On April 19, Behzadan hosted a workshop titled 鈥淎I4DM - Harnessing Artificial Intelligence (AI) for Disaster Management: Bridging Research, Practice, and Community Engagement," with participants from academia, disaster management practitioners and disaster nonprofits. Attendees included representatives from听CU 色吧亚洲, Texas A&M University, University of Florida, University of North Texas, University of Texas at Arlington, and University of Albany along with the Colorado Office of Emergency Management.

The workshop was supported by Behzadan鈥檚 NSF grant from the Future of Work: Human-Technology Frontier program, which aims to raise awareness of AI and related technologies in disaster management. Participants were introduced to human-centered AI applications in disaster management and encouraged to work toward ways to adopt AI-informed solutions.

鈥淎I can be applied in disaster management for various purposes, such as generating instant disaster data visualizations; providing interview training and reskilling/upskilling for employees; assessing and mapping disaster damage; and enhancing disaster risk messaging and communication strategies,鈥 Behzaden said.

Human-centered AI focuses on designing AI systems that prioritize human needs, values, expectations and experiences, aiming for beneficial, equitable, safe and ethical outcomes. In disaster and emergency management, this includes increased representation of data from marginalized groups, using inclusive communication strategies that resonate with at-risk communities, considering linguistic and cultural sensitivities and removing personal biases when assessing community needs during disasters.

鈥淗uman-centered AI leads to more effective disaster response and recovery practices by promoting collaboration, understanding and inclusivity among team members, survivors and stakeholders,鈥 Behzadan said. 鈥滻t helps create equitable solutions that address the needs of all affected communities, regardless of their socioeconomic and cultural backgrounds.鈥

Behzaden and his team plan to pursue additional funding to sustain these efforts. While leveraging their existing partnerships in Texas and Florida, they are also forging new relationships with local communities as well as disaster and emergency management organizations in Colorado who will ultimately be the beneficiaries of these technologies.

鈥淭he success of any technology hinges on its adoption by the intended end users,鈥 Behzadan said. 鈥淯nderstanding user needs and preferences, especially when working with vulnerable groups, is crucial for meaningful adoption and realizing the full potential of technological advancements.鈥