On Sunday, our CEO Brian Collins, discussed the role of Artificial Intelligence/Machine Learning to enhance our ability to mitigate and respond to disasters during the GEOINT Foreward session.
Here are the top 3 takeaways:
1. The scale of events that emergency responders and the public encounter today are fast tempo, high impact events that stress our traditional processes of making decisions on the ground.
Our responders and the public must make decisions in the first 30 minutes of an event that we used to have hours to make - where should we stage resources?, which communities should be evacuated? Doing complex analysis such as developing risk assessments and creating achievable evacuation plans before an event have greater impacts on outcomes that those made during an event.
2. We have the data, we just don't have the time to look at it all in time to execute the decisions we must take to protect the the public.
Massive amounts of data about evolving events is now available, but the public and our first responders do not have the time to sift thru it all before making critical decisions such as evacuations. Using AI/ML to create intelligent alerting can empower us to make decisions based on live, real-world data that we would normally not have the time to observe and process.
3. Artificial Intelligence and Machine Learning can tip the balance to speed up our decisions, but we must begin to gain exposure to them now to develop the trust to rely on them.
AI/ML are best employed when focused on specific decisions such as risk-based preplanning and realistic evacuation models or intelligent alerting. However, improvement in our decisions cycles will require the public and first responders to understand and trust the output. The key to trust is exposure and familiarity... get tools out into use, ask for input, and listen to feedback.
Read more about the panel's discussions on artificial intelligence and geospatial data in Trajectory Magazine's post:
