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Government CIO Outlook | Monday, May 30, 2022
AI may be integrated into existing technological systems to extend their reach and provide faster responses and lower costs.
Fremont, CA: The coronavirus epidemic has exposed a global lack of catastrophe preparedness. Despite the fact that COVID-19 is not the first pandemic in recent years, the World Health Organization documented 1,483 diseases and pandemics between 2011 and 2018.
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The current pandemic will not be the last. Pandemic events are on the rise, according to a 2019 research from the Global Preparedness Monitoring Board. However, the global reaction is largely reactive, poorly coordinated, and hampered by a "lack of sustained political will."
These same problems can be seen in our response to other catastrophic disasters, whether they occur locally, nationally, or globally. Large-scale weather or earthquake events, as well as geopolitical conflicts, are examples.
We do, however, have tools at our disposal that we can use to our advantage. AI is one of them, which you may use at any step of the catastrophe life cycle to assist and extend the capabilities of existing systems and humans.
A worldwide catastrophe frequently begins in a hyperlocal hotspot. AI models that look for a surge in mentions or events across a set of recognised domains and cross-reference these with relevant data points can warn us about impending disasters.
For example, in our pandemic scenario, AI can follow reports of diseases or increasing queries linked to symptoms by mining social media data, news stories, public health data, or search engine inputs. These, along with information such as hospital admissions data, can be used to track the spread of a disease, alerting authorities when a specific density is achieved or when geolocation data shows that people from an infected area are going to a new site. In reality, an AI system was one of the first to notice the new coronavirus outbreak; all it needed were human eyes to see the significance.
AI can also be useful in predicting environmental hazards like earthquakes. A recent neural net experiment found 17 times more earthquakes than standard approaches, allowing scientists to create more accurate seismic models. AI models can also detect cyberattacks, outages, and supply concerns, among other things, allowing local and international institutions to be prepared in the event that these early warning signs turn into something more serious.
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