COVID-19 demonstrates that AI/ML remains underhyped

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When I wrote in October 2019, that AI/ML was underhyped, I was not even thinking of public sector applications. Luckily, Bluedot was. If you still believe AI/ML is overhyped, then I would encourage you to watch the 60 minutes piece from April 26th, 2019 on this very issue, and how really good data, and a really smart team, was able to help Canadian, Californian, and other clients, stay a step ahead of a rapidly spreading pandemic:

The computer algorithm that was among the first to detect the coronavirus outbreak

Using cell phone information and airline departure information from Wuhan, Bluedot was able to provide insights on which cities were going to be most at risk, and even from where the risk would spread from those first cities on the frontlines. Before that, Bluedot was able to raise the alarm about a possible health risk growing in Wuhan, not by relying on official China government sources, but other sources of information.

Bluedot was able to help California understand if the stay-at-home order was working, where it may not be working, and raise an alarm about where hospital hotspots may occur. In a world of finite resources, knowing where to deploy those resources is critical.

Behind the amazing tech was not surprisingly a leader who had the vision and persistence to knock on doors until he had access to the data he knew would make a difference. It took him over a year, and he started way before there was an inkling of the pandemic to come. Data is critical to the outcomes achieved by AI/ML.

We have only scratched the surface of what AI/ML+good data will be able to do in the future. The good data comes with privacy concerns and the AI/ML comes with ethical concerns. None the less, COVID-19 is showing us many things, including, AI/ML is still underhyped, and any Enterprise or Public sector entity that does not do that, is going to look as feckless as the current public sector entities not using it to fight the COVID-19 pandemic.

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