Active vs. Passive Collective Intelligence

As the Covid-19 pandemic moves into the fifth month of 2020, our collective focus is shifting. At first, everyone was talking about how to slow the spread of the virus and “flatten the curve.” Now, the focus is on how to open up the economy with as little damage as possible. Debates are raging about when and how to open up. However, very few people suggest that everyone stay hunkered down until we have a vaccine. So… if we are going to open up anyway, let’s be smart about it.

Fortunately, leveraging our Collective Intelligence (CI) can help! In my latest video, Episode 4: Active vs. Passive CI, I describe some examples of CI-powered technology that are already deployed in the battle against the Coronavirus.

Passive CI systems analyze the “digital footprints” that people leave on the internet when they visit different sites, buy things, click on things, do Google searches, publish articles, or generally go about their online business.

In contrast, Active CI systems ask hundreds, thousands, or even millions of online users to actively contribute information (or perform tasks) to solve problems. Active CI is particularly good at solving big problems that require efforts or information from many minds.

Google Flu Trends (GFT) – was one of the original Passive CI systems for public health. GFT analyzed patterns in Google searches related to the flu in order to predict outbreaks and hot spots. The system was developed in 2008 and had some great early success. Unfortunately, it ran into execution-related issues and ultimately was discontinued. However, the concept was brilliant. The folks at Google deserve a lot of credit for pioneering the approach. You can read more about it on Wikipedia at:

There is also decent article in Wired Magazine that talks about some of the challenges it faced:

On the Active CI front, there are a couple of apps that you can use TODAY to help battle the Coronavirus. The main challenge with these apps is getting enough people using them so that the data becomes useful. So… if you like the Apps, please spread the word!

CovidNearYou – is a free app, developed by Boston Children’s Hospital and Harvard Medical School that crowdsources whether individuals are feeling well or have Covid symptoms. Anyone willing to take a few seconds to answer simple questions is rewarded with a map that reflects information from all participants. (Visit to download and for more details)

FluNearYou – is the free sister app to CovidNearYou. It does the same thing for flu symptoms. (Visit to download and for more details)

There are also hybrid systems. These systems analyze “digital footprints” like a passive CI system, but then incorporate teams of experts who work together very actively.

GPHIN (Global Public Health Intelligence Network) – is a sophisticated system developed by Health Canada in collaboration with the World Health Organization (WHO) to scan thousands of online news reports, articles, and other information on the internet to identify disease outbreaks and other events of potential health concern. You can learn more at:

Larry Brilliant, gave a great TED talk about the importance of Early Detection and Early Response for pandemics. His talk also describes GPHIN. I highly recommend the talk. You can find it here:

I am extremely encouraged that multiple groups globally are working to leverage CI in the battle against the Covid pandemic. As we become more adapt at harnessing CI, I believe we will be able to apply CI not only to pandemics but also to a wide range of very challenging problems including climate regulation, preventing asteroid impacts, eliminating poverty and disease, and exploring the stars. So, it’s not just a light at the end of this pandemic tunnel that I see. It’s the rising, brilliant sun!

Stay safe, be well.


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