Published on March 18th, 2020 | by Emergent Enterprise0
Coronavirus: Seven Ways Collective Intelligence Is Tackling the Pandemic
Emergent technology is certainly helping global researchers and scientists find a vaccine for COVID-19 faster and more efficiently – and time is of the essence as new deaths are reported each day. This post from SingularityHub by ALEKS BERDITCHEVSKAIA and KATHY PEACH shares different ways the world is collaborating in the battle against the virus. Artificial intelligence is a big player in the fight and tech we take for granted like social media is a source of knowledge sharing that is contributing greatly. This virus will be contained, and with the help of technology, it will be sooner rather than later.
Tackling the emergence of a new global pandemic is a complex task. But collective intelligence is now being used around the world by communities and governments to respond.
At its simplest, collective intelligence is the enhanced capacity created when distributed groups of people work together, often with the help of technology, to mobilize more information, ideas, and insights to solve a problem.
Advances in digital technologies have transformed what can be achieved through collective intelligence in recent years—connecting more of us, augmenting human intelligence with machine intelligence, and helping us to generate new insights from novel sources of data. It is particularly suited to addressing fast-evolving, complex global problems such as disease outbreaks.
Here are seven ways it is tackling the coronavirus pandemic.
1. Predicting and Modeling Outbreaks
On December 31, 2019, health monitoring platform Blue Dot alerted its clients to the outbreak of a flu-like virus in Wuhan, China—nine days before the World Health Organization (WHO) released a statement about it. It then correctly predicted that the virus would jump from Wuhan to Bangkok, Seoul, Taipei, and Tokyo.
Blue Dot combines existing data sets to create new insights. Natural language processing, the AI methods that understand and translate human-generated text, and machine learning techniques that learn from large volumes of data, sift through reports of disease outbreaks in animals, news reports in 65 languages, and airline passenger information. It supplements the machine-generated model with human intelligence, drawing on diverse expertise from epidemiologists to veterinarians and ecologists to ensure that its conclusions are valid.
2. Citizen Science
The BBC carried out a citizen science project in 2018, which involved members of the public in generating new scientific data about how infections spread. People downloaded an app that monitored their GPS position every hour and asked them to report who they had encountered or had contact with that day.
This collective intelligence initiative created a huge wealth of data that helped researchers understand who the super-spreaders are, as well the impact of control measures on slowing an outbreak. Although the full data set is still being analyzed, researchers have released data to help with modeling the UK’s response to Covid-19.
3. Real-Time Monitoring and Information
Created by a coding academy based on official government data, Covid-19 SG allows Singapore residents to see every known infection case, the street where the person lives and works, which hospital they got admitted to, the average recovery time and the network connections between infections. Despite concerns about potential privacy infringements, the Singapore government has taken the approach that openness about infections is the best way to help people make decisions and manage anxiety about what is happening.
For dashboard enthusiasts, MIT Technology Review has a good round-up of the many coronavirus-related dashboards tracking the pandemic.