On April 15, US President Donald Trump announced that he would halt funding to the World Health Organization, accusing the WHO of mismanaging and even covering up the spread of the coronavirus.The larger problem, however, is that a centralized organization is not equipped to fight a 21st century pandemic.
The WHO was established in 1948. It is a specialized agency of the United Nations and is the largest international agency for public health. The main functions of the WHO indicated on its official website include: prevent emergencies and support development of tools necessary during outbreaks, improve access to essential medicines and health products, train the health workforce and advise on labor policies, etc.
As a specialized agency under the United Nations, it mainly plays a coordinating role, so some people have recently accused it of spending more on travel than medical expenses, which is clearly a misunderstanding of its basic function. In fact, as the largest coordination organization for global public health, conducting global investigation and coordination is its primary task, so large travel expenses are understandable.
Still, this travel cost also indicates that the WHO is using old-fashioned working methods to cope with a rapidly evolving situation. Even though such methods may have helped defeat diseases such as smallpox, the world has changed since then. Globalization has led to massive flows of people and goods zipping around the world. This exacerbates the spread of a pandemic, while making it harder for bureaucratic institutions to fight it.
Nor does it help that governments around the world have been less than transparent in responding to this virus. It is extremely difficult for a body like the WHO to glean the truth in this rapidly changing and opaque situation, especially when various countries offer differing versions of reality. Individuals in the organization may only observe part of the situation, and may also bring personal bias. And it could cost a lot of time for the WHO to communicate with local governments. When you have an epidemic spreading as fast as COVID-19, there is no time to waste.
So basically, we have one organization tasked with protecting the health and lives of 7 billion human beings, even as our perception of the epidemic is changing rapidly. This single organization is supposed to provide accurate and reliable opinions in a timely manner, as well as coordinate with governments around the world.
For such a complex situation, a single centralized organization is no longer adequate. A decentralized autonomous organization (DAO) system, based on the principles of blockchain technology, would be more appropriate.
The best weapon
Many are angry at the WHO for not providing a timely global warning, in particular by not characterizing the coronavirus as a "pandemic" until March 11. But such hesitation is not necessarily surprising. Politically speaking, early warnings can be a thankless task. Yes, a timely warning may have prevented a pandemic. But then if nothing seriously happened, such a warning would have been considered an overreaction and even a "false alarm" that wreaked economic havoc.
Therefore, a decentralized autonomous system (DAO) would be better equipped to provide timely warnings in the face of uncertainty. In other words, leave the warnings to an algorithm, not a bureaucracy that is hamstrung by political concerns.
Such a system would do a comprehensive analysis of data distributed all over the world, from medical reports, flight traffic data, weather reports and social network keywords. Anyone who has ever used big data analytics is aware that big data from multiple sources makes it hard to hide the truth. For this to work, of course, it is essential that the data itself be reliable, otherwise you will have a “garbage in, garbage out” problem.
Already, people from North America and Asia are trying to use the Internet and artificial intelligence to track and predict flu outbreaks. Back in 2008, Google launched a project called Google Flu Trends (GFT) to help predict flu outbreaks. By aggregating Google searches, it attempted to make accurate predictions of flu activity, providing estimates in over 25 countries. GFT no longer has its own website, but now provides data to other institutions.
Another new method, calledARGONet, was applied during the September 2014-May 2017 flu seasons with a higher accuracy rate than the ARGO method previously developed by researchers. According to researchers, the ARGONet method can provide the most accurate prediction of current flu activity to a week earlier than US states’ healthcare reports.
In a paper titled "Forecasting influenza activity using self-adaptive AI model and multi-source data in Chongqing, China" published in September 2019, we can see that researchers forecast flu trends in Chongqing, China by collecting multi-source data, including historical percentages of flu-like illnesses, weather, Baidu search index, and Sina Weibo data from Chongqing, and integrating it into an innovative Self-adaptive AI Model (SAAIM).
So, why not create more open and transparent data platforms to analyze and predict mass epidemics and the risks posed by various potential unknown viruses, instead of pouring money into traditional organizations?
For example, governments could deploy temperature monitoring sensors in all public areas with cameras, and upload the data of each area on a public blockchain that could be consulted and analyzed by the relevant agencies. It is worth noting that this would not necessarily violate privacy since the data does not need to be linked to a specific individual. The analysis of large-scale data sets makes it easier to analyze the situation of outbreaks in each region, and even to build more forecasts by integrating the surrounding outbreak maps with public transport data and even weather reports.
This is the way
Big data can offer a basis for decisions, AI algorithms can give predictions for the future, and blockchain technology can help ensure that this data is open and untamperable.
For decision-making, DAOs can use various means to stimulate collective intelligence to provide options. Decentralization helps ensure that these decisions and data are not overly biased towards one side and that the failure of some of the nodes will not bring catastrophic consequences if a wrong or ineffective decision is made.
We are already using quantum computers to calculate protein folding sequences, but we are still using World War II-era tactics to fight brand new viruses. This disparity may be contributing to the global death toll.
A centralized organization is not the right solution to a global epidemic. We need to combine artificial intelligence and blockchain technology to build systems that can make accurate and unbiased judgments, even under political pressure.
If we had a transparent, algorithm-based, decentralized response to epidemics, then maybe we wouldn’t need the WHO at all.