Discrimination might take place in the workspace, the housing rental market, or the banking industry. Many other entities might also gain access to the database.
Inaccurate data
Anyone who uses online banking knows how easy it is for a business or institution to build up a false narrative from inaccurate data.
Poor analysis of client data can lead to faulty conclusions about that person's financial health. The same kind of thing could occur concerning physical health, if decisions are made only at arm's length, using incomplete or inaccurate medical information.
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Inequalities of opportunity: Vaccines are not equally available to everyone. That is true on a national level, but even more so globally.
Access to reliable vaccines is limited in many countries. A global database could stoke divisions between the vaccine haves and have-nots.
In an extreme case, we might see nations faced with a pandemic going to war over vaccine access.
Machine learning
There are other potential pitfalls with any global digital infrastructure. Let me share just one more - and it’s a big one.
Among the many calls we’ve heard for a moratorium on the development of artificial intelligence, few voices have demanded deliberate limits on the amount of data we feed it.
Machines “learn” by collating and analysing swathes of data - much of it provided by human users in the course of their daily lives.
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The machines spot patterns and anomalies in the data. From these, they infer rules for behaviour. Gradually, they can improve their programming. They learn.
Machines networked worldwide via the Cloud have enormous potential for positive self-improvement. Conversely, if fed faulty data, they can change in ways that are harmful to human beings or the environment.
Building global databases - and governments would not stop with a vaccine database - will provide vast oceans of new data for machine learning.
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