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Did Big Data Fail Us During COVID-19?

Did Big Data Fail Us During COVID-19?

The COVID-19 pandemic has been something of a proving grounds for tech. Industry professionals have upheld the value of tools like big data for years, and now they have a chance to prove it. With the outbreak still raging on, you may wonder if big data has been all that helpful.

Governments and organizations across the world have employed big data to respond to the crisis. Some continue to sing its praises, but should that be the case? How has the world of big data affected the fight against coronavirus?

How Big Data Has Helped

Big data has undoubtedly been a useful service amid the pandemic. To determine the best strategies for addressing the outbreak, you must know how widespread the problem is. Without big data, tracking infection rates would be a far more challenging task.

Researchers have used various data, from GPS readings to temperatures, to help understand the disease. The scope of big data enables you to look at infection rates through a range of different lenses. As scientists still don’t know much about the virus, this versatility has proved useful.

The perspective that big data provides on the virus could also help find a treatment. Some organizations are using big data to model coronavirus so that they can run simulations of how it would interact with different medications. That way, they can find potential treatments to focus on in real-world lab tests.

Concerns Over Big Data in the Pandemic

You’ve probably noticed that despite these advantages, the world still seems to have little control over the situation. While you can’t blame that entirely on big data, there are some shortcomings to note. Most notably, privacy concerns may cause people to avoid testing and treatment.

When big data becomes part of healthcare, it raises concerns over patient confidentiality. If people know the government is tracking them, they may avoid doing anything that would create more data points. They may then stay away from vital services, like filing for ACA coverage online or logging into a health screening website.

As a result of these privacy fears, big data-based tracking may prove counter-effective. If you’re worried about privacy, you’ll avoid creating more data, which would skew results. More severely, you may not seek out treatment in fear of authorities overstepping their boundaries and looking at more of your information, like criminal records.

Using big data to fuel AI in healthcare could also misdirect efforts to fight the virus. AI tends to exaggerate human biases, which could lead to unreliable and even unjust results. Any misdiagnoses or false trends could cause these programs to direct officials away from the actual source of the problem.

Has Big Data Failed?

Big data has undoubtedly helped track the outbreak, but these results may not be accurate. It would also only take a few missteps for big data to misdirect anti-pandemic efforts. With these concerns in mind, has big data failed?

It’s difficult to say. Because of the nature of these drawbacks, you can’t be sure if they’re actual problems or just theoretical. At the same time, the benefits of big data amid the pandemic have yet to produce many verifiable results.

It remains unclear whether big data has helped or hindered the world’s coronavirus response. You may not know until after the pandemic is over, and you can look back on how it played out. Until then, it seems like big data is still a useful tool, but organizations should be careful with it.

Health and Safety in the Digital Age

The world is becoming more digital by the day. All of this data can be a tremendous resource for fighting disease, but there are also some noteworthy drawbacks. As healthcare and data become more intertwined, concerns over patient confidentiality are more prevalent than ever.

The marriage of medicine and big data is all but inevitable. Depending on how you look at it, that could be either a considerable benefit or a cause for concern. As this new age begins, we should probably proceed with caution.

Originally published by
Caleb Danziger - Read more from Caleb on The Byte Beat, his tech blog.
Inside Big Data | June 26, 2020

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