Big Data is as widely discussed as it is misunderstood. Though unfathomably large quantities of data are produced daily, most of it is unmanaged. It is processed through AI and algorithms rather than prying human eyes.
Despite the misunderstandings and discomforts surrounding this ever-expanding technology, it’s pretty safe to say that Big Data is here for the long haul.
And though Big Data handling and implementation can generate legitimate privacy concerns, it can also significantly impact everything from entertainment to crisis management.
What Are the Social Impacts of Big Data
This article takes a broad, sweeping look at the many social impacts created by Big Data.
1. Social Unease
One of the less quantifiable impacts of big data on the social scale is the public’s vague sense of distrust about how personal information is handled.
Some of this distrust is quite reasonable. It seems that hardly a month goes by without a significant data compromise cropping up in the news cycle.
Ignorance also plays its part. Much of the social discomfort concerning Big Data arises because very few people understand how their information is personally associated with them and anonymous.
Also frequently misunderstood is how much data is being reviewed by human eyes versus algorithms and AI.
As the supersaturation of Big Data continues to increase, public education may help stave off some discomforts. However, a degree of receptiveness to public opinion may also be required for data implementation to be truly harmonious.
In the relatively short time that the question has been in flux, we have already observed some companies being forced to pivot in their data implementation policies as they respond to public outcries.
To that end, it may be reasonable to assume that consumer opinion may have as much of a role as legislation in determining how information is used going forward.
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2. Significant Changes to the Business Framework
As businesses continue to move towards Big Data, there will be a necessary shift in workplace attitudes and practices to reflect the change.
You cannot achieve proper data implementation halfheartedly. It has already been well documented that companies wishing to improve their data implementation find the best results by significantly changing their culture.
This might include regular training, new technological infrastructure, shifts in traditional responsibilities, and other changes that begin at the corporate level and permeate throughout the entire business.
An emphasis on Big Data implementation at the corporate level has grown significantly over the past decade. Many businesses have yet to make the adjustments necessary for proper data implementation.
However, shortly, it’s reasonable to assume that people from a wide range of different professional backgrounds will find that their work responsibilities have in some way pivoted to include data implementation.
Similarly, it may be reasonable to expect an influx of people wishing to explore careers in data science.
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3. Better Medicine
Big Data has already played its role in the evolution of 21st-century medicine. Presently, some technologies pair data with AI to radically enhance the speed of diagnostics and treatments.
Historically, ailing patients have had to make regular trips to their physicians. At the doctor’s office, their vitals would be monitored, while the physician would consult their reference materials and possibly their colleagues to make their diagnostic determinations.
This imprecise, lengthy process can be complex for ailing patients and the healthcare system as a whole.
Add to this that many conditions can accelerate quickly, and a more precise portrait of a deep-seated healthcare problem emerges.
Data coupled with AI can do much to alleviate this burden. From a pure data collection standpoint, many wearable technologies now allow patient information to be taken remotely on a near-constant basis and then monitored at the physician’s leisure.
Thanks to the Internet of Things, medical devices such as heart monitors can record a patient’s vital signs to get real-time health information without stepping into a hospital.
Not only is this convenient for the patient, but it also saves physicians time, allowing them to direct their resources to more demanding cases.
From a diagnostic perspective, AI and Big Data can also speed things along by providing clear possibilities.
With the right technology, a physician can type in a patient’s general health information and symptoms.
An algorithm will then sort through a Big Data database and suggest what might be responsible for the patient’s ailments. Diagnoses get made faster. Fewer people become seriously ill, and the healthcare system functions more fluidly.
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4. Prescriptive Medical Recommendations
Similarly, better extensive data analysis may result in more prescriptive medical advice.
Whereas now, it might tell a twenty-five-year-old male to exercise for x amount of minutes a day and eat x amount of calories, Big Data could allow for more personalized recommendations.
Instead of providing the standard recommendations, which could just as quickly be located on a Google snippet, patients might receive suggestions specific to their race, height, weight, and family history.
Not only will this benefit the patient, but it will also further unburden the medical system by providing better preventive care.
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5. Crisis Management
Big Data is already playing a significant role in crisis management. For example, in 2008, a phone application in Kenya crowdsourced data on where the most violent episodes of social unrest occurred in the wake of a tumultuous election.
The program automatically generated maps illustrating where those seeking safe havens could go by harvesting real-time data from people on the scene.
Since then, interactive mapping technology has advanced considerably, providing many benefits to communities reeling from disaster. 2010, for example, Haitians could use a new Google tool called “Person Finder” to connect with missing loved ones following a disastrous earthquake.
By checking in online, big data reunited thousands of people with friends and family members over just a few days. Since then, other tech companies, including Facebook, have rolled out software capable of producing similar results.
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By harvesting data from social media, AI algorithms can also assist in emergency response by ensuring resources are used as efficiently as possible. As people suffering a natural disaster produce digital data, first responders clearly understand where they will encounter the greatest need.
Big Data also aids in disaster readiness. In the past disaster, simulations have been highly theoretical and largely inaccurate. However, data-generated simulations give crisis responders a clearer picture of how emergencies unfold.
6. Big Data and Advertising
Just about everyone with an online presence has experienced the surreal discomfort of Big Data-driven advertisements.
One can hardly even discuss a product without seeing it advertised on Facebook later in the day.
You needn’t even be online to find personalized advertisements that directly respond to your search history. Currently, digital billboards receive digital phone data from passersby and generate advertisements accordingly.
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While those uncomfortable with data tracks do have their recourses—limiting their online activity, clearing “cookies,” etc., the fact is that data creation in the digital age is not optional.
Uncomfortable though consumers may be on the receiving end of highly targeted ads, there are benefits. Businesses connect with a receptive audience, and buyers receive notifications for products they might like.
7. Crime Prevention
Crime prevention is another category for which privacy is sacrificed for the more significant benefit of social good.
One of the inherently uncomfortable aspects of preventing crime is that it necessarily applies suspicion to people who have yet to do anything wrong.
We already accept the application of crime-preventative measures to an extent. For example, airport security is applied indiscriminately to everyone who steps into a terminal.
TSA agents profile people in real time, and if they display suspicious behavior, they are subjected to additional security screening.
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Big Data allows this to unfold on a broader scale. For example, law enforcement can now use social media-generated information to identify the potential for violent crimes based on people’s public postings.
Law enforcement agencies can also use Big Data to maximize their limited resources on a perhaps less personally invasive scale.
Using analytical technology, police can establish well-defined maps of where crime rates are the highest and conduct their policing accordingly.
8. Big Data in Education
Big Data can enormously impact education, both for students and at an administrative level.
From the perspective of a university, it may use data to forecast what programs are in the highest demand—not just currently but over the next several years.
From there, they can use their resources to create programs that appeal most broadly to incoming first-year students.
Big Data can also help students. For example, using algorithms, students displaying at-risk behavior involving grades or classwork might be noticed and addressed sooner than would otherwise be possible, thus lowering the academic dropout rate.
Data can also help educators at every level develop courses of study that are effective and aligned with the student body’s broader educational needs.
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9. Entertainment
Entertainment has always been about giving people what they want. In a world where franchises are constantly in sequels, prequels, and reboots, fan service has never been so well catered to. Big Data allows entertainment companies to look at their audience’s wants.
This helps save time and money for content-producing companies by focusing effort on activities that produce the best outcomes. On the consumer end, it means audiences get more of what they want. We already live in a hyper-personalized world of content consumption.
Long gone are the days when viewers were beholden to the cable schedule. With streaming, people can see what they want when they want to see it. Data can further personalize entertainment by giving people extremely customized recommendations based on their previous history.
If you’ve ever enjoyed a Spotify playlist or been thrilled by a movie recommended by Netlfix, you can thank data processing and implementation for the experience.
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Conclusion
Unquestionably, Big Data’s continued persistence will be met with social comfort and any goodwill it receives. And yet, we can be equally confident that any dissent will ultimately enjoy the same efficacy as complaints concerning the emergence of the plow.
Such is the nature of emerging technology.
Big Data is a tool with benefits, both social and financial. As those benefits reveal themselves, people on the receiving end will inevitably grow more permissive of the technology’s shortcomings. Or, they won’t, and the technology will persist anyway.
The question is not how Big Data should shape our lives in the future. Though not new, the technology is currently young enough to be tamed in a way that suits general social preferences. Through social education, accountability, and advocacy, it is possible to enjoy a future where the benefits of Big Data are broadly enjoyed, and the shortcomings fade into obscurity.
