Written by Kayla Matthews
Let’s get this out of the way right now: data of any kind can simultaneously be both incredibly beneficial and damaging. Not all data has the capacity to be harmful on its own, yet the ways in which you choose to collect and leverage it can change that.
A simple email address, for instance, can be a great example. When you provide your address to a company for future communications, you’re aware they will be using your email address to contact you. While it’s likely many who collect your email will send you promotional content, you consent to this and know it’s going to happen.
But when a company gets your email address without your consent, the concerns become more potent. The party involved never gave you the option to avoid communications and mined your information without your express consent or knowledge.
The scenario is even worse in the case of more sensitive data, such as your phone number, your home address, family information or even your Social Security number or other personal identifiers.
The danger isn’t always because a company has hidden motives, either. Many mobile apps and analytics tools, for instance, can do things like track the time you spend at work, improve your efficiency and performance and help you make better decisions.
These apps and platforms aren’t an issue, but the vulnerability of the data they collect is. In the event of a data breach or cyber attack, the inherent risks can come to fruition.
How Big Data gets misused
In today’s hyper-digital landscape, data is necessary to partake in so many experiences. Shop online via retailers like Amazon, and the website tracks your order history and purchase data.
When you browse social media, your favorite platforms mine your interactions and interests for future targeted promotions and ads. Visit a chain restaurant’s website, and it collects your location data to better provide local and relevant information.
Data makes the online world go around, and, believe it or not, it now also helps facilitate real-world experiences too. However, even though it’s necessary, that doesn’t mean it’s always safe.
- The moral implications of improper profiling
One common form of big data and analytics businesses use to understand their consumers relies on a technique called algorithmic profiling. Through a variety of collected datasets and information, an analyst can merge and study the details to find more complex targets.
To create the datasets, automated algorithms sort data based on a variety of meta-information. However, much of the sorting flies under the radar, and as a result, remains proprietary and private. At any given time, people visiting a site or using an app have no idea the technology is categorizing them based on their actions.
Data profiling can lead to some extremely dangerous and morally concerning habits. For example, it is possible to compile lists with the names and contact information of rape victims, the addresses and locations of domestic violence shelters, people with specific illnesses and more. People called data brokers can then get their hands on these lists and sell them to interested businesses.
Pam Dixon from the World Privacy Forum testified to the U.S. Congress about these exact things happening.
Similar to the problem with algorithmic profiling, big data can be — and currently is — a source of both intentional and unintentional discrimination in all forms, not just race and nationality.
A Google study, for instance, revealed men and women see separate online job ads, resulting in men being exposed to ads for higher-paying jobs and better opportunities, more often.
It’s not always due to direct targeting from a specific individual or group, however. Facial recognition has a tough time identifying those who are not white or fair-skinned. On personal devices like a smartphone, it’s frustrating. Yet, when companies or law enforcement agencies use the technology on a greater scale for activities like criminal identification and profiling, it’s not only unethical but puts vulnerable people at risk.
- Data, system and collection errors
With the sheer amount of data being collected, and how it gets collected, there is certainly room for error. How does the system or business know, for example, that you prefer strawberry over vanilla?
With smaller details that are less consequential, this isn’t an issue, nor is it scary. In fact, it can be silly to see how many odd things advertisers suggest for you based on something like your past browsing habits or recent purchases.
But what about when the information is much more crucial to your life or opportunities? What about when it involves your identity entirely? Australia’s automated debt recovery system has been the target of complaints, many of which purport the system inaccurately targets improper or vulnerable people.
Welfare cuts in the U.S. powered by big data systems have also come under fire for harming the lives of many innocents in Indiana, Florida and Texas due to inaccuracies.
Misinformation visualization — the improper visualization of data — is also possible through collection or processing errors. This can lead to distorted or corrupted data that has unintended consequences for both your audience and organization.
This brings us to the question: how do we know a system is truly accurate and that an algorithm is working properly? What happens when there are errors or bugs, and how do we address them?
- Data breaches or cyber attacks
Massive troves of data must have a home somewhere. Companies tend to deploy their own local or in-house data centers to this end, or they outsource the systems and handling to a third-party provider. In any case, the collected information gets stored on remote servers often not far from an open connection. It is exposed, especially to outside and unscrupulous groups.
In the event of a large data breach, which happens often these days, that information and data can quickly become compromised. Sometimes the root cause is lax security, while other times, it’s through no fault of the company that was collecting said data — though they are certainly still responsible for it. Yet the compromised data is affecting thousands, maybe even millions, of people.
A widescale data breach comes with many consequences and repercussions. It can lead to identity theft, blackmail, reputation or social damage, and even financial or personal issues. The companies that owned the data can face legal and financial punishment, as well.
- Political or social manipulation
It’s crazy to think about, but the more people and organizations know about you, the more influence they can have on your life choices. For example, the rise of bots that circulate false information online has been a frequent topic of recent media coverage concerning the effect they can have on political polarization.
In these circumstances, the disseminated information often gets manipulated based on hidden motives. This spread of misinformation causes both social and political harm. In this way, propaganda has taken on a new form in the modern digital age.
The Oxford Internet Institute revealed the results of a study on this problem, exploring how misinformation via social media can be weaponized to manipulate public opinion. You might also be surprised to learn these tactics are in use in at least nine countries, likely more.
How do we prevent data harm?
Everyone should strive for greater transparency, better security and protections, accountability and due process for modern digital data and its handling. Public and political pressure is the best way to get things done, and put standards, regulations and limitations in place to protect the public.