The power of data: why it matters and how can we overcome its challenges

We live and work in a data-centric world. Every action of our over-digitalized lives has some correlation with data. With every click we make in our browsers, every message we send through our phones, each bank transaction and purchase we make, there’s some data exchange that triggers data collection, storage and analysis.

Though this isn’t precisely a new phenomenon, the effects of data in our everyday lives have grown to colossal dimensions. When I first started BairesDev the only data we had to work in our business strategies was the one that we were able to collect by thorough inference processes, surveys and reports. Nowadays, we have the possibility to gather large datasets automatically from countless sources that allow us to rapidly gain insights about almost any person. 

While this seems fantastic for companies of all sizes, I’ve always had the feeling that businesses should take a deep look into the processes of data science. There’s a fine line between publicly available data that can drive great business experiences and a simple privacy intrusion. I was not alone in this opinion and the topic is now more open to discussion than it ever was.

Privacy scandals surrounding tech giants like Google and Facebook and the recent introduction of the General Data Protection Regulation (GDPR) by the European Union has brought the general public’s attention to the data subworld that businesses know oh so well. There’s still a lot of discussion to be had and several controversial points surrounding data usage and privacy. 

In that context, saying that data matters is an understatement. The age of information has turned it into a crucial asset for companies but also into a topic of concern for everyone involved. That’s why I’ll share some thoughts with you about its current usage, its ethical implications, and how its responsible management can lead to a beneficial relationship between companies and users.

How we use data today

Whenever I talk to colleagues, go to conferences, or read articles online, data is always in the spotlight. The Big Data trend has helped put it in that place, as the massive volumes of information that are being gathered today are now under scrutiny from advanced AI-based tools to organize, manage and analyze said data. There are several things businesses are doing with that, including:

• Understanding and serving users: one of the primary uses of data, as the collected information allows businesses to know their customers through their demographics, preferences and behaviors
• Predicting trends and behaviors: knowing the users is the first step to create predictive models. Thus, companies can anticipate how the user will behave in the light of new products and features as well as identify when certain actions could have their biggest impact. 
• Tailoring content: personal data lets companies tailor their content to serve it to the most appropriate segment within its customer base. In this way, businesses can reach out to their clients with the most relevant messages.
• Getting feedback on products and services: analyzing data businesses can understand how their clients feel about products and services, their features, and even about the whole brand. With that, they can redefine what they offer to fit the public’s needs.
• Identifying new business opportunities: data can also show new customer interests and issues. That information can be used to complete the products and services but also to detect potential windows to launch new businesses.

Of course, that’s the use we as business owners created to take advantage of data. But what about the consumers? Is data benefiting them? Of course! Data helps businesses to create better-tailored experiences for their customers. This goes beyond more relevant ads, to the point of giving better content suggestions, providing streamlined websites and interfaces, and even helping them discover new things.

The ethical challenges of collecting personal data

All I’ve said so far promises a win-win situation for both companies and users. However, that’s an ideal scenario that reality has proven slightly utopical. That’s because the growing use of algorithms to analyze big data limits human oversight, which can lead to responsibility, respect for human rights and fairness issues.

Let me put it more clearly. AI-powered solutions will be looking for maximum efficiency without following an ethical code. This means that data collection can exceed what’s perceived as public and step into the private world of users. In this context, privacy becomes a key component, and failing to acknowledge it can lead to social rejection of data-centric practices and a negative impact on our lives.

It’s not just the lack of human oversight or the fact that there is the risk that sometimes developers of AI software for big data analysis don’t take ethics into account. There’s also the growing issue of data mismanagement, that can stem from poor data handling or worse, from a fraudulent intention on behalf of the developers to gather private data illegally or without the user's consent. 

That’s a severe challenge that the whole digital industry has to rise against, as its implications go beyond a poor consumer experience. In fact, data mismanagement can have a huge impact on financial, political and personal spheres. In fact, the GDPR was born out of the need to control what some businesses (including tech giants such as Facebook and the Cambridge Analytica scandal) were doing with data collection. 

Unintentional poor handling of data can also facilitate cyber attacks, especially for financial purposes. Popular online scam techniques such as phishing and whaling take advantage of this kind of low-quality data management to steal sensitive data, such as credit card info and bank credentials. 

All of this causes a negative perception in the public that grows increasingly tired of how their personal data is treated, which in turn leads to a disbelief in the potential benefits data can bring to their lives. 

Building a path to responsible data management

The scenario I’ve painted above illustrates the aspects we need to address if we’re to keep using data in a responsible manner and with the public’s benefit as a primary goal. I’m sure there’s more to it but I think that introducing new regulations and laws, including ethical training in the formation of software developers, and increasing the security of data collection are the main pillars that will lead us to a new era of responsible data management.

Fortunately, we’re on our way there. The aforementioned GDPR, the Gramm-leach-Bliley Act (GLBA) for financial institutions, and the California Consumer Privacy Act (CCPA) are clear examples of the new regulations we need on a global scale to limit the abuses of companies, especially the digital behemoths capable of gathering colossal data sets. 

We also need to complement the regulations with the development of ethics-related soft skills for developers working on data collection algorithms. Thus, the people creating the software can already instill ethical concepts within the development itself. By embedding these ethical concerns in the core of big data analysis, the AI-powered solutions would “understand” certain predefined boundaries.

Finally, security has also risen up to the challenge. Since data breaches are increasing with each passing year, it’s logical for people to stop trusting services with their most personal data. Guaranteeing that digital environments where data is collected and stored are robust enough to avoid these breaches is key to rebuild part of that public confidence.

All in all, it’s a matter of privacy and security. While data privacy takes care of how data is collected, shared and used, data security protects data from external attacks. The combination of both in the context of a strongly regulated activity is the only way we can get our data-centric world to be beneficial for everyone. We’re taking certain steps in that direction but there’s still plenty to be done and it’s up to us, both business owners and users, to push for the data collection landscape to go in that direction.