Dare to be wise — Become data literate
“Hey, stop! Why did you decline sharing usage-data?” I asked a friend of mine while he was going through an online registration form for beta testing a new app. “I’m not giving them permission to use my data.” In fact, they were only asking to collect usage data to analyze how they can improve their app. They even expressed no Personally Identifiable Information will be collected. “They could misuse it one day,” he tried to justify his decision. “Ok, sure, go ahead!” I replied, and I think it was a mistake. Obviously, he could not understand the information given in detail and therefore decided to go for the most comfortable option available: Declining!
I should have helped him to understand where the fear of misuse is reasonable and where not. But I didn’t. It was the moment for me to realize that this friend of mine could be just a representation of people’s understanding of data & analytics. If this friend, whom I consider to be digitally literate, was not sufficiently literate from a data perspective, what does it say about people’s awareness of data literacy at all?
I have some thoughts and understandings I want to share, and maybe there are some arguments against my view and opinion I would like to hear.
“Answering the Question: What Is Enlightenment?” — Immanuel Kant
Thanks to his fundamental literacy, my friend read the online registration form and understood it was asking him to provide some data. He was literate enough to read the text within the registration form and enlighten what happens if he gives some information necessary to make it through the registration form and download the app. But when the online form asked him to decide if he allows analyzing usage data, my friend’s understanding of what it means precisely was lacking. His enlightenment degree (if there is a gradation of enlightenment) about data and its potentials being used was insufficient.
Kant describes the concept of Enlightenment to be “man’s emergence from his self-incurred immaturity” (=Unmündigkeit). He defines Unmündigkeit (which is the negation of Mündigkeit) as the disability to reason without being led by another person. In other words, if you reach Mündigkeit, you have the ability to conclude independently. Kant also explains Unmündigkeit is self-incurred not because of the lack of understanding “but in indecision and lack of courage to use one’s own mind without another’s guidance.”
Applied to the above anecdote: The lack of understanding forced this friend to use others’ general opinion to drive his decision. He didn't know why he actually refuses permission. The only reason he could claim was his data could be misused. This is indeed an argument, but not enough to justify his decision to be wisely chosen. Even for someone who uses social media platforms extensively without losing any thoughts to data misuse, the decision seemed absolutely arbitrary. At that moment, he lost the ability to think and make wise decisions independently; he lost his Mündigkeit.
And I think this is not just an issue; in the best case, it only would cost you benefits, but it can even be dangerous in the worst case.
Why enlightenment is essential and data literacy the key
It was estimated, in 2020, every person will create 1.7 MB of data every second, nearly 150 GB per day and person. If we want to understand how much data we are producing, let’s compare it to the byte size of an average novel containing 90k words, then 150 GB means to produce over 833 thousand novels each day. Not bad, considering the total books published ever is numbered 134 million, according to Google's efforts. That means it takes you just 161 days to write that many words containing in every published book ever. And this is actually happening by you and every other human being in the world simultaneously. Indeed we are writing the stories of our lives without being completely aware of it and are willingly (but not wisely) providing it to others to read.
Do we understand the down and upsides of data analytics and how they are related to data privacy? Is it a good tactic to generally consider data provisioning as a hazardous undertaking? To which degree of data granularity, I am OK to provide data to frame the risk I accept to receive the promised benefits? To answer these kinds of questions, we need a certain degree of data literacy.
Interestingly, very few will ever write and publish a book, but the global literacy rate is over 85% and increasing. In contrast, although everybody is producing data, I have a dim suspicion the data literacy rate is not 85%. I even wouldn’t wonder if the global data literacy rate is limited to the number of people working or studying in STEM.
Sure, the data industry only raised within the last 2 decades, there was no time to pay attention to data literacy on a societal level; some would argue. But the impact of data analytics (good and bad ones) on our lives is too significant to leave it to governments to react respectively and build up the necessary educational infrastructure. History showed us: it isn’t the best idea to rely on the government's flexibility and awareness. In some countries, we still educate our students with methods developed 100 years ago.
So if we want to have the chance for wise decisions regarding data topics, we need to educate ourselves and help others join and be prepared to enter the era of data literacy & enlightenment. Otherwise, we are dangerously underestimating the importance and the impact of data in our daily lives and leave it to others to decide what happens with our data.
“Sapere aude” — Dare to be wise!
Kant’s Motto of Enlightenment states to “Have the courage to use your own understanding.” This requires two things: courage and own understanding.
With increased understanding and knowledge of a specific topic, I have experienced that my courage to use my own understanding rises significantly. If that’s also true with others, it would be sufficient to work on understanding.
As a data professional, I think I can make wise decisions regarding permitting my data usage. And I am ok with sharing my data when I can understand companies are transparently sharing what kind of data they are collecting and for which purpose my data is being used. I am also checking if the company is underlying a governmental regulation as we have it in the EU (the implementation of GDPR). With this kind of strategy, I am avoiding a general demonizing of data analytics because I know companies use customer data to improve their services and products, which can benefit me as a customer. But we can also not close our eyes to very present cases where lack of transparency and enlightenment caused damage. Some companies gambled (Facebook’s Cambridge Analytica data scandal) and, with good reason, lost their customers' trust. Or the most recent news about Whatsapp’s alleged ambitions to share data with other Facebook companies. The lack of transparent and understandable communication about their upcoming Whatsapps policy changes does not help build up lost trust and causes a lot more confusion.
Because of these issues and the delayed governmental reaction to regulate the data industry, we should understand that most of the time, an awareness only happens when the damage was already too severe, and the medial attention raises. My learning is: Heaven helps those who help themselves.
Age of Data Literacy & Enlightenment
It’s your data. It’s your life. We should be enlightened of what, when, and why to share our data with others. We should wisely decide which passage of our life stories we want others to read and which should be kept for ourselves. In some cases, it makes sense to provide a chapter, but it might be a bad idea in others. If we can reach at least a degree of data literacy, which enables us to understand the pitfalls and dangers and understand when it can benefit, everybody would benefit—we as users and even companies.
We can not wait for centuries to get a data literacy rate of over 80%. We have to react faster, and luckily, we can do so. A vast amount of programs and free courses are available on the internet that describes and teaches the fundamental concepts of data analytics and what needs to be known about data privacy. We don’t need to learn the details data science and AI-related online courses provide to make better decisions regarding our data. Even some basic concepts are enough.
The ability of wise decision making is correlated to our literacy degree, no matter in which field. And since we are producing and consuming this much data every day, the importance of data literacy increases.
Dare to be wise — become data literate.
