Data literacy: Who Are The Haves And Have-Nots?

We're becoming a world enlightened by data - but how do we get everyone involved?


At the beginning of the 20th century, as agrarian society pivoted to more manufacturing and service orientation, literacy rapidly shifted from being an advantage to being a necessity. I think most would agree that without literacy, it’s virtually impossible to get by today. While virtually wiped out, sadly there is an over-representation of illiterates in the prison system, as well as in some of the poorest countries in the world. In the 21st century, we are pivoting to the digital era. Data literacy will hence evolve from advantage to necessity in a similar fashion.

This won’t be a painless transition. There is certainly no lack of data today. Rather, it’s increasingly everywhere, and in everything. As the void between the data and our ability to consume it seems to grow, various phenomena occur to bridge the gap. These include information bias (where we only get snippets, or feeds of information that we are ready to digest or that confirms our biases, for example through our friends, or algorithms in social media. Another contrasting angle is information pollution, where information intentionally gets diluted or poisoned. This is worrying for an information consumer. Perhaps even more worrying for the effect this has on algorithms and machine learning, acting on that information (and its control on our cars on the road, and drones in the sky). Paradoxically, what the widening gap between information and its consumption eventually leads to is increasing information fatigue, and in the worst case, information ignorance.

This summer, a range of current events, such as the American election campaign, and Brexit, led to discussions in the political discourse whether we’ve entered the 'post-fact' era. This could very well spread to other fields outside of politics as well. While I’d argue that a healthy dose of gut feel, intuition, and heuristics, are needed, it can’t be the only thing we rely on in the information age.

How do we then nurture data literacy, to close the gap? In my mind, it’s about much more than deciphering data. Rather, it’s about being literate enough to filter, synthesize, triangulate, contextualize, analyze, criticize and make use of it in the right way. Or as a recent paper jointly published by academics at MIT and Emerson University puts it; 'Data literacy includes the ability to read, work with, analyze and argue with data'.

Let’s briefly look at how we’re accustomed to consuming information from a generational perspective:

For Generation Y / millennials, data is more at the heart of their life experience. Grown up with a Google search box, and their use of ubiquitous computing and social networking means this group has grown up with information constantly at its fingertips. It could be anything from using an app on their phone to see what specific ingredients they’ve eaten or how many calories they’ve burned, through to checking Twitter to get real-time updates on the latest world events as they happen. Data is pervasive for these groups and they most likely will know how to use it. However, what’s often missing is pause for reflection, and source critique.

Older generations, like Generation X and the babyboomers tend to be more reflective and skeptical of the information. It’s not just tenure that has led to this, but often a solid grounding in conversation, irony, and debate. These generations lose an edge through not having the need, or more often the skills, to interact with technology and information on a daily basis. They haven’t grown up with access to omnipresent data, which means they had to reflect more over what they did have, resulting in longer attention spans.

However, age is not the key definer here. I used the two to make a point. It’s not chronology that matters, but mind-set. To be data literate, you need to learn how to combine the access to technology and data as enablers, but also to have the ability to stop, reflect, synthesize, contextualize, analyze and debate with data. And think about where it came from.

Let’s start there. This combination gets you a long way towards data literacy, and closing the gap in a world where information is omnipresent, but served up for bias, or worse still, polluted by various vested interests.

As data literacy pivots from advantage to necessity, how will the situation change as we continue forward in our data-driven world? How will future generations come to interact with data? It’s going to be an even more imperative part of their lives.

We’re already seeing school children equipped with technology for learning that provides them with data first-hand. They will grow up with data at their disposal – technology a key part of their education.

This is where we question nature vs nurture in the way we behave or decide our actions as humans. Will future generations become so reliant on data that they struggle to form opinions or make decisions without it? Or will machines make so many data decisions on our behalf that we can afford to remove ourselves from it, reflect much more, and take on a more abstracted approach to data literacy? Either way, it must be part of the curriculum, just like reading and writing is today. It’s the only way that fatigue could turn into energy. Ignorance and 'post-fact' into a renaissance of enlightenment.


comments powered byDisqus
Data culture small

Read next:

Building A Culture Of Data