One of the things I’ve noticed during this current moment of sheltering-in-place is the barrage of data permeating my news feeds and daily conversations. Every morning, the lead item on my daily doom scroll is a map of confirmed cases, death tolls, and lately, mercifully; recovered patients (all examples of data). In the U.S., urban communities of color are hot zones, drawing new attention to long-standing community inequity (data). Unemployment is skyrocketing (data), and small businesses are struggling (data). Population (data) is necessary to calculate the rate of spread, and apparently, so might be sewage surveillance (biological data). Political, economic, and civic discourse highlights the conditions (data) that must be in place to begin reentry. Countries that have been successful flattening their curves (data visualization) have been conducting mass tests and contact tracing with various privacy implications (data collection and personally identifiable information/PII). Medical staff are sharing information about potential treatments like proning that seem to help (anecdotal, best practice data).

Most of us are quite literally up to our eyeballs in data. Now is the perfect time to improve our data fluency.

Several years ago, I was working on a research project with a community of data security professionals (think CIA, FBI, etc.). I often include an ice breaker question to establish rapport. This time, when I asked the question, “what keeps you up at night?” They told me that, because of what they did for a living, they were worried about society at large. They talked about how uninformed and careless most people were about their data; that people couldn’t see what was happening around them. They were worried. They were bring it up with other parents at the soccer game worried.

Society is increasingly, and often invisibly, influenced by data. “We’re shedding data just by virtue of being alive,” according to The Future Today Institute. Yet, most of us are not keeping up with the pace of this digitalization of our lives. How do we ensure responsible use of our digital assets—like our health care information, our voter registration records, our Google searches, and our credit card purchase history? How do we learn to recognize when we’re being nudged?

In his podcast Against the Rules, Michael Lewis explores the role of the referee; a role whose effectiveness, in many arenas, has eroded. At a time with less institutional protection and fewer objective referees, we need to understand how data-driven systems work in order to rely on ourselves to act in ours and our communities’ best interests. Data are like the words that make up a language. To evaluate, understand, and engage, we must improve our ability to interpret shared meaning from many sources. We must acquire data fluency.

We are all data creators and consumers. We all already collect and analyze data daily. We just don’t recognize it as such. Our to-do lists represent data collected and prioritized. Our daily routines, the contents of our closets, and our coffee table books epitomize curated data collections. Every time we use GPS, browse online, visit the doctor, or pay for parking, we create digital data. And every time we create data, we sharpen our digital profiles. Our data plus the data of others, when considered together (or aggregated) and studied, yields information, which leads to predictions. This information has value. It has become a foundational societal currency.

Contact tracing has already become a reality as countries around the world try to lift stay-at-home measures. A necessary side effect of these efforts will be long-term privacy implications. We’re increasingly inviting deeper surveillance into our personal lives. Pew Research reports that as of mid-2019, 25 percent of American adults own a smart speaker. Never before has so much of our lives been tracked.

In her book Surveillance Capitalism, Shoshana Zuboff refers to this phenomenon as unprecedented, and the related conflict results in “a psychic numbing that inures us to the realities tracked, parsed, mined, and modified. It disposes us to rationalize the situation in resigned cynicism, create excuses that operate like defense mechanisms, ‘I have nothing to hide’ or find other ways to stick our heads in the sand, choosing ignorance out of frustration and helplessness.”

If you feel like you are among the psychically numb, you are not alone. Pew Research reports that 91 percent of Americans feel they have lost control of their data and don’t really know what to do to get it back. Many of us give away the personal data farm in exchange for convenience and fun. We broadcast personal data indiscriminately. It is a privacy paradox, and we have unwittingly become the product.

This paradox stems from a lack of data fluency. The good news is that we know now, thanks to brain science research from Carol Dweck and Jo Boaler and others, that anyone can learn anything. You don’t have to be a formally trained data scientist to develop fluency. Books like Dear Data by Giorgia Lupi and Stefanie Posavec provide accessible, creative techniques to observe, count, draw, and explain everyday data that anyone can learn. In her article in the Nightingale, Evelina Judeikytė explains how to learn data visualization in just one year!

The prevalence of data in our lives represents the need to repeatedly evaluate trade-offs. Narratives have power, as fellow management consultant John Hagel reminds us: “every successful social movement in history has been driven at its core by a narrative that drove people to do amazing things.” Powerful narratives can drive us to act or prevent us from taking action via distraction or disinformation. Predictive analytics are being employed across many sectors, often without our knowledge and sometimes in violation of laws. In order to exercise agency, we need to understand who controls the narratives coloring our daily realities.

Accessibility is particularly important. Data visualizations in the form of charts and tables have played a lead role in grasping COVID-19 implications. However, the blind and visually-impaired among us are frequently unable to access these renderings. And, as the College Board’s David Coleman explains in a 2019 Freakonomics episode, “the next area of math that’s hugely predictive of future success is … data analysis and problem-solving, including rates, ratio, proportion, designing quantities that interact with one another in that way, and watching their growth over time.” When economist Steven Levitt performed his own analysis of the SAT he found that, “twenty percent of the SAT math questions test data fluency, and 10 percent of the questions on what used to be the verbal section are data questions also. A decade ago, those numbers would have been close to zero.” Data fluency has the potential to galvanize communities affected by seemingly intractable systemic forces. Or, it can broaden existing inequities even further.

Despite the potential for manipulation, improved connectivity and open data have propelled society forward. Perhaps no sector has experienced this more meaningfully than peer-to-peer health care, where innovations without widespread commercial applications have improved lives. The Open Artificial Pancreas System project, an open technology for people with Type I diabetics that works with their insulin pump to automatically regulate their blood glucose overnight and between meals; is my favorite such example, because its founder was not technically trained. She is a patient living with a chronic condition. Data can supply help and hope from unexpected sources.

In order to use data to advance equity in our communities, we must first stop perpetuating the myth that data are too complicated and instead adopt a fluency mindset. We can educate ourselves by reading, paying attention to discourse, and practicing. While your sourdough starter is rising is the perfect time!

• In addition to books, there are online courses, associations, meetups, webinars, events, podcasts, tutorials, and blogs from which to learn. Educators at all levels and in all subjects can prioritize data fluency and find ways to infuse it into their curriculum. Find some related resources here.
• Researchers can prioritize community-based participation to inform concept and narrative development. Here is one example of what this could look like in practice.
• More municipalities and institutions that support open source data can share and promote clean datasets, making them easier to use. In the meantime, there is an opportunity to forge new partnerships like finding data scientists to help explore potential bias in aggregated data sets, e.g., employment and workforce data. The Civic Switchboard is an example of this type of collaboration.
• Organizations can evaluate their data collection practices and better understand how to signal transparency like proactively communicating, “Why we ask for this?” and factoring “What we do with this data” into project development.
• Organizations can explore alternatives in evaluation, moving toward impact-based or outcome-based metrics wherever possible. Sometimes this exploration exposes operations that cannot fully support the desired reporting, resulting in a beneficial reset of project expectations and shaping future project scope.
• Technology businesses, especially, can adopt values that support human flourishing–versus extraction and manipulation–and reward employees who exercise those values to consider and avoid unintended consequences. They can support and enact national privacy policy reforms, which limit their use of personal information for prediction. Here is one such effort.
• Organizations can subsidize employee education and incent skill building by sponsoring training: from lunch-and-learns to more formal professional development opportunities. Here is a great resource.
• Professional associations can support organizational efforts by sourcing expertise from among their membership and contributing hands-on curriculum. They can open their membership to include those seeking to learn like journalists, educators, government staff, and citizens. Professional association members can engage in data fluency mentorship. For example, by providing accessible workshops on topics like data fluency and data visualization to promote awareness and build skills among nonprofits and community organizations. The Data Visualization Society has been hugely valuable for me.

There are already more than 60 COVID-19 vaccines in the works. When interconnected individuals with a common goal pool knowledge and share their assets, we experience unparalleled advances. Data fluency is foundational to societal and civic engagement. It can invigorate constituencies and shift systemic power dynamics. At a time when we trust fewer entities to watch our backs and we can become crippled by fear and powerlessness, data fluency can help us find and activate opportunity narratives. There is no Babbel application, though, we must learn to speak the language.