Just Numbers

By Jimmy Pan

There is a certain allure to numbers — clarity, coherence, control. They can be understood quickly, are used to assess aptitude, and assert confidence in decisions. In short, numbers calibrate uncertainty into momentary absolutes. Their abstracted sense of order helps explain complex issues and reduce esoteric crises into digestible approximations, but we must not forget, numbers are also interpretations tangled in complicated dynamics of power. As Sally Engle Merry notes, in her book The Seductions of Quantification, while “quantification is seductive” it is crucial to interrogate the origins of this form of knowledge and “keep open channels of contestation and resistance to their hegemony.”

The emergence of the novel coronavirus across the world and the proliferation of unpredictable crises stemming from this pandemic has brought the world view of quantification into sharp focus. COVID tracking dashboards, death counters, case number charts, virus timelines and graphs of the daily increase or decrease in new cases attempt to convey a story of comprehension, but instead reveal both the apathy of numbers and the desensitizing global appetite for infographic culture. We live in a world of itemized narratives governed by universalizing numbers.

My hometown, Kings County, ranks third on the dashboard’s chart of counties with the most numbers of deaths (as of October 16th, 2020). Excavating deeper into the trove of data I search for additional context to this ranking and eventually discover an infographic status report for the ‘county’ scale, as seen in Figure 3. My immediate unsettling anxieties about my mother, who is living in this top fatality area, are fleeting, quickly replaced with a disorientation by numbers. The sense of urgency about the real dangers of the pandemic is immediately challenged by the report’s visualization of the county case data — 5,719 deaths to 70,569 cases. An 8% death rate is alarming yet the visual cues, a small red bar compared to a large blue bar, makes it seem acceptable.

Graphics derived from tallies can impart insight about a situation quickly and reinforce understanding, but it is also important to recognize the limitations to representation. Information absent of empathic methods in knowledge creation will inevitably be contentious, fuel ideological conflict, and exacerbate disparity. Data, by itself, does not create inequality but it can be co-opted to contribute to bias. While the COVID pandemic, racial injustice, and climate change are vastly different in material terms, they are all nonetheless afflicted by lethargic data — numbers without narratives.

How are these threats measured and evaluated? By what means, at the human scale, can we detect or perceive effective change towards escaping these threats? What information can be used to gain the confidence of those who are skeptics? When facing such monumental problems, it is expected for trust to fall upon statistics; But it is equally important to accept that projections concerning intricate problems are often abridged and numbers are not the only arbiters of the future. I do not want my America to be a mono-reality, defined only by sterile numbers on a page.

In the above example, the presentation of somber statistics did not provoke a reflection on racial bias or inspire inclinations to change the criminal justice system. Instead, the numbers validated bias as a ‘reality’ that should exist. In other words, numbers created facts. Numerical data and their corresponding portrayals — like indicators, as Sally Engle Merry points out — “aspire to measure the world but, in practice, create the world they are measuring.”

From a behavioral science perspective, it would seem as if society — in this current moment — is stuck in cycles of entrapment by consonant data, where the process of “action, justification, further action” will only continue to intensify partisan postulations. In addition to this definition of entrapment, Carol Tavirs and Elliot Aronson, in Mistakes Were Made (But Not by Me), cautions us about the powerful authority that confirmation bias has over knowledge creation with a reminder about self-justification: “everyone can see a hypocrite in action except the hypocrite.”

Models, I would contend, are also absent of appropriate levels of compassion. In order to construct better models, we need a higher level of anecdotal ‘noise’ from the afflicted to support the ‘signals’ of interpretation by the so-called experts. Where science struggles to make meaning, design thinking must lead, by deploying artistic and ethnographic methodologies to create images of the world that emphasize the importance of intimate storytelling.

The first step must be the choice to compose humanized data, the ‘slow’ data of autobiographical nature — thorough records about the experiences of suffering and survivor stories, not merely obituaries of names and their professions. What an individual has accomplished is who they are, but how they suffered is not always revealed as a part of their existence — a world filled with sanitized identity. The media is far too often obsessed with eulogy.[1]

‘Predictions’ about the future, especially about complex situations like COVID-19, racial justice, or climate change will inevitably influence large swaths of society. Real lives are at stake, but ‘realness’ is subjective and multifarious. If an individual has not been personally affected by the pandemic, racism, or climate stress, their ‘truth’ may in fact be that these threats do not exist, at least not yet. If we — designers, planners, and policy makers — can be critical about how cities are designed and how policies governing society are defined, then we must be able to examine the questions we ask when trying to envision esoteric and entangled futures as well as the statistics those questions construct.

Empathic data appeals to curiosity, elicits more critical questions, and does not accept a cursory reading of our multiple realities as a single, monolithic reality. The fragile impermanence of our individual realities reveals the personal adaptive capacity that emerges in each of us when we face adversity. The coupling of this humanized, unrefined, and dissimilar qualitative data with comprehensive refined statistics is crucial for any attempts at activating restorative justice. What form does empathy take in tables of data and how can numerical data elicit emotion? What constitutes valuable data and who is it valuable for? How can data say more?[2]

Dear data, you are powerful, so please, be more nuanced.

Dresner, Howard, and Jim Ericson. Big Data Analytics Market Study. n.p: Dresner Advisory Services, LLC, December 20, 2017.

Merry, Sally Engle. “A World of Quantification” in The Seductions of Quantification: Measuring Human Rights, Gender Violence, and Sex Trafficking. Chicago: The University of Chicago Press, 2016: 1–26.

Reinsel, David, John Gantz, and John Rydning. The Digitization of the World — From Edge to Core. IDC White paper. DOC# US44413318. n.p: Seagate, November 2018.

Special Initiative for Rebuilding and Resiliency. “PlaNYC: A Stronger, More Resilient New York.” New York: City of New York, June 2013.

Tavris, Carol, and Elliot Aronson. Mistakes Were Made (but not by me). Orlando, Fl.: Harcourt, Inc., 2007.

U.S. Congress, House of Representatives. Green New Deal. H. Res. 109. 116th Congress, 1st session. (February 7, 2019).

Figure 4 “PlaNYC: A Stronger, More Resilient New York.” Special Initiative for Rebuilding and Resiliency. New York: City of New York, June 2013, 2.

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