Data Feminism - The Importance of Being Earnest

Statistics and economics are two sciences which are adept at explaining the past than predicting the future. While Nobel Laureates of all science streams are awarded for their studies that transform the future, the Sveriges Riksbank Prize in Economic Sciences invariably goes to an economist who explains the past. Statistics is definitely not as vast as economics and, therefore, could be diagnosed with a lesser effort for the maladies that plague it. Data Feminism is a delightful step in this direction. Authored by two American academics, Catherine D'Ignazio and Lauren Klein, this book is eminently readable and shorn of the intimidating academic-style writing. Books written by academics are a semantic nightmare. Their convoluted jargon compulsively prioritise the writers’ erudition over readers’ understanding.  This book is more a passionate plea for action than a lofty intellectual pursuit.

At the outset, the choice of the title is thoughtful and suggestive. Feminism is used as a metaphor for fair opportunities and treatment. The book, like feminism, is both a problem-statement and a potential response. The allegories don’t end there. The book begins with story of Christine Darden, the famed black NASA Aeronautical Scientist, who broke the barriers of race and gender through the American race for space supremacy. In an era where computers were still in their infancy, most complex mathematical problems were solved by humans. Particularly, women. More particularly, three black women - Katherine Johnson, Dorothy Vaughan, and Mary Jackson.  It might look incredulous but these human computers were termed as unskilled manpower and were refused higher positions. Their arresting yet inspiring journey, is subject of a bestseller and a blockbuster, The Hidden Figures. The authors state that, “It is because of both her contributions to data science and her advocacy for women that we have chosen to begin our book, Data Feminism, with Darden’s story”

A decade ago, data sets that lacked integrity were primarily a problem concerning the Government. More precisely, the welfare state. The quintessential welfare state desperately sought cues from data to formulate policies that could maximise the impact of its alleviation initiatives. But the increase in the power of computation and decrease in the cost of computation, both exponentially, made Artificial Intelligence a ubiquitous presence in less than a decade. Not just the Government, but corporations and commoners are nibbling the fruit which is longer forbidden. Falling costs and easy access will soon ensure that AI would be as essential as electricity. As AI seeks to play crucial role in both decision making and service delivery, faulty data set trained AIs are contagions that could get unleashed in the most unsuspecting manner.

Sample this. A father discovered his teenage daughter’s pregnancy when he found a drab promotional discount coupon from a Fortune 500 retail-chain behemoth in his letterbox. The fiasco was an unintended result of an innocuous request from the marketing team to identify customers who are pregnant. The team was guided by another piece of research, most probably from another data set, which revealed that pregnancy is a major life event to convert a casual shopper into a life-time customer. The data scientist working for the Company devised pregnancy detection model which gave a pregnancy prediction score to each customer based on the purchasing patterns. The young lady’s purchasing patterns ticked off the pregnancy detection model and the marketing division religiously courted her with discount coupons.

The entire episode, needless to say, swirled into PR tornado that caught the corporation completely unawares. While most look at such incidents as a privacy breach, a closer scrutiny would reveal a latent gender angle to it. Would such triggers be set off if an underage boy bought liquor or contraceptives? What we see is a data collection system that adversely affects the privacy of a particular gender. These are the issues that Data Feminism explores. The inequality in privileges and oppression that data sets create, perpetuate and accentuate. The result is a sub-standard data set that neither serves the purpose of the corporation or its customer.

The book studies the pitfalls of the current data sets through the framework of Intersectional Studies and explores actionable solutions. Coined in 1989 by Kimberlé Williams Crenshaw, an American civil rights advocate and a scholar of critical race theory, Intersectional Studies analyze how different combinations of social and political identities result in varying levels of oppression and privileges. Intersection Studies look at not just the data, but the intent, context and process embedded in it. Are the right questions asked for collecting data? For example, it is common to find surveys asking women the kind of contraception they prefer. But they are seldom asked if they have access to abortion. A bad data set leads to flawed policy response. It neither wins the Government votes nor improves the lives of citizens.

The good thing about bad data sets is that they can be improved. What is worse is data sets that don’t exist. In a democracy, if you don’t get counted, you don’t exist. Governments are biggest collectors of data and in democracies it is natural that such efforts are driven by electoral prospects. Missing data threaten to leave vulnerable sections of people out, particularly in the first-past-pole system. For example, which one would take precedence? Data on child abuse or data on unemployment? It wouldn't be surprising if the unemployment count be done by Government while child abuse data be left to an NGO.

While I would reserve the reasons for the bad data sets and other related stuff for the next post, I would leave you with the wonderful work of a Nigerian-American artist Mimi Ọnụọha which has been highlighted in this book. She created The Library of Missing Datasets which contains files with compelling titles such as “Public list of citizens on domestic surveillance lists", “People excluded from public housing because of criminal records”, “Poverty and employment statistics that include people who are behind bars” etc. Just that when you open the file, it is just empty.

Simple yet profound.

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Humankind : A New Wine from an Old Bottle

 In 1993, two motivational speakers, Jack Canfield and Mark Victor Hansen, decided to publish a book that was a compilation of inspirational true-life stories. After being rejected by all major publishers, it was picked up by a small publisher from Florida who specialized in self-help books. When the book came out, it was a success that breached both the imagination and expectation of the authors. The massive popularity of the book nudged the creators to start a series and it continued to top the New York Times Bestseller list for the next five years. Since then, Chicken Soup for the Soul evolved into a separate company with varied interests from publishing and pet foods to philanthropy.

As a young adolescent, I did give some of my time to a couple of these books. They were a good and easy read. But they were just that. Their stories altered my worldview only as much as a well-made biopic. In this age, most of those stories will pass as an early morning whatsapp forward. I often wondered if anecdotes from the lives of others really inspire us? Chicken Soup for the Soul probably thought that stories from ordinary folks could inspire people for their relatability quotient. We may think that emulating Mohandas is easier than Mahatma. But anecdotes are just what they are. Stories that linger in your consciousness just a little longer than the smile they bring on your visage.

Rutger Bregman’s Humankind doesn’t inspire and that is the best thing about it. The best inspirations last only as long as the goosebumps they arouse. For stories to trigger a change, they need to set you on a thinking trail. Have relook on the truths you lived with. Show you a flicker of possibilities that were dormant. Humankind tries this with a different set of anecdotes, studies and experiments. But these are not about persons. They are about communities. Communities ravaged by war. Communities convicted for crimes. Communities condemned by the Ice Age. And what does he try to say with all these examples? “That most people, deep down, are pretty decent.”

Is that all? You don’t need 400 odd pages to say this. This is something we all know. In the first chapter, Bregman even declares that this is a radical idea which could turn the world on its head. You will be forgiven if you find him bombastic. But as you flip through the pages, it will dawn upon you that it is an axiom that you knew but never believed. No, not because you lock your home or you don’t leave a wad of cash on a park bench. It is because we believe that it is stupid to give a power saw to a murder convict during his time at the penitentiary. Humankind introduces you to the thought that not giving a power saw to the convict is stupid.

Throughout the book, Bregman challenges such self-fulfilling prophecies. Truths that appear true because you want to believe that they are true. You may not be convinced, but you definitely will be shepherded into thought experiments to simulate his postulates. That is where Humankind succeeds. And the best part of the ride is that there are no heroes in the book whom you can emulate. No character who makes you a lesser mortal. Look at the story of a murder convict with a power saw. It took one convict, a few prison officials and an entire town, into which the convict was released upon the completion of his sentence, for the idea to succeed. Humankind is about communities that believed in a thought and miracles created by that communal belief.

It is remarkable that in his ode to humanity Bregman doesn’t shy away from talking about holocaust and terrorism – the most visible challenges to our faith in the goodness of others. For some, his endorsement of Hannah Arendt’s controversial hypothesis, Banality of Evil, may appear to be a red flag. But wait, he is not done yet. Bregman finds love even among terrorists. In the chapter, “How Empathy Blinds”, he quotes the American Anthropologist, Scott Atran, who has studied the anthropology of religion and terrorism. “Terrorists don’t kill and die just for a cause. They kill and die for each other.” Bregman argues that most terrorists join their organizations due to fraternal love rather than a belief in an ideology or cause.

Bregman studies people across ages and of various ages. From Neanderthal to the modern man; From six-month old infant to a sixty-year-old man. And everywhere, he finds that they are innately good. Humankind takes you through a fascinating journey of human nature. How evolution favoured a weaker and naïve Homo Sapien over a stronger and smarter Neanderthal? Why humans who are capable of immense love are also adept in mind-numbing cruelty? Through answers to these questions, we discover a man who was always around us but never seen in the light that Bregman sheds. And through that man, we see the society in a different light. Of course, like any other radical thesis, the assertions, reasons and the adjunct interpretations may be questioned. But the final conclusion of Bregman definitely deserves a consideration. Not because of his persuasion or the allurement of his thought. But because of the endless answers it could provide to the questions we encounter as we navigate the maze of the modern world.

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