New book

Do you know what a FICO score is, or the value of your own score?

Not everyone does, even though FICO scores are incredibly fateful for individuals and their households. Why? Because today FICO scores govern access to credit, and credit is usually needed to make big purchases (for example, financing a new car, or getting a mortgage to buy a home), to deal with short-term emergency expenses (like surprise medical bills), or to maintain consumption when household income gets interrupted because someone lost their job.

A high score means easier credit, while a low score means expensive credit (higher interest rates) or even no credit at all. That these scores play such a central role should come as no surprise because, in fact, FICO scores were designed to govern access to consumer credit, on a mass scale. But now they are used in other contexts as well, and so have become even more consequential.

Surveillance is everywhere these days, but its punitive impacts are experienced unevenly. Police patrol minoritized communities, algorithms discriminate against people of color, borders screen out migrants and refugees, and identification systems mislabel gender nonconforming individuals.

Growing concern over surveillance has spawned many colorful forms of resistance. In my recent book, Crisis Vision: Race and the Cultural Production of Surveillance, I analyze dozens of resistance artworks that seek to interrupt surveillance abuses.

By paying attention to the work of artists, I argue that we can learn about the deeper logics of surveillance and become more reflexive about our responses.

The flaws of the modern economic system in the Western world have become pervasive with the dominance of the Big Tech firms, while antitrust regulation and enforcement struggle to restrain these firms. We cannot blame the Big Tech firms for mastering the rules of an economic system that allows profit maximization to override societal values such as sustainability and well-being.

What is the root cause of these challenges, and how can we cope with them?

In my recent book, I examine several grand challenges and identify one underlying cause: our economic system reinforces opportunistic behavior by prioritizing profit and utility maximization. Despite heterogeneity in individuals’ inclinations to behave opportunistically, this system rewards the opportunists while penalizing those who seek to benefit others. To remedy this, I propose an alternative economic system – the cooperative economy, which is instituted on prosocial behavior.

What happens when we systematically measure the quality of knowledge in academic settings? For thousands of scientists across the United Kingdom, the answer is dishearteningly close to their hearts: measured and quantified knowledge becomes more similar and homogeneous, eroding the organizational and epistemic diversity of their fields over time.

This is what I find in my recently published book The Quantified Scholar: How Research Evaluations Transformed the British Social Sciences. Focusing on the evolution of four disciplines (anthropology, economics, political science, and sociology) I find that a specific way of measuring the quality of knowledge—periodic country-wide assessments of Britain’s public universities—has resulted in more homogeneous disciplines, both in terms of their organization and their content.

Supplemental education, such as test-preparation coaching and after-school tutoring, has become increasingly influential in determining educational outcome and social inequality. To date, most studies on supplemental education have focused on its impact on students and glossed over the supply-side story: how do supplemental education organizations (SEOs) operate and how do they transform in the context of major socioeconomic transitions?

In a recently published book, I examine the expansion and transformation of the world’s largest and most vibrant for-profit education industry—China’s supplemental education industry (the Industry) during the last four decades’ market transition. In the 1980s, all leading Chinese SEOs were nonprivate state-affiliated schools or small mom-and-pop ones stuck in dilapidated classrooms and informal practices.

How and why did they evolve into private and globally financed for-profit corporations, despite systematic restrictions by the Chinese state?

A common question when meeting someone new is asking them, “What do you do?”

People’s work, and the labor market more broadly, occupy millions of people’s lives in the U.S. and around the globe. But why is “What do you do?” often the first question? Of course it’s partly because most people need the money that work provides—and often need more money than their particular labor market job offers. It’s also because what we “do” is often shorthand to others for “who we are.”

Yet “who we are” does not begin to touch the lack of opportunity in many of today’s labor market jobs, whether in manufacturing, printing, construction, healthcare, clerical work, retail, real estate, architecture, or automotive services. These are occupations and industries that have employed nearly two-thirds of the U.S. workforce since 1980, as workers in these areas since the 1980s until today vividly describe in my new book.

The Fourth Industrial Revolution has significantly changed the world through big data, artificial intelligence, and other forms of automation. Hence, the workplace is increasingly fraught by technological disruptions and consequent loss of long-term employment security for all generations. Even educated Millennials who are popularly considered as digital natives are not spared the anxiety of automation and rapidly changing requirements for new skill sets.

How can Millennials best adapt to a transforming world and prepare themselves for a vastly unsettling future of work? My new book Shaping the Futures of Work: Proactive Governance and Millennials aims to provide answers to these questions. Why Millennials? I study their careers because they are currently in large numbers in the workforce.

Is worker ownership the way to eliminate workplace inequalities?

While organizational scholars here and elsewhere have long focused on the range of mechanisms that create and maintain a variety of social inequalities within workplaces, the context of capitalism and investor-owned firms minimizing worker voice and power is generally treated as a given.

However, an alternative form of enterprise exists: worker cooperatives, businesses owned and democratically controlled by their workers. Although worker cooperatives are still a small proportion of U.S. enterprises, an estimated 4,700 workers in as many as 1000 worker cooperatives produced over US$238 million in revenue in 2020. Indeed, as part of the anti-inequality activism that arose from the Great Recession, worker cooperative numbers have essentially doubled in the last decade across multiple industrial sectors, increasingly with the support of unions and local municipalities, and have shown great resilience during the pandemic years. Under conditions of worker ownership and control, we might assume resistance to and disruption of the kinds of class, ethnoracial, and gender inequalities that have been central to these social movements and their organizations.

Corporate managers used to track stores through weekly or monthly sales records, phone calls, and in-person visits. Today, software creates near-constant – but not necessarily meaningful – communication between store managers and their senior corporate counterparts.

Metrics like “sales per hour,” which captures a store’s sales revenue per labor-hour, now drive moment-to-moment corporate decisions about staffing. These just-in-time scheduling practices try to match the sales volume to workers on the clock at any moment.

The goal is to minimize labor costs. Yet, the result may not be higher profits.

In January 21 of 2016, Bloomberg Businessweek published a cover story titled “Why Doesn’t Silicon Valley Hire Black Coders”. Vauhini Vara followed a cohort of Black computer science students enrolled at Howard University located in Washington, D.C., one of the oldest historically Black universities in the United States. Even after a Google engineer upgrades the curriculum, students in this cohort are denied opportunities to work full time in Silicon Valley. Vara informs the reader that “although 20 percent of all black computer science graduates attend a historically black school … the Valley wasn’t looking for those candidates”.

In this same year, Reveal’s Center for Investigative Reporting analyzed the diversity reports of Silicon Valley technology firms. It found that Black employees made up no more than 2 percent of the 23 companies, who had released their figures. Eight of the twenty-three companies that provided their demographics including Google, Twitter, Square and 23andMe, did not report a single Black woman in an executive role. In a separate study conducted by The Ascend Foundation, a pan-Asian foundation, found that the number of Black and Latinx women had actually declined between 2014 and 2017.