The Answer to Rising Inequality Isn’t Redistribution

Nathan Gardels and Nicolas Berggruen, co-author’s of Renovating Democracy: Governing in the Age of Globalization and Digital Capitalism discuss “predistribution,” as opposed to redistribution to combat inequality

Congresswoman Alexandria Ocasio-Cortez (D., N.Y.) made headlines by calling for “taxing the robots” of the emergent digital economy. That followed her previous call for a 70% top marginal income-tax rate on the richest and Sen. Elizabeth Warren’s (D., Mass.) plan for a 2% wealth tax on assets worth more than $50 million (and 3% on assets worth more than $1 billion).

By putting inequality front and center on the political agenda as the U.S. heads into the election season, Democratic politicians are trying to capture the populist zeitgeist.

The redistributionist rhetoric has some investors concerned. Ray Dalio, who runs the world’s largest hedge fund, says he foresees “some kind of revolution” coming. Even JPMorgan Chase’s Jamie Dimon feels compelled to talk about the “fraying” of the American dream of upward mobility and the need to address capitalism’s inequities.

We’d like to propose a new approach that would enhance both the skills and assets of the less-well-off in the first place—we call it “predistribution,” as opposed to redistribution. This idea has two aspects.

The first is upskilling the workforce so that people are prepared for the steady disruptions of an ever-innovating, knowledge-driven economy. That means promoting public higher education as the bedrock of opportunity, much as secondary education was in the industrial era.

Public higher-ed is already the most certain route to upward mobility and will be more so in the future. A study of all American universities in 2017 showed that California State University, Los Angeles, was the top school in the nation in generating upward mobility for graduates from low-earning families. More of its students (9.9%) from the bottom 20% income cohort made it to the top 20% in the years after graduation than at any other institution surveyed. While the number may sound modest, Cal State LA’s mobility rate is more than five times the mobility rate of the average U.S. college (1.9%).

The second aspect of predistribution responds to the hard reality coming our way: Technological innovation, from basic automation to artificial intelligence, is divorcing employment from productivity growth and wealth creation.

Since income through employment will diminish and even disappear where tasks are routinized, more of people’s incomes in the decades ahead should be drawn from an ownership stake in the robots that displace them. All working-age citizens should possess an equity share in the growing wealth of companies where intelligent machines drive productivity gains.

One way this can be done is through national savings accounts, in which all participate, that are invested in mutual-fund type instruments mixed with diversified venture-capital pools. Another way is to provide a “dividend” for all citizens by parceling out shares of initial public offerings in the stock market, especially from companies that commercialize publicly funded research and development.“

Platform cooperatives” are another way: For example, everyone in a neighborhood could own a piece of ride-sharing services that operate there, or those who share their personal medical data would get a royalty payment from pharmaceutical inventions based on that data. The public could be assigned equity shares of any IPO by companies that benefited from publicly funded R&D. Another way, as California Gov. Gavin Newsom has proposed, is a “data dividend” for the use of your personal data by big tech.

If the greatest social divide is between those who own capital and those who have to live off their labor alone, then the key answer to rising inequality is to boost the capital of those who have less of it. Increasingly, a return on capital ought to supplement sole dependence on wages and salaries. Instead of paying ever more exorbitant taxes to fund the income of others, we would be paying ourselves. To put it another way, the most effective way to reduce inequality is to spread the equity around.

This suggests that a policy agenda for fighting inequality in the future economy ought to focus on fostering “universal basic capital” instead of relying mostly on transfer payments of redistributed wealth. To close the social chasm that has emerged, we need to break down the structure of inequality, not perpetuate it.

Just because the wealth and income gap today is at the 1920s level of the Gilded Age doesn’t mean we need to return to 20th-century solutions. Let’s not fight the last war in the trenches of the fast-fading era of labor-intensive manufacturing, but advance a new social contract that is fit for purpose as digital capitalism takes hold.

Nathan Gardels is co-author with Nicolas Berggruen of Renovating Democracy: Governing in the Age of Globalization and Digital Capitalism. (University of California Press, April 2019).

composed by Arswain
machine learning consultation by Anna Tskhovrebov
commissioned by the Berggruen Institute
premiered at the Bradbury Building
downtown Los Angeles
april 22, 2022

Human perception of what sounds “beautiful” is necessarily biased and exclusive. If we are to truly expand our hearing apparatus, and thus our notion of beauty, we must not only shed preconceived sonic associations but also invite creative participation from beings non-human and non-living. We must also begin to cede creative control away from ourselves and toward such beings by encouraging them to exercise their own standards of beauty and collaborate with each other.

Movement I: Alarm Call
‘Alarm Call’ is a long-form composition and sound collage that juxtaposes, combines, and manipulates alarm calls from various human, non-human, and non-living beings. Evolutionary biologists understand the alarm call to be an altruistic behavior between species, who, by warning others of danger, place themselves by instinct in a broader system of belonging. The piece poses the question: how might we hear better to broaden and enhance our sense of belonging in the universe? Might we behave more altruistically if we better heed the calls of – and call out to – non-human beings?

Using granular synthesis, biofeedback, and algorithmic modulation, I fold the human alarm call – the siren – into non-human alarm calls, generating novel “inter-being” sonic collaborations with increasing sophistication and complexity. 

Movement II: A.I.-Truism
A synthesizer piece co-written with an AI in the style of Vangelis’s Blade Runner score, to pay homage to the space of the Bradbury Building.

Movement III: Alarmism
A machine learning model “learns” A.I.Truism and recreates Alarm Call, generating an original fusion of the two.

Movement IV: A.I. Call
A machine learning model “learns” Alarm Call and recreates A.I.Truism, generating an original fusion of the two.