Weekend Roundup: Data as Labor

It’s time to bargain for data rights.

Nathan Gardels

Data as labor. (WorldPost Illustration)

Sometimes an analogy to something old yields an insight into something new. That is the case with the idea of “data as labor,” promoted by Glen Weyl and Matt Prewitt of RadicalxChange.

For these innovative minds, data is for the digital age what labor was for the industrial era. It is, as Karl Marx put it, the “form forging fire” that creates value through production. In order to capture a fair share of that value and set the terms of work, laborers organized into unions that could bargain with those who owned the means of production. So too, they argue, all of us who generate value through our shared data should organize into “data cooperatives” as bargaining units to capture our share of the value we produce and set the terms of its use by the big platforms that, for now, control and exploit our personal data to their immense profit.

On our own as individuals, we each have little power, and can reap slim value. But by joining together to create a countervailing institution to the great information trusts like Facebook or Google, we can set the terms of privacy, as well as sell or lease our data to them as we see fit, instead of simply trading all that away with a click in return for free access to their platforms.

As during the heady days of the labor movement, there will be skirmishes and dramatic confrontations ahead. For everyone to take back control of their data would hit at the heart of the big-tech business model, and they will be loathe to let go.

There are lots of issues to resolve. How will the collective value of data be distributed back to the individual user-producer? Should that captured value be invested in a kind of “sovereign data fund” from which all get dividends? Instead of selling or leasing data to the big platforms, might it be wiser, and in the end more equitable, for cooperatives themselves to own a share in the intellectual property itself?

Before such a system is put in place, don’t we need first to define data rights similar to the way performers own their tunes that play across multiple platforms? And to define data rights, both as privacy and as property, mustn’t everyone have a verifiable data ID? What is the value, and who controls it, when your data and my data overlap?

California, which hosts Silicon Valley, has already led the way by passing the nation’s most sweeping digital privacy legislation last year. The state’s governor, Gavin Newsom, called for a “data dividend” for citizens in his State of the State speech in February. And now a legislative task force is hard a work defining what that might mean, including along the lines suggested above.

The analogy of data as labor helps define the right questions in order to get the right answers. It marks a major turn in these still early moments of digital capitalism that these questions are on the table. And the momentum is building.

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.

RAVE (IRCAM 2021) https://github.com/acids-ircam/RAVE