CoC—Ch. 4, 134-151

IoT or the Metaverse = LAC (Operationalizing Life’s Annexation to Capital)

Is/will be the social world for us or for them? 

Data colonialism brings legibility privileges (they can “read and interpret us” but we can’t fully understand them) to the social quantification sector over the lives of data subjects.

Internet of Things (IoT). The goal is clear: to install into every tool the capacity to continuously and autonomously collect and transmit data within privately controlled systems.

Simply put, the Internet of Things operationalizes the capitalization of life without limit. The Metaverse would do so even more. 

The new social theory

Because computers can only process “ideas that can be made computable,” a computer model’s selection of what it can count shapes how that computer “meet[s] the world.”

I am a little chagrined over how often folks ignore (or write about) companies capturing social features as though programming is not intentional. 

Computers do not select what counts – – the people who program them do.

The important point is not the details of Google’s constantly changing algorithm.
The important point is that each software system—and every interface built on that software—embeds decisions that encapsulate a particular “theory of the social” the software’s functioning relies on.

Once again, “that each software system – and every interface built on that software—embeds” as though the software itself does the embedding. It’s just not true. But if we continue to look at programming as though it has no human agency we will continue to take for granted that (for example) engineers working in the Silicon Valley know what’s best for society. It’s probably time to take a more serious look at how and why programmers write the code that they write.

Generally speaking, in comparison to the research that is done about the outcomes of software implementations (how Google works or how Facebook influences politics) precious little research has been done about programmers and programming.

The Hollowing Out of the Social Sciences (something of a side issue that is important to me)

Particularly in this country, that which was taken to be the “social sciences” have been co-opted by mathematics, statistics, and quantitative methods as a whole. 

Bradley is a good example: our curriculum requires quantitative analysis techniques but does not require qualitative analysis techniques. Human science requires qualitative analysis but we have substituted quantitative analysis instead. This is a historical development having very little to do with competition technologies or the Internet. These features were in place before computers and networks became prominent. This is a feature of the post-Cartesian split.

On the one hand, the ways that academics study life has very little to do with the way the life proceeds. 

One of the problems with quantitative research is that it often “operationalizes” human variables by substituting mathematical operations, counting X as though it is fully representative of Y. Where X is a number and Y is a human attribute. 

The map is not the territory.

The behavioristic reduction of human experience to what can be tracked serves the capitalization of life perfectly.

The critical study of  algorithmic justice raises awareness about potential biases in databased decision-making.

Discrimination by design

Today’s social knowledge is produced principally through privately controlled data extraction with a goal to discriminate between social actors for economic advantage.

Algorithms help “fram[e] problems” and provide the classifications on which broader social differentiations are constructed. But “many classifications are now embedded in markets,” a notable example being credit rating systems.

[extra credit book: Weapons of Math Destruction]

Datafication in the justice system

Predictive policing based on surveillance and algorithmic analysis of traffic and crime. Sentencing and parole dictated by algorithmic predictions about recidivism and/or rehabilitation. Facial recognition systems that are biased by inability to read darker skin colors.

A toxic mix of complex calculative processes (protected by software developers’ legal privilege) and on-the-ground deals to protect the algorithms’ workings from accountability even to government.

Unjust government by proxy

“Data’s very exchangeability depends on abstraction and “the stripping away of narrative” that “facilitates the . . . insertion of numbers in new locations and their adaptability in new contexts.”

Such lateral re-categorization affects people very differently depending on their status. Disadvantaged groups, such as poor mothers, have always had little control over how state agencies gather and exchange information and judgments about them.

Decision-makers often do not understand the workings of their data sources.

Data processing generates proxies—regular correlations that stand in for other variables of social knowledge—out of which larger models of the world to be governed are built. The whole point of proxies is to black-box a more complex social domain while facilitating intervention.

There is no such thing as neutral data: training data drawn from and reflective of an already highly unequal world (for example, data that reflects patterns of racial discrimination and racially linked socioeconomic inequality in the raw facts of where people live) risks hard-baking those inequalities into new interpretations and judgments.

There is a bigger danger too. If lack of accountability to context is becoming a principle of the new social knowledge, then this serves data colonialism (the mutual implication of human life and digital technology for capitalism) rather well. Abstraction means removing from view the textures of social life that might otherwise provide the reference point for social actors to hold social knowledge to account.

Above all the risks being hollowed out by the new social knowledge is the space from which human actors could once imagine themselves with a license to speak truth to power.

Numbers come to over-rule voice.

A rising injustice

If no resistance is forthcoming, the capitalization of life is destined to reconstruct Hobbes’s “state of nature”—a battle of all against all—via an algorithmic simulation that preserves, indeed stimulates, social appearances while regrounding them in capitalism’s general drive to profitable extraction.

Ethics must start out from an understanding of the self. What if the boundaries of the self too are under sustained attack by data colonialism?