Meredith Whittaker Profile picture
May 25 11 tweets 6 min read Twitter logo Read on Twitter
📢NEW ARTICLE!!!

In which I connect Charles Babbage & his 19th c. blueprints for digital computation to industrial labor control & the creation of a regime of denigrated, disciplined "free" labor.

All of which has its roots in plantation slavery. 1/

logicmag.io/supa-dupa-skie…
Labor division, worker surveillance & record keeping are techniques that emerged on plantations as ways to extract as much labor from enslaved workers as possible. Well before they were deployed in industrial factories. 2/
Babbage was both the early co-designer of digital computing & an influential theorist of labor discipline. Both Babbage's "engines" & his labor theories repackage, expand on, and encode plantation techniques, particularly labor division and worker surveillance. 3/
With this in mind, we can understand Babbage's work in total as striving to maintain British empire–itself reliant on the industrial mass-production–in the face of the 1833 abolition of West Indian slavery & sustained worker uprising in Britain. 4/
How to get workers to shut up & produce was the question. Applying plantation techniques of labor discipline & control, modified a white British workforce, can be seen as Babbage's answer. An answer he provided in the form of his computational designs and in his labor theories.
This is not a thin connection. His "engines" were shaped to directly encode templates for labor division, and were themselves tools for worker automation & surveillance, whose architectures assumed they would be applied in contexts of a divided, rationalized workplace. 6/
This work is a start and I hope it helps collectively marinate on the limits of computational logics, recognize the central role of antiblackness in computing history, and confront why, ~200 yrs later, plantation logics continue to scale via centralized computational systems. 7/
This work also owes a great debt! Thank you first to @UpFromTheCracks. I would not have written this for anyone else and it was a truly collaborative effort. Khadijah is *brilliant* and for real my favorite, most trusted editor. Thank you <3
I also want to thank @sarahbmyers, @veenadubal, @ambaonadventure, #RashidaRichardson for their incredibly helpful comments, interventions, and support. And @nantarsya for their insight on a much earlier version.
AND thank you to @wewatchwatchers, #NicholasFiori, @DainaRameyBerry, @sunhahong, @danmcquillan, @natashaiskander, @timnitGebru, @ruha9, @alexhanna, @s_premchander, #StefanOuma, @CC_Rosenthal, #ThomasCHolt, & many others whose work taught me & grounded me and helped me continue♥️
Subscribe to Logic(s) for this, and all the good stuff. Extremely grateful it exists.

logicmag.io/supa-dupa-skie…

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More from @mer__edith

Apr 16
NYT "AI" explainer misleads. Deep learning techniques date from the 1980s, & "AI" had been hot/cold for decades, not slow until 2012. There was no new "single idea" in 2012. What WAS new, & propelled the AI boom, was concentrated resources (data/compute) controlled by tech cos 1/ Image
The access to massive data (aka surveillance) and compute made old "AI" techniques do new things. And showed that "AI" could profitably expand "what could be done" with the surveillance data already created by the targeted ad companies that dominated the industry. 2/
Telling an accurate story leads to much more relevant questions than simply narrating "AI" as resulting from scientific progress -- a singular idea from Zeus' head! Indeed, conflating scientific progress w tech co products is one way these cos staved off regulation for so long 3/
Read 7 tweets
Jan 20
Early 2000s profitable startups gave their handful of workers novel perks/freedom. These cos/their workplace culture got big. Late 2010s tech labor gained power + made demands. Now a hint of recession = excuse to break promises/reestablish dominance over workers. It's not about $
To further clarify what character limits made difficult: It's not directly about the $ in that these companies can afford to pay these workers. It's about performing labor discipline for shareholders + lowering the bar for present & future workers in a way that curbs labor power
Read 5 tweets
Jan 3
OK! let’s talk about That Op-ed. The one that insisted not only that privacy is dangerous, but that not affirmatively building surveillance into communication tools is a radical ideological position. 1/ web.archive.org/web/2023010119…
Dunking on the arguments is easy. And dunk many have, often with the gentleness of a professor grading a struggling student they don’t want to discourage. I’ll direct you to @evacide, @matthew_d_green, @kurtopsahl, @radleybalko, @bendreyfuss, @Iwillleavenow, @cFidd, @timbray 3/
But what’s going on here isn’t substance. And that’s what I want to focus on. Those of us invested in defending privacy need to understand that this op-ed wasn’t written for people with expertise, and its purpose won’t be perturbed by expert rebuttal. We’re not the audience. 3/
Read 7 tweets
Dec 23, 2022
Thanks for raising this. We did disable some languages recently. In choosing which to keep, we opted for the official language of a given region (in the case of HK, Traditional Chinese). We did this for a couple reasons... 1/
1. the most basic reason: good translation, which is especially important around privacy/security, is expensive and we're a nonprofit. 2/
2. supporting the large number of languages we were previously including made the Signal client file size extremely big, which caused problems for people in low-bandwidth environments & for those with devices that didn't have a lot of storage 3/
Read 5 tweets
Nov 16, 2021
📢New paper! In which I work through a lot of my uncomfortable observations since joining academia, examining the alarming-but-quiet capture of academic AI research by big tech, what this means for how and what we know about AI, and how we can resist.

interactions.acm.org/archive/view/n…
In it I trace the history of the recent turn to AI, which was less about algorithmic advances and more about the concentrated data and compute resources controlled by a consolidated tech industry. Who still gatekeepers these resources.
As "AI" became the hot new thing, universities wanted a piece. And getting one was reliant on access to corporate compute and data resources. W/o these you could do work, but you're not gonna beat the benchmark, and tenure, prestige, big NSF grants would be farther out of reach.
Read 10 tweets
Sep 2, 2021
Jen, thank you and solidarity. You're not alone. For the last years AI Now -- the team, myself and other leadership -- struggled to remove Kate and Jason Schultz from the organization and to recover from the toxic pattern of extraction and harm.
I stand with the team. It cost us significantly, in terms of our individual work and mental health, and in terms of our collective access to and standing w/in the academic prestige networks where these two hold power.
I learned a lot about how academic & non-profit institutions are (way too often) structured in ways that celebrate + reward racialized extraction and abuse while propping up white celebrity & power. Solidarity now and forever with everyone working to change this.
Read 5 tweets

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