March 28th, 2023
The Rebel Tech Newsletter is our safe place to critique data and tech algorithms, processes and systems. We highlight a recent data article in the news and share resources to help you dig deeper in understand how our digital world operates. DataedX Group helps data educators, scholars and practitioners learn how to make responsible data connections. We help you source remedies and interventions based on the needs of your team or organization.
IN DATA NEWS
“A lot of so-called AI systems are fueled by millions of underpaid workers around the world, performing repetitive tasks under precarious labor conditions. These tech companies hire data labelers, delivery drivers, and content moderators. Startups are even hiring people to impersonate AI systems like chatbots, due to the pressure by venture capitalists to incorporate so-called AI into their products. London-based venture capital firm MMC Ventures surveyed 2,830 AI startups in the EU and found that 40% of them didn’t use AI in a meaningful way.”
The conveniences of AI that we enjoy are thanks to low-wage essential data laborers. While tech companies make 100s+ millions of dollars, a data labeler on average makes $1.77 per task. To add insult to injury, data labelers are surveilled and must perform each task under 50 second time constraints. Data labelers do the hard heart work that prevent the masses from seeing what they see. They’re also being paid poorly to behave as soulless algorithms in order to help a more complicated web of soulless algorithms (called large language models) in order to digitize the human experience through an intentionally whitewashed lens.
These data labelers should be added as yet-another demographic harmed by the implementation of AI systems and platforms. So let’s list all the communities affected by automated decision systems: Black people, Latin people, Indigenous people, Asian/South Asian people, Pacific Islander people, womxn people, LGBTQ+ people, disabled people, non-Christian people, low-wage data labelers and so on. Aren’t we, as humans, tired of ‘discovering’ groups of people made invisible by the tech ecosystem? Aren’t we ready to insist that AI systems and platforms must contain an enforceable standard of humanity?
|Click Here to Read the Entire Article on Noema|
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Data Conscience: Algorithmic Siege on our Humanity delivers an incisive and eye-opening discussion of how to fix tech’s dominant philosophy of “move fast and break things” with a renewed focus on equity and oppression. The book explores how to address discrimination in the digital data space with several known algorithms, including social network analysis, linear regression and sentiment analysis.
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A WORD FOR BLACK WOMEN IN DATA
The way Black women engage in data work is valid, verified and valued. The times of bending to societal pressures are acceptable. My first PluralSight course (30-min video in their Professional Development Talks Series Path) will teach you how to say no without guilt, trust your voice and own your data expertise boldly. Check it out ;-)
Dear sis: “You wanna fly, you got to give up the sh*t that weigh you down.” ~ Toni Morrison
Black Women in Data Summit
September 23-24, 2023
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Daily-ish rest routine suggestion: Make your space smell good. A dozon drops of peppermint oil a few times a week has a calming effect. Give it a try.
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