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Milagros Miceli

6 results

The logo for the Data Workers' Inquiry project, which features the outline of a monitor screen in red with a white megaphone on it and the words "Data Workers' Inquiry" in the middle.
Labor
Data Workers

Data Workers' Inquiry

Centering the experiences of data workers in machine learning by using the Workers' Inquiry approach to uncover opportunities for collaborative knowledge exchange and collective organizing. Go to https://data-workers.org to find zines, reports, documentaries, podcasts and more created by 16 data workers from 4 continents.

Painting of two knowledge workers, running inside a wheel embedded within a computer mouse, struggling to keep pace as a powerful hand (representing employers or capitalistic forces).The image reveals that despite AI and digital adoption, rising productivity expectations often trap workers into producing more with less. Rather than easing labour, AI technologies risks raising the baseline demands, accelerating the pace of work under the illusion of progress. This image was selected as a winner in the Digital Dialogues Art Competition, which was run in partnership with the ESRC Centre for Digital Futures at Work Research Centre (Digit) and supported by the UKRI ESRC.o

AI-fueled inequities

AI is fueled by the artists, writers and “zombie trainers” (see below) supplying training and evaluation data without consent or compensation. Vulnerable populations like refugees and gig workers are hired as data workers under exploitative working conditions (see Data Workers Inquiry). These same vulnerable populations are also the first to experience the harms of AI systems, whether it is through automated weapons or surveillance systems (see Surveillance Watch). This page has more of our research on the inequities fueled by AI systems.

Image: Leo Lau & Digit / https://betterimagesofai.org / https://creativecommons.org/licenses/by/4.0/

A colorful slide of what looks like post its. With "Who is who in data labeling?" first and then a bunch of sketches of people. Most of the text in the post its is not legible. But there is a title, "Stakeholders Map"
Research Frameworks

Documentation & accountability

Guidelines for ethical data annotation and release practices without exploiting workers and stealing data.

An illustraion with a bunch of concentric circles and semi circles in black. The background is white. Exploited workers
Data Workers
Human Rights

Exploited workers fueling AI

Showing the extent to which vulnerable populations like refugees are both exploited laborers fueling “AI” systems and those most harmed by them. Read our papers and articles to learn more.