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Milagros Miceli
@MilagrosMiceli
Sociologist + Computer Scientist | PI: data-workers.org | Head of @JWI_CriticalAI | Research Lead @DAIRInstitute | 🍉🇦🇷💚she/ella
Berlin and Buenos Aires
Joined April 2013
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    En tiempos de cientificidio y oscurantismo en mi país, estoy orgullosa de ser la primera científica argentina reconocida por la revista @TIME como una de las 100 personas más influyentes a nivel mundial en el campo de la inteligencia artificial.
    I am thrilled to be recognized by @TIME as one of the 100 most influential people in the field of artificial intelligence for my work with Data Workers' Inquiry. #TIME100AI time.com/time100ai I want to take this opportunity to share a few reflections on my work👇🧵
    Portrait of Milagros Miceli in a frame that reads TIME100/AI 2025.
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    I’ve been investigating the political economy of AI with data workers at “impact sourcing” companies for years. After reading this piece, I have thoughts, feelings, and a few questions: 1/x
    The workers behind AI rarely reap its rewards. One nonprofit in India is trying to fix that. After years of reporting on the darker side of the AI industry, I traveled to India with one question. Could its alternative model really work? time.com/6297403/india-…
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    I am thrilled to be recognized by @TIME as one of the 100 most influential people in the field of artificial intelligence for my work with Data Workers' Inquiry. #TIME100AI time.com/time100ai I want to take this opportunity to share a few reflections on my work👇🧵
    Portrait of Milagros Miceli in a frame that reads TIME100/AI 2025.
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    🚨New preprint! “How Data Can Be Used Against People: A Classification of Personal Data Misuses” papers.ssrn.com/sol3/papers.cf… We stress that data protection is not to protect data but to protect people, and propose a taxonomy of how individuals can be harmed by personal data misuse.
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    Our new article with @adrienneandgp & @timnitGebru out now @NoemaMag! We describe how labor exploitation and surveillance fuels AI and argue that supporting transnational worker organizing should be at the center of the fight for “ethical AI.”
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    ✨I'm incredibly happy and grateful to be joining @DAIRInstitute and this amazing team led by researchers I've admired for years, the great @timnitGebru and @alexhanna! With them, I will be thinking through data labor and ways of engaging communities in AI research.
    Today we welcome @MilagrosMiceli as a research fellow. Milagros's research focusses on labor conditions and power asymmetries in outsourced data work as well as their effects on machine learning datasets. She has conducted ethnographic fieldwork, interviews and workshops...
    A headshot of Milagros Miceli, a light skinned woman with straight brown hair (pulled up in a bun), wearing a light pink blazer, a white shirt and a necklace. The background is dark pink.
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    📢Thrilled to finally introduce ✨the Data Workers' Inquiry ✨our 15 community researchers ✨and the repository! This is a long thread and a reminder to join an event that will challenge what you know about data work: data-workers.org/events/ July 8, 5 pm CET/11 am EST, 1/x🧵👇
    A flyer of the Launch Event for the Data Workers Inquiry. At 8 am PT / 11 am EST / 5 pm CET there is the firt panel, called "What is the Data Workers' Inquiry +Q&A". 45 minutes later the data workers will be introduces and at last panel 2 called "How to do data workers organize in the face of exploitation + Q&A" will take place at 12 pm EST. It will be held online on zoom on the 8th of July. RSVP  at https://tinyurl.com/data-workers.
    A flyer outlining the talk series (part 1): - All online. 8 - 10:30 am PT, 11am - 12:30 pm ET, 5-6:30 pm CET. - More info and registration: data-workers.org/events Talk series: - July 8. Online. English with captioning. How do data workers organize in the face of exploitation? Speakers: Mophat Okinyi, Richard Mathenge, Krystal Kauffman Moderation: Adio Dinika - July 22. Online. English with captioning What does precarity look like for data workers? Speakers: Yasser Alrayes, Roukaya Al Hammada, Wilington Shitawa, Adio Dinika Moderation: Krystal Kauffman - August 26. Online. Spanish with simultaneous English translation What grievances are specific to data work in Latin America? Speakers: Oskarina Fuentes, Alex Chávez, Camilla Salim Wagner Moderation: Milagros Miceli - Sept. 9. Online. English with captioning What training do data workers need and what do they get instead? Speakers: Fasica Gebrekidan, Anonymous Worker, Yasser Alrayes, Laurenz Sachenbacher Moderation: Krystal Kauffman
    A flyer outlining the talk series: - All online. 8 - 10:30 am PT, 11am - 12:30 pm ET, 5-6:30 pm CET. - More info and registration: data-workers.org/events Talk series: - Sept. 23. Online. English with captioning What impact does content moderation have on workers’ mental health? Speakers: Sakine Bozorg, Fasica Gebrekidan, Botlhokwa Ranta, Krystal Kauffman Moderation: Milagros Miceli - Oct. 7. Online. German with simultaneous English translation Data work as a career? Professionalizing content moderation in Germany. Speakers: Anonymous, Data, Worker, Milagros Miceli Moderation: Laurenz Sachenbacher - Nov. 4. Online. English with captioning.  Who else does data work? Speakers: John López (WGA), Tadhg Mac Eoghain (Guerrilla Media Collective), Arte es Ética, Alex Hanna Moderation: Milagros Miceli
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    I successfully defended my dissertation!🎉 Thanks to my beautiful family for their patience, to my amazing advisors @alexhanna and @AntonioCasilli, to all my collaborators, and to the data workers who allowed me to tell their stories. I couldn't have done this without you all!❤️
    Dr. Milagros Miceli smiling and holding a big bouquet of flowers after successfully defending her dissertation.
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    I did it! I submitted my dissertation. Still can't believe it's my name on the cover🥹💪 Thanks to everyone who helped me get here! Special thanks to the best advisors ever, @alexhanna and @AntonioCasilli. The defense will take place on August 29.
    Dissertation title: Whose Truth? Power, Labor, and the Production of Ground-Truth Data.
Author: Milagros Miceli
Committee: Prof. Uwe Nestmann, Prof. Bettina Berendt, Prof. Antonio Casilli, and Dr. Alex Hanna.
    Abstract (summary):
Data work for ML is outsourced through BPOs and platforms. The data workers are kept apart from the rest of the ML production chain. They work under precarious conditions and are subject to continuous surveillance. This focuses on the production of ground-truth data. Through fieldwork at two BPOs located in Argentina and Bulgaria, interviews, and a longitudinal participatory design study, this dissertation situates data production in specific settings shaped by particular market demands, local contexts, and labor constellations.  The findings show that ground-truth data is the product of subjective and asymmetrical social and labor relationships.  Documentation practices are key for making naturalized “truths” encoded in data visible and contestable. Improving material conditions in data work, empowering workers, and recognizing their labor as a powerful tool to produce better data are key steps toward deliberation and contestation in data work and ML technologies.
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    Replying to @MilagrosMiceli
    Finally, I want to highlight that AI is always “BY the people.” But before claiming that it is also “FOR the people,” we need to ask who owns the technologies that are fuelled by data workers. The answer probably doesn’t include “the people.”
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    💫Professional news💫 In parallel to my work at @DAIRInstitute, I'm starting a new position as Research Lead of the newly funded group “Data, Algorithmic Systems, and Ethics” at @JWI_Berlin. Best thing about the new role? I'll have the chance to advise amazing PhD students!🤩
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    Replying to @MilagrosMiceli
    I have argued repeatedly that the empowerment of data workers leads to better data. I explored the link between labor conditions and data quality in my dissertation: depositonce.tu-berlin.de/items/81f40f41…
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    📢Thrilled to announce the launch of the✨Data Workers' Inquiry✨repository and talk series! Join us on July 8 for an online event where data workers will discuss wage theft, violent content, uncertainty, and their efforts to organize and resist. RSVP here tinyurl.com/data-workers
    A flyer with the event details: 
Join us for the launch of the Data Workers' Inquiry, a community-based research project where data workers are the researchers!
- Monday, July 8,  8 - 10 am PT / 11 am - 1 pm EST / 5-7 pm CET.
- Online on Zoom. Registration: tinyurkl.com/data-workers
Agenda:
- Panel 1: What is the Data Workers' Inquiry? + Q&A
Speakers: Milagros Miceli, Laurenz Sachenbacher, Camilla Salim Wagner, Adio Dinika, Krystal Kauffman.  Moderator: Timnit Gebru
- Introducing the data workers.  Moderator: Milagros Miceli
- Panel 2: How do data workers organize in the face of exploration? + Q&A
Speakers: Mophat Okinyi, Richard Mathenge, Krystal Kauffman. Moderator: Adio Dinika
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    📢New paper #CSCW2022 w/ @TianlingY @ella_es_adriana @JulianPosada0 Sonja Wang @zweipohl @alexhanna! For 2.5 years, we worked closely with data laborers to reimagine data documentation as a process oriented towards preserving their voices. 💫Read more here:arxiv.org/pdf/2207.04958…
    Paper screenshot w/ title and abstract.

Documenting Data Production Processes: A Participatory Approach for Data Work.

Previous research has proposed standardized checklists to document datasets. This paper expands that field of inquiry by proposing a shift of perspective: from documenting datasets towards documenting data production. We draw on participatory design and collaborate with data workers at two companies located in Bulgaria and Argentina, where the collection and annotation of data for machine learning are outsourced. Our investigation comprises 33 semi-structured interviews, five co-design workshops, the development of prototypes, and several feedback instances with participants. Our findings highlight the value of designing data documentation based on the needs of data workers. We argue that a view of documentation as a boundary object can be useful when designing documentation to retrieve heterogeneous, often distributed, contexts of data production.