Lauren Klein
Professor of Data & Decision Sciences and English
Professor at Emory University, director of Digital Humanities Lab and Atlanta Interdisciplinary AI Network.
Lauren Klein is a Professor of Data & Decision Sciences and English at Emory University, where she directs the Digital Humanities Lab and Atlanta Interdisciplinary AI Network. Before arriving at Emory, she taught in the School of Literature, Media, and Communication at Georgia Tech. She received her PhD in English and American Studies from CUNY Graduate Center, and her AB in Literature (English and French) from Harvard University.
She works at the intersection of data science and machine learning (what people are now calling ‘AI’), data and AI ethics, and American literature and culture, with an emphasis on research questions about gender and race. She is the author of several books, including Data Feminism (MIT Press, 2020), coauthored with Catherine D’Ignazio, which was named a ‘Must-Read Book for Spring 2020’ by WIRED Magazine, and An Archive of Taste: Race and Eating in the Early United States (University of Minnesota Press, 2020), which shows how thinking about eating can help to tell new stories about a range of people, from the nation’s first presidents to their enslaved chefs, who worked to establish a cultural foundation for the United States. Her next major project, _Data by Design: A Partial History of Visualization and Power, coauthored with members of my research group, will be published in print and online by MIT Press in Fall 2026. With Matthew K. Gold, she edits Debates in the Digital Humanities (University of Minnesota Press), a hybrid print-digital publication stream that explores debates in the field as they emerge. The most recent book in this series is Debates in the Digital Humanities 2023.
Recently Elsewhere
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What Data Do and Do Not Represent: Visualizing the Archive of Slavery
IEEE Computer Graphics and Applications · 2025
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Entanglements for Visualization: Changing Research Outcomes through Feminist Theory
IEEE Transactions on Visualization and Computer Graphics · 2025
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Data Feminism for AI
2024
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ارزشها و معیارهای ما برای پاسخگو نگهداشتن ما
2024
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اعتبار عکسها
2024
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بررسی فمینیسم داده، توسط ایزابل کارتر
2024
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تقدیر از سازمانهای اجتماعی
2024
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قدردانی
2024
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مقدمه: چرا علم داده به فمینیسم احتیاج دارد
2024
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نتیجهگیری: بیایید تکثیر شویم
2024
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۱. فصل قدرت
2024
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۲. جمعآوری، تحلیل، تصور، آموزش
2024
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۳. در مورد نگرشهای عقلانی، علمی، و عینی در مقابل دیدگاههای اسطورهای، خیالی، و غیرممکن
2024
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۴. آن چیزی که شمارش میشود اهمیت دارد
2024
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۵. تکشاخها، سرایدارها، نینجاها، جادوگران، و ستارههای راک
2024
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۶. اعداد خود صحبت نمیکنند
2024
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۷. کار خود را به اشتراک بگذارید
2024
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Entanglements for Visualization: Changing Research Outcomes through Feminist Theory
2024
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The Power of Absence: Thinking with Archival Theory in Algorithmic Design
2024
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What Data Visualization Reveals: Elizabeth Palmer Peabody and the Work of Knowledge Production
Harvard Data Science Review · 2022
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Seven intersectional feminist principles for equitable and actionable COVID-19 data
Big Data & Society · 2020