Berkeley’s Sociology Department is known around the world for its excellence in research and teaching. Our faculty advance cutting edge research and teach in most sociological specialities. Our PhDs are leaders in universities and research centers across the US and in many other countries. And our BAs populate the ranks of innumerable professions, bringing with them the skills and special perspective of Berkeley sociology.
We are proud to make these contributions from the world’s leading public university. At Berkeley, we combine intellectual rigor with a commitment to public service through our research, teaching, and service on campus and beyond.
For the past six decades, Berkeley’s Sociology Department has consistently been ranked among the world’s top sociology departments. Our graduate program is ranked #1 in the latest U.S. News and World Report, and our undergrad degree is currently the best in the US according to College Factual and features on Grad Reports’ Best College List 2020.
Prof. Einstein served graduate students as a model of prudence in remaining unfashionably true to the grand…
Inequality by Design: Cracking the Bell Curve Myth
As debate rages over the widening and destructive gap between the rich and the rest of Americans, Claude Fischer and his colleagues present a comprehensive new treatment of inequality in America. They challenge arguments that expanding inequality is the natural, perhaps necessary, accompaniment of economic growth. They refute the claims of the incendiary bestseller The Bell Curve (1994) through a clear, rigorous re-analysis of the very data its authors, Richard Herrnstein and Charles Murray, used to contend that inherited differences in intelligence...
Departmental Colloquium Series
Antonio Casilli, "How Artificial Intelligence Fosters Global Inequalities: A Four-Country Study on Data Work "
Wednesday December 11th, 2024 at 2:00 pm - 3:30 pm
Blumer Room - 402 Social Sciences Building & Via Zoom
Abstract:
While public debate focuses on how AI might affect human labor, this talk reverses the perspective by examining how human labor shapes AI. Recent evidence shows that data-intensive machine learning systems rely heavily on a concealed workforce.