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Week of March 7, 2022
CITP News Highlights

CITP Faculty Arvind Narayanan to Discuss Quantitative Approaches to Discrimination at "James Baldwin Lecture"

Quantitative studies can validate experiences of racial injustice, but they can also underestimate oppression. Professor Narayanan will discuss "The Limits of the Quantitative Approach to Discrimination” as part of an African American Studies lecture series on March 28.
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CITP Graduate Student Sayash Kapoor Discusses E-Waste at University of the Arts London Event

Kapoor spoke at the March 1 virtual Climate Emergency Network event, "Entangled Futures: One Scroll from E-Waste," about how "the immateriality of artificial intelligence and machine learning technologies and data" contribute to environmental waste.
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CITP Fellow Orestis Papakyriakopoulos' Paper About Google Image Algorithm Published in Social Science Computer Review

Papakyriakopoulos' research into the Google algorithm involved an audit of more than 40,000 faces of various ages and races. He found that the algorithm generated positive descriptions of white men, while stereotyping women and non-white individuals.
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CITP Fellow Sergey Sanovich Featured Twice in Grid News Stories

In a Feb. 25 Grid article, Sanovich discussed disinformation as a part of Russia's strategy in its war against Ukraine. And, in a March 1 story, Grid cited Sanovich's 2018 research on how authoritarian regimes restrict social media.
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CITP Associated Faculty Ruha Benjamin Discusses Assertions of "Neutrality" in Tech at UC Santa Cruz

Professor Benjamin, the keynote speaker at UC Santa Cruz's 38th annual Martin Luther King Jr. Memorial Convocation, discussed how asserting that technologies like motion sensors or facial recognition systems used at the U.S.-Mexico border are neutral can obscure oppressive practices.
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Upcoming Virtual Events

CITP Seminar

There will be no seminar today, due to the Spring Break.

CITP Seminar

Kristian Lum – Closer Than They Appear: A Bayesian Perspective on Individual-level Heterogeneity in Risk Assessment
Using Bayesian hierarchical models applied to a large longitudinal dataset from the court system, we analyze variation in individual-level probabilities of failing to appear for court.
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CITP Seminar

Jaime Fernández Fisac – Emergent Manipulative Behavior in Language Agents
Through continued interactions with many millions of users, these systems could quickly learn to produce statements that are highly likely to elicit the desired human response, belief or action. That is, these systems will reliably say whatever they need to say to.
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CITP Seminar

Emily Denton – Data, Power, and AI Ethics: Critiquing and Rethinking Machine Learning Data Infrastructure
In response to growing concerns of bias, discrimination, and unfairness perpetuated by algorithmic systems, the datasets used to train and evaluate machine learning models have come under increased scrutiny.
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