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Aleksandra Korolova
@korolova
Assistant Professor @PrincetonCS, @PrincetonSPIA, @PrincetonCITP. Work on AI auditing, privacy & fairness. Past: @USCViterbi @Snap @Google @Stanford @MIT
New York, NY and Princeton, NJ
korolova.com
Joined May 2009
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  • Pinned
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    Aleksandra Korolova
    @korolova
    Feb 13
    Honored to be selected and looking forward to serving with so many amazing experts.
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    UN Office for Digital and Emerging Technologies
    @ODET_UN
    Feb 13
    Meet the Members of the Independent International Scientific Panel on AI. ✨ Forty experts from around the world coming together to put science at the core of international AI efforts. Learn more: tinyurl.com/ai-panel-membe…
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    Aleksandra Korolova
    @korolova
    Apr 9, 2021
    Facebook’s ad delivery algorithms have been known to introduce bias and create echo chambers for job, housing and politics ads for several years. Our latest research shows that for job ad delivery, Facebook’s algorithms are not merely biased, but discriminatory under US law. 🧵
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    Aleksandra Korolova
    @korolova
    Apr 17, 2024
    Meta AI claims to have a child in a NYC public school and share their child's experience with the teachers! The reply is in response to a question looking for personal feedback in a private Facebook group for parents. Also, Meta's algorithm ranks it as the top comment! @AIatMeta
    184K
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    Aleksandra Korolova
    @korolova
    Apr 9, 2021
    Replying to @korolova
    8/ Our paper ant.isi.edu/datasets/addel… and presentation youtube.com/watch?v=pynLRE… will appear later this month @TheWebConf.
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    Aleksandra Korolova
    @korolova
    Apr 9, 2021
    Replying to @korolova
    7/ Our work shows that despite commitments in response to prior studies, settlements, & a civil rights audit, Facebook hasn't made visible progress in addressing discrimination in its ad delivery algorithms; and calls for meaningful algorithmic transparency to be mandated by law.
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    Aleksandra Korolova
    @korolova
    Apr 9, 2021
    Replying to @korolova
    2/ We develop a new auditing methodology to distinguish between skew introduced by job ad delivery algorithms that may be explainable by differences in qualifications (permissible by law) from skew due to factors such as the ad platform’s optimization for its business objectives.
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    Aleksandra Korolova
    @korolova
    Feb 20, 2024
    Honored to become a 2024 Sloan Research Fellow. Deeply grateful to my incredible collaborators and students who made the research possible, and to my family, mentors and colleagues at @Princeton and @USCViterbi for their unwavering support. #SloanFellow
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    Sloan Foundation
    @SloanFoundation
    Feb 20, 2024
    We have today announced the names of the 2024 Sloan Research Fellows! Congratulations to these 126 outstanding early-career researchers: sloan.org/fellowships/20…
    20K
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    Aleksandra Korolova
    @korolova
    Apr 9, 2021
    Replying to @korolova
    4/ We apply our methodology to Facebook and LinkedIn using neutral job ads for delivery drivers, software engineers, and sales associates, and find a statistically significant skew in delivery by gender in Facebook’s case for all three job categories.
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    Aleksandra Korolova
    @korolova
    Apr 9, 2021
    Replying to @korolova
    6/ Although there may be a debate about allocating responsibility for discrimination between advertiser and platform when the advertiser asks to optimize for clicks, the responsibility for any discrimination observed in “reach” ads rests on the ad platform.
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    Aleksandra Korolova
    @korolova
    Apr 9, 2021
    Replying to @korolova
    3/ The idea is to simultaneously run ads for jobs with identical qualifications but skewed gender distributions in reality. The pairing controls for factors such as competition from other advertisers, allowing to isolate the role of the delivery algorithm in reproducing biases.
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    Aleksandra Korolova
    @korolova
    Apr 9, 2021
    Replying to @korolova
    5/ The gender skew in delivery persists even when an advertiser chooses to optimize for “reach”, i.e. aims to show their job ad to a broad audience, rather than only to the people likely to click it.
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    Aleksandra Korolova
    @korolova
    Jun 14, 2023
    Our new @FAccTConference paper “Discrimination through Image Selection by Job Advertisers on Facebook”. We investigate prevalence of a new means for discrimination in job advertising – through the disproportionate representation of people of certain demographics in job ad images.
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    Aleksandra Korolova
    @korolova
    Dec 10, 2019
    We show that Facebook’s ad delivery algorithms hinder political campaigns’ ability to reach diverse voters, impose differential pricing, and contribute to the creation of informational filter bubbles. arxiv.org/abs/1912.04255 w/ @lukshmichowk @sapiezynski @amislove & @aaronkbr
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    arxiv.org
    Ad Delivery Algorithms: The Hidden Arbiters of Political Messaging
    Political campaigns are increasingly turning to digital advertising to reach voters. These platforms empower advertisers to target messages to platform users with great precision, including...
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    Aleksandra Korolova
    @korolova
    Nov 3, 2017
    Our research calling for transparency of Apple's differential privacy eng arxiv.org/abs/1709.02753, publicized by @Wired, @EFF effects change images.apple.com/privacy/docs/D…
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    arxiv.org
    Privacy Loss in Apple's Implementation of Differential Privacy...
    In June 2016, Apple announced that it will deploy differential privacy for some user data collection in order to ensure privacy of user data, even from Apple. The details of Apple's approach...