Pratyusha Kalluri
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View article: Computer-vision research powers surveillance technology
Computer-vision research powers surveillance technology Open
An increasing number of scholars, policymakers and grassroots communities argue that artificial intelligence (AI) research-and computer-vision research in particular-has become the primary source for developing and powering mass surveillan…
View article: People who share encounters with racism are silenced online by humans and machines, but a guideline-reframing intervention holds promise
People who share encounters with racism are silenced online by humans and machines, but a guideline-reframing intervention holds promise Open
Are members of marginalized communities silenced on social media when they share personal experiences of racism? Here, we investigate the role of algorithms, humans, and platform guidelines in suppressing disclosures of racial discriminati…
View article: AI generates covertly racist decisions about people based on their dialect
AI generates covertly racist decisions about people based on their dialect Open
Hundreds of millions of people now interact with language models, with uses ranging from help with writing 1,2 to informing hiring decisions 3 . However, these language models are known to perpetuate systematic racial prejudices, making th…
View article: Dialect prejudice predicts AI decisions about people's character, employability, and criminality
Dialect prejudice predicts AI decisions about people's character, employability, and criminality Open
Hundreds of millions of people now interact with language models, with uses ranging from serving as a writing aid to informing hiring decisions. Yet these language models are known to perpetuate systematic racial prejudices, making their j…
View article: The Surveillance AI Pipeline
The Surveillance AI Pipeline Open
A rapidly growing number of voices argue that AI research, and computer vision in particular, is powering mass surveillance. Yet the direct path from computer vision research to surveillance has remained obscured and difficult to assess. H…
View article: Easily Accessible Text-to-Image Generation Amplifies Demographic Stereotypes at Large Scale
Easily Accessible Text-to-Image Generation Amplifies Demographic Stereotypes at Large Scale Open
Machine learning models that convert user-written text descriptions into images are now widely available online and used by millions of users to generate millions of images a day. We investigate the potential for these models to amplify da…
View article: When and why vision-language models behave like bags-of-words, and what to do about it?
When and why vision-language models behave like bags-of-words, and what to do about it? Open
Despite the success of large vision and language models (VLMs) in many downstream applications, it is unclear how well they encode compositional information. Here, we create the Attribution, Relation, and Order (ARO) benchmark to systemati…
View article: The Values Encoded in Machine Learning Research
The Values Encoded in Machine Learning Research Open
Machine learning currently exerts an outsized influence on the world, increasingly affecting institutional practices and impacted communities. It is therefore critical that we question vague conceptions of the field as value-neutral or uni…
View article: On the Opportunities and Risks of Foundation Models
On the Opportunities and Risks of Foundation Models Open
AI is undergoing a paradigm shift with the rise of models (e.g., BERT, DALL-E, GPT-3) that are trained on broad data at scale and are adaptable to a wide range of downstream tasks. We call these models foundation models to underscore their…
View article: The Values Encoded in Machine Learning Research
The Values Encoded in Machine Learning Research Open
Machine learning currently exerts an outsized influence on the world, increasingly affecting institutional practices and impacted communities. It is therefore critical that we question vague conceptions of the field as value-neutral or uni…
View article: Learning Controllable Fair Representations
Learning Controllable Fair Representations Open
Learning data representations that are transferable and are fair with respect to certain protected attributes is crucial to reducing unfair decisions while preserving the utility of the data. We propose an information-theoretically motivat…