51 citations · 53 across the 12 of their papers we have counts for
4 papers · 1 filter
"I want to be pushed, I want to grow": Enabling social workers to design evaluations of LLM augmentation in their work
Anna Kawakami, Chloe Qianhui Zhao, Renee Shelby +3
Workers are increasingly asked to adopt AI systems to assist their work, yet are rarely given a voice in defining what meaningful AI augmentation should look like or how to evaluat…
How Tech Workers Contend with Hazards of Humanlikeness in Generative AI
Mark Díaz, Renee Shelby, Eric Corbett +1
Generative AI's humanlike qualities are driving its rapid adoption in professional domains. However, this anthropomorphic appeal raises concerns from HCI and responsible AI scholar…
Measuring What Matters: Connecting AI Ethics Evaluations to System Attributes, Hazards, and Harms
Shalaleh Rismani, Renee Shelby, Leah Davis +2
Over the past decade, an ecosystem of measures has emerged to evaluate the social and ethical implications of AI systems, largely shaped by high-level ethics principles. These meas…
Taxonomy of User Needs and Actions
Renee Shelby, Fernando Diaz, Vinodkumar Prabhakaran
The growing ubiquity of conversational AI highlights the need for frameworks that capture not only users' instrumental goals but also the situated, adaptive, and social practices t…