2 citations · 2 across the 2 of their papers we have counts for
5 papers
"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…
Funding AI for Good: A Call for Meaningful Engagement
Hongjin Lin, Anna Kawakami, Catherine D'Ignazio +2
Artificial Intelligence for Social Good (AI4SG) is a growing area that explores AI's potential to address social issues, such as public health. Yet prior work has shown limited evi…
AI Failure Loops in Devalued Work: The Confluence of Overconfidence in AI and Underconfidence in Worker Expertise
Anna Kawakami, Jordan Taylor, Sarah Fox +2
A growing body of literature has focused on understanding and addressing workplace AI design failures. However, past work has largely overlooked the role of the devaluation of work…
Do Responsible AI Artifacts Advance Stakeholder Goals? Four Key Barriers Perceived by Legal and Civil Stakeholders
Anna Kawakami, Daricia Wilkinson, Alexandra Chouldechova
The responsible AI (RAI) community has introduced numerous processes and artifacts (e.g., Model Cards, Transparency Notes, Data Cards) to facilitate transparency and support the go…
Studying Up Public Sector AI: How Networks of Power Relations Shape Agency Decisions Around AI Design and Use
Anna Kawakami, Amanda Coston, Hoda Heidari +2
As public sector agencies rapidly introduce new AI tools in high-stakes domains like social services, it becomes critical to understand how decisions to adopt these tools are made…