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Found 5 papers, 1 papers with code
Amplify Initiative: Building A Localized Data Platform for Globalized AI
This dataset in turn can be used to evaluate models for their safety and cultural relevance within the context of these languages.
Socially Responsible Data for Large Multilingual Language Models
There is growing interest in multilingual LLMs, and various efforts are striving for models to accommodate languages of communities outside of the Global North, which include many languages that have been historically underrepresented in digital realms.
A Toolbox for Surfacing Health Equity Harms and Biases in Large Language Models
Our contributions include a multifactorial framework for human assessment of LLM-generated answers for biases, and EquityMedQA, a collection of seven datasets enriched for adversarial queries.
The Equitable AI Research Roundtable (EARR): Towards Community-Based Decision Making in Responsible AI Development
This paper reports on our initial evaluation of The Equitable AI Research Roundtable -- a coalition of experts in law, education, community engagement, social justice, and technology.
Closing the AI Accountability Gap: Defining an End-to-End Framework for Internal Algorithmic Auditing
Rising concern for the societal implications of artificial intelligence systems has inspired a wave of academic and journalistic literature in which deployed systems are audited for harm by investigators from outside the organizations deploying the algorithms.
Computers and Society
