A new auditing framework measures how much of the public's submitted viewpoints is lost in AI-generated consultation summaries, finding that official summaries represent the population worse than a random set of participants and that critical voices are most likely excluded.
Proceedings of the 2021 ACM conference on fairness, accountability, and transparency , pages=
6 Pith papers cite this work. Polarity classification is still indexing.
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Audit of ChatGPT, Copilot, Gemini and Perplexity finds ~16% of cited sources are AI-generated across 712 queries on politics, health and environment.
Proposes a three-level taxonomy of Cultural Awareness, Cultural Sensitivity, and Cultural Competence for AI evaluation, grounded in intercultural communication scholarship to improve validity in multicultural contexts.
WeatherSyn is the first instruction-tuned MLLM for weather forecasting report generation, outperforming closed-source models on a new dataset of 31 US cities across 8 weather aspects.
REGLU guides LoRA-based unlearning via representation subspaces and orthogonal regularization to outperform prior methods on forget-retain trade-off in LLM benchmarks.
The study adapts ecological diversity measures to evaluate platial representations in GPT and DALL-E images, finding low diversity, greater gains from prompt revision than generation, and stereotypical feature use.
citing papers explorer
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Participatory provenance as representational auditing for AI-mediated public consultation
A new auditing framework measures how much of the public's submitted viewpoints is lost in AI-generated consultation summaries, finding that official summaries represent the population worse than a random set of participants and that critical voices are most likely excluded.
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Synthetic Sources?: Auditing Generative Search Engine Citations for Evidence of AI-Generated Sources
Audit of ChatGPT, Copilot, Gemini and Perplexity finds ~16% of cited sources are AI-generated across 712 queries on politics, health and environment.
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Defining Cultural Capabilities for AI Evaluation: A Taxonomy Grounded in Intercultural Communication Theory
Proposes a three-level taxonomy of Cultural Awareness, Cultural Sensitivity, and Cultural Competence for AI evaluation, grounded in intercultural communication scholarship to improve validity in multicultural contexts.
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WeatherSyn: An Instruction Tuning MLLM For Weather Forecasting Report Generation
WeatherSyn is the first instruction-tuned MLLM for weather forecasting report generation, outperforming closed-source models on a new dataset of 31 US cities across 8 weather aspects.
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Representation-Guided Parameter-Efficient LLM Unlearning
REGLU guides LoRA-based unlearning via representation subspaces and orthogonal regularization to outperform prior methods on forget-retain trade-off in LLM benchmarks.
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Assessing the Geographic Diversity of AI's Platial Representations in Image Generation
The study adapts ecological diversity measures to evaluate platial representations in GPT and DALL-E images, finding low diversity, greater gains from prompt revision than generation, and stereotypical feature use.