8 citations · 17 across the 4 of their papers we have counts for
5 papers
Why human-AI relationships need socioaffective alignment
Hannah Rose Kirk, Iason Gabriel, Chris Summerfield +2
Humans strive to design safe AI systems that align with our goals and remain under our control. However, as AI capabilities advance, we face a new challenge: the emergence of deepe…
Is More Data Better? Re-thinking the Importance of Efficiency in Abusive Language Detection with Transformers-Based Active Learning
Hannah Rose Kirk, Bertie Vidgen, Scott A. Hale
Annotating abusive language is expensive, logistically complex and creates a risk of psychological harm. However, most machine learning research has prioritized maximizing effectiv…
Looking for a Handsome Carpenter! Debiasing GPT-3 Job Advertisements
Conrad Borchers, Dalia Sara Gala, Benjamin Gilburt +4
The growing capability and availability of generative language models has enabled a wide range of new downstream tasks. Academic research has identified, quantified and mitigated b…
Memes in the Wild: Assessing the Generalizability of the Hateful Memes Challenge Dataset
Hannah Rose Kirk, Yennie Jun, Paulius Rauba +7
Hateful memes pose a unique challenge for current machine learning systems because their message is derived from both text- and visual-modalities. To this effect, Facebook released…
Bias Out-of-the-Box: An Empirical Analysis of Intersectional Occupational Biases in Popular Generative Language Models
Hannah Kirk, Yennie Jun, Haider Iqbal +5
The capabilities of natural language models trained on large-scale data have increased immensely over the past few years. Open source libraries such as HuggingFace have made these…