71 citations · 122 across the 8 of their papers we have counts for
8 papers
Reimagining AI in Social Work: Practitioner Perspectives on Incorporating Technology in their Practice
Katie Wassal, Carolyn Ashurst, Jiri Hron +1
There has been a surge in the number and type of AI tools being tested and deployed within both national and local government in the UK, including within the social care sector. Gi…
Identifying and Mitigating Privacy Risks Stemming from Language Models: A Survey
Victoria Smith, Ali Shahin Shamsabadi, Carolyn Ashurst +1
Large Language Models (LLMs) have shown greatly enhanced performance in recent years, attributed to increased size and extensive training data. This advancement has led to widespre…
The Progression of Disparities within the Criminal Justice System: Differential Enforcement and Risk Assessment Instruments
Miri Zilka, Riccardo Fogliato, Jiri Hron +3
Algorithmic risk assessment instruments (RAIs) increasingly inform decision-making in criminal justice. RAIs largely rely on arrest records as a proxy for underlying crime. Problem…
Racial Disparities in the Enforcement of Marijuana Violations in the US
Bradley Butcher, Chris Robinson, Miri Zilka +3
Racial disparities in US drug arrest rates have been observed for decades, but their causes and policy implications are still contested. Some have argued that the disparities large…
Why Fair Labels Can Yield Unfair Predictions: Graphical Conditions for Introduced Unfairness
Carolyn Ashurst, Ryan Carey, Silvia Chiappa +1
In addition to reproducing discriminatory relationships in the training data, machine learning systems can also introduce or amplify discriminatory effects. We refer to this as int…
AI Ethics Statements -- Analysis and lessons learnt from NeurIPS Broader Impact Statements
Carolyn Ashurst, Emmie Hine, Paul Sedille +1
Ethics statements have been proposed as a mechanism to increase transparency and promote reflection on the societal impacts of published research. In 2020, the machine learning (ML…
RAFT: A Real-World Few-Shot Text Classification Benchmark
Neel Alex, Eli Lifland, Lewis Tunstall +9
Large pre-trained language models have shown promise for few-shot learning, completing text-based tasks given only a few task-specific examples. Will models soon solve classificati…
Institutionalising Ethics in AI through Broader Impact Requirements
Carina Prunkl, Carolyn Ashurst, Markus Anderljung +3
Turning principles into practice is one of the most pressing challenges of artificial intelligence (AI) governance. In this article, we reflect on a novel governance initiative by…