About

Hi! I’m Eddie, I use he/they pronouns. I hold a Bachelors in Linguistics and a Masters in Psychological Sciences. I developed an interest in algorithmic fairness during my three years working at a digital marketing agency.

I have been able to pursue this interest at post-graduate level thanks to the Centre for Doctoral Training in NLP at the University of Edinburgh, where I am supervised by Björn Ross, Vaishak Belle and Zachary Horne.

My work addresses the public response to biased NLP technologies, my motivation being that it is only by understanding how those impacted by these technologies behave that we can develop suitable bias mitigation methods. My interests also lie in developing less biased models, and in the robustness of bias measurement methods. I consider my thesis to constitute an enquiry into the harms of language technologies, informed by the social sciences. On this blog you will find posts spanning my range of interests.

You can read my published work here:
❤️ A Robust Bias Mitigation Procedure Based on the Stereotype Content Model Read my TL;DR here
💛 Potential Pitfalls With Automatic Sentiment Analysis: The Example of Queerphobic Bias Read my TL;DR here
💚 This Prompt is Measuring MASK: Evaluating Bias Evaluation in Language Models Read my TL;DR here
💙 Stereotypes and Smut: The Misrepresentation of Non-cisgender Identities by Text-to-Image Models
💜 Typology of Risks of Generative Text-to-Image Models

You can also read about my work here:
Blog post on bias in sentiment analysis which draws on my paper
Interview with Queer in AI about transphobia in text-to-image models

And listen to me talk here:
Presentation at the Queer in AI workshop on my transphobia in TTI models paper
Presentation at the Controversies in the Data Society Seminar Series where I argue measuring bias (in abstract) is pointless

I took part in a panel discussion at the Scottish AI Summit in March.

I have previously spoken at the Controversies in the Data Society seminar series and the Social Data Science Hub Seminar Series.

If you find my work interesting, consider tipping me here: