The Team

Below is last year’s executive team. We are currently recruiting for a new executive team. At this moment, please get in touch with Suny or email president@oxai.org only if you are interested in a leadership role

Team member

Adhithya

Team member

Elle

Team member

Tiffany Horter

AI Labs

OxAI Labs is a student-led research organisation, focused on ML fairness. We do impactful research, while helping students develop AI research skills.

Join our labs team to collaborate on hands on AI projects. We organise projects for all levels, from novice to pro, and welcome people from all academic backgrounds..

Applications

We have not yet started recruiting for our AI research projects. Please follow us on facebook and sign up to the mailing list so you hear when we start recruiting!

Labs Academic Publications:

  • VISOGENDER: A dataset for benchmarking gender bias in image-text pronoun resolution

    S. M. Hall, F. G. Abrantes, H. Zhu, G. Sodunke, A. Shtedritski and H. R. Kirk. (2023) NeurIPS Datasets and Benchmarks 2023

    Read the paper

  • Bias Out-of-the-Box: An Empirical Analysis of Intersectional Occupational Biases in Popular Generative Language Models.

    Kirk, H. R., Jun, Y., Volpin, F., Iqbal, H., Benussi, E., Dreyer, F., Shtedritski, A., & Asano, Y. (2021). Advances in Neural Information Processing Systems, 34, 2611–2624.

    Read the paper

  • Balancing the Picture: Debiasing Vision-Language Datasets with Synthetic Contrast Sets

    B. Smith, M. Farinha, S. M. Hall, H. R. Kirk, A.Shtedritski, M. Bain (2023) NeurIPS workshop SyntheticData4ML

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  • A Prompt Array Keeps the Bias Away: Debiasing Vision-Language Models with Adversarial Learning.

    Berg, H., Hall, S. M., Bhalgat, Y., Yang, W., Kirk, H. R., Shtedritski, A., & Bain, M. (2022). Proceedings of AACL - IJCNLP

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  • Memes in the wild: Assessing the generalizability of the hateful memes challenge dataset.

    Kirk, H., Jun, Y., Rauba, P., Wachtel, G., Li, R., Bai, X., Broestl, N., Doff-Sotta, M., Shtedritski, A., & Asano, Y. M. (2021). Proceedings of the 5th Workshop on Online Abuse and Harms (WOAH 2021), 26–35.

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  • Privacy-Preserving Object Detection. Synthetic Data Generation Workshop (ICLR)

    He, P., Griffin, C., Kacprzyk, K., Joosen, A., Collyer, M., Shtedritski, A., & Asano, Y. M. (2021). ICLR Workshop on Syntetic Data Generation

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  • Looking for a Handsome Carpenter! Debiasing GPT-3 Job Advertisements.

    Borchers, C., Gala, D., Gilburt, B., Oravkin, E., Bounsi, W., Asano, Y. M., & Kirk, H. (2022). Proceedings of the 4th Workshop on Gender Bias in Natural Language Processing.

    Read the paper