ΑΙhub.org
 

The Good Robot Podcast: featuring Arjun Subramonian


by
20 January 2023



share this:
Space scene with words Good Robot Podcast

Hosted by Eleanor Drage and Kerry Mackereth, The Good Robot is a podcast which explores the many complex intersections between gender, feminism and technology. In this episode, Eleanor and Kerry talk to Arjun Subramonian on queer approaches to AI and computing.

Arjun Subramonian on queer approaches to AI and computing

In this episode we talk to Arjun Subramonian, a Computer Science PhD student at UCLA conducting machine learning research and a member of the grassroots organisation Queer in AI. In this episode we discuss why they joined Queer in AI, how Queer in AI is helping build artificial intelligence directed towards better, more inclusive, and queer futures, why ‘bias’ cannot be seen as a purely technical problem, and why Queer in AI rejected Google sponsorship.

Listen to the episode here:

For the reading list and transcript for this episode, visit The Good Robot website.

Arjun Subramonian (pronouns: they/them) is a brown queer, agender PhD student at the University of California, Los Angeles. Their research focuses on graph representation learning, fairness, and machine learning (ML) ethics. They’re a core organizer of Queer in AI, co-founded QWER Hacks, and teach machine learning and AI ethics at Title I schools in LA. They also love to run, hike, observe and document wildlife, and play the ukulele.

About The Good Robot Podcast

Dr Eleanor Drage and Dr Kerry Mackereth are Research Associates at the Leverhulme Centre for the Future of Intelligence, where they work on the Mercator-Stiflung funded project on Desirable Digitalisation. Previously, they were Christina Gaw Postdoctoral Researchers in Gender and Technology at the University of Cambridge Centre for Gender Studies. During the COVID-19 pandemic they decided to co-found The Good Robot Podcast to explore the many complex intersections between gender, feminism and technology.




The Good Robot Podcast




            AIhub is supported by:


Related posts :



Optimizing LLM test-time compute involves solving a meta-RL problem

  20 Jan 2025
By altering the LLM training objective, we can reuse existing data along with more test-time compute to train models to do better.

Generating a biomedical knowledge graph question answering dataset

  17 Jan 2025
Introducing PrimeKGQA - a scalable approach to dataset generation, harnessing the power of large language models.

The Machine Ethics podcast: 2024 in review with Karin Rudolph and Ben Byford

Karin Rudolph and Ben Byford talk about 2024 touching on the EU AI Act, agent-based AI and advertising, AI search and access to information, conflicting goals of many AI agents, and much more.

Playbook released with guidance on creating images of AI

  15 Jan 2025
Archival Images of AI project enables the creation of meaningful and compelling images of AI.

The Good Robot podcast: Lithium extraction in the Atacama with Sebastián Lehuedé

  13 Jan 2025
Eleanor and Kerry chat to Sebastián Lehuedé about data activism, the effects of lithium extraction, and the importance of reflexive research ethics.

Interview with Erica Kimei: Using ML for studying greenhouse gas emissions from livestock

  10 Jan 2025
Find out about work that brings together agriculture, environmental science, and advanced data analytics.

TELL: Explaining neural networks using logic

  09 Jan 2025
Alessio and colleagues have developed a neural network that can be directly transformed into logic.




AIhub is supported by:






©2024 - Association for the Understanding of Artificial Intelligence


 












©2021 - ROBOTS Association