ΑΙhub.org
 

The Good Robot Podcast: Featuring Shannon Vallor


by
13 March 2024



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, Shannon Vallor talks about feminist care ethics, techno-virtues and vices, and the ‘AI Mirror’.

Shannon Vallor on feminist care ethics, techno-virtues and vices, and the ‘AI Mirror’

In this episode we chat to Shannon Vallor, the Baillie Gifford professor in the ethics and data of AI at the University of Edinburgh and the Director for the Centre for Technomoral Futures. We talk about feminist care ethics; technologies, vices and virtues; why Aristotle believed that the people who make technology should be excluded from citizenship; and why we still don’t have the kinds of robots that we imagined that we’d have in the early 2000s. We also discuss Shannon’s new book, The AI Mirror, which is now available for pre-order.

Listen to the episode here:

Professor Shannon Vallor is the Baillie Gifford Chair in the Ethics of Data and Artificial Intelligence at the Edinburgh Futures Institute (EFI) at the University of Edinburgh, where she is also appointed in Philosophy. She is Director of the Centre for Technomoral Futures in EFI, and co-Director of the BRAID (Bridging Responsible AI Divides) programme, funded by the Arts and Humanities Research Council. Professor Vallor’s research explores how new technologies, especially AI, robotics, and data science, reshape human moral character, habits, and practices. Her work includes advising policymakers and industry on the ethical design and use of AI. She is a standing member of the One Hundred Year Study of Artificial Intelligence (AI100) and a member of the Oversight Board of the Ada Lovelace Institute. Professor Vallor received the 2015 World Technology Award in Ethics from the World Technology Network and the 2022 Covey Award from the International Association of Computing and Philosophy. She is a former Visiting Researcher and AI Ethicist at Google.

Find the episode reading list here.

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 :



Identifying patterns in insect scents using machine learning

  19 Dec 2025
Scientists will use machine learning to predict what types of molecules interact with insect olfactory receptors.

2025 AAAI / ACM SIGAI Doctoral Consortium interviews compilation

  18 Dec 2025
We collate our interviews with the 2025 cohort of doctoral consortium participants.

A backlash against AI imagery in ads may have begun as brands promote ‘human-made’

  17 Dec 2025
In a wave of new ads, brands like Heineken, Polaroid and Cadbury have started celebrating their work as “human-made”.

AIhub blog post highlights 2025

  16 Dec 2025
As the year draws to a close, we take a look back at some of our favourite blog posts.

Using machine learning to track greenhouse gas emissions

  15 Dec 2025
PhD candidate Julia Wąsala searches for greenhouse gas emissions in satellite data.

AAAI 2025 presidential panel on the future of AI research – video discussion on AGI

  12 Dec 2025
Watch the first in a series of video discussions from AAAI.

The Machine Ethics podcast: the AI bubble with Tim El-Sheikh

Ben chats to Tim about AI use cases, whether GenAI is even safe, the AI bubble, replacing human workers, data oligarchies and more.

Australia’s vast savannas are changing, and AI is showing us how

Improving decision-making for dynamic and rapidly changing environments.



 

AIhub is supported by:






 












©2025.05 - Association for the Understanding of Artificial Intelligence