ΑΙhub.org
 

The Machine Ethics Podcast: Ethics of digital worlds with Richard Bartle


by
12 April 2022



share this:

Richard Bartle
Hosted by Ben Byford, The Machine Ethics Podcast brings together interviews with academics, authors, business leaders, designers and engineers on the subject of autonomous algorithms, artificial intelligence, machine learning, and technology’s impact on society.

Ethics of digital worlds

Richard Bartle joins us again after his appearance on episode 65 to chat about the metaverse, different ways to design AI controlled NPC, the lack of progress of AI in games, ethical considerations of games designers, ethics of AI life, virtualism, ‘smart’ AI, robot rights and more…

Listen to the episode here:

Dr Richard A. Bartle is Honorary Professor of Computer Game Design at the University of Essex, UK. He is best known for having co-written in 1978 the first virtual world, MUD, the progenitor of the £30bn Massively-Multiplayer Online Role-Playing Game industry. His 1996 Player Types model has seen widespread adoption by MMO developers and the games industry in general. His 2003 book, Designing Virtual Worlds, is the standard text on the subject, and he is an influential writer on all aspects of MMO design and development. In 2010, he was the first recipient of the prestigious Game Developers’ Conference Online Game Legend award.


About The Machine Ethics podcast

This podcast was created, and is run by, Ben Byford and collaborators. Over the last few years the podcast has grown into a place of discussion and dissemination of important ideas, not only in AI but in tech ethics generally.

The goal is to promote debate concerning technology and society, and to foster the production of technology (and in particular: decision making algorithms) that promote human ideals.

Ben Byford is a AI ethics consultant, code, design and data science teacher, freelance games designer with over 10 years of design and coding experience building websites, apps, and games. In 2015 he began talking on AI ethics and started the Machine Ethics podcast. Since then, Ben has talked with academics, developers, doctors, novelists and designers about AI, automation and society.

Join in the conversation with us by getting in touch via email here or following us on Twitter and Instagram.




The Machine Ethics Podcast

            AIhub is supported by:



Subscribe to AIhub newsletter on substack



Related posts :

What I’ve learned from 25 years of automated science, and what the future holds: an interview with Ross King

  30 Mar 2026
We launch our new series with a conversation with Ross King - a pioneer in the field of AI-enabled scientific discovery.

A multi-armed robot for assisting with agricultural tasks

and   27 Mar 2026
How can a robot safely manipulate branches to reveal hidden flowers while remaining aware of interaction forces and minimizing damage?

Resource-constrained image generation and visual understanding: an interview with Aniket Roy

  26 Mar 2026
Aniket tells us about his research exploring how modern generative models can be adapted to operate efficiently while maintaining strong performance.

RWDS Big Questions: how do we highlight the role of statistics in AI?

  25 Mar 2026
Next in our series, the panel explores the statistical underpinning of AI.

A history of RoboCup with Manuela Veloso

  24 Mar 2026
Find out how RoboCup got started and how the competition has evolved, from one of the co-founders.

Information-driven design of imaging systems

  23 Mar 2026
Framework that enables direct evaluation and optimization of imaging systems based on their information content.

Machine learning framework to predict global imperilment status of freshwater fish

  20 Mar 2026
“With our model, decision makers can deploy resources in advance before a species becomes imperiled.”

Interview with AAAI Fellow Yan Liu: machine learning for time series

  19 Mar 2026
Hear from 2026 AAAI Fellow Yan Liu about her research into time series, the associated applications, and the promise of physics-informed models.



AIhub is supported by:







Subscribe to AIhub newsletter on substack




 















©2026.02 - Association for the Understanding of Artificial Intelligence