“Machines That Fail Us”, Episode 5: The shape of AI to come

The “Machines That Fail Us” podcast series tried to make sense of why AI systems and algorithms are prone to errors and to problematic outcomes, analyzing what AI errors are and what do they express about the nature and possibilities of such machines. Looking at these errors has been particularly interesting for analyzing what these machines really are and what they can really do, as errors can serve as magnifying lens for shedding light on how AI and algorithmic systems make sense of humans and reality. After looking at the present, with the last two episodes of the podcast we tried to make sense of the future.

First, we start by discussing ways for making AI global and diverse by looking at different techno-cultures and perspectives from the Global South. Today, in the final episode of the series, we discuss what alternatives may look like and what should be put in action to concretely build them, starting from alternative data and business approaches than those of Big Tech. We close the “Machines That Fail Us” podcast series with Frederike Kaltheuner, founder of the consulting firm new possible, a Senior Advisor to the AI NOW institute and one of the leading experts on the intersection of emerging technology, policy, and rights.

“Machines That Fail Us” #5 | The shape of AI to come

The “Machines That Fail Us” podcast is made possible thanks to a grant provided by the Swiss National Science Foundation (SNSF)’s “Agora” scheme. The podcast is produced by The Human Error Project Team in cooperation with the Communication office of the Universität St. Gallen (HSG) and postproduction is curated by Podcastschimiede. Philip Di Salvo, who works as researcher and lecturer in the HSG’s Institute for Media and Communications Management and is part of The Human Error Project since 2022, will be the main host of the podcast. Episodes will be released on the HSG website, on The Human Error Project website and all major audio and podcasting platforms.