Machines that fail us

About Machines that fail us

From educational institutions to healthcare professionals, from employers to governing bodies, artificial intelligence technologies and algorithms are increasingly used to assess and decide upon various aspects of our lives. However, the question arises: are these systems truly impartial and just in their judgments when they read humans and their behaviour? Our answer is that they are not. Despite their purported aim to enhance objectivity and efficiency, these technologies paradoxically harbor systemic biases and inaccuracies, particularly in the realm of human profiling. “Machines That Fail Us” investigates how AI and its errors are impacting on different areas of our society and how different societal actors are negotiating and coexisting with the human rights implications of AI. The "Machines That Fail Us" podcast series hosts the voices of some of the most engaged individuals involved in the fight for a better future with artificial intelligence. The first season of "Machines That Fail Us" has been made possible thanks to a grant provided by the Swiss National Science Foundation (SNSF)’s "Agora" scheme, whereas the second one is supported by the University of St. Gallen’s Communications Department. The podcast is produced by the Media and Culture Research Group at the Institute for Media and Communications Management. Dr. Philip Di Salvo, the main host, works as a researcher and lecturer at the University of St.Gallen.

Publisher

University of St. Gallen, Philip Di Salvo

Category

education · news · technology

Language

en

Explicit

No

First episode

20 Mar 2024

Latest episode

24 Jul 2025

Latest episodes

10 episodes in the feed.

1. 

   24 Jul 2025

   Machines That Fail Us - Season 2, Episode 5: "Heating Algorithms: AI and the Climate Crisis"

   Artificial intelligence promises a smarter future, but at what cost? In this final episode of “Machines That Fail Us”, we take a look at the often-overlooked environmental footprint of AI’s relentless hunger for data and computing power. We discuss these issues with Noman Bashir, the Computing & Climate Impact Fellow at the MIT Climate & Sustainability Consortium and a researcher at the MIT Computer Science & Artificial Intelligence Laboratory.

2. 

   19 Jun 2025

   Machines That Fail Us - Season 2, Episode 4: Creative Machines: Rethinking Art with AI

   Art historian Valentina Tanni explores generative AI's impacts on art, discussing opportunities, challenges, ethical questions, and the future of human-machine collaboration in artistic creation in this interview.

3. 

   15 May 2025

   Machines That Fail Us - Season 2, Episode 3: Who governs AI? Global challenges in addressing harm

   In this episode, we delve into the global push to regulate artificial intelligence, as governments around the world are faced with the challenge to respond to its social and ethical challenges. With a focus on Latin America, Brazil in particular, we discuss how regulators are confronting the risks posed by deepfakes, online misogyny, and copyright violations, among other issues. AI regulation is rapidly becoming a global priority, as policymakers confront the ethical, legal, and societal consequences of increasingly powerful technologies. From misinformation to algorithmic discrimination, the risks posed by AI systems are no longer hypothetical; they are already influencing public discourse and challenging existing legal frameworks. In this episode, we turn our attention to Latin America, with a particular focus on Brazil, to understand how the region is responding to these challenges. These issues are not only technical but deeply social, intersecting with questions of gender, race, and power in digital spaces, and reminding us just how central and consequential AI "errors" can be. The debate currently unfolding in Brazil offers a lens into the broader struggle faced by many countries: how to assert digital sovereignty and protect their populations while keeping pace with a rapidly evolving technological landscape. In particular, we’ll examine how regulation must address some of the most insidious uses and misuses of AI, especially those connected to online misogyny. In this episode of Machines That Fail Us, we dive into this issue with Prof. Mariana Valente, who serves as an assistant professor at the Law School of the University of St. Gallen and is also a director and board member at Brazil’s InternetLab. Valente is a Brazilian lawyer and scholar, her work centers on the intersection of human rights and technology. Over the past decade, she has been actively engaged in research, writing, public speaking, and teaching on gender inequality in digital spaces, with a particular emphasis on online gender-based violence (OGBV) and the corresponding legal frameworks, policy responses, and law enforcement practices.

4. 

   27 Feb 2025

   Machines That Fail Us - Season 2, Episode 2: "Teaching the Machine: The Hidden Work Behind AI’s Intelligence"

   The training and coding of AI systems, particularly generative ones, depend on the work of humans teaching machines how to think. This work includes content moderation and labeling, is often conducted under exploitative conditions in the Global South, and remains hidden from users' view. In this episode, we discuss these issues with Adio Dinika, a Research Fellow at the Distributed AI Research Institute (DAIR), where he investigates the invisible labor behind AI systems and how it reflects the various inequalities within the AI industry. We often perceive AI tools as entirely artificial, if not almost magical. In reality, the effectiveness and reliability of these systems depend significantly on the labor of humans who ensure that generative AI tools, for example, produce responses that are moderated and free from harmful or toxic content. High-quality training data is essential for building a high-performing large language model, and this data is made up of precisely labeled datasets—a task still carried out by human workers. However, this work is predominantly performed by people in the Global South, often under exploitative and unhealthy conditions, and remains largely invisible to end-users worldwide. The roles of these invisible workers, along with the challenges they face, represent some of the most visible signs of inequality within the AI and tech supply chain, yet they remain little discussed. In this episode of Machines That Fail Us, we dive into this issue with Adio Dinika, a Research Fellow at the Distributed AI Research Institute (DAIR), an international research center focused on the social implications of AI, founded by Timnit Gebru. Together with Dr. Dinika, we explore the hidden human labor behind AI systems and the real, human nature of artificial intelligence.

5. 

   30 Jan 2025

   Machines That Fail Us - Season 2, Episode 1: "Artificial Lies and Synthetic Media: How AI Powers Disinformation"

   How is artificial intelligence being used for disinformation purposes? How effective can it be in influencing our reality and political choices? We discuss the rise of synthetic media with Craig Silverman, a reporter for ProPublica who covers voting, platforms, disinformation, and online manipulation, and one of the world’s leading experts on online disinformation. In the first season of Machines That Fail Us, our focus was to explore a fundamental question: what do AI errors reveal about their societal impact and our future with artificial intelligence? Through engaging discussions with global experts from journalism, activism, entrepreneurship, and academia, we examined how AI and its shortcomings are already influencing various sectors of society. Alongside analyzing present challenges, we envisioned strategies for creating more equitable and effective AI systems. As artificial intelligence becomes increasingly integrated into our lives, we decided to expand these conversations in the new season, delving into additional areas where machine learning, generative AI, and their societal effects are making a significant mark. This season begins by examining AI's role in the spread of misinformation, disinformation, and the ways generative AI has been used to orchestrate influence campaigns. Are we unknowingly falling victim to machine-generated falsehoods? With 2024 being a record year for global elections, we will explore the extent to which AI-driven disinformation has shaped democratic processes. Has it truly had an impact, and if so, how? In this episode, we are joined by Craig Silverman, an award-winning journalist, author, and one of the foremost authorities on online disinformation, fake news, and digital investigations. Currently reporting for ProPublica, Craig specializes in topics such as voting, disinformation, online manipulation, and the role of digital platforms.

6. 

   4 Jul 2024

   Machines That Fail Us #5: "The shape of AI to come"

   The AI we have built so far comes with many different shortcomings and concerns. At the same time, the AI tools we have today are the product of specific technological cultures and business decisions. Could we just do AI differently? For the final episode of “Machines That Fail Us”, we are joined by a leading expert on the intersection of emerging technology, policy, and rights. With Frederike Kaltheuner, founder of the consulting firm new possible and a Senior Advisor to the AI NOW institute, we discussed the shape of future AI and of our life with it.

7. 

   13 Jun 2024

   Machines That Fail Us #4: Building different AI futures

   We don’t necessarily have to build artificial intelligence the way we’re doing it today. To make AI really inclusive we must look beyond Western techno-cultures and beyond our understanding of technology being either utopian or dystopian. How could our AI future look different? We asked Prof. Payal Arora, a Professor of Inclusive AI Cultures at Utrecht University.

8. 

   16 May 2024

   Machines That Fail Us #3 Errors and biases: tales of algorithmic discrimination

   The records of biases, discriminatory outcomes, and errors as well as the societal impacts of artificial intelligence systems is now widely documented. However, the question remains: How is the struggle for algorithmic justice evolving? We asked Angela Müller, Executive Director of AlgorithmWatch Switzerland.

9. 

   18 Apr 2024

   Machines That Fail Us #2: Following the AI beat – algorithms making the news

   What’s the role of journalism in making sense of AI and its errors? With Melissa Heikkilä, senior reporter at the MIT Technology Review. Host: Dr. Philip Di Salvo.

10. 

    20 Mar 2024

    Machines That Fail Us #1: Making sense of the human error of AI

    What are the errors that artificial intelligence systems can make and what’s their impact on humans? The Human Error Project team discusses the results of their own research into AI errors and algorithmic profiling.

Reach and audience

Public platform figures. Ratings count people who left a rating, not total listeners.

Spotify

5.0 / 5

1 ratings

Podcast Authority Score: 14 / 100

A composite of feed quality, social presence, YouTube performance and engagement. Read the methodology.

Quality

14

Social presence

0

YouTube

0

Engagement

32

Contact Machines that fail us

Guest appearances

Does not typically book guests

Based on episode analysis; this does not confirm that the show is currently accepting guests.