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 Tha
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Signup to Generate a PitchFrom 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.
Recent episodes include "Machines That Fail Us - Season 2, Episode 5: "Heating Algorithms: AI and the Climate Crisis"" (24 July 2025, 32 minutes), "Machines That Fail Us - Season 2, Episode 4: Creative Machines: Rethinking Art with AI" (19 June 2025, 30 minutes), and "Machines That Fail Us - Season 2, Episode 3: Who governs AI? Global challenges in addressing harm" (15 May 2025, 33 minutes).
Machines that fail us publishes roughly monthly, with episodes averaging 32 minutes across 10 episodes.
Booking probability for Machines that fail us is 18%, and the host is rated Selective on guests. Machines that fail us requires a Pod Score of 80 or higher. Machines that fail us's contact route on record: verified email.
The strongest fits for Machines that fail us are IT Services & Software Development and Scientific Research & Development. Machines that fail us has an education audience.
Machines that fail us is an education podcast with 10 episodes published.
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Episode #5
<p>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...
<p>In this episode, we deal with the impacts of generative AI on art and aestethics, looking at how the rise and commercial success of tools such as Dall-E, Midjourney, and Sora have raised profound questions in the art...
Episode #3
<p>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...
<p>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...
<p >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...
<p>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...
<p>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...
<p>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...
<p>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.</p>
<p >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...
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