Hosted by Unknown Host · 🇺🇸 US · EN · 10 episodes
Established thought leaders with verified media credentials.
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
Unknown Host hosts Machines that fail us, a education show with 10 episodes published.
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
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 wor
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 Amer
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
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
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
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 uto
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 j
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.
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.
Sponsor detection runs nightly. Check back soon.
No public pitch examples yet for this show.
Generate your own personalised pitchBased on semantic analysis of episode topics and host coverage, this show is a strong guest fit for executives in:
Industry fit is computed by PitchCentric using vector embeddings of the show's episode catalog.
Shows with the most semantically similar episode content. Pitch one, pitch all; producers cluster.
Machines that fail us has a verified contact on file. Create a free PitchCentric account to access it and generate a personalised pitch in seconds. Research at least 3 recent episodes first and lead with a specific angle that serves their education audience.
Machines that fail us is hosted by Unknown Host. The show is categorised under education (technology) and has published 10 episodes.
Machines that fail us has published 10 episodes.
Machines that fail us regularly covers education, technology, news. It sits in the education category, with a technology focus.
Machines that fail us is accessible for guests with genuine education expertise. A personalised, episode-aware pitch will still outperform a generic one every time.
Machines that fail us hasn't explicitly signalled guest openness in recent episodes. That doesn't rule out pitching. your hook just needs to be especially compelling and relevant to their recent content.
Episodes of Machines that fail us average 32 minutes. a focused format where a clear narrative arc and tight preparation matter most.
Our data rates Machines that fail us's guest bar at 80/100 (Premium tier). Established thought leaders with verified media credentials. Sign in to PitchCentric to see how your own Pod Score compares against this show.
Methodology. Booking Probability™ blends Listen Score, 30-day Virality, open-to-guests detection, and Apple ratings. Data refreshed every 60 minutes. Listen Score and Booking Probability are calculated by PitchCentric. Last enriched 12 days ago.
