Machines that fail us

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 MI...

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 world, and especially when it comes to visual arts. AI is reshaping how art is created, experienced, and valued. In this episode, we explore the opportunities and challenges artists f...

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 r...

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 Ins...

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...

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 Kal...

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.

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.

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.