<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 utopian or dystopian. How could our AI future look different? We asked Prof. Payal Arora, a Professor of Inclusive AI Cultures at Utrecht University. </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 utopian or dystopian. How could our AI future look different? We asked Prof. Payal Arora, a Professor of Inclusive AI Cultures at Utrecht University.

Machines That Fail Us #4: Building different AI futures

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.

News

Technology

Education

Tech News

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.

Share Machines That Fail Us #4: Building different AI futures

Sign up to save your podcasts

Machines That Fail Us #4: Building different AI futures

Machines That Fail Us #4: Building different AI futures