Why do we find it easier to trust some concepts and ideas over others? Mathematician Adam Kucharski explores the science of uncertainty, revealing how the very human need for explanation shapes trust in science, fear of technology and belief in conspiracy theories.For a chance to give your own TED Talk, fill out the Idea Search Application: ted.com/ideasearch.Interested in learning more about upcoming TED events? Follow these links:TEDNext: ted.com/futureyouTEDSports: ted.com/sportsTEDAI Vienna: ted.com/ai-viennaTEDAI San Francisco: ted.com/ai-sf Hosted on Acast. See acast.com/privacy for more information.
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You're listening to TED Talks Daily, where we bring you new ideas and conversations to spark your curiosity every day. I'm your host, Elise Hu. Where do conspiracy theories come from and how do they spread? For mathematician Adam Kucharski, this question is key, especially as we navigate a world full of complex and overwhelming things, from climate and health to AI.
In his talk, he shares why he finds comfort in leaning into the unknown, but asks us to consider why it's crucial that we find better ways to trust the things we cannot explain and to explain the things that we do not trust.
It's not easy to explain why aeroplanes stay in the sky. A common explanation is that the curved shape of the wing makes air flow faster above and slower beneath, creating lift. But this doesn't explain how planes can fly upside down. Another explanation is that the angle of the wing pushes air downwards, creating an equal and opposite upwards force.
But this doesn't explain why, as the angle gets slightly steeper, planes can suddenly stall. The point is, aerodynamics is complex. It's difficult to understand, let alone explain in a simple, intuitive way. And yet, we trust it. And the same is true of so many other useful technologies in our lives. The idea of heart defibrillation has been around since 1899.
But researchers are still working to untangle the biology and physics that means an electric shock can reset a heart. Then there's general anesthesia. We know what combination of drugs will make a patient unconscious, but it's still not entirely clear exactly why they do. And yet, you'd probably still get the operation, just like you'd still take that flight. For a long time,
This lack of explanation didn't really bother me. Throughout my career as a mathematician, I've worked to separate truth from fiction, whether investigating epidemics or designing new statistical methods. But the world is complicated, and that's something I'd become comfortable with.
For example, if we want to know whether a new treatment is effective against a disease, we can run a clinical trial to get the answer. It won't tell us why the treatment works, but it will give us the evidence we need to take action. So I found it interesting that in other areas of life, a lack of explainability does visibly bother people. Take AI.
One of the concerns about autonomous machines like self-driving cars is we don't really understand why they make the decisions they do. There will be some situations where we can get an idea of why they make mistakes. Last year, a self-driving car blocked off a fire truck responding to an emergency in Las Vegas. The reason?
The fire truck was yellow, and the car had been trained to recognize red ones. But even if the car had been trained to recognize yellow fire trucks, it wouldn't go through the same thought process we do when we see an emergency vehicle. Self-driving AI views the world as a series of shapes and probabilities.
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