Skip to main content

Sabine Hossenfelder - Five Way Interview

Image © Joerg Steinmetz
Sabine Hossenfelder grew up in Frankfurt, Germany. She has a PhD in physics and is presently a Research Fellow at the Frankfurt Institute for Advanced Studies. Her current work is mostly in the foundation of physics. She has written over 80 research papers on topics ranging from quantum gravity to particle physics, cosmology, astrophysics, statistical mechanics, and quantum foundations. 

Sabine is creator of the popular YouTube channel Science without the gobbledygook. Her first book Lost in Math was published by Basic Books in June 2018. Her writing has been published, amongst others, in Scientific American, New Scientist, The Guardian, Aeon, Nautilus, and the New York Times. Her latest book is Existential Physics: A Scientist's Guide to Life's Biggest Questions.

Why Science?

Because I’m a curious person and science constantly teaches me new things. 

Why this book?

Physics taught us some deep lessons about the nature of time and reality and the limits of science that I think physicists don’t talk about enough. I wanted to tell people what we have learned, but also tell them where physics crosses over into pure speculation. So my book basically demarks the boundary between physics and religion and philosophy.

Why is the distinction between unscientific and ascientific important?

It’s like the distinction between atheist and agnostic. An atheist does not believe that god exists, an agnostic has no opinion about whether god exists or not – it’s a neutral position. We call something unscientific when it does not follow scientific methodology. By ascientific I mean something that science says nothing about. For example, planning your day based on what the horoscope says is unscientific. The idea that other universes exist that we cannot interact with is ascientific. Science can’t tell us whether they exist, but it also can’t tell us that they don’t exist. It’s not unscientific to believe in those other universes.

The distinction matters to me because ascientific ideas I think should have a place in our lives, and brains, and hearts. They should not be thrown out with those ideas that go against science just because our vocabulary doesn’t distinguish the two. 

What's next?

I am planning to have a weekly “Science News” show on my YouTube channel “Science Without the Gobbledygook”. As you can probably guess, I spend a lot of time reading science news, but not everyone has the time. So, once a week, I want to summarize the biggest science news for busy people, and hopefully have some interesting conversations about them! We’ll start this in a 10 week trial in early October. 

What's exciting you at the moment?

Like all astrophysicists, I am excited about the results from the Webb telescope. The data from early galaxies could really shake things up, and finally convince the community that the dark matter hypothesis has severe shortcomings. 

Interview by Brian Clegg - See all of Brian's online articles or subscribe to a digest free here

Comments

Popular posts from this blog

Math for English Majors - Ben Orlin *****

Ben Orlin makes the interesting observation that the majority of people give up on understanding maths at some point, from fractions or algebra all the way through to tensors. At that stage they either give up entirely or operate the maths mechanically without understanding what they are doing. In this light-hearted take, Orlin does a great job of taking on mathematical processes a step at a time, in part making parallels with the structure of language. Many popular maths books shy away from the actual mathematical representations, going instead for verbal approximations. Orlin doesn't do this, but makes use of those linguistic similes and different ways of looking at the processes involved to help understanding. He also includes self-admittedly awful (but entertaining) drawings and stories from his experience as a long-time maths teacher. To make those parallels, Orlin refers to numbers as nouns, operations as verbs (though he points out that there are some flaws in this simile) a

Everything is Predictable - Tom Chivers *****

There's a stereotype of computer users: Mac users are creative and cool, while PC users are businesslike and unimaginative. Less well-known is that the world of statistics has an equivalent division. Bayesians are the Mac users of the stats world, where frequentists are the PC people. This book sets out to show why Bayesians are not just cool, but also mostly right. Tom Chivers does an excellent job of giving us some historical background, then dives into two key aspects of the use of statistics. These are in science, where the standard approach is frequentist and Bayes only creeps into a few specific applications, such as the accuracy of medical tests, and in decision theory where Bayes is dominant. If this all sounds very dry and unexciting, it's quite the reverse. I admit, I love probability and statistics, and I am something of a closet Bayesian*), but Chivers' light and entertaining style means that what could have been the mathematical equivalent of debating angels on

2040 (SF) - Pedro Domingos ****

This is in many ways an excellent SF satire - Pedro Domingos never forgets that part of his job as a fiction writer is to keep the reader engaged with the plot, and it's a fascinating one. There is one fly in the ointment in the form of a step into heavy-handed humour that takes away its believability - satire should push the boundaries but not become totally ludicrous. But because the rest of it is so good, I can forgive it. The setting is the 2040 US presidential election, where one of the candidates is an AI-powered robot. The AI is the important bit - the robot is just there to give it a more human presence. This is a timely idea in its own right, but it gives Domingos an opportunity not just to include some of the limits and possibilities of generative AI, but also to take a poke at the nature of Silicon Valley startups, and of IT mega-companies and their worryingly powerful (and potentially deranged) leaders. Domingos knows his stuff on AI as a professor of computer science w