Grace Lindsay - Four Way Interview

Grace Lindsay is a computational neuroscientist currently based at University College, London. She completed her PhD at the Centre for Theoretical Neuroscience at Columbia University, where her research focused on building mathematical models of how the brain controls its own sensory processing. Before that, she earned a bachelor’s degree in Neuroscience from the University of Pittsburgh and received a research fellowship to study at the Bernstein Center for Computational Neuroscience in Freiburg, Germany. She was awarded a Google PhD Fellowship in Computational Neuroscience in 2016 and has spoken at several international conferences. She is also the producer and co-host of Unsupervised Thinking, a podcast covering topics in neuroscience and artificial intelligence. Her first book is Models of the Mind.

Why science?

I started my undergraduate degree as a neuroscience and philosophy double major and I think what drew me to both topics was the idea that if we just think rigorously enough we can make a lot of progress understanding how the world, and ourselves as humans in it, works. Now, as a practicing scientist, I really do appreciate the strict standards for critical thinking and evidence-backed beliefs this profession has instilled in me.

Why this book?

I am a computational neuroscientist and most of the time that I tell people that they really don’t have any idea what it means. Computational neuroscience is an approach to studying the brain that involves mathematical analyses and model-building, and it is becoming an increasingly dominant way for neuroscientists to try to understanding how the brain works. I wanted to share the fruits of this field with the world so that they can see what the future of neuroscience will look like, but also provide the context and history that shows how mathematics has always played a role in our understanding of the brain.

What’s next?

I’m a scientist, so I am going to keep on doing my research, which is about building mathematical models of how the brain processes and uses visual information. But I would like to write another book someday--possibly about modelling in science more generally, including physical and mathematical models.

What’s exciting you at the moment?

I’ve been trying to follow some of the progress in how scientists are trying to address and prevent climate change. While climate change obviously still fills me with a lot of anxiety, I have felt a sense of excitement and respect for the people using science creatively to innovate in this area.

Comments

It's On You - Nick Chater and George Loewenstein *****

Going on the cover you might think this was a political polemic - and admittedly there's an element of that - but the reason it's so good is quite different. It shows how behavioural economics and social psychology have led us astray by putting the focus way too much on individuals. A particular target is the concept of nudges which (as described in Brainjacking ) have been hugely over-rated. But overall the key problem ties to another psychological concept: framing. Huge kudos to both Nick Chater and George Loewenstein - a behavioural scientist and an economics and psychology professor - for having the guts to take on the flaws in their own earlier work and that of colleagues, because they make clear just how limited and potentially dangerous is the belief that individuals changing their behaviour can solve large-scale problems. The main thesis of the book is that there are two ways to approach the major problems we face - an 'i-frame' where we focus on the individual ...

Introducing Artificial Intelligence – Henry Brighton & Howard Selina ****

It is almost impossible to rate these relentlessly hip books – they are pure marmite*. The huge Introducing … series (a vast range of books covering everything from Quantum Theory to Islam), previously known as … for Beginners , puts across the message in a style that owes as much to Terry Gilliam and pop art as it does to popular science. Pretty well every page features large graphics with speech bubbles that are supposed to emphasise the point. Funnily, Introducing Artificial Intelligence is both a good and bad example of the series. Let’s get the bad bits out of the way first. The illustrators of these books are very variable, and I didn’t particularly like the pictures here. They did add something – the illustrations in these books always have a lot of information content, rather than being window dressing – but they seemed more detached from the text and rather lacking in the oomph the best versions have. The other real problem is that...

The Laws of Thought - Tom Griffiths *****

In giving us a history of attempts to explain our thinking abilities, Tom Griffiths demonstrates an excellent ability to pitch information just right for the informed general reader. We begin with Aristotelian logic and the way Boole and others transformed it into a kind of arithmetic before a first introduction of computing and theories of language. Griffiths covers a surprising amount of ground - we don't just get, for instance, the obvious figures of Turing, von Neumann and Shannon, but the interaction between the computing pioneers and those concerned with trying to understand the way we think - for example in the work of Jerome Bruner, of whom I confess I'd never heard. This would prove to be the case with a whole host of people who have made interesting contributions to the understanding of human thought processes. Sometimes their theories were contradictory - this isn't an easy field to successfully observe - but always they were interesting. But for me, at least, ...

Search This Blog