Show Notes
On this "very special" episode of Unsupervised Thinking, we partner with our fellow podcasters over at Always Already, a critical theory podcast, to burst out of our respective academic bubbles and tackle issues of science and society. The fodder for our conversation is Brain Storm, a book by Rebecca Jordan-Young, that lays out the evidence that prenatal hormone exposures influence gender differences in behavior later in life. In the book, she claims that the sum total of the studies she covers only offers weak support for the hypothesis, and that scientists need to appropriately incorporate other factors into their models such as socialization and environment.
While we use this book as a common starting point, our conversation quickly moves beyond the particulars of these gender science studies. We start by questioning who is the intended audience of this book and what it's trying to say to different groups. This moves us into a discussion on critiques of science made by non-scientists and the role that those should/could play in shaping research agendas. We also spend some time dissecting the two-way street between science and society: particularly, how are common notions of gender shaped by scientific studies and how do society's stereotypes seep into the methods of science? An underlying disagreement about the nature of truth peppers the discussion, but we hold off on a full blown debate on that. Ultimately it is clear that the extent and cause of gender differences in behavior is far from settled science, and that is something on which we all can agree.
More from Unsupervised Thinking
Grace wrote a book! And she talked to Brain Inspired host Paul Middlebrooks about it. The book is about the many different ways mathematical methods have influenced neuroscience, from models of single cells all the way up to equations to explain behavior. You can learn more about the book and how to get it in ebook, audiobook, and hard cover worldwide by visiting tinyurl.com/h9dn4bw7 On this cross-posting of Brain Inspired, Grace talks about the book and the field of computational neuroscience more generally. Give it a listen and go check out other episodes of Brain Inspired for more great conversations.
Most neuroscience research takes place in a full, live animal. But brain organoids are different. Brain organoids are three-dimensional blobs of brain grown from human stem cells and they offer novel access to the study of human brain development. On this episode we go beyond our computational comfort zone to talk about the history of stem cells, the potion of chemicals needed to get these little blobs to grow, and the extent to which they mimic features of the human brain when they do. We also discuss the promise of studying and treating disease through personalized organoids, and how this gets hard for higher level disorders like schizophrenia. Then we get into questions of embodiment and if giving these organoids more means to interact with the world would make them better models of the brain and of information processing. Finally we get to the ethics of it all, and find that bioethicists these days are actually chill AF. Throughout, we find out that Josh is not surprised by any of this, and we tackle the pressing moral issue of our time: is it OK to eat your thermostat?
Most neuroscience research takes place in a full, live animal. But brain organoids are different. Brain organoids are three-dimensional blobs of brain grown from human stem cells and they offer novel access to the study of human brain development. On this episode we go beyond our computational comfort zone to talk about the history of stem cells, the potion of chemicals needed to get these little blobs to grow, and the extent to which they mimic features of the human brain when they do. We also discuss the promise of studying and treating disease through personalized organoids, and how this gets hard for higher level disorders like schizophrenia. Then we get into questions of embodiment and if giving these organoids more means to interact with the world would make them better models of the brain and of information processing. Finally we get to the ethics of it all, and find that bioethicists these days are actually chill AF. Throughout, we find out that Josh is not surprised by any of this, and we tackle the pressing moral issue of our time: is it OK to eat your thermostat?
The age-old debate of nature versus nurture is now being played out between artificial intelligence and neuroscience. The dominant approach in AI, machine learning, puts an emphasis on adapting processing to fit the data at hand. Animals, on the other hand, seem to have a lot of built in structure and tendencies, that mean they function well right out of the womb. So are most of our abilities the result of genetically-encoded instructions, honed over generations of evolution? Or are our interactions with the environment key? We discuss the research that has been done on human brain development to try to get at the answers to these questions. We take about the compromise position that says animals may be "born to learn"---that is, innate tendencies help make sure the right training data is encountered and used efficiently during development. We also get into what all this means for AI and whether machine learning researchers should be learning less. Throughout, we ask if humans are special, argue that development can happen without learning, and discuss the special place of the octopus in the animal kingdom.
The brain is the result of evolution. A lot of evolution. Most neuroscientists don't really think about this fact. Should we? On this episode we talk about two papers---one focused on brains and the other on AI---that argue that following evolution is the path to success. As part of this argument, they make the point that, in evolution, each stage along the way needs to be fully functional, which impacts the shape and role of the brain. As a result, the system is best thought of as a whole---not chunked into perception, cognition and action, as many psychologists and neuroscientists are wont to do. In discussing these arguments, we talk about the role of representations in intelligence, go through a bit of the evolution of the nervous system, and remind ourselves that evolution does not necessarily optimize. Throughout, we ask how this take on neuroscience impacts our own work and try to avoid saying "represents".