Dr Guy Emerson (a.k.a Guy Karavengleman) is a computational linguist working at the Cambridge University Computer Laboratory. In this episode, we discuss issues surrounding LLMs such as ChatGPT, GPT-3, GPT-4, and Google Bard. Guy is concerned about misinterpretations of what the technology does and is capable of. As a computational linguist, he works on language models with a focus on semantics and human language acquisition, and thus questions of linguistic meaning and understanding are particularly relevant to his work. While LLMs are an impressive technology with startling capabilities, we need to be aware of when we may be fooling ourselves about their potential. In this episode, we discuss what LLMs are; ways in which they have been misrepresented and misinterpreted; ethical questions about the companies developing this technology; and what they might be used for.  Enjoy the episode. *** SUPPORT You can support the podcast and join the community forum by visiting https://www.buymeacoffee.com/edubookcast .

147. Large language models (LLMs) - interview with Dr Guy Emerson

Education Bookcast is a podcast principally for teachers and parents who would like to know more about education. We cover one education-related book or article each episode, going over the key points, placing it in context, and making connections with other ideas, topics, and authors. 

Topics include psychology, philosophy, history, and economics of education; pedagogy and teaching methods; neurology and cognitive science; and schools and school systems in historical and international perspective.

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In order to understand learning, we need to understand the result of learning - expertise. This is much easier to approach in so-called "kind" domains, such as chess, where the rules are fixed and all information is available. However, there exist more "wicked" domains than this, such as tennis (where your opponent changes each match) or stock market investment (where the world is different each time). How do we study the development of expertise in fields such as these? Chapter 22 of The Cambridge Handbook of Expertise and Expert Performance, entitled Toward Deliberate Practice in the Development of Entrepreneurial Expertise: The Anatomy of the Effectual Ask, concerns expertise in the art of entrepreneurship. This is a wicked domain par excellence, so much so as to throw into doubt the applicability or at least the generalisability of ideas about expertise from other domains, and yet the Handbook has a chapter approaching this topic, which is commendable.  In this episode, you will hear about two key concepts that have arisen out of research on expert entrepreneurship - the Effectual vs. Predictive Frame; and the Entrepreneurial Ask. In other words, we will look at what research has to say about successful entrepreneurs' true attitudes vs. the popular conception in the media, and how they develop their skills. Enjoy the episode. *** RELATED EPISODES 125. Entrepreneurship education and conspicuous consumption 125+. Interview with Rasmus Koss Hartman

156. Entrepreneurial expertise

There has been a ton of research on how experts see things differently than novices. (Like, with their eyes.) Everything from where they look, how long they focus for, and their use of peripheral vision, to their ability to anticipate what is going to happen through picking up subtle visual patterns. In this episode, I summarise and discuss this research. Enjoy the episode.

155. How experts see

Mindset was the first thing I spoke about on this podcast. I even did a separate episode going into the controversies surrounding replication of Carol Dweck's original work. Then there were stress mindsets, introduced by Kelly McGonigal in her book The Upside of Stress. (I happen to have also covered a book by her twin sister Jane, Reality is Broken, about applying the motivational principles learned by game designers in wider life situations). But now I've encountered another kind of mindset: self-motivation mindset. Although the authors of Self-Regulation of Motivation: A Renewable Resource for Learning (2019) didn't name it that, it clearly is a type of mindset, in that it is a belief about oneself and one's potential. So now that we have not one, not two, but three mindsets to think about, I think it's time we tried to generalise as much as we can, and simply admit: mindsets matter. What other beliefs could there be that are affecting people's learning? Enjoy the episode. *** RELATED EPISODES 1. Mindset by Carol Dweck 68. The Upside of Stress by Kelly McGonigal 131. Mindset: Does it Replicate?

154. Mindsets everywhere

I haven't spoken on the podcast yet about my personal experience learning dancing. At university, I took part in dancesport, which is competitive ballroom and latin dancing; and in the last few years I have been learning to dance tango. I am struck by the differences in philosophies, skill sets, values, and learning cultures between these dance styles, so I wanted to share my experience with you. Enjoy the episode. *** Music used in this episode: Uno by Anibal Troilo  https://open.spotify.com/track/5TFzKLS8tjVMikVaOllr8L?si=69d0c8fbee934d2e Orgullo Criollo by Osvaldo Pugliese  https://open.spotify.com/track/74CjrywI50qOpaLrXo02ik?si=91b1644591a74407 Wake Me Up Before You Go-Go by Wham!  https://open.spotify.com/track/0ikz6tENMONtK6qGkOrU3c?si=76304e73b1b04754 Dear Future Husband by Meghan Trainor  https://open.spotify.com/track/3cU2wBxuV6nFiuf6PJZNlC?si=0dd4a5e2a23c46bc ...plus one surprise I won't spoil.

153. Comparing learning different dance styles: Argentine Tango vs. Ballroom & Latin (Dancesport)

This is my first ever attempt at a VIDEO podcast. If you just listen to the audio, you should be fine. This was a video produced for the STEM MAD conference in Melbourne in October 2023. Unfortunately I couldn't attend the conference, so I made this video to introduce the panel discussion on the role of generative AI in education. Enjoy the episode.

147. Large language models (LLMs) - interview with Dr Guy Emerson

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