Introduction (Lecture) — Course home

All right. Hello and welcome everyone. It is July 7th, 2023, and we are in the first introductory session of the course Active Inference for the Social Sciences. This is going to be a really exciting course and journey that we're all going to join and co-create together. With no further ado, I will pass it to... Please mute. Turn off the live stream, Avel. Thank you. Complex systems and feedbacks with cyber-physical systems will be a theme. We told you it would be. I will pass now to Avel for the introductory session. If you're watching live, please feel free to write any comments or questions in the chat and I'll relay them at the end. On to the lecture. Thanks, Avel. Go for it. Go for it. So, hi. Do you hear me well? There was a sound issue. Okay, cool. I'm Avel. I organized, I guess, the course. I had the idea and worked on the curriculum. Do you see the slides well? Looks good. And just make sure to close the YouTube video or mute it. So, hi. Do you hear me well? There was a sound issue. Okay, cool. Okay, I did not know how to do that. So, this is the introduction session of the course, very unsurprisingly. My name is Avel-Gena Kerlue. I am a founding member of Kairos Research and I am a non-funding member of Active Inference Lab, which co-organizes the course. And first, I will basically present the teaching team. So, we have Danielle, which is here with us, which is a PhD in Ecology and Evolution, studying Ant Leavior in an eco-evo kind of way, who is a president and co-founder of the Active Inference Institute and who is interested in among other things about philosophy and cognitive security. Then we have Ben, which is also here with us, which is a second year PhD candidate in philosophy at the University of Sussex, which, like me, interested in 4e cognition, which is embodied inactive, embedded, and extended cognition. We don't need to get into that now. He will explain to you. And in the Proactive Processing, which is basically working on the cognitive science of technology. And then we have the people who are not here today, which are Mau Albarassa, PhD candidate in the Cognitive Computing at University du Québec, Montréal, which is Head of Product Innovation and Research at Versus Private Sector Research Lab in AI and the Mathematics of AI, which specializes in Well-Active Inference. This theory we are working on right now. Script theory, which she will extend. Maybe I will talk a bit of it today, but she will be the one who explains what script theory is to you. And Modern Artificial Intelligence. Hello, we have Laurence González, also a PhD candidate, also in philosophy, but in Wollongong, I believe this is how you say it, in Australia, which is centered in philosophy of mind and in the status of information processing, as the term is used in cognitive science. And then there is me. So I made a career timeline, because when I talk about what I did, people get confused. I did physics, math, I did engineering, I did cognitive science, I did research in ecology and evolution, I did a master's in complex system physics, and I did like one year, apparently, given my timeline, or two, no, more than two, of independent research as a part of Kairos Research and as part of the French Society of Clioidamics. Before I started the PhD I'm doing now, which is something about the relation between mind and material culture, we will get into that at some point. And the question and motivation I have are essentially describing the relation between phenomenology, so the way to experience the world and physical reality, which I have the fringe view that somehow phenomenology is constructive of physical reality, which could have weak and strong interpretation, I subscribe to both. I'm trying maybe more importantly here to explain or at least describe how social cultural life form, to say the irregularities that in the life of human social life are constructed, which is hard. And I'm trying to build a research that is effective at…