Time-consciousness in computational phenomenology: a temporal analysis of active inference

Hello and welcome. It's Active Inference Guest Stream number 42.1 on May 10th, 2023. We're here with Juan Diego Bogota and Zach Jabara. We're going to have a presentation, Time Consciousness in Computational Phenomenology, a Temporal Analysis of Active Inference by the authors, followed by a discussion. So thank you both very much for being here. We'll look forward to your presentation and off to you. Cool. Thank you. So I should start now, right? Brilliant. So hello everybody. My name is Juan Diego Bogota. I'm one of the co-authors of this paper. I'm a PhD student at the University of Exeter in the UK and kind of my broad interests are philosophical phenomenology and how it can be related to empirical sciences and more specifically to cognitive science and to our understanding of consciousness. So what we're going to do now is I'm going to give a broad context of our paper. I'm going to talk about the theoretical and philosophical context that motivated our paper and then Zach will talk about kind of the specifics of our analysis of active inference. So let me start now. So to kind of situate ourselves in the broader literature, I guess there's a big, big cluster of discussions and topics and approaches within cognitive science and consciousness studies that, as its names suggests, is trying to explain consciousness scientifically. Within that kind of big category of approaches, there's a very specific set, which is trying to connect philosophical phenomenology with the natural sciences. So we may call this the naturalization of phenomenology. I'll talk about all this in a bit. I just want to kind of situate ourselves within the broader context. One of these approaches is quite popular in some circles, which is called neurophenomenology. And it was first introduced and proposed by Francisco Varela in the late 90s. But recently, Varela's project has been kind of elaborated on by people within the FEP and active inference community. And they're talking about what is called computational neurophenomenology or computational phenomenology, which, as we'll see, tries to connect the original project of neurophenomenology, of bringing together cognitive science and phenomenology. And this is where our project is situated. Our main purpose in the paper was to give a temporal analysis of the structure of active inference. And in a bit, I'll explain to you why we thought this was important. So, as you probably know, consciousness is a bit of a difficult phenomenon to explain scientifically. We have nowadays a lot of models and theories, scientific theories, to try to address consciousness. But there's always this kind of lingering worry that there is a gap, an explanatory gap, between our empirical understanding of the world, nature, and consciousness. Because how we usually do science is try to address and to capture empirical phenomena from a third-person perspective. Whereas consciousness is something that is allegedly given only from a first-person perspective. So we're always experiencing the world from our first-person perspective. And allegedly, we don't really have access to consciousness as this empirical phenomenon we can see in the world. So that's kind of an epistemological gap between how we do science and how we understand consciousness without doing much science. There's also the so-hard problem of consciousness, which is to say that we don't really know how something like consciousness may arise from, say, neo-biological phenomena or empirical phenomena more generally. So this is kind of a general context which shows that consciousness is quite difficult to understand. I don't think we would want to say that it's impossible to explain it from a scientific perspective, but it's somewhat difficult. So in the broader context of consciousness studies, since the early 90s, there's been some proposals within cognitive science and philosophy, I find, that is trying to connect this whole idea of explaining consciousness…