Season 8 Episode 2: The Information Environment, Philosophy, and AI
Season 8 Episode 2 [download this episode (MP3, 24.4 MB)]
In this episode Elizabeth chats with Étienne Brown who is an associate professor in the Department of Philosophy at the University of Ottawa. From recommending algorithms to AI chatbots, Étienne has spent the last ten years exploring how the fight over attention is reshaping democratic discourse and why he thinks AI products should face safety review before release. They dig into the ethics of who controls AI and talk about the risks of a few private companies holding power over the information we consume.
Additional Resources:
Read The Attention Merchants by Tim Wu as a companion read.
Check out Elizabeth’s report on The Political Uses of AI in Canada.
For more context about the conspiracy-belief study on how dialogue with an AI chatbot reduces conspiracy beliefs read, Durably reducing conspiracy beliefs through dialogues with AI
Étienne mentions Elizabeth's past work: The echo chamber is overstated: the moderating effect of political interest and diverse media Check out Étienne Brown’s op-ed, La Silicon Valey a besoin d’un organisme de réglementation indépendant on regulating AI like the pharmaceutical industry.
Contributors:
Host: Elizabeth Dubois
Research Lead: Areej El-Sharif & Sarah Pledge-Dickson
Transcript: Areej El-Sharif
Audio Editing: Sarah Pledge-Dickson
Translation: Julianne Bernier Robert
Publishing and Promotion: Aaron Brisson
Producer: Sarah Pledge-Dickson
Episode Transcript: Season 8 Episode 2: The Information Environment, Philosophy, and AI
Read the transcript below or download a copy in the language of your choice:
Elizabeth Dubois: [00:00:05] Welcome to Wonks and War Rooms, where political communication theory meets on the ground strategy. I'm your host, Elizabeth Dubois. I'm an associate professor and university research chair in Politics, Communication and Technology at the University of Ottawa. My pronouns are she/her. Today, we're chatting with Étienne Brown, who is a professor in the philosophy department at uOttawa, and we're chatting about the information environment and AI. Étienne, can you introduce yourself, please?
Étienne Brown: [00:00:31] Yes. I'm an associate professor in the Department of Philosophy here at the University of Ottawa. I work in the Applied Political Philosophy of Technology. And for about ten years I've been mostly thinking about social media and the role that social media plays in democratic discourse. I tend to approach this from a normative perspective, which is the term that philosophers used to say, what should we do about things? And increasingly, I'm thinking about how artificial intelligence is impacting the informational environment.
Elizabeth Dubois: [00:01:06] Amazing. Thank you so much for being on the podcast today. I'm really excited for our conversation. We want to talk about this idea of that information environment and the ways that AI is impacting it. But I know that your work has not started with AI in these kind[s] of questions of how our information environment is shifting. And so I thought maybe it would be helpful for us to do a little track back, at least as far back as recommender systems, because there's a bunch of different technologies that have been shifting our information environment over time. And AI chatbots are one of the newest ones, but it's not the only one. Can you talk to us a little bit about what that kind of series of technologies are?
Étienne Brown: [00:01:47] Yeah, absolutely. So I came to social media in about 2017. At the time, I was a postdoctoral researcher at the Université de Montréal. It was just the aftermath of the election of Donald Trump, and there was really a movement within philosophy, especially within political philosophy and epistemology, which is the branch of philosophy that studies knowledge and knowledge formation. There was [...] really a movement of philosophers who wanted to think about what had just happened politically. I think this happened in a lot of disciplines, but it happened with[in] philosophy, too. And then philosophers really started to kind of analyze the dynamics of communication and knowledge formation and the political dynamics on social media platform[s]. So my first research project was about misinformation. What should we do about it? Is removing it compatible with free speech? That kind of question. But while I was thinking about social media, I became much more interested about what we can call the infrastructure of social media. So not just about the content, what people say, but how social media actually works. And that led me to the topic that you've mentioned, which is recommendation algorithms. Right. Those ranking algorithms that basically populate our feeds that determine what we see first, what we see second and third when we scroll down. And to this day, I think that these algorithms have a pretty important impact on the way people consume information, the way people share information, and the kind of quality of public discourse generally that we have, you know, in Canada and abroad.
Elizabeth Dubois: [00:03:28] Yeah, that makes a lot of sense. And those recommenders, you know, that's why TikTok is so addictive and why Netflix always knows exactly what you should watch next and all of that kind of stuff. But then when we think about the potential political impacts, you've already mentioned the questions of mis and disinformation. What are the other kinds of things that you see as relevant here? Another way to ask this question is why do we care about the information environment from a political perspective.
Étienne Brown: [00:03:57] I guess a classical story, which I believe is the story that, you know well, considering some of your past work, for instance, on echo chambers, one central line of discourse that we'll hear is that recommender systems basically optimize for engagement, right? That's the technical term to say that they will present users with any kind of content that they find engaging or make them react. Any kind of reaction is good, right? It can be joy, it can be anger, it can be liking, it can be the angry emoji, it can be commenting, it can be resharing. And one general worry is that that way of ranking content leads people to be quite confrontational or antagonistic and polarizing on social media platforms, so that there's kind of a general deterioration of public discourse. Another worry is that people tend to seek content that expresses views that they already hold or with which they agree. So one effect can be the creation of echo chambers. All of this is very contested, right? And I think it's important for me as a philosopher to kind of remind myself of that, because I'm not the one who conducts the empirical study. Social scientists do. So that's one traditional worry. I'm very interested in that. I'm very interested in question[s] about the role that anger should play or can play in Democratic politics.
Étienne Brown: [00:05:28] There's a lot of bad. But I don't think it's only bad. But another question that I've been really concerned with relates to what we can call the concentration of influence on social media platform[s]. Right? So we have this idea in democratic theory. But I think when thinking about democracy [it is] generally about equality and equal participation, including in online discourse, right. Everyone should have a decent chance of [...] influencing the opinions of others and hopefully these opinions will influence the decision makers. But one thing that we can observe or has been observed on social media platforms is that there's an extreme concentration of influence, right? So that the people that attract attention on X or Facebook really are usually a vocal minority and there's a significant amount of people that get no attention at all. So it's interesting to think about that. I think it's [...] a thought that might bring an element of complication to this idea that social media platforms have enabled every citizen to have their voices heard. Right? To some extent, I think that's true. But if you look at those dynamics they are the results of recommendation algorithms, right? To kind of bring things full circle, also create this kind of inequality. So that's something that I've been interested in.
Elizabeth Dubois: [00:06:51] Yeah. It's super interesting to think about that because obviously, and I don't want to fully rehash this discussion because it's been had on a lot of podcasts, but there are lots of freedom of expression concerns when it comes to how you deal with an information environment that is disordered or potentially problematic. There are certainly very clearly some societal harms that have come from recommender systems, for example, but you don't want to infringe on expression. That said, I think it is really useful to remember that just because you can gain lots of reach on these platforms doesn't mean that reach is itself the same thing as expression. And that then leads me down the line of how is AI starting to change these kinds of things? I think about things like the use of generative AI tools to create these fake accounts, or these AI generated accounts essentially on platforms, and they are starting to monopolize presence on different platforms. And so, not only is there a concentration of influence, but that influence might not even be human.
Étienne Brown: [00:08:02] Yeah, absolutely. I think you're right to distinguish speech and reach. It's frequently done, I think, in public discussions. And I think we should do it. And one thing that's interesting on social media platforms is that if you don't violate, let's say, what is often called community guidelines, right, or moderation rules, you can say basically whatever you want. So you can express yourself quite freely, but that doesn't mean that people will pay attention to what you're saying. And it's interesting, right? Because if you think about what happened before in offline settings, typically when people spoke in a town square, in the street or in a park or at a demonstration, they had a pretty good idea of the audience that were in front of them. So they were in this position where they could kind of evaluate what was going to be the reach of their speech. But I think reach has gotten much more complicated on social media platform[s] because of these recommendation algorithms. So sometimes it's very difficult to tell whether or not your discourse is getting attention, getting traction or not. [...] I don't think anyone should be obligated to pay attention to you if they're not interest[ed] in what you [have] to say. But at the same time, I do think that when people express themselves on social media, they do so because they want to communicate with others.
Étienne Brown: [00:09:19] And that kind of requires reach. And then just to tie back [to] the point that you were making, it's absolutely the case that there's more and more automated or AI generated content on social media. And I think it's not unreasonable to think of this as a kind of obstacle, right, to talking to other people, because you might create a situation where people are trying to communicate with others, but then other people's attention go to automated, artificially generated content. So I think that one thing that algorithms or recommendation algorithms really did in scholarship, both in social science and philosophy, is I think that they tend to kind of move or shift the focus from expression. And I'm still very interested in that topic to what we can call the distribution of attention, right? Or this idea that attention is a valuable resource for people, for democracy, but it's relatively scarce, right? There's a legal scholar in the US called Tim Wu who made this point, who said that moving into a context where attention is increasingly scarce because there's so much content being generated, really kind of modifies the kind of question that we want to ask about expression. And that's the kind of reflection that's been influential for me.
Elizabeth Dubois: [00:10:35] Yeah, that makes a lot of sense. And I'll take this moment to note that we've got annotated transcripts. And so we'll have links to things like Tim's argument there when we talk about the impacts of AI or potential impacts of AI on our information environment. What do you mean? Like, what kinds of AI are you thinking of? Because I don't know about you, but I've been ending up in a lot of conversations where people are talking about AI and it's [a] revolutionizing thing and everyone's talking about completely different technology. So what does it mean for you?
Étienne Brown: [00:11:07] Yeah, it's the million dollar question. And like you, I have been in many conversations where I feel we're not talking about the same AI. So I think recommendation algorithms count as artificial intelligence. I mean, you know, you read computer science papers from a few years ago and they will say things like recommendation algorithms are one of the most successful application[s] of AI, right? But I feel that there's been a pretty humongous shift that has happened in recent years since the release of, you know, the first large language model to the public, which was ChatGPT. I don't think it was the first large language model, but it was the first released to the public. I think it was in late 2022, November and then suddenly you have these chatbots that are kind of high performing, freely accessible to which you can ask basically any questions to what kind of shirt goes with that pant[s] to, is it true that the moon landing was fake? And I think that increasingly when people mention AI, that's what they mean, right? They mean, what is called generative AI, so AI that is used to generate content, and especially large language models, which are a kind of generative AI that generates text. So I think that's now the focus of the conversation. But it's important to remind ourselves that there's very different kinds of AI and different kinds of technology might impact democratic discourse in different ways.
Elizabeth Dubois: [00:12:41] I think that's a really important point. We often get focused on generative AI and even more particularly, these chatbot applications of those LLMs. And we might miss some of the other kinds of ways that AI is getting incorporated into our political lives. So I did a whole report a couple years ago on political uses of AI in Canadian politics. And yeah, of course, these chatbots and synthetic content are part of it. We've all heard about deepfakes, but there are really interesting ways that data is being collected and analyzed at a massive scale. That's all AI informed in terms of the processing of that personal information about people, or the kind of decision making that goes into how you design particular campaign messages, those kinds of things. So the short story is, it's super broad. If we come back to this question of the information environment, when we're thinking about these different kinds of tools, what could be the utility of these tools for folks, right? We often default to [...]deepfakes, oh my gosh, be afraid of AI and democracy, but I think there's probably some positives. And I'm curious to know what your thoughts are on that.
Étienne Brown: [00:14:01] Yeah, absolutely. The short and true answer is I'm not completely sure what my perspective on this is. I think we're so early in the process. It's going to be interesting to see. So as you've mentioned, one worry is the kind of proliferation of artificially generated content and what we can define as public squares or nearly public squares because they're privately owned. I'm thinking of social media platforms again. You've mentioned deepfakes, right? That's a worry that there's going to be extremely highly realistic misinformation that's going to proliferate on platforms like TikTok and X and Meta. And then I think [that] perhaps for me, one other interesting question is what's going to happen when citizens interact with chatbots, large language models, not because they're trying to generate content that they're going to post elsewhere. So not for political campaigning, not for generating misinformation that's going to travel to other parts of the internet, but just because they're interested in having a conversation and seeking some information, right, to acquire information about the world, which is a very human impulse and a laudable one. And then you'll find in public discourse and even in scholarship, that there's kind of a division between more optimistic and more pessimistic perspectives. So let's start with the optimistic perspectives. There's been some studies. And again, you know, when a researcher says there's been some studies, always be careful because it's always possible that in two years there's going to be a replication of that study that's going to fail or a different similar study that finds another result.
Étienne Brown: [00:15:40] But there've been some studies that show that, for instance, people who hold conspiracy theories that engage with the chatbot tend to progressively abandon the conspiracy theory as a result of the chatbot kind of gently pushing back. Right? Another optimistic perspective [...] comes from a paper that's called the Habermas machine. So Habermas, Jürgen Habermas is a German sociologist, [who] is known for defending discourse ethics, right? This idea that there is a specific way we should engage, rational way, we should engage with one another when discussing about issues of public concern. And the study finds that when you have people who disagree and a chatbot plays the role of the mediator between them, it's actually sometimes better than human mediators at creating a view or content that both sides are going to end up agreeing with, right? So I think there's this dream that conversational AI, which is another term for chatbots, will play this kind of salutary role in democratic politics. Maybe by depolarizing people making people less angry at each other, maybe at finding common ground between people, maybe by fighting misinformation. That depends on the chat bot that you use. I think they're all programmed quite differently, and I think it's a bit early to know whether or not this will actually happen.
Elizabeth Dubois: [00:17:05] Yeah.
Étienne Brown: [00:17:06] The more pessimistic perspective, I would say, says something like be careful. Those chat bots tend to be sycophants, so don't expect them to push back. They often don't. They often will try to say things that will make you feel good about yourself. So if you're holding some hateful views or you're holding some false views, it might not push back. It also speaks with incredible authority. And I think I don't know if you've interacted with them a lot. I have, and then I can feel this effect where when the chatbot says something, it just seems true and it seems authoritative. And it's just one perspective, but it's kind of the perspective from nowhere or the perspective from everywhere, because it's been trained on the entire internet and other writings. So it's very easy to defer to this kind of speech, this kind of interlocutor that gives a lot of power to the people who develop them and decide what they can say and what they won't say. And I think that marks an important contrast with social media, right? You can lock yourself into an echo chamber on social media, but chances are that if you're active on social media, you're actually seeing this agreement at play. You're actually seeing people holding different perspective[s] and this very fact kind of reminds you that there is disagreement, right? And that things are not set in stone and I think some people worry that we might lose that when we're interacting with chatbots.
Elizabeth Dubois: [00:18:41] Yeah. And to layer on to that when we're interacting with chatbots, you mentioned, you know, it depends on which one you're chatting with, who's created the tool, what safeguards have been put up, what it's been designed for, what training data it has been fed. But the idea of personal influence really is rooted in this social connection that you have. And because it's rooted in social connection, it then gets tied to things like being able to build tolerance for others and other ideas, and being able to have empathy for other perspectives, even if they're not the ones that you hold. And I wonder how much of that social connection is lost, even if you have a conversational agent that is otherwise perfect in terms of getting you the information you need and making you feel good about it as you're being told you're wrong or whatever it is that's happening.
Étienne Brown: [00:19:39] Yeah, I think that's a very important worry, you know, the kind of intimacy or companionship or, you know, some even would say friendship, some would certainly push back on that. That you can create with an AI agent is something that I hope to have the chance to think about more in the next few years. I think ethically, it's absolutely fascinating. Generally, I think you're right. Right. I think that the experience that I have, and I think a lot of people have when you interact with a chatbot, is that, in a sense, it's an incredibly low risk, intimate experience, right? You're alone with this machine, and this machine is programmed basically to never really make you feel bad, right? So it feels like it's a low risk. You can say whatever you want, maybe it's going to push back, but if it's if it's going to push back, it's going to push back in an extremely tactful, gentle manner. And, and I don't know about you, but I know for sure that interacting with humans, including members of my family and friends, this is not how things always go, right? Things are more high stakes at a dinner party, or just when you're interacting with a friend and your friend might react very well or be angry. I don't know if you hold a conspiracy theory. A friend might be quite angry at you, or if you say something that they consider to be discriminatory or hateful, they might get angry at you. And then there's this kind of complexity and tolerance building that happens. And, you know, I think what many people around ourselves, we need to remind ourselves, even if we have a political disagreement, that we share things in common with them, if it's a member of your family, maybe there's someone who's been incredibly supportive through all your life and you have this kind of solid bond with them, and then you know that it's okay sometimes to have some disagreement and things can get heated, and then you can apologize and things go, well.
Étienne Brown: [00:21:32] I think you're right to think that maybe [...], if you turn to an AI confident instead of having those kind[s] of discussion[s], you're not going to develop this view, that it's sometimes okay to disagree with some people. And when you are actually confronted with disagreement in your real life, to react very badly to it. Right? So that's a general concern. And I think we're like, you sensed it when asking a question. We're verging on the personal because the skills that we might lose when interacting with an AI is not just about political discussion. It's just general social skills, right? It's just this capacity to be uncomfortable, to go through the discomfort, to look back on the discomfort, to grow. As a result, I think a lot of researchers and including myself, are worried about the fact that AI might just be a kind of new frictionless environment that might not prepare us very well for human interaction, even romantic relationships, which like human relationships, are full of friction all the time. Right? And I think being a competent social actor requires you to build a tolerance to this discomfort and just go through it.
Elizabeth Dubois: [00:22:47] Yeah. There's so much to unpack here. And I want to bring us back to then, the question of regulation and, and policy making around this, because there are all of these potential problems, potential harms. Some of them seem quite clearly to me in the purview of, say, a government who has an election agency that needs to ensure the integrity of those elections. Right? So we for sure need to make sure that these tools aren't convincing people not to vote. Right? Because that goes against the whole ideals of democracy. On the other hand, there's questions of, well, if you choose not to put yourself in an environment where you develop good social skills, that's up to you. And should the government step in and say, no, you have to develop social skills, that seems a little less certain to me. I wonder if you could reflect a little bit for us on where you see there being need for or potential for useful regulation and what that might look like, because this is notoriously really, really difficult.
Étienne Brown: [00:23:53] Yeah. The question about regulation is close to my heart. I'm inclined to say, because I think the general picture that we've had with social media and AI chatbots generally is a situation where basically industry, by that, I mean, you know, what is often referred to as big tech. So Google, Meta, TikTok [...], and now the big AI labs, OpenAI and Anthropic, X, which are also developing Grok, basically are calling the shots about what should be released to the public, what safety is enough safety, what the AI chatbot should be able to do and not do, what the AI chatbot should be able to say or not say. I'm talking about chatbot[s], but increasingly those AI can do things right. So we're talking about increasingly AI agents. And I feel I don't know if you share this feeling that regulatory bodies, the Canadian government, the European Union, UK are kind of running after those labs and trying to kind of legislate after the fact. And some pretty bad things have happened as a result of that. Right. So, there's been stories of teens that have committed suicide after extensively engaging with chatbots and the chatbots, not sufficiently pushing back against their kind of suicidal ideas and trying to incite them to seek help. I just think that this model of regulation is generally bad, right? So I've said this in an op ed a few years ago, and I still believe it. I think [that] the better model is closer to what happens in the drug development industry, right. Which is basically [...] you should have a regulatory body that gets to decide whether or not a specific product is safe enough or has been tested enough or [...] is demonstrably safe enough to be released to the public.
Étienne Brown: [00:25:55] Right. Because I think in a sense, democratic citizens and democratic governments generally are kind of robbed of a power that should belong to them. I don't really buy the discourse that you're going to slow down innovation. It's going to be too dangerous. There is a geopolitical dimension that's complicated, but I'm very worried that [the] industry should decide when a product is ready to [be] release[d]. Right. [...] It's a hard question to know exactly what the regulation should be. But I certainly think that especially if you're going to have young people use AI chat bots. And of course, the Canadian government [...] seems to be thinking about putting some age restrictions on the use of social media platform[s] and also AI chatbots. But I think that it should be governments that decide when a chatbot has been safe enough or has been, you know, visibly capable of pushing back against someone who is expressing distress or distressing thought. I don't think we should leave this to the people who have a financial stake in the commercialization of these products. I think it's always a bad system to let the people who have a financial interest in commercializing a product to decide when it's safe enough. Right, right. Because it's very difficult to put yourself in an impartial position to be an impartial observer. We generally try to avoid this generally, this idea that the people who can make a quick buck should be the ones deciding whether or not something should be commercialized. I think this general lesson of democratic politics should apply in the case of AI too, right?
Elizabeth Dubois: [00:27:31] Yeah, that makes a lot of sense. And you think about it. It's like the companies that often have shareholders that they are responsible to are clearly incentivized to say, “yes, my product is totally fine”. Right? They're not incentivized to have stricter limits or to dig deeply into all of the possible outcomes of their tools, or even the most common possible outcomes of use of their tools, right? Because all of them maybe is impossible, but they aren't incentivized in the current system to be able to do that. And so thinking about how better regulation would work, I think you're right, really does require separating the people who are creating the tools and profiting off of them from the people who are deciding whether or not they're safe enough. I wonder if there are any other actors that we need to be thinking about in this kind of who's responsible question. We've talked a little bit about the creators of the tools or the platforms themselves of government. Are there others that hold responsibility in our information environment as these AI tools are being increasingly incorporated?
Étienne Brown: [00:28:39] Yeah, I think that users have some sort of responsibility. There's a part of me, I often say this to colleagues, right? There's a part of me that's angry that users have to do this work. Academics, students, any kind of citizens who want to participate in public discussion. Because I've got the feeling that they've been dropped on their head. They're wreaking havoc in the world of education, in politics. And now we have to decide individually, I think, what is a good use of artificial intelligence, right? I'm kind of annoyed that I have to do this work [laughs] because, I didn't really want to. I was happy how things were, but I also don't want to be this person that just decides that, you know, I'm not going to touch AI in any way or I'm going to try to preserve the kind of pre AI society. I don't think that's realistic. So I think everyone has to do [that]. And I think it's ethical personal work. I think everyone has to do that. So I think we should do it. But I think we have a right to be annoyed about the fact that we have to do it, because I've got a feeling that no one really asked for this situation. I don't know how you feel.
Elizabeth Dubois: [00:29:52] I completely agree. I think for me, a lot of my use of generative AI tools in particular, and as I've started to engage more with conversational agents, like the goal is just figure out what it can do and what it can't do, understand its limits. And I feel really fortunate to have gone through my whole education without these tools, so that I've built up all of these critical thinking capacities so that I can, I think, reasonably, hopefully evaluate what's coming out from these tools as I prompt them. But before I let you go, I did want to ask the final question that is going to be common across every episode this season, which is, what is something you, from your perspective as a philosopher in this case, want policy makers to know that you think maybe they're missing.
Étienne Brown: [00:30:44] Yeah. So often one of my pitch[es], and that applies to both social media platform reflection on social media platforms or AI chatbot, which or both the heart of current like Canadian digital policy with Bill C 34, for instance, is that there's been a lot of public discussion, let's say, in the last decade, about what we can call platform harms, some of which we've discussed in this episode. Right? So like misinformation, hate speech, polarization, echo chambers, digital addiction, radicalization. There are some very good reasons why we should think about that, right? We don't want platforms that harm people. We don't want chatbots that harm people. Social scientists are the best position, I think, to study what those harms are. But there's another question that is a[t] the very heart of political philosophy. That's always been a preoccupation of mine, and even more so with this incredibly and increasingly powerful AI lab labs. And that's the question of power. Again, we've touched upon it, but regardless of the effects that social media platforms have and AI chatbots have, regardless of their harmful effects, I think we need to seriously think about whether or not we want to live in a society where a few private companies have an incredible amount of say about what information we consume [...] on social media platforms when interacting with AI chatbots. I think this is dangerous. I think this kind of concentration of power, concentration of influence within a capitalist economy where people are incentivized to commercialize products to make money is a dangerous situation. So increasingly in my work, I draw from [a] philosophical perspective, according to which the very concentration of private power is bad and dangerous and something that we should avoid.
Étienne Brown: [00:32:46] So if I can invite policy or even researchers in other disciplines to think about, one thing is to think a little bit more about the dispersion of power of this kind of concentrated power. And I think [...] there's a really nice synergy or complementarity between computer scientists, social scientists, and political philosophers. Right. I'm not the one who can tell you whether platforms polarizes society. I can't run the study. It's not my job. But I can think about the risk that comes with a kind of concentration of power. So I just think we should think about harms and power together, not just about harms. I would even go further by saying something like, from the perspective of democracy or democratic theory, like the way philosophers think about democracy. If someone holds unaccountable power over your unchecked power over you, you are in a relationship of inequality, right? And you might see the very existence of that relationship or that kind of hierarchy that exists between you and the power holder as an affront to your kind of basic equality as democratic citizens, right? This kind of basic, equal dignity that I think is something that a lot of people cherish. Certainly I cherish. So yeah, I think we should think more about power. It's one of the things that I like that I like thinking about that makes me happy to read some political philosophy.
Elizabeth Dubois: [00:34:07] Wonderful. Thank you so much. This has been a really, really fun and interesting conversation. There will be all kinds of links to various things in the show notes for people who want to read further. But for now, I will thank you for your time.
Étienne Brown: [00:34:20] Thanks to you, Elizabeth. This was a wonderful discussion.
Elizabeth Dubois: [00:34:24] All right. Thanks for listening. That was our episode looking at the information environment and AI. I hope you enjoyed it. As always, we've got a bunch of links to different resources in the show notes, and you can head over to polcommtech.com for annotated transcripts available in English and French, with a ton more resources and further reading. This season of Wonks and War Rooms is supported in part by the University of Ottawa's Office of Vice President, Research and Innovation, my University Research Chair in politics, Communication and Technology, the Faculty of Arts and the center for law, Technology and Society. I also want to acknowledge that I'm recording from the traditional and unceded territory of the Algonquin people, and I want to pay respect to the Algonquin people acknowledging their long standing relationship with this unceded territory.
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