Jeffrey Herlijimira (2:29)

Before we start our conversation, I wanted to introduce our co host Alex Rivera, Instructor of Philosophy at the University of Puerto Rico in Maya Ues. He is a UPRM graduate and like myself, before coming over to the humanities he studied computer science.

Alex Rivera (2:42)

Like Jeffrey said, my name is Alex and yeah, before my degree in philosophy I had experience in computing science and even though I did go to another route of my academic journey, I still love technology and all of these things like AI, algorithmics, etc. It is something that fascinated me too much. So I'm glad to be here today.

Jeffrey Herlijimira (3:12)

Awesome. So this by the way, this is the second episode that we've done on algorithmic culture before the Internet. Alex and I recorded a conversation in Spanish a few weeks ago which I'll link down below in the it's also on the new Books Network en Espanol and I'll link it down below in the Description in an age before the Internet, there were libraries, books, and most important, there were people and relationships. Now in our classrooms we have the first generation of students who are contained, submerged in a sense in a domain of digitization that is silently operated by artificial intelligence. Whether this involves chatbots, predictive searches, GPS instructions, text editing, reading summaries, or algorithms that manage everyday life, many are subordinates to to what Professor Hector Eike, our colleague here at the University of Puerto Rico in Maya Oes has termed a substitute reality. And as Eric hall has argued, we are in a consciousness winter. Cognition has become digitized, dispersed across algorithmic and biological systems, and there are no respites. Algorithmic influence promises, or at least tries to overtake lived experiences and knowledges. If thought, consciousness and bodily existence have shifted away from the meditative human designed experiences, we need tools and infrastructure and questions that allow people to develop human skills in relation to their immediate environment. Ted Strife's wonderful book looks in on these conditions, and he also takes a macroscopic view of them, one that situates contemporary algorithms within their histories and development from antiquity to Cambridge, England to Cambridge, Massachusetts and here to Maya West, Puerto Rico. Ted Strefas examines the evolving concepts and definitions of culture, including the development of cultural studies, and he highlights the importance of language in the history of technology. His book offers a historical and interdisciplinary perspective on the relationship between culture and computing and provides a much needed context for algorithmic injustices that plague the world today.

Alex Rivera (5:02)

Yeah, in my case I had the transition from the floppy disk to the disk and now the lt's digital world. So I had some experience before this overhaul taking of the Internet, the over thinking of the Internet, taking all the world. What you say? So it is fascinating to me to now have a younger generation that it is fully immersed in the Internet world and algorithmics. So it is good that we had a book such like Algorithmic Culture that allows us to evaluate the concepts of culture and technology and how they combine and how it is going to affect us and it is affecting us today. And so we can have a perspective how that started and how that process is going forward. It is extremely important to understand how these algorithmics change us without ourselves knowing all the time. You know, we are not consciousness about how most of the time how this, you know, social media, even Google itself, just by recommendation. No, you know, the first one, the first one you click is the one that you get. So that's a way of manipulation. And obviously that happens in social media all the time. So it is extremely important to understand and study these concepts and themes. So now I would like to ask the first question to Ted. Ted, could you tell us a bit about your biography, your interests, training and experiences?

Ted Strefas (7:13)

Sure, I'm really happy to. And just thank you again, Jeffrey and Alex, for having me on the podcast. I really appreciate the opportunity to speak with you and your listeners. So the Algorithmic Culture before the Internet book, like a lot of my work, starts at the end of things rather than at the beginning of things. So it opens with a Scene from the 2018 feature film Ralph Breaks the Internet, in which the main character and his kind of sidekick meet an embodied, personified algorithm by the name of. Yes. And so this, to me, is a really interesting kind of moment of arrival for the idea of an algorithm and also for algorithmic culture, because, you know, algorithm is this, like, really technical term. And when I started this project, kind of around 2009, 2010, a lot of people didn't actually know this word algorithm, and it wasn't one that would just kind of like easily slip off the tongue in the English language. And so the question that I was trying to think about here, just apropos of Ralph Breaks the Internet, is, you know, how does the super technical term become so widely accepted, used and understood that it would appear of all places in a children's movie? Right. And so that sort of opens up then the broader question that gets me into the substance of the book, which is, you know, how did it ever make sense to use computational tools, algorithms, specifically to classify, sort and prioritize cultural goods? Things like, you know, movies, music, even friendships and relationships? And the kind of, like, point of curiosity for me is, you know, like, culture as an idea and as a set of practices is supposed to be kind of like the epitome of the humanities and of human experience more generally. So it doesn't at least intuitively make a lot of sense, at least in principle, why culture and computation at this moment in history would come to mingle so freely, you know, kind of so easily and decisively. And that riddle is really the one that I try to work out in the book historically, right? So it starts at the end, and then it kind of works backward to the beginning. So basic argument of the book, for folks who might not have read it, is that culture and computation came to be entangled in language long before they manifested in the technological wizardry of Silicon Valley. And so you asked about kind of my experience and how it relates to the book. And I had background in a number of different fields, but primarily what I would describe as cultural studies. So I was introduced to cultural studies as a kind of interdisciplinary field of study at the University of New Hampshire, where I had the good fortune to work with Professor John Ernie, who has since moved on to Hong Kong. And then I did my graduate work at the University of North Carolina at Chapel Hill, where I worked with Lawrence Grossberg. And it was there that I really kind of got that really deep training in cultural studies. And it was really in those contexts and through the work of the English, actually Welsh, literary critic and cultural studies scholar Raymond Williams, that I was introduced to the idea that culture, definitionally speaking, isn't something that you can take for granted, and that it's best treated as a variable rather than a constant. I think that's one of the real hallmarks of cultural studies that a lot of people miss. They think it's the study of culture, when in fact, it's the study of culture as a problem that sort of shifts over time. Last thing I'll say here is just that it was at UNH that I also learned the basics of what's sometimes called medium theory, sometimes described as kind of like media form, looking at the apparatus in studying with Professor Joshua Meyerowitz. And it was that that sort of got me into the world of media history, which drives a lot of the research in the Algorithmic Culture book. And I also had a very good fortune of studying with Janice Radway at Duke University when I was at UNC Chapel Hill. Those universities are just a few miles apart. And she was really instrumental in kind of teaching me a lot of the fundamentals of historical research and specifically media historiography.

Jeffrey Herlijimira (11:30)

Wonderful. Fantastic. I wanted to share just a little bit of something that Alex said during our conversation in Spanish. His observation that really Struck me was that I'm translating here, but these are unavoidable. PowerPoint, Word, the Internet browsers, all of these push into your field of vision. They're designed to distract you. And I wanted to just elaborate on that and to talk a little bit about. They are distracting us in the name of other people's judgments, and sometimes AI's judgments about what is best for you. And what is best usually means what is most likely to keep you on this device so that ads may be sold, so that we become almost like bovine and lethargic, so to speak, almost like in the Matrix. And your attention is the goal, and your lethargy, your boredom and kind of brain rot would be kind of their gain. And I really enjoyed your focus on the logocentric dimension of all of this. And specifically, one of the words that comes up are scriptocentrism, which Alex and I both took out. And so one of the. Also another phrase I want to kind of launch a question out of was that distancia es liberation or distance from these is liberation if these involve atrophy and if distance is the only liberation from these. I don't agree with that myself. I think that there are some wonderful outcomes from AI. But I wanted to just pose that as a question. How do you feel about all of these processes as a whole?

Ted Strefas (12:57)

Well, just thank you so much for the close and careful reading and also for the attention to those kinds of dimensions of the argument, specifically that argument about scriptocentrism. And the reason that that's important to me, in part, is that one of the problems of this book is just kind of the continual problem of the things that different forms of media do with us and to us when they arrive on the scene. And so, you know, just trying to sort of like, track the history of culture and computation through a number of different media contexts or environments, much of which was the history of print. And of course, that descriptive centrism is just, you know, so sort of like, central to the argument, because in many ways, that I think is part of the shock that we are experiencing, particularly, Jeffrey, you and I, people of this generation that were born pre digital, where we're able to really kind of see and bear witness to the transition and to understand kind of what happens when you are born into a world where there are human cultural intermediaries, right? So people who are like librarians or DJs or the video store clerk way back in the day, or even people who were professional matchmakers, right, who, you know, set people up on Dates and help people find their significance of significant others. Like what happens when you start to slip out of that world into this other world that you are describing, which is a world in which machines do the vast majority of that type of work for us very instantaneously and in many cases, somewhat uncannily. Sometimes it's a complete and utter failure, but sometimes the work is actually done in ways that sometimes seem incredibly right. And so the point that you're raising there, I think is a really critical one, right? And it's the critical one that's apropos of the media historical question, which is, you know, what do you give up in the shift from the one to the other, from the, you know, let's call it the analog into the digital. And that point about human judgment, I think is a really critical one, right? Because that is the crux of it. It's also a labor question also, right? Because, you know, these systems are creating vast structures of unemployment where previously there were people who were involved and employed as, say, DJs or video store clerks or whatever. A lot of those jobs are drying up or quite radically changing. So there's that political economic dimension. But then the sort of broader epistemological question is, what happens when human beings outsource a lot of this everyday decision making to parties that are not human? And in some ways it's fine. I don't need to necessarily have a person recommend every single movie that I need to say, see, right? But at the same time, you know, there is something to be said for the kind of conversation or dialogue that you can have within a human being, right? Because you can't really sort of like, ask Netflix, why did you recommend this movie to me, right? They'll show you a pattern of behavior that led the algorithm to that particular film. And you can either give it a thumb up or a thumb down. But that's not the conversation of culture that has been historically the crux of the way in which culture has worked. And so I think this is really kind of the critical stake in thinking about the shift from the one paradigm to the digital paradigm, the pre digital paradigm to the digital paradigm. And that is that question of like, well, what happens when you give up on that idea of the engaged human dialogue, right? The question and answer, the sort of poking in the prodding. Why did you recommend that to me, Huh? I never thought of myself that way. I didn't know that you saw me. Like, you just can't ask those kinds of questions of an algorithm. And so just that Dialogical part of culture, I think is a lot of what we see slipping away in our time. Well.

Alex Rivera (16:57)

That last point that you made, basically how you can ask these questions through algorithm including, we can include that in conversation with the AI, because when you like for example, you are with a chatbot, you can ask him why the chatbot recommended this option. No, like it might try, but in reality it doesn't know because it doesn't have any type of conscience. And obviously this applies with algorithms because a base, some kind of argument. And so this part of the. That is lost in the process of. Oh, well, I like this because why ABCD versus a simple explanation that doesn't have any profound consequences, only then a straightforward answer. And I think that that is important that we have lost in the, in the process.

Ted Strefas (18:12)

I think that's absolutely right. And just, you know, if I could maybe just add a little bit something to that too. You know, I think about the way in which AI interfaces tend to work, like ChatGPT and you know, like, yes, of course they are conversational and ostensibly dialogic, but you know, when, when you hear their tone, it's always just sort of like upbeat and trying to just sort of like massage the ego of the user. And like, that's okay. I don't think there's necessarily anything wrong with that, but it does in some respects cut down on what I was describing before, which is not necessarily just the dialogical aspect of culture and cultural decision making and cultural engagement and kind of figuring that out, but also the agonistic dimension of that too. Right. That culture is not only supposed to be a dialogue, but it's supposed to be something that is kind of worked out in ways that involve a kind of like, you know, struggle, a give and take, a back and forth. And that's not the way in which AI systems tend to work. Right. They tend to be very much about pleasing the user and making the user feel good. And you know, like, culture should make people feel good, but it shouldn't only make people feel good. Right. And I think that that's one of the things that we see now emerging just in terms of the kind of, you know, tenor or tone of these technological artifacts.

Jeffrey Herlijimira (19:38)

Yeah, excellent, excellent. I wanted to share two of the citations, both on page 67, that really struck me. People making history under conditions not of their own making and then secondary also on 67, who gets to count as important in our lives, how, to what extent and in what specific context, even though they're text based, they reach so much farther into our lives, into who we are and to who we can be. In your opinion, when you go back and you. And you reread parts of it, what stands out?

Ted Strefas (20:07)

Thanks for asking that question. And, you know, in many ways, I think what you're pointing to out of the gate here is the most important, which is what readers take away. But in terms of my own relationship to the book, I. I really struggled with how to execute this project because it's like most of my work, kind of a strange project. It comes at things that are conventionally understood, but it comes at them in, you know, sort of sideways. So the starting point, I guess, for just thinking about this question, like, what am I proud of? Is, you know, the history of computation is usually explored through, for lack of a better way of putting it, the history of computation. You know, like looking at the technology that are, you know, computational technologies, the big figures like Alan Turing and, you know, just von Neumann and all of those names that you hear kind of over and over again. The problem, though, is that that doesn't really give us an adequate picture of that history, particularly as it relates to the history of culture or maybe even to any history. So, like, just the way I think about things, our world is much too complex for causes to be singularly attributable to just one field or one set of authors gathered around a single discipline. So in the Algorithmic Culture before the Internet book, I try to trace the history of computation as it was influenced or framed by words and ideas brought to us significantly through the humanities and the social sciences. And of course, then there's some necessary spillover into the world of the history of science. But in the periods that I'm looking at, even like, as far back as the 9th century CE, like, this is before the establishment of formal science. And so what I try to suggest is that we need to be careful about how and with respect to whom we're deploying even that term, right? Because, like, is it proper to talk about the history of science before the establishment of formal science? And I don't necessarily think that it is. So that's one of the things that I'm really proud of, is trying to kind of shift the locus of the history of computation so that it has a wider frame of reference. And, you know, the other sort of piece of this too is just thinking about the inspiration of the book from the work of Raymond Williams, the Welsh writer whom I had mentioned earlier. His book Culture and Society, which was published in 1958, is, like, really an inspiration for the algorithmic Culture book. And in some respects, I consider the book to be a kind of companion or sequel or rewriting of culture and society, but for our own age. The thing that's interesting to me about Williams book is that it was a work of literary and intellectual history that tried to show how a bunch of English authors confronted the Industrial revolution of the machine age, but in a way that it wasn't just their words or outlooks, kind of like reflecting that age. But, you know, William's argument is that they actually helped to constitute that age. Right. And it was at a couple of levels. Right. An intellectual level, but also at the level of what Williams was calling the structure of feeling. Right. So just the kind of, like, tenor of the times, as it were. Now, the thing about this is that Williams wasn't much of a sociologist. He was very much a literary critic, and an incredible one at that. But he sort of took for granted the circulation and uptake and impact of words and ideas related to culture in the period that he was studying. So in Algorithmic Culture before the Internet, I try to do similar analytical work, but also then to kind of add in that sociological dimension about algorithmic culture that wasn't really available in his work or his analysis of culture in the 17, 18 and 1900s. And so, yeah, so I'm, like, really kind of proud of the way in which I try to sort of synthesize those different kind of elements, you know, the sociological, the historical, but also trying to challenge the conventional ways in which those fields or disciplines were operating methodologically.

Alex Rivera (24:14)

The next question is, how does this book relate to your previous work and to your position at the university? Have these ideas been developed to classes, conversations or conferences?

Ted Strefas (24:28)

Yeah. Thank you, Alex, for asking this question. And it's such a wonderful question because I think so often when we're thinking about academic or intellectual work, we only focus on the products, the outcomes, what's said, you know, the final object. And I just am so grateful to have an opportunity to talk a little bit about the process. So Algorithmic Culture before the Internet is a direct outgrowth of the first book that I published. This was in 2009. It's a book called the Late Age of Everyday Book Culture From Consumerism to Control. And the third chapter, which is the middle chapter of the book, is ostensibly about the history of Amazon, the retail giant that started out as a bookseller. And one of the things that really becomes the kind of entry point for that chapter is a history and analysis of. Of the use of codes to essentially keep track of products, right? So things like the Universal Product Code, the upc, the International Standard Book number, ISBN. And so what happened in the course of kind of doing that research is there was a, I don't know, a sort of loose end where I began to realize that there were these conversations that computer systems were having about books, which is their cultural goods, right? And it was a conversation that human beings were by and large exempted from. Right? Because most people can't look at a UPC and know what book that it references or look at an ISBN number and be able to decode it. So that there were these conversations happening about culture and cultural goods that human beings were kind of adjacent to, but not actually privy to. And that becomes the kind of entry point for thinking about this idea of algorithmic culture. But the real sort of crux of it was in April 2009, and I talk about this in the algorithmic culture. Before the Internet book, there was a kind of mishap with Amazon, where 55,000 gay, lesbian, bisexual, transgender queer books in their catalog were delisted. And, you know, there are many reasons why, you know, folks were kind of like blaming different people and things. But in many ways, this was a result of an algorithmic mishap. It was an early instance of what we would now today call algorithmic bias. But we didn't have that language in 2009. But it was right around that time also that I was reading Alex Galloway's book, Essays on Algorithmic Culture. And it was really with that kind of Amazon incident that I connected the dots between that work early on in the late age of print, the delisting of the LGBTQ titles on Amazon, and then this idea of algorithmic culture. And so started to develop essentially the basic arguments of the book, at least in a very early form, in a blog that I used to maintain called the Late Age of Print. So it was, yeah, just kind of an ongoing series of things that just sort of happened one after the other after the other in very close priority that helped me to understand that the locus of. Of culture and cultural decision making was significantly shifting in the direction of computer systems and algorithms. You know, just in terms of my own kind of positionality with respect to my work here at the University of Colorado Boulder. I am in the Department of Media Studies. I very proudly chair that department. My background is in communication. So most of my training and degrees, they all come in fact from communication departments. So I definitely work at the Intercession of Media Studies and Communication here at the University of Colorado. I have what's called a courtesy appointment in the Department of Information Science. So I'm not full fledged faculty there, but I am certainly friend of the department and work over there sometimes in different capacities. I've been claimed by the folks in digital humanities in many different ways, especially with the late age of print book. And it's an identification that I really tried to let in and embrace because I think there's amazing work in the digital humanities. And just kind of on my own over the years, I developed an interest in the history and sociology of science, which again, are not things that I kind of, you know, formally do in terms of my university appointments, but they're definitely kind of intellectual or disciplinary points of reference. And all of those things, all of those different sort of fields and aspects of my training come together in algorithmic culture before the Internet.

Jeffrey Herlijimira (29:23)

Excellent, Excellent. I wanted to share a former colleague of ours here in Puerto Rico, Scott Kushner, who was an invited researcher with us in 2023, he gave a couple of talks on similar topics in media studies. And I wanted to quote from him to kind of introduce this question. And one of the things that he said is that these environments shape the possibility of thought and being. They also shape the way that the ways that societies form also a wall or a turnstile being more effective in changing people's behaviors than a person saying go that way. As I read your book, one of the things that I that gave me pause, especially in the first book part, the first, say, 70 or maybe 90 pages, was the reluctance to use of the verb manipulate in favor of the verb orient. And to orient something is to give it direction. Yes. And algorithms do this, but I think that they do more. And I think part of the reason we need to have these conversations is because they are so powerful and persuasive in manipulating in the way that they take away human agency and lull us into these kind of trances, so to speak, in which we vulnerable to manipulation towards pattern of behavior that result in consumption, but also in violent behaviors, also in extremist behaviors and things. And I personally, I don't have confidence that our contemporary algorithms have much intrinsic value. And I think that they're destructive to our attention to our cognition and to our interactions with other human beings. And I feel like, not necessarily that we need a better relationship with them, but we need less contact with them. And it's almost like we're in a gilded age and where amid these structures that surround us that are out of control now, in fact, we are being almost obliged to Use them right now. In the last week or so, I've had to buy a new car in Puerto Rico. And one of the things that you have to have in Puerto Rico is a car, because the way the infrastructure is put together. And I remember I had to go to these towns. I drove all around the island looking for a car, and I had to go to these towns that I never go to, like Las Marias in San Sebastian. And. And every single. I had a repetition of the same conversation. The person would say, oi pon lone in. And I had to say, I don't have a smartphone. I don't have a gps. And it was like the people couldn't believe me. I don't have a gps.

Ted Strefas (31:36)

Now.

Jeffrey Herlijimira (31:37)

All that being said, I wanted to say that what I didn't expect was the second part of your book is when you go into the arc of precisely what I was hoping to read and what I wanted to read. The narrative arc that Ted puts in is one that I really enjoy because the liner faces the argument and made me appreciate the first part of the book even more in what he was working up to. And for me, I think that really comes together with what he says about agent, what you say about agency. And then on 229, the point is to invite you to reclaim definitional agency. Beautiful. Beautiful. It was a wonderful. That track that ilo, as we say in Spanish, was really wonderful. And so I had a question. My question, like I've long preambled this question, is how can we do that? I think that writing about algorithms and discussing it like we're doing today, those are excellent. But beyond that, are there any kind of practices that we could consider in our daily lives?

Ted Strefas (32:29)

Yeah, just thank you for that lead in and a really interesting set of examples and experiences that you're narrating there, Jeffrey. And I want to go back to the image of the turnstile, which I think is a really interesting one. And the argument that, you know, like, a turnstile is more persuasive than, you know, most people and, you know, kind of getting someone to behave in a certain way. And, you know, I don't disagree, but I think in many ways, you know, the reason I use the word orient rather than manipulate has everything to do with the fact that I believe that some people look at the turnstile and, you know, they comply. But there are a lot of people that look at the turnstile and just jump it, you know, and I. And I think that that is in some ways, you know, really the. The crux of what's at stake here, and that is that we have these objects and these technologies that are doing their best essentially to provide a path of least resistance, right? To say, this is the direction in which I need you to go, and you're supposed to go, and you will be rewarded if you go. And I think part of the allure of that is it just allows us to make this kind of unthinking progression through our everyday lives. But I think the most interesting part about that is there is always that kind of room for maneuver, and it's room for maneuver that we don't often recognize until other people partake of it. And more to the point, I think until more people sort of partake of it en masse. So the more people who jump the turnstile, the more people who then feel at liberty jump the turnstile, right? It becomes this kind of accumulative process. And so I think that that is in some respects, kind of like what we're looking at here with algorithmic culture. And so I think there are a couple of parts to the question that I'll try to address in turn. The one is about definitional agency, which admittedly is kind of a somewhat strange part of the argument, because here is a book that is ostensibly all about technology, and then it sort of ends on this note about defining terms like what's. What's that? What. What is that about? How do you get from the one to the other? And so, you know, so much of the narrative of the book is driven by language, right? And to return to what I had said earlier in the conversation, right, the argument of the book is that the rudiments of algorithmic culture emerge in language, right, long before they are manifested in technology. Right? And so what that means then is that words essentially give us a certain type of imagination, right, an ability then to go on to build material worlds based on the kinds of understandings and accesses to reality that that language opens up for us. And so that's why I spend a lot of time thinking about the definitions of words and also the politics of defining words. Because part of what's at stake, if you don't like the way in which this world of our is going, you know, technologically or otherwise, you know, well, maybe, you know, there are different modes of struggle, right? We have to, you know, struggle with respect to political economy. We need to think about, you know, law, policy, regulation, all of those kinds of things. But maybe part of what we also have to do, too, is dream up new definitions of worlds of Words, excuse me, so that we can then go on to build different worlds. And so that's the, the argument about definitional agency. The other piece of that though, of course, is that most people don't feel at liberty to define terms, right? So if you want to define a word, what do you do? You go to the dictionary, right, which is the authoritative source, and it does the work for you. And so the sort of like sub argument here then is not only about creating a different vocabulary by means of which to talk about algorithms and culture and their relationship, but also to reclaim the idea that you, you are at liberty as a human being to define the terms and conditions of your life literally and figuratively, and not only to rely on those kinds of authoritative sources which have a certain type of investment in defining words in particular ways. So there's that piece. And again, I don't mean to say that defining words is going to get us out of all of our problems, but I do think it needs to be a piece of a larger sort of political struggle. And then, you know, to go back to this larger point, you know, how do you resist algorithmic culture? I mean, it really is just so incredibly difficult to escape, as you were just describing, through the parable of not having a smartphone. I mean, to your credit, you know, you, you kind of got out, right? Although one is never completely out because of course, you know, Alex is sitting right next to you. Alex may have a smartphone in his pocket, and that may be eavesdropping on you and recording things and making judgments and things like that. So it is quite the enclosure. And so I think in many respects we do need different forms of regulation. I think that that really is a fundamental baseline that is just deeply and profoundly lacking right now. And that's not going to change anytime soon given sort of the relationship between the tech industry and government, at least in the United States. But I think that that has to be part of what Raymond Williams long ago called a long revolution, right? Where you're playing essentially a long political game, rather than one that is simply about six months from now or a year from now, or even five years from now. What does the world look like 50 years from now? And what are the things that we need to do to create a regulatory environment that's going to get us to there. And I think that that's really the interesting and difficult question that we need to be thinking about, because so much of the world of technology is about short term thinking. And I think that part of what we have to do is exercise that muscle which is the long term thinking.

Jeffrey Herlijimira (38:24)

Excellent, excellent. Alex has the next question, but I wanted to just jump in here really quickly and say this is excellent where you said words give you a way to create a type of imagination. I feel like that's a really excellent understanding of words as a crucible of experience, but also also of creation. And yeah, I think just to kind of follow up a little bit about regulation and about our relationship to these devices and to these patterns of words and patterns of exposure to them. I feel like a lot of times the infrastructure, it's almost like cars that we have to use cars now because of the way that the infrastructure has been developed in a way that is destructive to our bodies, destructive of the environment and smartphones. The same thing is happening. And luckily we are or some people are able to kind of separate from that. I feel I did work in algorithms development for a period of time before while I was a graduate student. And it's part of the reason that I need to have that distance from it. And I feel like it is liberating because, for example, here on campus we have, there's a. What do you call that app? The WhatsApp group. And I'm not on it, obviously, because I don't have smartphone. And it is so refreshing because there's so much tension that's created and so many problems and that. And then people see me and they're like upset about this or that and, you know, they have to explain it to me and it's like, well, okay, you know, but it really allows me to kind of have a very healthy, I think, relationship with other people, but also with the, you know, with my time and with, with my exposure to the Internet and these different types of things. But I think that's exactly right, what you said about, about relationship speculation and about some oversight and some thought about the way that these things are happening. And I absolutely agree that the 50 year scope is the important one.

Alex Rivera (40:10)

Yeah, I wanted to add that in my own experience. I remember that in high school I didn't want to use WhatsApp. I didn't want to install it at all. But I was in a band, so at one time they just forced me to install it because we needed to communicate and they didn't have other options. So from that point, so WhatsApp. But I mentioned that because at some point, you know that some things are forced into you not because you wanted them, because, you know, there's something that it is like inevitable at some degree. Fortunately, in the case of Jeffrey he could manage that. My case.

Jeffrey Herlijimira (41:08)

Well, yeah, I think if I were younger, like, if I were a teenager, I think it would be a lot more difficult. Like, I have a son who's going to turn 12 next week, and. And my wife wants us to get a smartphone or a phone for him. They want to get a flip phone for him.

Ted Strefas (41:19)

I said, you know what?

Jeffrey Herlijimira (41:20)

I don't. I mean, he does need to call us sometimes because the power goes out at school, the water goes out, and we've got to go and pick him up. But all his friends have fun. So just have, you know, or whoever's with him, you know, to give us a call. And that's what he. That's what he does.

Alex Rivera (41:34)

Yeah. Yeah. Those messages are different. Yeah. At the moment you told us the context, how you envision this book and how you connected to other works that you did in the past and even with your academic studies in communication. So I want to ask this now. What did you learn to your research? Were there any unexpected insights or points? Is the final product similar to what you initially. Initially in Vines?

Ted Strefas (42:15)

Yeah, I love this question. It's such a hard question. And really, there's just so much there. I mean, this was a book that took a very long time to write and was a real journey, just, you know, as any book is. But this one felt like it was, you know, like. I don't know, just like an epic level journey rather than a regular journey across town. So, I mean, in terms of, you know, unexpected points or things that I had, you know, kind of learned along the way, I mean, one of them was, I keep mentioning the word methodology. And it's funny because it was not like, a concern of mine. I was never someone who was particularly interested in questions of research methodology until coming to this book. And, you know, I made a decision relatively early on in the course of working on this project that I would try to sort of explore things in the vein, as I said, of Raven Williams and specifically his work on keywords, which tends to look at words that are kind of doing kind of strange things semantically, and they're kind of like an index of a changing social reality. Right. That social reality is starting to shift, and words then become a kind of bearer of those changes in certain respects. But the thing that was interesting to me in the course of doing the research, at least from a methodological standpoint, is I had to confront what I never really sort of recognized before as the profound methodological limits of doing work in keywords. And there's so many Works in keywords. So many books that have that particular term in the title that it just. It's like a thing. And suddenly what happened in the course of the research is that it became a problem that I had to work through. So, you know, one of the early revelations was that Williams developed keywords very much within the context of print culture, right? So I had mentioned all of the literary figures that he was studying in Culture and Society and other works of his, right? That he was someone who developed this methodology for studying language in its relationship to social change. But it was just completely invested in not only print culture, but like really sort of like dominant and print culture. All right, so the canon of 19th and 20th and 18th century English writers. And so, like, one of the questions that I had to deal with as I was doing the research for algorithmic culture before the Internet was how well does that methodology apply or hold up when you're talking about a hybrid oral manuscript culture of the 9th century when something like dictionaries hadn't even yet been invented, Right. Or how could keywords account for statements that aren't issued in public? Like, that might, for example, exist in an FBI file, Right. Hidden, ostensibly from view. And so it was like those kinds of questions that became really interesting methodological challenges that allowed me to sort of extend the methodology of keywords, which, like, was not something that I had set out to do at all, but was something that I had to work through as a result of the empirical method material that I was encountering. So that's one thing. Second thing was a very late and startling insight. This was almost one of the last things that I wrote in the book, which was a kind of discovery of an early tentative connection between the words culture and algorithm in the 1850s. Not the 1950s, but the 1850s. And this was in the work of Matthew Arnold, the famed 19th century British poet, political writer, school examiner. Guy did a lot of work. You know, he was beginning to think about the word cultivation in the 1850s, which is the word in the English language that immediately preceded culture. It basically did the same thing. He was looking at cultivation in his political writings at the very same time that he was composing a poem called Sohrab and Rustum, which was set in the land of Khwarzim, which is the ancestral home of Muhammad IBN Musay al Khwarizmi, who was the namesake of algorithm. So just kind of like a weird sort of historical coincidence, I call it in your Ms. I think that algorithm and culture, you know, had this encounter in the 1850s and just in answer to the last part of the question, you know, like, did this book, you know, look anything like I had envisioned it? And the answer is absolutely not at all. This was supposed to be a book that had a contemporary focus. I published an article with Professor Blake Halonen back in, I think, maybe like 2016 or 17 about the Netflix prize, and that was originally supposed to be, you know, like, one of the case study chapters. It was going to be a totally contemporary book, but then everybody started writing about algorithms and contemporary stuff, and it was great, and they lapped me. And so I'm like, what else do I have to say? So I went the historical. In 2015, I published another sort of related article article called Algorithmic Culture, which is where I started to piloted the methodology of keywords. But the words that I focused on were information, crowd, and algorithm, only one word of which algorithm made it into the final book. So you can see that there was quite a process of winnowing here, and it took me a really long time to figure out or find the story, which in many ways, I'll admit, is still kind of like an arbitrary one, just in terms of how and where the boundaries are drawn. Like, I do think you could tell this story similarly and differently, depending on kind of where one sort of turned the spotlight. And the other thing I would just say here, too, is that I really see this narrative of the book existing in the midst of a lot of overlapping narratives about culture and computation, some of which I engage in the introductory chapter and at different points throughout. So, yeah, this is a book that had a beginning that ended up looking almost nothing like the ending.

Jeffrey Herlijimira (48:18)

Excellent, Excellent.

Ted Strefas (48:19)

Wow.

Jeffrey Herlijimira (48:19)

Words as a bearer of those changes. That's in my notes right now. Excellent stuff. Excellent stuff.

Ted Strefas (48:24)

Scott.

Jeffrey Herlijimira (48:25)

So kind of building on that question, is there anything that you would change if you were to kind of come back and. Well, or how about if you were to write a sequel? Like, where would you start?

Ted Strefas (48:36)

Yeah, well, the thing that was happening. So I finished the book manuscript, I think it was in. It would have been in 2022, the fall of 2022. That's when the final revisions were made. And so, you know, this was essentially. What would that be like a year before ChatGPT launched? It was almost exactly a year before ChatGPT launched, if I'm recalling correctly. I could be a little bit off on the timing, but in any case, like, the book was written with a kind of, you know, nascent awareness of AI as it relates to these kinds of questions, but it was not ready to confront them, because in some ways the technology wasn't quite yet publicly available. And so, you know, if I were thinking about, you know, a sequel or a rewrite of this book or whatever it happened to be, I mean, it would really have to put artificial intelligence front and center, which is, you know, there's overlap with algorithmic decision making, but it's not exactly kind of like the same, you know, set of questions. And that's in part because, you know, algorithms are very much, you know, procedural, and they are sort of beholden to, you know, kind of step by step progression of instructions. You know, make this decision if this input comes, make that decision if that input comes, and so on and so forth. Whereas, you know, with the large language models and things like generative AI, it's, it's a bit more improvisational, if there's kind of like less, you know, there's more guidance than formal instruction, I guess, for lack of a better way of putting it. And so the thing that's like, really interesting for me is, you know, with algorithms, when we're talking about cultural decision making, we're talking about following essentially pre prescribed procedures by means of which to say yes to this thing, no to that thing, or yes to this output, no to that output. Generative AI is different because there is a kind of ostensible creativity there. And I say ostensible because mostly a lot of the creativity is a function of pattern and pastiche. And so you'd have to really think about what it means to use computational tools not only to make decisions about culture, the algorithmic piece, but actually to make culture. I mean, I think that's the critical question that we're thinking about or that I would be thinking about here just if I were imagining kind of like an extension of algorithmic culture before the Internet. That question of creativity, I think is really critical. And it also then raises that question, which is, what is culture when human beings are not the only ones producing it. Previously it was what is cultural decision making when people are not the only ones making the decision? But the locus of the question seems to be shifting now.

Jeffrey Herlijimira (51:25)

Awesome. Awesome. I wanted to just follow up before Alex, as this hour has flown by, but I wanted to ask. I wanted to just follow up for Alex as our final question. One of the things that you said that kind of just stuck with me is about people jumping the turnstile and thinking about the ways that, that people, well, how do they play with the algorithms? I mean, the people are there, resistance, the solidarity against them, and about playing with them a little bit, I would say. Just one thing that I do is. But I have to use Amazon because there's not a lot of other options that things that deliver here to Puerto Rico. And I looked up shower curtain one time, and all of a sudden I was a shower curtain man. They were shower curtain stuff. And so I started that. So I did, like, these fake searches, hot sauce, model airplanes, you know, things. Things that I want to get, I'd rather have in my suggestions. So those are all really cool angles. And so they're in the. So the algorithm is attempting to control us, but it's. But is it. To what degree does it succeed? You know, how do we jump the turnstile? I think that's. That's. That's what. A really interesting point that you brought up. Thank you.

Ted Strefas (52:29)

Yeah.

Alex Rivera (52:29)

So. So, yeah. So basically now we want to move a little bit more in the context of our Java Eco, particularly in Mayaguez. So I want to ask this question. You can situate the argument with Puerto Rico today. What can a reader, specifically a student in Mayague today use, learn and apply from your book in their life or academic career?

Ted Strefas (52:56)

Yeah. Thank you for asking this question. And, you know, just caveat here. I'm no expert in Puerto Rico. I have been to the island twice and only very briefly. So just, you know, all of those caveats certainly apply here. And just with respect to the answer, then, you know, it has to really be just provisional ideas. And these are ideas for which I would invite feedback or even pushback, given my very limited experience visiting Puerto Rico. So, like, one thing I would think about here is just again, that line that we talked about a little while ago, that line of argument which is about defining and redefining terms, right? To not underestimate the degree to which language is and can be a source of power and empowerment. I think that that's a really important point for students to take away because again, thinking about the kind of model of the dictionary, right? It's this authoritative source that you go to. To do the work of defining terms, right? But what would it mean to feel as though you were empowered to define the terms of your life? Like, that's a very different relationship to words and language. And so I think more students should embrace that also. Recognize, of course, then the limits of that, which is like other people have to accept your definitions, and you have to do the work to get them accepted. But to recognize that we do have that power in agency, I think is a critical thing that. That students, and really anyone should. Should Maybe take away. Second thing I would say is also then the methodology of keywords. I talked a little bit about this before, but the thing to recognize here is not only was it forged in, you know, print culture, but it's, you know, forged within a decidedly English language context. Right. And so what we have to recognize here then is the linguistic and experiential, you know, kind of like centrism of that methodology, of that paradigm. And also then maybe, you know, students need to start thinking about other models that they could look that would challenge that Anglocentrism. And I'm thinking about two in particular. One is a project by Gent's called Keywords Reoriented, which is a kind of comparative keywords project looking at English language and Asian languages, specifically Chinese. And then another project, related but also a little bit different, is Escobar et al's Pluriversal Dictionary project, which really tries to de center through a kind of keywords project, but never saying that it's beholden to Williams or keywords. That really tries to dissenter the experiences of the global North. And I think that that would be a really interesting kind of project to undertake from the vantage point of Puerto Rico. So, like, think about, you know, what would keywords look like not only in the Spanish language or even comparatively across, you know, say, Spanish and English, but more specifically, you know, Puerto Rican Spanish or with respect to a kind of broader Caribbean frame of reference. Right. I think these things would be really interesting for students in Mayaguez to start to think about and to explore. And then kind of lastly, the idea of the Algorithmic Culture book is in part that we need to develop new vocabularies and repertoires of language to help people imagine different technological worlds. And it seems to me that Puerto Rico would be just an incredible location. Right. An island, a space between political worlds, a cultural crossroads where students could undertake that work. So there's just, you know, so much possibility here. I see. For. For your students to engage with these ideas, but really to take them in a direction that I know because of my own, you know, experiential and linguistic and geographic limitations that I was unable to take them.

Jeffrey Herlijimira (56:57)

Wow. Excellent. Yeah, I have to agree. I mean, I feel like here in Puerto Rico, there is. The students are endowed with cultural and linguistic sensibilities that are very unique. Where can you be, have your own voice and you can articulate your own. You know, I feel like here we have this really, the fact that we're an island and two being, you know, distant from the mainland I think creates that very healthy distance from those certainties that are expressed in a certain way speaking Spanish or English or their blends. So thank you for that. I have to agree, Alex. So thank you guys. This has been a wonderful conversation. I'm so happy that we got the chance to sit down and to talk to you about this book, Ted. And if you're coming to Puerto Rico again, we'd love to have you give a talk here at our campus. Please spread the word and come and we'll set up some excellent activities for you.

Ted Strefas (57:51)

Yeah. Whenever I'm there. Consider it done.

Jeffrey Herlijimira (57:54)

Excellent. Excellent. So thank you guys so much. Alex and Ted, I have this last little bit I wanted to say so. The celebration of the digital ties strives to justify an intrusion into human life and into human thought. Ted Streefas wonderful book sets a pre digital infrastructure to understand the problems of the present. So thank you very much for this book and thank you for the conversation today.

Ted Strefas (58:35)

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