The naughty algorithm, the chaotic algorithm, the baby algorithm who is still learning, the "dumb," unnuanced algorithm. All these are "algorithm adjectives," real terms we have observed in use at scholarly conferences focusing on the present and near-future of publishing. These adjectives are not exclusive to the scholarly sphere, but find their equivalents in media reports: flawed, secretive, shaky, and uncanny algorithms.1`                                    

Algorithmic adjectives are anthropomorphic, bringing aspects of humanity to evolving understandings of artificial intelligence. We are scholars attuned to digital change, who pay attention to the growing role of algorithms in the decision-making processes of publishing and reading. We are also scholars attuned to people, curious about the emotional discomfort that algorithms generate. This discomfort, in society and in academia, is apparent in the anthropomorphic adjectives mentioned above. So the Post45 Contemporaries call for a "Reading with Algorithms" Cluster, with its encouragement to deliver "experimental pieces/formats befitting the topic," inspired us to develop our thinking about these algorithmic imaginings. Adjectival approaches to algorithms, we argue, are revealing about the discursive practices used by scholars and industry professionals, and about people's affective relationships to the things books that algorithms act upon. These adjectives demonstrate emotional responses towards algorithmic culture, responses that are largely negative, critical, or dismissive. We decided to learn more about these practices by testing what happens when we present book recommendation algorithms as truly anthropomorphised little things. Such an experiment derives from our conceptual school, "Ullapoolism," developed over several years in order to bring a creative/critical, arts-informed approach to our study of contemporary publishing and the creative economy more broadly. Ullapoolism is post-data, activist, and autoethnographic, drawing on situated knowledge that enacts creative critique and playful experimentalism. We used an Ullapoolist approach in a prior Contemporaries cluster, "Ecologies of Neoliberal Publishing." That piece, "Megativity and Miniaturization at the Frankfurt Book Fair," is an investigation of size, scale, and value at the world's biggest trade fair for the publishing industry. During fieldwork at the Frankfurter Buchmesse, we measured parts of the Fair, got lost in others, and then made miniature versions of it when we got back home.2

Critical approaches to reading (and publishing) with algorithms are rapidly developing, as the work within this cluster so amply demonstrates. As we set out to explore a specifically Ullapoolist intervention, we asked ourselves the question: how are we to imagine the role of algorithms in the publishing industry of the future? More specifically, how might the two of us, publishing scholars known for our unusual research methods, tackle this central theoretical and practical question? How might a playful humanising of book algorithms draw attention to social, material, and even epistemological relations in book culture?

"Breakfast with AlgoBooks" builds on existing and emerging critical scholarship of algorithmic culture, but takes a sideways, creative approach in order to reveal and play with societal as well as scholarly assumptions underpinning that scholarship. (Please note that if you'd like to get involved by performing this article as a play, you'll need seven characters plus a narrator, along with some chairs that look comfortable, various props, a dog, and a baby.3)

Our creative approach is informed, and furthers, conceptualizations of algorithms "as culture" and "composed of collective human practices." In his ethnographic research with music tech companies, Nick Seaver explains that such conceptualizations often move away from the "popular critical discourse that pitted algorithmic recommendation against human curators, claiming that 'algorithms' could not understand music well enough to recommend it." Rather, many of  the workers Seaver interviewed expressed a different viewpoint as "humans within a system described as inhuman," that "'algorithms are humans too,' [as] one of [Seaver's] interlocutors put it."4 In "Breakfast with AlgoBooks," we take this ethnographic, algorithm-as-culture, argument to a logical if absurdist conclusion, generating a creative ethnography that makes algorithms sort-of people.

We wanted to create something, then, where the anthropomorphised little things existing in the heads of many are encouraged to speak (sometimes even to speak back) and in so doing to further interrogate the affective stances taken at the intersection of algorithmic and book cultures. Several modes for presenting our anthropomorphised creatures could be imagined: a podcast, a cartoon strip, or an "it-narrative" (a story told from the point of view of a thing).5 Ultimately, the idea we decided upon to showcase our anthropomorphised book algorithms is one that has a long history in book culture: the book-themed segment of a TV chat show.

Reader recommendation services have long been offered through mass media. The middlebrow book culture of the mid-twentieth century, for example, had a strong association with radio.6 Contemporary scholarly and industry interest in the mediatisation of book recommendation was piqued by the phenomenon of Oprah's Book Club, which started in 1996; and by the Richard and Judy Book Club, a section of the popular UK Richard and Judy chat show that commenced in 2004. Today, much book recommendation action has moved to social media, but book chat is still a feature of the television landscape: NBC's morning TV show Today co-host and former first daughter Jenna Bush Hager runs a very successful eponymous book club across both the TV show and social media.

Scholars have argued that book chat segments on television programs promote a view of book culture as domestic, feminized, and warmly relational that is, as middlebrow.7 The morning television talk show itself is a feminized form. As Helen Wood details in relation to the British context, the mid-morning time slot "is significant for terrestrial channel schedules as it is marked out for the housewife-consumer."8 While chatbots and other forms of artificial intelligence are often gendered as female think of the default voices of Alexa and Siri this gendering is designed to flatter the egos of male consumers along with any others who have internalized the patriarchy.9 Taking algorithms out of the realm of the tech-bros and into the women-oriented frame of morning TV allows for new discursive practices to develop. It prompts questions about the targets and mechanisms of technology and capitalism: who the consumers are, and for whom the programming (of algorithms, of television shows) is done. Our contribution to this cluster brings the scholarly insight around the gendering of middlebrow book culture into (literal) conversation with digitally-enabled, platformised recommendation modes. Can algorithms be domestic, feminized, warmly relational?

Our experimental intervention, then, is written in the format of a light, magazine-style TV chat show: "Breakfast with AlgoBooks." In this segment, the book Algos explain their recommendations to eagerly awaiting viewer-readers. The script anthropomorphically imagines what's going on inside the heads of the algorithms, the effects they produce, and their responses to human feedback.

A jauntily handwritten character list, announcing, within a TV screen-like box: Breakfast with AlgoBooks! ... with your host ALLY! ... and ... SUBBY SERENDIPITY SKELTER STAR SNOOT +baby SPROG! +SPOT the dog!

Meet the Algobooks!

Sshh, the show is about to begin . . . 

10am. The theme tune plays. Type dances across the screen . . .


Cameras focus on 7 plush chairs, upon which are seated 7 sort-of people of various shapes, colours, sizes. The music fades, and a female-type character smiles warmly at the camera.

An artist's impression of a screenshot of the Algos in the Breakfast with AlgoBooks studio.

(An artist's impression of a screenshot of the Algos in the Breakfast with AlgoBooks studio)

ALLY perkily: Welcome to Breakfast with AlgoBooks, the only TV show where you can hear direct from Algorithms themselves about how they make reading recommendations to you, our worldwide community of algorithmic readers!

Digitally created carousels of books fly across the screen, pouring from all sides, taking seemingly haphazard pathways as the theme tune plays again . . .

ALLY: This morning, we have a very special edition of the show. Normally we invite one or two guest Algorithms to join us, but today we have not one, not two, not three, but six Algorithms and me, your resident cyborg helping all you full humans navigate the gap between human and machine! The Algos will be making recommendations to you and boy! do we have some super suggestions but we'll also have a conversation about what it takes to make a great Algorithm. You'll be hearing some trade secrets today, some candid insights from those key voices who make our reading what it is . . .

The Algorithms on either side of Ally react in various ways to her opening remarks: a beaming smile; a wink; a dreamy glance beyond the camera; an unblinking stare directly into the camera.

ALLY turns to her left: First of all, welcome back from Algobabby leave, Subby! It's your first time back since having your own little algorithm Sprog who's here with you today.

Sprog gurgles adorably.

ALLY: And next to Subby we have our other regular guest algorithms, Snoot, and on my other side, Star. Always great to have you with us, and we've got a great recommendation enquiry coming up later on which I know you'll be very ready for. But before that, let me introduce our new guest Algos for today's special expanded segment: welcome Suspire, welcome Skelter and welcome Serendipity and . . . who's that by you, Serendipity?

The camera focuses in on a small black and tan dog seated quietly at Serendipity's feet, who looks up questioningly as the attention of the other Algorithms swivels to Serendipity.

SERENDIPITY: This is Spot. Spot the Dog.

Spot barks in a friendly manner.

SKELTER: I love dogs! Is he an Algodog, or . . . ?

Spot looks up questioningly at Serendipity again.

SERENDIPITY: lifts eyebrow. This is Spot. Spot the Dog.

SKELTER: Erm, OK. Can I pet him?

SERENDIPITY: If you must.

Skelter reaches a hand out to Spot, who licks it happily.

ALLY: Well, here we have a happy scene of Algobods and their dogs! Smashing! But let's get onto the business of book recommendation. Before we turn to the specifics of a particular request, though, I want to ask this illustrious panel several questions: What's it like to be an Algorithm? What is an Algorithm anyway? And what's it got to do with books?

All the Algorithms look thoughtful in their various different ways.

ALLY: Hmm, where shall we start . . .? Star, we've come to trust your recommendations very highly tell us more about how you work . . .

STAR adjusts a blue flower behind one earprong, and looks dreamily beyond the camera for a few seconds before starting to speak: Thank you Ally. It's a privilege to be able to speak today about this most special business of ours, although I prefer to call it a vocation. I like to think of an Algorithm as the deep wisdom of the universe, that knows you better than you know yourself. We quietly gather clues about you some call them data points but as those who know me will guess, I prefer a more mystical nomenclature signs, even. Once our net is full of information, we set to work without you even realising it . . . and then just the moment you are ready for it a recommendation floats down upon you . . . the perfect recommendation you never knew you wanted . . .

ALLY: Thanks Star! It's true that your recommendations always feel like an unexpected blessing. Snoot, tell us your approach . . .

SNOOT nods thoughtfully: Much of what Star says makes sense to me, but my approach is a little less how shall I put it celestial. Research shows that the best way to think of us cultural algorithms is as contingent, performative sociotechnical processes: partly human-designed, partly computational.

A fast-thinking assistant producer finds the specific research that Snoot airily alludes to, and a ticker tape display scrolls across the bottom of the TV screen. It reads:


SNOOT: For me, data points are crucial epistemological information. They allow me to make stretch recommendations for you. I'm going to recommend books you didn't expect, but which are still closely related to your previous choices. Think of me as your smart friend. I'll lead you to the books worth finding . . .

SUBBY: Well, sure, but not everyone wants to be stretched, and not everyone is trying to read great literature. As an algorithm, I'm a little more "of the people" I look at what everyone else has been buying, and reading, and yes, I take a little sprinkle of publishers' marketing budgets but it's just to capture oops I mean captivate readers, to bring readers and publishers together, so everyone knows what the biggest books are, the bestsellers that everyone (including you) will be talking about.

Another ticker tape display appears:


SUBBY: Algorithms like me sometimes get a bad rap for being basic, but I'm just trying to do my best by everyone in book culture. I don't think taking money from publishers is a problem.

Serendipity coughs.

SUBBY: You agree with me, right, Serendipity?

SERENDIPITY: My thoughts are a proprietary secret. You don't have enough money to find out what they are. Nor do publishers. Let me just say though: you can definitely trust individual tech billionaires. They *are* culture.

Skelter bends down and pats Spot, who yaps delightedly and turns round in circles

SUSPIRE: Well I have a different approach to all of you. I think "data points" reproduce human biases, as does "intuition". With respect, you Algorithms are making recommendations that will just lead to more discrimination, and more exclusion of readers and writers with marginalised identities. As an Algorithm, my function is to actively disrupt and work against the racism and sexism of existing decision-making processes in culture.

The assistant producer rapidly searches Google Scholar, and further ticker tape references appear on the screen:


SKELTER interrupting: Disrupt! That's what I do! Sheer chaos! No pattern! Total randomness!

SUSPIRE: Umm . . . no. No offence, but I'm not sure how helpful that is to anyone. I'm a crowd-funded social collective and I have very deliberate objectives. I'll recommend a book by a person of colour, a book from a small press in South Asia, a book about queer young people . . .

SUBBY: But books about queer young people are very popular right now!

SNOOT: and cool . . .

SUSPIRE: Well, yes, but I'll make sure this progressive development lasts and takes root. I don't want these books to be abandoned by publishers when they decide they need to make more money by discovering a new trend, the next big thing.

SERENDIPITY: Unless "the next big thing" is a colony on Mars, I'm not interested. You can just keep reading the thoughts of my master, in his upcoming memoir.

ALLY: Err . . . ok. Well, that's a variety of approaches. There's nothing simple about Algorithms! Let's see them in action with a caller from our at-home audience who is looking for a new book! And . . . we've got Noelle on the line right now, hi Noelle!

NOELLE line occasionally cutting out: Hi! Thank you Ally! I'm so excited to be calling in, it's my first time (aside: sssh baby, mommy's on the phone) . . . OK. So I've just finished reading the Booker Prize winner, The Seven Moons of Maali Almeida, by Shehan Karunatilaka. I really liked it but now I'm looking for something new. My question for AlgoBooks is, what should I read next?

ALLY: Over to you, Algos!

SKELTER: Hi! Seven Moons you say? Well then, can I suggest this mobile of the solar system? These plane tickets to Sri Lanka? Good Old Secret Seven by Enid Blyton? The Moons of Jupiter by Alice Munro?

SERENDIPITY: Settle down Skelter, I've got this. Serendipity here. I am going to thoughtfully recommend a book that people all around the world are loving and talking about right now. Freedom of Speech by Elmer Tusk. It got my cerulean tick, I can tell you.

SNOOT visible shudder: Ick, Serendipity. [Addresses guest by looking into the camera.] Hi, I'm Snoot. Did you say you'd just read the Booker Prize winner? I used to read those, but I've found that the Booker Prize has become very . . . middlebrow. Now I read the Nobel Prize winner each year. Have you read much Annie Ernaux? Her most well-known book is Happening, that's the one with the film adaptation, but I prefer The Years, it's much longer of course, a modern Proust. Needless to say I read it in the original French. My pal Subby probably disagrees with my choice.

SUBBY: Of course I do, Snoot. If anything the Booker Prize has just gotten more out of touch and obscure every year. If you're looking for something a bit more readable than Seven Moons, but also a mordantly comic crime caper, maybe you should try The Bullet That Missed, it's the third book in the Thursday Murder Club series by that funny UK guy from the TV, Richard whatsisname.

SUSPIRE: Can I interrupt, or should I say disrupt? I can't help but notice that all my Algorithm friends are recommending books by White people. Diversity in the publishing industry is really important and we can all make a difference through our reading choices. Based on your last read, which is great, can I suggest reading another book by a Sri Lankan author, perhaps a woman? Jean Arasanayagam's poetry collections are amazing.

STAR: I love that recommendation Suspire. But I'm going to suggest something different. [Staring deep into: the eyes of the guest/the camera/the middle distance]. I'm Star, and I know what a special reader you are. I know the book you need right now in your life. It's not logical, it's not based on a "formula". Sometimes books are pressed into our hands at just the right moment, with love, and I want to do that for you. The book you should read next is Middlemarch. Don't worry that the suggestion doesn't make sense. Just gorge yourself on the book, weep, film yourself weeping on BookTok. Feel your way through this reading life.

Ally and all the Algos (bar one, Serendipity) nod thoughtfully; emitting a mutual cheer and several soft yeses for their collective wisdom and Star's paean to the emotive power of books.

ALLY: Thank you, all of you. That was an incredible display of what Algos can achieve, if readers trust them a little, give them some space to generate ideas. I'm sure all of our watchers will agree that this very real diversity indicates how rich Algos are, and how readers should have faith that your manifold recommendations can be embraced wholeheartedly.

A barely perceptible flash of anger crosses Serendipity's otherwise impassive visage. "Nonsense," Serendipity mouths, holding up Freedom of Speech. Star glances fearfully at Serendipity, and notices Sprog has crawled over towards Spot. As Algobabby and Dog play hide and seek, Serendipity is mouthing the same phrase over and over again...

SERENDIPITY: Freedom of Speech! Freedom of Speech! Freedom of Speech! CERULEAN TICK!!!

STAR: Sprog! Come back from there!

SPROG starts crying: Bwaaaaaaaaaar!

Subby gets up out of the plush chair, and scoops up Sprog, who continues to cry, until words start to form.


STAR: NO! Subby, stop Sprog! That's evil talk!

SUBBY: Don't worry Star, Sprog is just repeating what Serendipity was saying. Just because Serendipity always recommends the same book doesn't mean Sprog will. Sprog is just learning to be an Algo at the moment . . . And you know children, they like the same book over and over and over again.

STAR: It's dangerous! People are always accusing Algos of being in the hands of big corps and tech giants! Of vested interests! You have to protect Sprog!

ALLY: Star, you're very upset . . .What's the matter? Sprog's back with Subby now, and look, Spot has joined them, ahhhhh . . .

Serendipity glares at Ally.

STAR: Thanks Ally . . . but this whole incident has made me think I don't want to be an Algorithm anymore.

SKELTER: Surely not Star! Your recommendations can be a bit . . . way out . . . but you're a great Algo . . .

Star sniffs, a tear falling from each eye.

STAR: It's just, well, I got some bad feedback the other day. It knocked me for six. I thought I was OK and I really enjoyed giving my recommendation just now, but I don't think I want to be an Algorithm anymore . . .

SUSPIRE: Oh, Star you mustn't read your reviews!

SUBBY: Absolutely not! Stay away from them. Humans are really cruel you know . . .

SNOOT: You're not tough enough, Star. You could ask for an upgrade build, some resilience perhaps, a bit of reflection . . .

SKELTER: Yes, let's all make some changes! Everyone stand up! Some music Ally?

Ally nods, gesturing towards the producer behind the camera. The gentle strains of a madcap tune from Mary Poppins start to play as the Algos get up and form a dancing jig. More books fly in carousels across the set. Sprog gurgles and Spot barks with delight, running round in circles, jumping up at Serendipity. Serendipity's cloak falls away, revealing clockwork whirring within. Skelter grabs a print book from the table and sticks it into the mechanism. Serendipity grinds to a halt . . .

SERENDIPITY: Cerulean tick! Ceruuuuuuu . . . tiiiiick . . . tiiiiiick . . . tooooock . . . . . .

SKELTER: Embrace the CHAOS!!! Disrupt the BIAS!!! Come on everyone, we can do good!!! Let us RECOMMEND!!!

Ally and the Algos (apart from the stilled Serendipity) form a wild rumpus. The studio fills with books, flying delightfully aloft above the Algos' heads. The Algos reach up and pull books down at random, open a page, read a few lines, and laugh, and cry, and look serious, and toss the books back up into the air, rumpus round again, and grab another book, occasionally showing the front cover to the camera as they whirl around gleefully, without ever tiring . . .

Ally moves to the front of the studio, and speaks directly into the camera.

ALLY: Well, what an episode of AlgoBooks that was! Thank you to all our guests and regular Algos. We'll be on air again next month please do send in your recommendation requests as usual. But this month we'd also love to see some pictures or even fanfiction focused on your favourite Algorithms. You know we love self-publishing as well! Goodbye from all of us! See you next time!!

As she speaks the rest of the Algos continue to rumpus, apart from Serendipity who is taken away on a stretcher. Spot stays with Skelter, leaping up at the books and occasionally plucking one out of the air.

Beth Driscoll and Claire Squires have, as Blaire Squiscoll, written The Frankfurt Kabuff Critical Edition (Wilfrid Laurier University Press, 2023), and often collaborate through the principles of Ullapoolism. You can read the Ullapoolist manifesto here:

Beth Driscoll (@Beth_driscoll) is Associate Professor in Publishing, Communications and Arts Management at the University of Melbourne. Her research focuses on contemporary book cultures across two main domains: socio-cultural practices of reading, and the global publishing industry.

Claire Squires (@clairesquires) joined the University of Stirling in 2009 as Director of the Stirling Centre for International Publishing and Communication. Claire's research interests focus on the history of the book, publishing studies and book cultures in the twentieth and twenty-first centuries, both in the UK and globally.


  1. Katherine Gemmell, "Amazon.Com (AMZN) Faces Class Action Suit Over Abuse of Secretive Algorithm - Bloomberg," October 20, 2022; Kari Paul, Johana Bhuiyan, and Charlotte Simmonds, "How Does TikTok's Uncanny Algorithm Decide What You See? We Tested It on Three People," The Guardian, November 6, 2022, sec. Technology; Casey Ross, "Epic's Overhaul of a Flawed Algorithm Shows Why AI Oversight Is a Life-or-Death Issue," STAT (blog), October 24, 2022; Ezgi Toper, "How TikTok's Shaky Algorithm Fails to Protect Users from Harmful Content," TRT World, October 26, 2022. []
  2. Ullapoolism has also extended to the writing of a comic erotic thriller set at the Fair, Blaire Squiscoll's The Frankfurt Kabuff (forthcoming in a critical edition from Wilfrid Laurier University Press), and ongoing investigations into the canapé as a synecdoche for book culture. A fuller explanation of Ullapoolism can be found in "The Epistemology of Ullapoolism: Making Mischief from within Contemporary Book Cultures." See  Beth Driscoll and Claire Squires, The Frankfurt Book Fair and Bestseller Business (Cambridge University Press, 2020),  Blaire Squiscoll, The Frankfurt Kabuff (Kabuff Books, 2019); Beth Driscoll and Claire Squires, The Frankfurt Kabuff Critical Edition (Wilfrid Laurier University Press, 2023), and  Beth Driscoll and Claire Squires, "The Epistemology of Ullapoolism: Making Mischief from Within Contemporary Book Cultures," Angelaki 25, no. 5 (2020): 137-155. []
  3. The first experimental performance of "Breakfast with AlgoBooks" took place at the 2022 Independent Publishing Conference in Melbourne, and was visually recorded in this tweet: Sophie Masson [@SophieMasson1], "A Playful--Literally :-) Presentation about Book Recommendation Algorithms at the Independent Publishing Conference. Https://T.Co/XukmVPJRLn," Tweet, Twitter, November 24, 2022. []
  4. Nick Seaver, "Algorithms as Culture: Some Tactics for the Ethnography of Algorithmic Systems." Big Data & Society 4, no. 2 (1 December 2017), 5, 3. []
  5. Leah Price, "From The History of a Book to a 'History of the Book,'" Representations 108, no. 1 (2009): 120-138. []
  6. Joan Shelley Rubin, The Making of Middlebrow Culture (University of North Carolina Press, 1992).[]
  7. For some of this scholarship see The Richard & Judy Book Club Reader: Popular Texts and the Practices of Reading, edited by Jenni Ramone and Helen Cousins (Routledge, 2011); Beth Driscoll, The New Literary Middlebrow: Tastemakers and Reading in the Twenty-First Century (Palgrave Macmillan, 2014); Cecilia Konchar Farr, Reading Oprah: How Oprah's Book Club Changed the Way America Reads (SUNY Press, 2005); Danielle Fuller and DeNel Rehberg Sedo, Reading Beyond the Book: The Social Practices of Contemporary Literary Culture (Routledge, 2013). []
  8. Helen Wood, Talking with Television: Women, Talk Shows, and Modern Self-Reflexivity (University of Illinois Press, 2009), 8.[]
  9. See Yolande Strengers and Jenny Kennedy, The Smart Wife: Why Siri, Alexa, and Other Smart Home Devices Need a Feminist Reboot (MIT Press, 2021).[]