Algo-Lit
An Introduction to AI Literature

ENGL 116B | Prof. Daniel Scott Snelson
http://dss-edit.com | dsnelson @ humnet
Tues & Thurs | Rolfe 3121 | 12:00 – 1:50pm
Office Hours held in Kaplan 203 (IRL/Hubs)
Book here: danny snelson .youcanbook.me

PROMPT

We might begin by asking, what is not algorithmic literature today? Rather than introduce algorithmic literature or “algo-lit” as a distinct literary category, this course wonders if it’s still possible to consider literature beyond the algorithmic conduits that characterize the networked present. The creation and study of literature today is facilitated by a range of digital formats and networked consoles, each of which introduce new practices of production, circulation, reception, and reading. Alongside these transformations, we’ll explore a range of new literary genres inhabiting, for example, computer scripts, image macros, social media, sound releases, interactive applications, video games, and print-on-demand books. Thinking through the present, this introduction examines the history and future of literature through the everyday experience of the algorithms that run computers and electronic devices. From the history of digital poetics to recent internet publications, we’ll track the development of literature under the influence of algorithmic computation up to works published in the present, as they emerge throughout the quarter. In lockstep, the course considers the category of “algorithmic literature” as a way to think about historical works remediated to the internet, in a wide range of (post-)digital and generative AI formats. The course requires short weekly critical experiments in an open format, as well as a final project, which may be critical or creative in form, developed in conversation with the instructor. No previous experience in programming, poetry, or literature is required.

Required Texts

Every effort will be made to make course content freely available or via university resources. This will be a topic of conversation as we formulate our syllabus

Syllabus Info

As a general outline for the course, take note that these are broad strokes subject to change. This course is fully interactive, growing and responding to its users. Each week will build on previous weeks, class conversations, and the directions that our experimental study happens to follow. The content of the syllabus will be updated regularly as a result, though the requirements will remain fixed. The syllabus will only be completed after we finish the course, and all research (including your own) has been collected

Attendance Policy

Given the brevity of the quarter, unexcused absences will cut into your participation percentage. If you must miss a class, it is your responsibility to make arrangements with me both before and after the absence. Proposals for interaction commensurate with a two-hour session will be accepted.

Learning Outcomes

This course will develop critical and creative tactics for experimenting through, with, and for algorithmic literature. Through a series of experiments and collaborative productions, a substantial body of critical and creative work with algo-lit will be generated. Alongside creative scholarly production, students will learn new critical trends in literary studies and the digital humanities. Particular attention will be paid to gender, race, class, and ability in these works. Technical and poetic proficiency will work hand-in-hand to develop new perspectives on digital culture and today’s digital (and post-digital) literary platforms.

Discord Server

Throughout this course, our central meeting place will be Discord. To the uninitiated, it’s a chat server that we’ll be using as our Course Management System. All news and information about the course will be conducted over Discord. An invitation and signup to the dedicated (private) server will occur on our first meeting. This is a platform for informal conversation, weekly experiments, and advance preparation for course meetings and play sessions. Responsive posts are encouraged.

Online Posts

This course will double as an online research group that gathers, generates, and comments on algorithmic writing. We will use a variety of platforms to create new readings of the works we study and to gather inspiration from fellow travelers. All work posted to the “wider internet” must be psuedonymous, operating under an invented avatar. This is simultaneously a creative decision and a means of guarding your privacy to enable experimentation across the internet. We’ll discuss this aspect of the course over the first week, and further revision to the process of posting and sharing may respond to course use patterns as they develop.

Laptop Use

We will be *playing* in a variety of modes—part of the course will be to learn how to work in these platforms in a university setting. How does one have meaningful conversation while playing a game? What does a collaboration using ChatGPT look like? What collective literary works might emerge via Google Docs? Throughout, we’ll interrogate the form and function of our technology alongside the literary works we discuss each week.

As such, the course will require access to a computer and adequate internet access in order to fully participate in the range of activities we will explore. If you have any questions or concerns about your setup, please feel free to write or meet with me at any time.

Access Note

This course aims to facilitate access to research and exploration across a variety of platforms. Please don’t hesitate to draw attention to any point of access that might be improved: from the volume of the conversation, the size of text, the digital access to the texts, and so forth. All possible accommodations will be made. Additionally, or for more information, you may contact the CAE at (310) 825-1501, or access the CAE website at www.cae.ucla.edu.

Course Actions	Due Date	% of Grade
Course Participation & Play. (See descriptions above.) This is a collaboration-based course. We only get to meet on a handful of occasions this quarter—your input before, after, and during each session is paramount to the course's function & collective success.	Ongoing	20%
Experiments. This course will require weekly experiments with our selected works. Your timely engagement with the weekly experiment will enable the ongoing conversation of the course. Please note that these are experiments in the fullest sense—you are expected to play, fail, discover, and surprise yourself. Grades will be non-qualitative given timely assignment fulfillment.	Ongoing, due Wednesday evenings	30%
Discord Server Interactions. Playful, constructive, collaborative, civil, expanding, informal conversation should characterize the "virtual classroom" that is Discord. This includes: gathering & sharing resources; responding to peers' works & sharing your own creative process; idle chatter; pet pictures; etc. Before each session, you should at minimum share: 1) Mondays: post your reflections on the work(s) and reading(s) for each session. Wednesdays: alongside your experiment, post reflections on the process & related materials. Post at least two responses to peers' works or commentary on both Monday & Wednesday. 2) Collective Research: due by Thursday of each week, post one link to a work of Algo-Lit for the week ahead. Duplicates get no credit! 3) Something else (to any Discord channel: enrich our community!).	Ongoing, due before class meetings	20%
Final Project. Open format, open platform, full creative license. Play with a system we haven't had a chance to explore or develop a previous experiment into a full-fledged work. Must synthesize and respond to course materials & conversations. Collaboration, invention, exploration all encouraged. Group finals are entirely encouraged. We will develop the scale & scope of final projects in conversation. At its core, you will use an experimental technique to respond to the algorithmic format of your choice.	12.17.23	30%

Thematic

Tuesday

Thursday

Week 0 — Introduction to Algo-Lit

Tool Aggregator:

There’s An AI For That

Field Mapping (advance models):

Rita Raley & Jennifer Rhee, eds. Critical AI: A Field in Formation (2023)

Katherine Bode & Lauren Goodlad, eds. Critical AI: Data Worlds (2023)

Play:

Collectively determine experimental grounds for our collective study & play of algorithmic literature.

Read:

N. Katherine Hayles, “Electronic Literature: What Is It?” (2007)

Week 1 — Poetry & Poetics

Anti-AI Tools:

Glaze

Nightshade

Explore:

Allison Parrish, Portfolio (2007-22)

Lillian Yvonne-Bertram, “A New Sermon on the Warpland” (2021)

Sasha Styles, Technelegy (2023)

Ana Maria Caballero, bitforms (2023)

Joy Buolomwini, Poet of Code (2023)

David Jhave Johnson, ReRites (2017-19)

Read:

Christopher Funkhouser, “Digital Poetry: A Look at Generative, Visual, and Interconnected Possibilities in its First Four Decades” (2006)

Collective Experiment:

Produce a collaborative work of speculative algo-lit scholarship.

Imagine you are a literary historian writing an academic book in the year 2063, looking back on the last four decades of AI-generated literature. Prompt GPT to produce a coherent study of the politics, ethics, movements, outliers, and significance of 40 years of algorithmic literature.

Week 2 — Narrative & Storytelling

Tools:

We’ll collect tools in this column, but a variety of aggregators can give you the most up-to-date lists of what’s available to play with.

For example, see: There’s An AI For That, linked above

Or, for a more curated list, see: Filipe Calegario, Awesome Generative AI List (a well-curated list of critical, technical, and practical tools for AI generation across a range of media types and modalities)

Explore:

Latitude, AI Dungeon (2019-)

Unsupervised Pleasures (queer.ai), “Ultimate Fantasy” series (2020-)

Botnik, Harry Potter and the Portrait of What Looked Like a Large Pile of Ash (2018) (see also: Demon Flying Fox, Harry Potter by Balenciaga (2023)

Ross Goodwin, 1 the Road (see also: Automatic On the Road) (2018)

NaNoGenMo + Zach Whalen, NaNoGenMoCat (2013-)

Read:

Minh Hua and Rita Raley, “Playing With Unicorns: AI Dungeon and Citizen NLP” (2020)

Matthew Kirschenbaum, “Prepare for the Textpocalypse” (2023)

Bonus (optional):

Emily M. Bender, Timnit Gebru, Angelina McMillan-Major, Shmargaret Shmitchell “On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜” (2021)

Models:

Vauhini Vara, “Ghosts” (2021)

K. Allado McDowell, Pharmako-AI (excerpt, 2021) (see: Elvia Wilk “What AI Can Teach Us About the Myth of Human Genius,” (2021))

Experiment:

Produce a narrative work of algo-lit.

Collaborate with the generative text algorithm of your choice (GPT, Bard, etc) to produce a new work of literature. Develop a framework for delineating your (human) input and the text that is generated (algorithm). Develop a way to indicate the process of its generation. Play and experiment with the form that an algo-collaboration might take.

Week 3 — Art & Aesthetics

Tools:

DreamStudio.ai (stable diffusion interface)

Playform.io (training for artists)

Lookx.ai (architecture tools)

Explore:

Lina Dounia, Mostly GAN + Mostly Prompt Works (-2023)

Sophia Crespo, Selected Projects (-2023)

Nora Al-Badri, Works (-2023)

Jenna Sutela, nimiia cétiï + Making of (2018)

Minne Atairu, Igún + Hair Studies, (2020-23)

Kashish Hora, This X Does Not Exist (2023)

Refik Anadol, Unsupervised (+related @MoMA) (2023)

Melissa Heikkilä, re: Greg Rutkowski, MIT Tech Review (2022)

Jerry Becerril, Assessment Examination (Survey Horror) (2023)

Watch:

Shalini Kantayya, Coded Bias (Netflix, 2020)

Read:

Mashinka Firunts Hakopian, The Institute for Other Intelligences (2022) (excerpts posted to Discord) (+optional: video)

(Extended cut: Hakopian, “Art histories from nowhere: on the coloniality of experiments in art and artificial intelligence” (2023))

Models:

Kira Xonorika, Expanded.Art: “Exploring Identity through Gender and AI” (2023)

Moresin Allahyari, ماه طلعت / MOON-FACED (2022)

Experiment:

Produce an aesthetic work of algo-lit.

Produce a work that reveals the limits of AI image generation OR that reveals the limits of the IRL world. In other words: you may work in either direction. On the one hand you may use image generators against themselves to reveal their limitations, biases, errors, or flaws (see, for example, Hua’s work on the limited gender imaginary of Craiyon). On the other, you may use image generators to imagine something otherwise impossible to see in the world (see, for example, Kira’s speculative imaginaries of hyperhumanity). Or, as always, eschewing both: you may meditate on these themes using the image-making media (paper, canvas, stylus, etc) that you prefer.

Week 4 — Comics & Memes

Selected Tools:

The Dall-e 2 Prompt Book

How Dall-E 2 Actually Works

Explore:

Ilan Manouach, Fastwalkers (2021) (+works) (See also, “A Deep Learning Pipeline for the Synthesis of Graphic Novels” (2021))

Yannis Siglidis (with Manouach), The Neural Yorker (2020-23)

Zach Whalen, VAUDn oc HORRRR (2020) (see also this thread)

Steph Maj Swanson (Supercomposite), LOAB (Content warning: body horror) (2022)

Dina Kelberman, I’m Google (2011-present)

Max Read, “Is A.I. the Greatest Technology Ever for Making Dumb Jokes?” (2023)

Eliza Strickland, DALL-E 2’s Failures Are the Most Interesting Thing About It (2022)

Explore subreddits: r/aigeneratedmemes, r/dall_e_memes, and r/SubSimulatorGPT2 among others (2023)

Read:

Hannes Bajohr, “Operative Ekphrasis: The collapse of the text/image distinction in multimodal AI” (Preprint, 2023) (See also: “Dumb Meaning” (2023))

Nicolle Lamerichs, Generative AI and the Next Stage of Fan Art (2023)

Models:

Steve Coulson + Midjourney, The Bestiary Chronicles (2022-23)

T. Kingfisher, A Different Aftermath (2022)

Christen Bach, Entering the Data Core (2022)

Rian Sygh, Dall-E Mini Twitter Comic (2022)

(See, for example: AI Comic Books and The Comics Beat Roundup)

Experiment:

Produce a sequential work of algo-lit.

Using the format of your choice, produce a comic (or a collection of memes) about AI-generated images that uses SOME FEATURE of algorithmic production. For example: the algorithm may produce images that you caption, or you may use an AI-generated script for original drawings or photos. Or: following Manouach et al, develop your own pipeline to generate the entire work with off-the-shelf AI tools. See models above for image-production ideas. Imagine new ways to perform the articulations of “operative ekphrasis.”

Week 5 — Music & Sound Art

Tools:

Never Before Heard Sounds

Loudly

Boomy

Soundful

WZRD (responsive vis)

X-Minus Pro (karaoke versions)

Explore:

Dustin Ballard, There I Ruined It (2020-present)

AI Remix Sampler: Drake/Weeknd Heart on My Sleeve (see NYT’s take), The Beatles “Now & Then” (see BBC), AISIS (Oasis): The Lost Tapes, Winehouse Lost Tapes of the 27 Club, Kanye West Delilah, Kurt Cobain Young and Beautiful, Toad Sings Chandelier (and IRL precursor), Sinatra Where Is My Mind? +MANY OTHERS, see: r/AI_Music

Quosmo Lab, AI DJ Project (2018-)

Dadabots, RELENTLESS DOPPELGANGER \m/ \m/ \m/ \m/ \m/ \m/ \m/ \m/ \m/ \m/ \m/ \m/ \m/ \m/ (2019-)

Complex, AI Future Roundtable (2023)

Spotify, AI DJ (2023-)

Archinet, Audio AI Timeline (2023-)

Read:

Mark Fisher, “What Is Hauntology?” (2012) + excerpts from Ghosts of My Life: Writings on Depression, Hauntology, and Lost Futures (2014)

Mary Caton Lingold, Darren Mueller, and Whitney Trettien, “Introduction” to Digital Sound Studies (2018)

(Optional: Ge Wang, “Humans in the Loop: The Design of Interactive Ai Systems” (2019) (see: Music & AI))

Models:

Holly Herndon, Holly+ (2022), Jolene (2022), and Proto (2019), (see also: Herndon and Matt Druhurst, Interdependence Podcast (2020-) and Have I Been Trained?, (2023))

Grimes, Elf.Tech (2023)

YONA (Ash Koosha and Isabella Winthrop), Oblivious (2018) (Dazed interview) (Auxuman Vol. 1)

Brud, Lil Miquela (2016-) (VH profile) (“Meet Miquela: The A.I. (Artificial Influencer) Who’s Now Worth $125 Million“)

VOCALOID, Hatsune Miku (2007-) (see: Wiki summary) (see also: Rice, Explaining Voicaloid (2021))

Experiment:

Produce a sonic work of algo-lit.

In this two-part experiment, we’ll use the tools explored thus far to imagine a fictive character, modelled on Lil Miquela, Spawn, Yona, Hatsune Miku, and others. Introduce your synthetic character with a name, image, description, and some sonic material (of your choosing), along with anything else (!) posted to the streaming platform of your choice (SoundCloud, Bandcamp, YouTube, etc). Some (or all) elements of your character should use generative algorithmic techniques. Early drafts are due for Thursday’s session (where we can workshop and continue collective development). Next week, we will build in performative and speech-synthesis components to these characters.

Week 6 — Voice & Performance

Tools:

Seamless (see info)

VOCALiD (see Northeastern profile)

Revoicer (see Washington Post profile)

Many others (see Theresanaiforthat)

Explore:

Stephanie Dinkins, Conversations with Bina 48 (2014-ongoing)

Brent Katz, Josh Morgenthau and Simon Rich, I Am Code: An Artificial Intelligence Speaks, Poems by code-davinci-002 (2023) (samples at WP) + Audiobook voiced by Werner Herzog (see NYT)

Amanda Morris, Alexa Juliana Ard and Szu Yu Chen, “Patients were told their voices could disappear. They turned to AI to save them” (2023)

DAISYS.ai, AI Shakespeare (2023)

Rob Price, “APP, LOVER, MUSE” (2023)

Mario Klingemann, A.I.C.C.A (2023)

MeowTalk (2023)

Explore spoken audio resources: UbuWeb Sound & PennSound (1995-ongoing)

Read:

Amina Abbas-Nazari, Golden Owens, Michelle Pfeifer, and Dorothy R. Santos, Sounding Out!: Racial Bias in Speech AI Series (2023)

Tiina Männistö-Funk & Tanja Sihvonen, “Voices from the Uncanny Valley: How Robots and Artificial Intelligences Talk Back to Us” (2019)

(Bonus) See: Liz W. Faber, Introduction to The Computer’s Voice: From Star Trek to Siri, “The Talking Computer Paradox (Dis)Embodied Gender and the Acousmêtre” (2020)

Models:

Lauren Lee McCarthy, LAUREN works (2017-ongoing) (see McCarthy “Feeling at Home: Between Human and AI“)

Jack Vedal, Neuro-Sama the AI VTuber (2023) (see Automaton and Bloomberg)

Virtual Humans (2020-)

Experiment:

Produce a performance work of algo-lit.

Working with your constituted avatar groups from last week, develop some form of collaborative approach to your avatars. (Also, you may use your developed avatar from last week or invent a new one if you prefer.) This can take many forms: perhaps they interact online, perhaps they record a song together, perhaps their internal struggle is recorded as an audiobook of AI voices? IDK: forge your own path as a group! It can be as highly COORDINATED (say, active full member participation) or DISPERSED (say, a game plan for your group where everyone works individually) as you like. The only requirement is that you use some form of synthetic SPEECH or PERFORMANCE (broadly construed: for example, comment threads are a kind of performance) — that interacts IN ANY WAY with other members of your group.

Week 7 — Moving Images about AI

Selected Home Cinema Screenings:

Metropolis (1927)

Bladerunner Series (1982-2022)

Wargames (1983)

Terminator Series (1984-2019)

A.I. Artificial Intelligence (2001)

The Matrix Trilogy (2001-2021)

Dennou Coil (2007)

Wall-E (2008)

Black Mirror (2011-2023)

Her (2013)

Ex Machina (2014)

Plastic Memories (2015)

Love Death + Robots (2019-2022)

Mitchells vs. the Machines (2021)

M3gan (2022)

The Creator (2023)

Final Project Demos:

By Wednesday night, post a short demo (any length, but give some sense of what shape the project might take) as well as a “pitch” of ~200 words for your final project. Let’s break down those two components:

1) THE DEMO: this should use the platforms / forms / media that you’re imagining using for your final project. It can be a short test, or a small sample, or a starting point to your larger project. But it should, at minimum, TEST OUT some idea you may have for your final (you’re not stuck with this idea, of course, totally subject to workshopping, but getting a test going is the best way to start and see if an idea is feasible).

2) THE PITCH: this should outline what you imagine your final project will be. Your pitch should include: the form, the platform, the content, and the significance (or argument) of your project. How will your work speak back to the systems we’ve been studying? What critiques or insights might it offer? What does it surface in algorithmic writing? How does it perform its argument? What are your hopes and dreams for this project? For now, think BIG, be ambitious. We’ll workshop and discuss challenges and scale on Thursday together.