Patrick Lichty Artist & Writer – Studio Visits Posthuman Atelier – CAS AI Image Art talk 2023 transcript

PATRICK LICHTY – Conceptual Artist, Writer

Discussion of project, “Studio Visits: In the Posthuman Atelier” before the Computer Art Society (of Britain).

All material is copyright Patrick Lichty, all rights reserved. The Computer Arts Society CAS talk AI & Image Art, 1 June 2023. For the full video please visit the CAS Talks page

Visit Patrick Lichty’s website here.

Patrick Lichty

Patrick Lichty

I am Patrick Lichty, an artist, curator, cultural theorist, and Assistant Professor of Creative Digital Media at Winona State University in the States.  I will talk about my project, a curatorial meta-narrative called “Studio Visits: In the Post-Human Atelier.”  Much of my AI work has yet to be widely shown in the West, as until two years ago, I had spent six years in the United Arab Emirates, primarily at Zayed University, the Federal University in Abu Dhabi.  I have been working in the New media field for about 30 years, dealing with notions of how media shape our reality.  So you can see some of my earlier work in this slide; I was part of the activist group RTMark, which became the Yes Men, the Second Life performance art group Second Front, and some of my Tapestry and algorism work.

This slide shows my 2015 solo show in New York, “Random Internet Cats,” which comprises generative plotter cat drawings.  The following slide shows some of the asemic calligraphy I fed through GAN machine learning.  I worked with Playform.IO’s machine learning system to create a personal Rorschach by looking for points of commonality in my calligraphy.  I called the project Personal Taxonomies, and other works, like my Still Lives, generated through StyleGAN and Playform.IO.  So I’ve been doing AI for about 7-8 years and new media art for almost three decades.  Let’s fast-forward to now.  I decided to go away from the PyTorch GAN machine learning models I used with my Calligraphy work and my paintings at in the middle of last year.  Switching to VQGAN and CLIP-based diffusion engines, I worked with NightCafe for a while.  Then I found MidJourneyAI.  And at first, I was only partially satisfied with the platform as I was on the MidJourneyAI Discord server and saw people working with basic ideas.  I decided to focus on two concepts as I decided to think of what I was doing as concrete prose with code.  And then secondly, I decided to take contestational aesthetics, as my prompts would contain ideas not being used on the MidJourney Discord.

I wanted to find the concepts for my prompts that needed to be less representational than the usual visuals of a CLIP-based AI.  I did two things.  First, I ignored everything typed on the MidJourney Discord, which was almost an aesthetics of negation.  And then, I considered the latent space of the Laion-5 database that MidJourneyAI was using as an abstract space.  I decided conceptually how to deal with a conceptual space using abstract architecture.  I decided to start querying it with images like Kurt Schwitters’ Merzbau, just as a beginning, as well as Joseph Cornell.  I did about twelve series called “The Architectures of the Latent Space,” illustrated here.  They are unusual because they still refer to Schwitters but are much more sculptural and flatter.  And so these went on for about twelve series.  But this was the beginning of my work in that area, then I started finding what I felt were narratives of absence.

I have considerable differences in abstraction – multiple notions of abstraction, as I want to see what is transcendent in AI realism.  For example, I started playing with real objects in a photography studio.  This image is of a simulated photo of a four-dimensional cube, a tesseract, which isn’t supposed to be representational.  Still, it was exciting that it emerged and illuminated the space.  And so this told me that I was on a path in which I was starting to confuse the AI’s translator and that it was beginning to give results that were in between its sets of parameters, which is interesting.  One body of work where my attempts at translator confusion are evident is The Voids (Lacunae), basically brutalism and empty billboards.  It is inspired by a post that Joseph DeLappe from Scotland made on Facebook of a blank billboard.  And one of the things that I noticed that these systems tried to do is that they try to represent something.  They try to fill space.  If there’s a blank space, it tries to put something in it.

MidJourney AI tries to fill visual space with signifiers.  One of my challenges was forcing the AI engine to keep that space open.  So this resulted in experiments with empty art studios and blank billboards.  Artists were absent or had no physical form, which was the conceptual trigger.  These spaces have multiple conditions and aesthetics, with a lot of variation.  The question lingered, “How do I put these images together?”  There are numerous ways to deal with them, so I made about 150 or 200 in a series and then created a contact book.  And this gets away from this idea of choice in AI art, anxiety, and so on.  I have a book that’s ready for publication so that someone can see my entire process and they can see the whole set of images.  But in this case, what I thought was very interesting is that I wound up going into a bit of reverie around the fantasy of these artists who I’d been looking into their studios, and they weren’t in, or they didn’t exist in a physical form.

Having worked in criticism, curation, and theory, as well as being an artist, I decided to take these concepts and create a meta-structural scaffold to create a curatorial narrative based on this concept of the body of 50 artists.  When I visited their fictional studios, thinking about theoretical constructs such as Baudrillard and Benjamin’s ideas of absence and aura, I created a conceptual framework that was a catalog for a general audience but preceded the exhibition.  There’s precedent for this.  There’s Duchamp and the Boite en Valise.  I’ve done work like this before, constructing shows in informal spaces like an iPod.  Here is a work from 2009, the iPod en Valise, as the iPod is a ‘box’ (Boite) for media work.  And then I thought, why can’t I do the same with a catalog?  Why can’t I use the formal constraint of the catalog to discuss the sociology of AI and some of the social anxieties putting this into a robust conceptual framework beyond its traditional rules?  So another restriction that I have frequently encountered as a New Media curator and artist is time.

A moment in time, when technological art or a form emerges is often ephemeral.  Curating shows on handheld art, screen savers, etc., show these might have a three to six-month period of time in which art is fresh.  Studio Visits is tied formally to the MidJourneyAI 4  engine because MidJourneyAI 5 has a different aesthetic.  A key concept is where the work situates itself in society and how it’s developing in a formal sense.  And then, is there time to deploy an exhibition before the idea goes cold?  And most times, most institutions are, unless you’re dealing with a festival, planning about a year out, possibly two.  And, of course, for every essay I’m writing now, there is a disclaimer saying that this is written at such a date, such a year, such a month, and this may be obsolete or dated by the time you read this, in the case of something developing as quickly as AI, this idea of being aware of the temporal nature of the form itself.

So I decided to deploy the catalog first, as the museum show would emerge from this, and create the catalog and then exhibit.  As I said before, I’ve been making these contact books, which are reverse-engineered catalogs;  I’m almost up to 15 editions.  I’ve only mentioned about six or seven on my Instagram so far.  But in general, I’m looking at curation as an artistic scaffold.  Given this project, a curatorial frame structure creates a narrative around meta-structural conceptual ones rather than representing the images themselves.  It’s a narrative dealing with society’s anxieties about AI and culture.  What happens if we finally eliminate those annoying artists and replace them with AI as a provocation?  So here’s the structure of the piece.  The overall work is the catalog.  There is a curatorial essay, the artist’s name, statement, and the studio “photograph.”  The names derive from the names of colleagues.  So I’m reimagining in a synthetic lens my community, the studio image, as we can see through the narrative that I’ve presented.  I started generating these empty spaces and let myself run through about a few hundred.

I chose the 50 most potent synthetic studio images.  A description emerges using MidJourrneyAI’s /describe function.   The resulting/Describe prompt, a brief discussion of the artist and what they do, is fed to GPT-3, which generates a statement.  So here’s the form of an artist’s layout.  You have the name.  The following layout is the first one I did for Artificium, 334-J452, inspired by George Lucas’ THX 1138.  And the layout came from this initial image.  I took these with a description from MidJourneyAI and put it into GPT-3.  The artist’s statement is as banal as any graduate school one and reads, “As an artist, my work expresses my innermost thoughts and emotions.  I seek to capture the energy and chaos of the world around me, using bold brushstrokes and vibrant colors to convey my message.”   So these were 50 2-page spreads.  The book is  112 pages and fits very much with a catalog format.  So the name, as said before, was based on the conceptual frame of the artist I was thinking of, based on the image generated, some of the concerns I saw in the mass media, and loosely upon those of names of colleagues, family, et cetera.

In many ways, I was taking a fantasy and re-envisioning my community through a synthetic lens.  These images came first when developing across the imagined artists of diversity, identity, species, and planet.  This reimagining is interesting because I wasn’t necessarily thinking of my ethnographic sphere.  I worked in Arabia, West Asia, and Central Asia and dealt with people from Africa and the subcontinent.  So many of these people of my experience figure into this global latent space of imagined artists, not just those of the European area or even those, more specifically, North America.  And then I expanded this to species and planet, as we’ll see in a moment.  So here we have an alien sound artist.  The computer in this studio is almost cyberpunk and has a very otherworldly art studio image.  I must remember which artist this is, but it has a New England-style look.  And then third one is a Persian painter obsessed with color, Zafran Pavlavi, based on my partner, Negin Ehtesabian, who is currently coming to America from Tehran.

This slide is a rough outline of the structure of the catalog.  I take the name and the framework of the artist’s practice, and you can see here that this information went into GPT-3 reading statements almost indicative of the usual graduate school art statements.  Once again, these elements reflect some of the anxieties in the popular media.  = I’m using this as a dull mirror from a visual sociology standpoint, based on scholars like Becker.  In addition, this is a draft, but more is just a pro forma approach to the conceptual aspect.  The project catalog is available on Blurb.  It’s about $100 and still needs a few little revisions.  But, this is something that is from a materialist perspective in basically inverting many practices regarding the usual modalities of exhibition curation and execution of a show or an exhibition.  I’m also thinking about the standard mechanisms of artistic presentation within an institutional path.  So not only is this dealing with AI, but it’s using AI to talk about the sociological space, the institutional space in which these works inhabit, and how these works propagate.

Studio Visits deals with institutions, capitalism, and digital production.  So issues this project engages concerning AI exacerbate social anxieties about technology.  The deluge of images problematizes any cohesive narrative.  Using this meta-narrative through this conceptual frame, I can focus on some of the social and cultural questions about AI and the future of society and how it affects it within a fairly neat package.  Design and curatorial fictions provide solutions for cultural spaces.  Cultural institutions typically need to catch up with the speed of technology.  Then bespoke artifacts, which are problematic, can remain in place long enough for the institution to adopt them.  In other words, if you get something together and get it out there, you can have that in place, take it to the institution, and hopefully, they can explicate the work.

I’ve been asked about a sequel.  I’ve had many people ask me who these artists are.  What’s their work look like?  You can see excerpts of their work in the studios.  But people were asking me to take the conceit one step further, and I’m starting to work on that idea and show the portraits of the artists and their work.  This portrait is of the artist Zafran, who I talked about earlier.  These both continue the fiction and then humanize the story, which also problematizes it.  And so this is this project and its ongoing development in a nutshell.  I invite you to go to my Instagram at @Patlichty_art, and thank you for your time.

In closing, this is another portrait of the artist Vedran VUC1C.  And once again, this is an entirely constructed fantasy.  But once again, as Picasso said, these are lies that reveal the truth about ourselves.


CAS AI and Text Talk 26 April 2023 Transcript

AI and Text Talk – Geoff Davis – 26 April 2023 – Computer Arts Society CAS

See below for the transcript of the whole evening, the

    • introduction from Geoff Davis,
    • the four speakers from the book,
    • Tivon Rice,
    • Ray LC,
    • Maria Cecilia Reyes and
    • Shu Wan.
  • Mentioned in Geoff’s introduction as successful contemporary gallery text-art artists:
    • Sasha Stiles – Technelegy
    • Mark Webster – Hypertype 

Many references are at the end.

Click here for the full Talk video on Youtube.

AI Creative Writing Anthology

The invited speakers in the Talk are in this new book and spke about their work with AI, art and education.

AI Creative Writing Anthology Geoff Davis 2023 GPT-4 ChatGPT
AI Creative Writing Anthology Geoff Davis 2023

Geoff Davis is the editor of the AI Creative Writing Anthology (Leopard Print London) which has 20 stimulating entries and a lot of extra material.

Each author describes their process and feelings abut using the generators so it provides an insight into using AI text. The book is on Amazon and most other sites and has a large free sample.

Please visit:

Computer Arts Society AI and Text Talk

This is a longer version of the Computer Arts Society AI and Text (part of the BCS) talk 26 April 2023. This talk and my next one on 1 June 2023 about AI and Images will be collected into a short document in June 2023.

Text-based AI 

26th April 2023


Hello everyone. Thanks to everyone at the Computer Arts Society,  and Kerry and Maria of the Community Team at the British Computer Society for hosting this talk.

Thanks for Sean Clark for organising the talks series and looking after the Zoom.

This evening we will start with a short introduction, explaining how and why these new AI text generators appeared and came to be so controversial and exciting.

I will show some current AI text-art from Sasha Stiles and Mark Webster, along with a quick look at my own Story Generator.

I will provide an overview of the uses of text to writers and creatives, the technology, ethics, and artificial general intelligence.

Then we will go on to the four Speakers.

Please note that there is a longer version of this talk available, please see the references at the end of the talk. Some areas like technology and ethics are expanded.

I will not be dealing with text used to generate images, in systems such as Stable Diffusion and Midjourney, as there is an upcoming AI and Image talk on 1st June. Please subscribe for that if you have not already done so

 The Speakers

Tivon Rice from DXARTS at the University of Washington

Models of Environmental Literacy

Ray LC  from City University of Hong Kong

Immortals poems, which are generated reformulations, and

Designing for Narrative Influence with the Drizzle project –Machine Learning and Twitter communications

Maria Cecilia Reyes from Universidad del Norte in Colombia

Using AI as a co-writer for fiction and poetry and

its possible applications in immersive and interactive storytelling

Shu Wan from Univeristy of Buffalo

Aspects of Generated Text in Education for Lecturer and Student.

So we are covering quite a range here tonight.

This will be followed by audience questions and discussion.


A quick note on terminology: ‘AI’ will be used as shorthand for the computer generators. Current systems are not ‘Artificial’ (who decides what is natural) or ‘Intelligent’ (a divisive term with no settled definition; also dualist). But everyone uses the term.

I assume that most people here have used ChatGPT or other similar systems. Yet in my 2021 AI research into how professional writers use generators, which provided a text generator and editor, only 8 out of 82 writers had used them before – 10%.

At that time the public systems like Talk to Transformer and GPT-2 were not widely available. And even if heard of, were looked upon with bafflement and some suspicion. This immediately changed to positive regard after using them for creative tasks (Geoff Davis research ref.).

I will first run through the various ways in which generators are useful to writers and creatives, before we get into more detail.

  1. Idea Generation: generators can be a powerful brainstorming partner
  2. Collaborative Writing: generators can suggest sentences, paragraphs, or entire stories based on your prompt input. This is useful if you have writer’s block, or for ambient literature and art (also known as personal content creation
  3. Style Transfer and Text Transformation: adapt your writing to the style of a famous author, or turn your prose into poetry
  4. Editing and Proofreading: AI-driven tools can assist you in polishing your work.
  5. Visual Storytelling: text-to-image AI models can generate illustrations, concept art, or even comic panels based on your written descriptions.
  6. Cross-disciplinary Collaboration: By facilitating communication between diverse artistic fields, AI can inspire innovative, interdisciplinary projects and collaborations.
  7. Personalized Storytelling: AI can help create tailored content for specific audiences or individuals, this is good for diversity
  8. Adaptive Storytelling: AI can be used to create dynamic narratives that evolve and change based on user input, choices, or actions. This can lead to non-linear storytelling, and interactive narratives. This is often used in games.
  9. Sentiment Analysis for Creative Feedback: AI can analyze the emotional tone of a text, providing valuable feedback on the effectiveness of your writing.
  10. Creativity as Data: AI can analyze large volumes of creative works to identify patterns, trends, and insights that can inform your own artistic practice
  11. Ethical Considerations: By engaging in thoughtful and responsible AI practices, you can contribute to the development of a more inclusive, diverse, and ethical creative landscape.

Style transfer is still popular, and much easier to do in the modern generators ChatGPT, GPT-4 and OpenAssistant.

In the AI Creative Writing Anthology book, I have two examples, using a famous optimistic poem about technology, “All Watched Over by Machines of Loving Grace”  by Richard Brautigan published in 1967. I simply asked the generator to rewrite the poem in the style of Scottish writer Irvine Welsh, and cyberpunk inventor William Gibson. These came out really well. If you want to take a look, the Irvine Welsh one is on the front page of my website. Previously to do this you’d have to fine-tune the generator by loading new training data.


Geoff Davis

This is a procedural story generator or PSG – simple but effective.

Claimed by digital art curator Georg Bak to be a ‘precursor of ChatGPT’.

MA4 Story Generator 

Mark WebsterHypertype generative series, using IBM Watson Sentiment Analysis.

Selected several texts and papers on AI and emotion, then analysed them with IBM Watson Sentiment Analyser, to produce a set of texts for use in a generated art series – 300 different images.

Sasha Stiles is very well known, she founded “theverseVerse” online poetry site. Wrote the Technelegy book shot, makes videos, and much more. Sold artworks at Christies recently.

All references are at the end of the document.

I wanted to show these artists as it shows it is possible to have a successful career doing text art, it’s not just a hobbyist thing.

[Edit: two interesting writers on AI and text are Janelle Shane who wrote You Look Like a Thing and I Love You, and does the AI Weirdness blog; and Gwern Branwen who runs, please search for them.]

Now I will discuss some of the background.

A Brief History Of Modern Generators

Earlier AI systems used a rule-based approach to create so-called expert systems, which attempted to encode all the actions in a domain, and then reproduce it accurately. This works well for limited domains like those of robots in factories, which have to work accurately with no errors, or help systems with a series of set actions depending on input events. Expert systems did not scale and were not transferable to other domains.

For instance, BRUTUS (BRUTUS ref.) was a ‘Storytelling Machine’ or fiction writing expert system, from 1999, which was a tremendous research effort in conjunction between academic researchers  and IBM, AT&T, and Apple Computer, but wrote hardly anything of any general use, and was never developed further.

All of this historical work paved the way for a new approach to AI called machine learning, using so-called neural nets modelled on the brain. These did not attempt to manually describe each step in a program of actions.

The famous artist Harold Cohen programmed a system called AARON in the 1970s to generate drawings in his own style. This is an example of a personal generative expert system. He joked that he’d be the first artist in history to have a posthumous exhibition of new work.

The first neural net was the Perceptron, invented in 1943 but not built until 1958. It was a hardware system for image identification.

In the last ten years, once computer speed and power increased along with a huge increase in the amount of data for training available from the internet, Natural Language Processing and Machine Learning could really increase in usefulness.

Advances in machine learning from data sets continued with Recurrent Neural Nets or RNNs (RNN ref.) and other architectures, and received a significant boost with the invention of the Transformer architecture at Google Brain in 2017.

GPT stands for Generative Pre-Trained Transformer, which means the system is pre-trained on text data and then generates more text based on the statistical likelihood of the next text token. The more text data and the more training (nodes and layers of the neural net) the more realistic the text will be. (GPT ref.)

These systems are generally known as Large Language Models or LLMs (LLM ref.).

A quick list of the main areas of AI and text is:

  1. Natural Language Processing (NLP)
  2. Machine Learning (ML)
  3. Deep Learning (DL, also Deep Neural Nets DNN): A subfield of ML

This is all used to make

  1. Chatbots and Virtual Assistants – ChatGPT, Google Assistant, Alexa, Siri etc.
  2. Text Generation and Summarization
  3. Translation and Language Understanding
  4. Search
  5. Transcription from speech
  6. In our area, Creative Support Tools CST and Copy Writing Assistants
  7. Many new tools that arrive daily

This is a technical area we won’t go into in this talk. I have provided references, see below.

Because of the adaptable and unpredictable nature of the new generators, they still produce errors and can fail, or can give false answers. The generators  are created to give answers, and will always give an answer if asked, so if the data is lacking they will just make something up. These errors are known as hallucinations. The wrong answers are presented convincingly, and can fool naive users, and limit their usefulness in critical areas.

The latest GPT-4 system from OpenAI is far better at world knowledge than earlier versions, even ChatGPT, and gives much more accurate answers.  It’s worth mentioning that Open Source systems such as OpenAssistant (OA ref.) are now comparable with commercial systems.

A world model (to prevent nonsensical answers) is thought to be created internally, on the fly, in order to more efficiently process an answer from the vast amount of data in the neural net. Researchers are now seriously claiming actual intelligence for the latest systems, rather than only production of statistically likely simulations (AGI Sparks ref).

General Intelligence

To quote Sebastien Bubeck of Microsoft,“the new wave of AI systems, ChatGPT and its more powerful successors, exhibit extraordinary capabilities across a broad swath of domains. In light of this, we [can] discuss whether artificial INTELLIGENCE has arrived.” (Capitals in original.)  This is known as AGI or Artificial General Intelligence, and within Microsoft, Bubeck’s team is devoted to the “Physics of Artificial General Intelligence” (AGI Sparks ref).

It’s worth noting that consciousness is not the same as intelligence.

Intelligence is a goal-orientated ability, such as calculating numbers, playing chess, controlling a robot or car, writing some text, making an image. No mental awareness is required.

In AI research, achievements are denied as the goalposts keep on moving in the definition of intelligence. Now, people say text generators have no intelligence as they are only statistically selecting the next words to output, despite their superhuman abilities in text production.

I won’t even mention the Turing Test.

By the way, non-Western cultures have a different approcah to robots and AI. Japan, Asia, do not have this constant Western fear of impending destruction (which is from intense state competion i.e. war across history I guess).

[Edit, 1 May 2023: Geoffrey Hinton, the top AI researcher at Google, has resigned saying the AI is getting too powerful. Several researchers and observers including Elon Musk, who cofounded OpenAI, have called for a 6 month ban on updating the AI generators, as AI risks are not fully understood. But the main companies and open source groups are in a race to develop bigger and better AI models, so speed of development will increase.]


The ethical dimension applies to AI generally, from text to search, control systems and everything else, and is a very hot topic, with many in the AI industry predicting existential disaster, with humans becoming obsolete in a few years. Fear of the robot overlord is also common, based largely on fear of a superhuman intelligence having human emotions and drives such as power mania, need to dominate, and status anxiety (very common in academia and the arts).  This scenario is shown in the Terminator movie series.

Actually, no-one knows what might happen, but so far there has been an explosion of creative use in image generators and text uses in literary experiments. Since AI is already here, one would already expect disaster to be encroaching, but there is no sign of this.  I prefer to take a more pragmatic approach to AI as a tool, perhaps a very significant one as Bill Gates says: “AI is the most important tech advance in decades.”

The Alignment problem is whether AI values are aligned with human values.

Fake news, propaganda and so on were around a long time before AI arrived. Detecting AI text is hard, and automatic detectors like GPT-Zero are easy to trick so other methods are arriving to separate falsehoods from truth. But since both sides of any political debate claim the truth, this is obviously more of a human problem than a technical one.

Crimes using AI voice mimicry such as virtual kidnapping scams, as well as deepfake videos, are on the rise.

The issue of gender and race bias is also a big topic, although more recent generators such as ChatGPT have guardrails (software protections) in place to reduce or remove this sort of bias. Some commentators object to a left wing libertarian bias in the current generators, such that a new ‘right wing AI’ is being developed, and Elon Musk has also joined in the race with his new company X.AI.

I am currently researching the topic of AI emotional tone at UAL, with a new academic paper due soon. Links for all this are in the references.

Data Dignity and Copyright

The basic creation of large language models is controversial as the text data is taken from the internet. In the case of GPT-4 researchers say quite seriously that the entire internet has been used to train the model. But no-one has ever been paid. The concept of Data Dignity has appeared, which is that all the originators of this text should be paid, by a forensic process examining where it all came from. This is unlikely as it is very hard to separate out data sources even at the level of training the model.

Reddit and Stack Overflow are going to charge for data, which was previously freely available. These companies receive less revenue if AIs take over computing support, discussion and code help roles, using all their original data to do so (Lanier ref.).

In the field of text to image, some copyright court cases are in progress regarding art images used to train text to image generators, as individual artist styles are easily identifiable (Loizos ref.).


Some artists object to AI in principle, for high energy usage, or because it might reduce authorship or creativity. However, in my recent study, only 8% of 82 professional writers felt they did not own the generated text. Many creatives already use code for generative art, or use programmed filters in tools such as Photoshop.

There is a huge grey area as AI is already part of the infrastructure, used in editors, search, predictions, translation, learning and so on. Most see AI as advantageous in terms of productivity increase, extension of creative skills, new art forms, and practical uses in medical and legal support in poor countries with limited professional resources for ordinary people.

There is also some debate about the amount of energy used to train the systems, but these costs are low compared to general power use. The computing industry uses a huge amount of energy for general activities such as entertainment, administration, etc., so a little used for next generation technology is a drop in the ocean. However newer models are designed to use less energy.

Class and Progress

Most mainstream articles about AI start with an alarming ‘end of civilisation’ quote, often from someone like Elon Musk. In the case of computing, the new technology has been changing working-class jobs for decades, but that has been promoted by the media as thrilling progress. Now that typical middle-class jobs like journalist, academic or lawyer might be affected, existential dread is promoted instead.  More academic studies of potential threats from AI include the influential book Superintelligence by Nick Bostrom (Bostrom ref).

Generating Computer Code

Warning: Can produce insecure code. Always tell it to make secure code. Check if you don’t know.


Using generators for code is also a big area now, with GPT-4 scoring 10/10 on programming employment tests at expert level. Although it still needs guidance and reviewing, generators code clearly and also add comments, and can explain their steps, which makes it useful to beginners and experts alike. It speeds up code production from hours to minutes.

In the AI Creative Writing Anthology which I recently edited, Brian Reffin Smith, the winner of the many electronic art prizes and a member of Computer Arts Society, has an imaginary chat between ELIZA, the first computer therapist, and Karl Marx’s statements in the Communist Manifesto. He then later asked ChatGPT to produce a new version of the ELIZA code with many extensions for art assessment, which is now available to view only, on Facebook (Brian Reffin Smith ref.).

I have used GPT-4 to code modern versions of my old generative art, originally written in BASIC.

AI code assistants like Copilot from Microsoft using GPT3 can be run with Python and other languages. Already up to half of Python code is produced by the Copilot assistant. (Copilot ref.) If this is true of course.

Before we go onto the speakers, I will run through some other areas.

Ambient Art – Personalized Content Creation

There is a field of ambient art and literature where people generate for fun, as a pastime, with no intention to create a final product. Interesting outputs such as generated images, memes or poems and lyrics might be deleted after creation, kept private or shared on social media (Ambient Art ref.).


AI can also be used in game environments to create dialogue, descriptions, control characters, generate scenes, and control plot lines (Games ref.)

Creativity of Older  Generative Systems

Many commentators have commented that the older generators such as GPT-2 or the Open Source GPT-J 6B are more useful for stimulating creativity, as the outputs are more randomised, which was the point of old experimental systems such as Dada’s ‘Exquisite Corpse’ or William Burroughs ‘Cut-ups’. The older generators are also easier to fine-tune with one’s own work.

However with newer systems from ChapGPT onwards, you can just ask it to rewrite text in the style of James Joyce, or Irvine Welsh, etc., or put in a sample of your own prose for it to copy the style from.

The newer models are usually controlled with something called prompt programming to get a specific output.

 Creativity Assistance &  Creativity Support Tools

It is worth noting that nowadays many artists use AI for part of their work process rather than all, perhaps for creative ideas or copy writing. The generators can be seen as expert assistants ready to do any task, a bit like a ghostwriter or art team.

I have a hybrid generator and editor Story Live, which I made along with Fabrice Bellard using his Open Source Text Synth. This is freely available, and also has a Text to Image generator and Translation (Story Software ref.).

There are many attempts to create a novel-writing AI system, but we do not examine those here. Some of these are in the references.

There are many attempts to create a novel-writing AI system, but we do not examine those here. Some of these are in the references.

I have researched and developed creativity support tools CSTs as they are known, with a zooming storyboard tool called Story Software still available in various versions.

I also have a hybrid generator and editor Story Live, which I made along with Fabrice Bellard with his Open Source Text Synth. This was made for research purposes but is now freely available, and also has a Stable Diffusion text to art generator and Translation (Story Software ref.).


Tivon Rice


Maria Reyes

Shu Wan

Geoff Davis

So I think we’re kind of ready for the speakers now.Then there’s a question and answer discussion period at the end of the speakers. So hello, Tivon.

Tivon Rice

I’m Tivon Rice, joining you from Seattle, and I really appreciate the opportunity to share what I’ve been working on lately. I am an artist and an educator teaching at the University of Washington’s department of Digital Arts and Experimental Media. Quick overview. For the past probably about six or seven years, I’ve been working with computer generated texts like this one we see on the screen generally to accompany my visual and sort of time based projects. And my work with machine learning or AI or whatever you want to call it, tends to oscillate between working with these systems in my studio in a purely creative mode, but then also sort of switching and critically examining how these emerging systems function in society or imagining how they will function in future society. And I explore these ideas through my teaching, through workshops, conferences, and the like. So I want to start by showing you part of a trailer for an experimental film that combines digital animation, photogrammetry, and a number of AI generated narratives. These are specifically fine tuned GPT-2 models, as Jeff sort of described sort of from an earlier era.

But let’s take a glimpse of this video and then I’ll further describe the project. So here we go. We’ll watch about a minute and a half of this.

VIDEO (spoken word and animations)

Models for environmental literacy.

Video Speaker 1

What is an island? Is it a graveyard? In what sense is it an island? Does an island denote a sense of spatial absence?

Video Speaker 2

I’m afraid of the absence. It seems to be forming on me. Its dark forms disturb me. The whole place silent. The stones are blur.

Video Speaker 3

All of this anxiety and worry goes hand in hand with an ongoing process of change. A change that, although not explicitly recognized by this program, has become obvious to all.

Video Speaker 2

This, for me, is the essential paradox of our stories. In finding our way within the world, we humans invent or modify or redefine reality in ever larger and more incomprehensible ways. So our words are not only a vehicle for revealing the world to the reader, but also a vehicle for revealing the reader.

VIDEO sample ends.

Tivon Rice

Okay, so the rest of the trailer and actually the entire 35 minutes minute film are linked on my website and demo pages. So I’ll leave that to you.

But I’d like to give some background to the research project that sort of spawned this about three years ago, actually, when I was living in Europe at the time. And I guess reflecting on the time that I was living in Holland and presenting my recent projects at exhibitions, conferences, and workshops, I found that many of the conversations that arose around AI and other digital techniques technologies asked how we could apply these ways of seeing and understanding large systems to the topic of the environment. And I think these questions are, of course, a product of the times.

But I also came to understand how the Dutch landscape, which may be one of the most highly engineered landscapes in the world, also provokes this kind of critical attention about the environments. So I was asked to participate in a number of, like, artistic research projects that sought to apply emerging forms of image production, mapping, world building and storytelling to the topic of the environment. We were sort of focused on very specific environments, like the barrier islands on the North Sea coast of the Netherlands.

Or more broadly, how can we begin to imagine ecology and the environments from new perspectives, possibly even and non human perspectives? Non-human centered perspectives. So this project, Models for Environmental Literacy, brings together three areas of research, one being field trips and workshops in which groups of artists, ecologists, authors, and musicians sort of visit these sites at the boundaries of human involvement and environmental change.

The second area would be natural language processing research. Earlier, I was working with a tool called Neural Storyteller, a very early RNN NLP model. But seeking to update these systems. How can they be made more accessible to broader creative communities like my students and those participating in my workshops? So I focused on the idea of fine tuning GPT-2 models.

The final area of work would be to develop a series of films, which we saw the intro right there. How could these films creatively reflect on the research as a whole, combining digital image that were collected at these sites, these virtual environments, with these narratives generated through fine tuned GPT-2 models? I’ve already touched on the field work that went into this. So because this work preceded Chat GPT or even GPT-3, I used the medium version of GPT-2 as a starting point. And this model is okay, maybe the glitches are kind of charming, but it’s also small enough that it can be fine tuned on a conventional computer that has a GPU. So I was able to fine tune three new language models of my own. And these are the voices for the film.

A number of different ecologically concerned AIs, one trained on eco philosophy, one on ecofiction, and one on very recent scientific reports about the current environmental crisis. And this is a good starting point for describing the position that I take when co-authoring with AI, and I identify at least three absolutely critical areas of knowledge that need to be built around working creatively with these systems.

First of all, we should know as much as possible about the language models data set. And so in this project, because I collected and trained or fine tuned my own data sets, that we see sort of brainstormed here, I believe it’s a lot more transparent and deliberate than working with black box models like GPT-3. But even so, moving forward and working with these large language models, I think it’s important to think about the very large data sets of arbitrary text scraped from the web, as Geoff described. How do we understand the tone and content, the truthfulness and the bias inherent in language that’s evolved on the Internet and that was ultimately used to train Chat GPT?

The second body of knowledge or skill set that I place importance on involves inference. How do we prompt these models to create text that is meaningful or suggestive or provocative to us? If we ask boring or superficial or unstructured questions, we’re going to get the same. In return, we’ll get this kind of like autocomplete behavior that outputs an endless, banal sameness. So how can we deliberately craft prompts that are more likely to produce interesting outputs? With these films, I thought about the logic of prompting and how GPT-2’s outputs could be used successfully successively as the following prompt it’s kind of like a feedback loop. So the logic in the dialogue of the first chapter is actually circular. One model is asked a very simple question tell me what you see. And the response to the output becomes the prompt, the input for the next model. So in this dialogue, the entire paragraph from the Scientist becomes the prompt for the philosopher, and the philosopher’s output is then the prompt for the author, and so on. And visually, the first chapter is focused on this strange Dutch island that’s called the Isolo, the Eye of the ISIL River. It’s like this perfectly circular manmade island designed to isolate toxic sediment generated during the engineering of the farmlands in the north of the Netherlands.

So the film’s animation sort of studies this uncanny, circular landscape and the surrounding waters in stark black and white. The second chapter is called Whisper Poems, and the logic of that dialogue is also circular, but only two or three words from the previous output is considered for the following input. So, like a whisper poem or a game of telephone, there’s some continuity, but also a greater chance of misunderstanding between the different models as the story evolves. That chapter is focused on the small islands surrounding Helsinki in the northern Baltic Sea. Sort of paradoxically. While the Baltic rises at 1.5 year, the islands in that area also rise twice as fast 3 year as a result of postglacial rebound. So again, these small bits of land presents a sort of paradoxical image in terms of human time frames, a sort of anthropocentric time frame, or perception of time or history or geo sort of temporal situations. So this film’s animation studies the sort of isolation and invisibility of number of these small, rocky islands and the surrounding waters. The final chapter is called Echo Chambers, and the logic of this dialogue is a feedback loop in which one model’s output becomes its own input over and over again.

So thus, each character has a much longer monologue without being in dialogue or being interrupted by the other voices. And each text is prompt with a very simple question where are we? This chapter is visually focused on a field trip we took studying toxic algae growth in Zayland, southwest Netherlands. And these blooms are caused by, like, excessive chemical use in agriculture. The over engineering of the Netherlands delta works after the 1953 flood. So the film’s animation studies the strange color and sort of dense texture of algae surrounding another number of islands in this estuary, which is essentially a dead sea. I said earlier that there are, like, three areas of knowledge that I feel need to be built around working collaboratively with NLP systems like these, understanding the underlying data sets, carefully crafting our prompts during inference. And the final idea, I believe, is deliberate co authorship of the outputs. So it’s important to be honest and say that I do step in and give the final form to these texts. And this decision to edit or gently reorganize the output from the machine learning system is my response to all these questions surrounding the artistic agency of machines.

Should we initiate these systems and then step back and take whatever they say to be the final raw output to sort of demonstrate that the technology works? Or are there moments where we can reinsert ourselves into the process and make decisions about how the output resonates with our own poetics? So, for me, in cultivating this kind of collaborative relationship with AI, what I’ve found is that as I observe a machine learning system develop some kind of understanding about language, that my own understanding of language begins to shift as well. And I can see from sort of like third person perspective how language evokes images and narrative decisions in my work. I’ll leave it there. Look forward to hearing from the other presenters. Once again, thank you for having me, and I hope we can chat about some of these ideas. Thank you.

Geoff Davis

Thanks a lot Tivon. That’s a really good piece. It’s good to see you explain it because I’ve only seen some of the text before, so that’s excellent. We’re having a discussion at the end.

So Ray, if you want to start.

Ray LC

Hi  everybody. How are you? Fascinating work by Tivan.

What I do, I’m an assistant professor of Creative Media at City University of Hong Kong, and I’ve been there since 2021. I have a neuroscience background. I got a PhD in neuroscience, but basically since about 2017, I’ve been working in Creative Media arts design this area. So I’ve also been using GPT-2, and because it’s got these quirky ways of expressing itself, kind of helpful for generating poetry, which is what I’m going to show you today.

I  run the studio for Narrative Spaces, which involves using basically looking at humans interaction with machines and with AI as our starting points for investigation. But we work with basically interdisciplinary, pretty much anti-disciplinary crowd of people, like roboticists and performers. We work a lot with dancers, et cetera, et cetera. So this is our page if you’re interested in taking a look.  [See references.]

The project that I will share today mostly will be about this work called Imitations of Immortality. It’s also a book, by the way, that was published, I didn’t bring that up. This is also a book that was published by Floating Projects Press. And so it looks like this classic poetry book written by two people, basically, me and GPT-2. Although I also want to be frank, is that I also curate GPT-2 as well, just like what Tivon was doing. This web page basically is kind of a web version of the book.

So what’s the workflow here? The inspiration here is that some of you might know William Wardsworth. Well, you probably all know William Wordsworth’s collection Intimations of immortality. So what I want to do is actually create a bunch of poems that were modeled on famous poems. A lot of them are British poems, actually. So, for example, there’s Dylan Thomas. Do Not Go Gentle Into That Good Night. There’s Alan Ginsburg’s Howl, for example. So what I did first was I wanted to make a kind of a variation on that classic poem. So today I don’t have time to show everything, so I’ll try to be interactive a little bit. So I’m going to show you my version of Elizabeth Bishop’s poem, which some of you know is called One Art.

“The art of losing isn’t hard to master;

so many things seem filled with the intent

to be lost that their loss is no disaster. “

So it’s a villanelle form, by the way. It has a particular rhyming scheme. So what I wanted to look at was what happened if I try to write a variation on this poem. And then I’m going to ask GPT-2 in this case to write a variation of this poem, with my help, of course, because I’m curating the text by giving it the Elizabeth Bishop voice. Basically, I gave a bunch of Elizabeth Bishop poems try to find that voice and then also to give it a starting primer. That’s how the GPT stuff was working back in those days. So I give it the first stanza from One Art and have it try to generate the rest of it. So in the interest of being in-depth versus in-breadth, I will show you my version of the poem. By the way, this is kind of interactive website, so I know things are starting to disappear because they’re getting forgotten. I’m sorry about that.

[Shows poem.]

Okay, so anyway, so it says the science of forgetting is not inscrutable. So much information pokes at our brain for attention that to forget is it is forgivable. So you can kind of see like this variation of the poem actually tries to be kind of a micro version of trying to write a variation. I try to follow all the structure, et cetera, et cetera, even the things where Bishop does parentheses with exclamation marks. For example, here the joking voice, a gesture I love. Or write it. That’s kind of the one main point of that poem. So I try to kind of reproduce those things in my way of writing it as well. Okay, so anyway, so you can go and watch this, including the ending. I kind of give that blah, blah, blah is unforgivable. So I kind of try to vary it that way, too. So, of course, the GPT version will not be that way. I’ll just show you because this is what this talk is about. Here’s what the GPT version comes up with. And just keep in mind it is curated, but I try to do it so that each stanza is what GPT wrote.

I choose the stanza, but I’m not going to rewrite this thing for GPT, right? Because that would be pretty unfair. But I did have to insert some line breaks here or there to make it work out. So again, this is the original poem. The art of losing is an art to master. This right here I’m showing you right now, hopefully you can see, is the GPT version, right?

[Shows pages from book.]

So it starts with the original stanza, and then it says the music is part of the song, though it be sung. The other hand is silent till the other side finds its master. The man that gives knows all. So as you can see, it kind of sort of has a voice, but it’s not really following Elizabeth Bishop it’s not following that logic, but it kind of keeps some of these interesting things. Like, for example, in the middle there, you can see thus close the truth. Parentheses, grab it and run. Exclamation mark, parentheses. How come no one has seen such a site for years? The stranger the disaster, the farther a word. It’s learning some form of this poem and kind of like regurgitating it in a kind of a funny kind of way, funny to us, quirky kind of a way.

And actually, if you see on the bottom there, they actually use this kind of disaster thing here as well. So it’s kind of learning to say things from the poem in this kind of fresh new style. So this is what the book of poetry is about. So in the book itself, you can basically well, you can actually pick up a copy if you’re in Hong Kong, but we’re trying to make it available in the future. Actually, I have it with me. I’m sorry, this is kind of random, but I do actually have it with me and just to show the form of the poem a little bit. So once you have the book in front of you, it’s also kind of a nice kind of thing. And the way I kind of you can’t really see it because I blurred out my screen. But the way I also design a book is also I basically don’t say who it’s by. So I put my poem and the poem by GPT-2 on opposite pages. So people are kind of forced to just read it without knowing kind of the authorship. Now, this was also published into a paper at RTech, an ACM conference.

And in that paper, basically just the short answer is that I basically asked, I gave particular stanzas of the poem to people who are reading it for the first time, like kind of on a survey. So what I found basically from that study is that, first of all, if I just give them stuff from my poems and from the GBD two, one more or less the whole corresponding stanza. If I give them those things, they’re not able to distinguish which one is human made versus which one is machine made, right? If you ask them, one of these is like the machine generated which one? It’s like 50 50. They can’t tell which ones are mine, which ones were the machine. But if you ask them which ones are more expressive, so you don’t tell them that the stanza was by me or by the machine. But you just ask them how expressive it is, right? You just ask them to judge how expressive they are. And then you go back and figure out which poems have a score of one versus a score of seven. Then you actually can see a significant difference where the poems I wrote are more expressive.

Without them knowing the identity, they found that the poems that I wrote were more expressive. So what that tells us is that actually, I believe that the readers have this kind of unconscious knowledge of who’s writing the poem, right? Because unconsciously, they cannot tell you who wrote it. But then there’s something about that poem that still strikes them differently. There’s still something about the way I wrote the poem that was more expressive to them in certain ways. Anyway, so that was kind of my take away from this. I had a great time with this project.

I know that Geoff was asking me to show you about some comics and things like that so you can take a look at this. Comics for climate change. Actually, I wanted to also echo Tivon’s work because I also work with climate change, and we used Twitter to get our feeds, our data to generate climate action text as well. So those of you who are interested, you can check out that work, which is in Drizzle and also in this Tamagotchi game that we created that also speaks in machine learning generated language. And this game in particular, you can actually also play online. So it’s like this Tamagotchi game that you can kind of have fun with and play with.

Anyway, so thanks so much and looking forward to discussing more.

Geoff Davis

Thanks a lot, Ray. That’s a really interesting talk. Very good to see the work. Apart from the poems, the Drizzle and the Tamagotchi are really interesting. So maybe we’ll do something else some other time. But thanks a lot. I’m going to put the next speaker on, Maria Cecilia Reyes from Colombia.

Maria Cecilia Reyes

Thank you so much for the invitation. I want to share my personal journey collaborating with artificial intelligence systems on co-generating worlds, fictional worlds, universes with words and images, but also what have been my thoughts about this collaboration. And I realized that there is something that is not artificial in this relationship with artificial intelligence. So my journey started not so long ago in 2018, at my work in the National Research Council of Italy, I was doing research about conversational agents in the field of education. At that time we were developing a tutor bot to help students that were engaged in massive online open courses. However, working with technologies and experts in the field, I couldn’t refuse to think about creative applications for conversational agents, especially vocal interfaces.

So for my creative life, I wanted to use a conversational agent to help people to edit a film made by pieces of videos from YouTube. I also started to work on an immersive space in a womb of a mother in which we could have a conversation with that mother by being physically immersed in that type of womb.

So we started to work on a mock-up and get projects and ideas that start, but then they have their own time to evolve. At the time I also had the opportunity to advise a couple of master thesis that were using chat bots. One of those was for helping elders through a device called Kibi, an intelligent device that were alerting, caregivers about the state, the physical state of the elders, and also had a vocal interface for the elders themselves to remember them when to take some pills or give them some advice, remember them to call someone. And another thesis was the development of a chatbot for a museum so users, visitors of the museum could have a previous experience before going into the Museum of the Electric Technique in Torino in Italy. But then I received a message in an email in 2019 from a friend and he says I’ve been writing poems since I’m a little kid and I don’t share very often my poems, but I share with personal friends. And this friend wrote me this. I put the two first lines of your poem to use the voice to communicate love. It’s not about putting words together into this new website, Talk to Transformer, which is GPT-2.

And the results were surprisingly good, you can do it again and again with different results each time. I had some good laughs thinking up the beginning lines of some surreal stories and seeing what the AI comes up with. But with your poem, the results were more artistic and not pure comedy. So I was very intrigued by this message.

I started to use Talk to Transformer at the time to give some prompts and some first lines of my real poems and see how the machine would react and what it would do with it later. So yeah, as a hidden poet, I started to show my poems to the machine, to any machine that I would come across with. So one of those was Talk to Transform and then Story Generator in 2020. Then when Night Cafe came out, I also started to give some lines of poems to Night Cafe to see what kind of images it would create and then MidJourney more recently. So the only poem that I saved from all these iterations was the poem that was published in the volume that was just published, AI Creative Writing Anthology, thanks to Geoff. I kept two images prompted by two of my poems.

[Shows tow images.]

So why these two images? I don’t know why in these nights when you stay awake and just experiment, sometimes some of that work just has a very short life but leaves deeper thoughts. So one of the images that I saved was this image of Genoa. It was a time in which I wrote a very angry text about the city. As an immigrant, I was going through many personal battles by giving this prompt, this idea of a Genoa in flames that the machine created this representation that stood to me and represented that feeling that I was going through at that time.

The other image is a bit more even more deep and personal. The first one was NightCafe. And this is MidJourney instead. And it’s poem about a moment in which two people that never got married in life while they were alive, they get together in heaven after passing away. And this is images really got a big emotional develop a big emotional connection with myself. But then in those moments and I think most people or the reactions that I get from my colleagues and friends experimenting with AI, I feel it’s sometimes very similar to what happens with Horoscopes.

Sometimes the confirmation bias that you kind of expect to have an idea of what would you like to get from the machine and then from any of those phrases or images that you get, then we as humans, we make our own conclusions and adapt those information to our lives. So what is that kind of prediction that sometimes AI chatbots can have for the use of common people that want to get that information into their own lives? So this is a question about where are we standing when we ask something to the machine?

I’m a PhD in digital humanities and I have been working in interactive digital narratives, especially in immersive interactive films. That’s my field of studies. So as a future research interest, I’m very interested in imagining AI generated immersive and interactive narratives. So I imagine being immersed in the movie or in the film, in the narrative and leave the control, the creative control to the machine to create the visual environments in which we are immersed, but also to create different outcomes of the story while we are interacting with that story in real time. So the machine and this is just provoking some ideas based on our cognitive data.

Some choices, conscious choices that we can make during the journey, the narrative. We can maybe talk to the machine. Maybe we can enter some text. Maybe we can just make some choices. And then the machine will create new story plots or continuation for the story. But also what if we interact with the machine and with the fictional universe, with our biological data and our breathing or our heart information and from there the artificial intelligence can take over and make the story more stressful or give us a break or take us into a more fantastic world.

But I’m concerned about two main aspects. One is coherence, that was another issue that I faced experimenting with some GPT-2 tools. Sometimes I wanted to just let the machine take over, but the coherence was not fully there. And the other one, especially when we talk about interactive narratives, is the dramatic progression. We want to make sure as creators, as storytellers, that our spectator or user is going somewhere, is going to experience a climax, a moment of euphoria in which everything makes sense and the narrative experience gives you that reward of a climax. So one very famous interactive drama is Facade by Michael Mateas from 2007. It is a conversation with this couple in their apartment and he uses an AI system. As users we interact with them through text and then the story develops in separate ways.

There are some plot points that are fixed and somehow guide the story so it doesn’t go everywhere. Another interesting project is Nothing for Dinner computer based interactive drama from 2015, and the group of Interactive Drama Tension or ID Tension from Switzerland that have been working on AI and interactive drama for some time now.

Just as a final thought, I think we humans are the ones that generate meaning that we make sense of what the machines are proposing and we are the ones that feel the effects of that material that is produced by the arbitrariness of the machine. So that’s why I think there is nothing artificial here in this relationship between us as creative and the artificial intelligence.

Thank you so much for your time.

Geoff Davis

Thanks Maria, that’s very interesting.

Now we’re going to move on to our last speaker, Shu Wan, who’s from the University of Buffalo.

Shu Wan

Hi, how are you guys? I’m Shu Wan. As you can see, the title of my piece today is Chatbots. During scholarship, how do I teach GPT in a history course? As Geoff said, I’m a professor in history at the the University of Buffalo in New York, USA. So I’m very happy to present my pedagogical research on how to protect students from using ChatGPT, and help students to use it. But not in violation of academic integrity. That’s the big issue.

So now I’ve seen American higher education. Last December 2022, I was assigned to teach an Asian History class in the term of January 2023. Well, a lot of time I wanted to use ChatGPT and it became a big issue. Everybody talked about that. That was the controversial issue of introducing or allowing the use of ChatGPT in a classroom. But once I decided to introduce it to my students in class by designing ChatGPT sessions, and adding it to my syllabus. So, on the first day of my class on January 4, I demonstrated magic of ChatGPT to my students.

After showing this slide [IMAGE] and playing a video of Canadian philosopher Jordan Peterson’s quarter of ChatGPT, I enter an example of prompt real lilm Large Emperor into the interface into the interface which output a brief introduction of the film as follows.

You can see here on the slide. And then I told students to use a high tech tool ethically, such that it must help them when they encounter difficulty employee powering, for exam.

However, I told students it’s not a good idea to replace your brain with a machine when doing a review essay. The reason I mentioned the film essays is because in my class students were assigned to write a film review about a film related to Asian history. And then finally at the end of class, I told students it certainly violates academic integrity if you use ChatGPT in completing your writing assignment. So please don’t do that.

And so in the following class demonstration, I instructed students to complete the Human Machine Collaboration Writing Assignment class, which consists of two sections. The first one, play with the text generation interface to produce machine made text and then manually, I mean by hand, compose a reflection on the influence of AI task generation technology on academic integrity.

The reason I chose to use Open Source things instead of ChatGPT is because it’s because of my intense concern about student’s privacy. I still remember the first time I logged into ChatGPT , I felt  very uncomfortable because it wanted me to provide my phone number.

I would say when I design these assignments and this class practice, I think okay, I need to take seriously students’ privacy. I don’t want students to do it because they need to complete assignments, they have to in a certain sense sell their privacy and information to ChatGPT or any other big company.

I appreciate you giving me the opportunity to participate in the writing projects in the AI Anthology. And from the project I learned how to utilize generative textings.

In my class at the end of the project, students require a combination of output of tech genearators and their own refresher on projects.

As you can see on this slide, students’ answers are very promising. Moreover, this platform permits students to read their classmates comments, and advise each other about how to deal with the issue.

So I want to say to instructors of history and scholars and professors, of English literature, etc.,  may be worried about students’ abuse of text generation technology. But it is my contention that there’s nothing to fear but fear itself, besides bribery. Face the threat.

Instead of avoiding any talk about it, we should avoid censors as well. With the emergence of some technology like a GBT Zero, they may detect their misuse of GPT or whatever. GPT  4 or in the future GPT 5.

The competition between the technology helping academic misconduct and its prevention is still ongoing. Along with the proliferation of detectors like GPT Zero. New detectors will be created constantly. So this issue brought by the technology could be solved by advancements of technology itself.

It’s more important to instruct students to maintain their academic integrity rather than just say, okay, you cannot use ChatGPT in a class for completing assignments. Well, we know students will do that. You just assume, okay, those students, they are so honest. They don’t do that. No, they must do that.

I want to talk about my prospect or my thoughts about the future of ChatGBT as it’s used in a classroom. So I want to say at least, you can see the priorities I demonstrate here.

I just want to say, okay, let’s try this in the class ‘Tragedy’. That’s fancy stuff. We can try that. But in the future, in the coming summer, I will teach another undergraduate class about Chinese history. I’m thinking at this moment, I’m designing my class.

I’m thinking about creating what I call a human computer co-authorship assignment. I will allow, not required, but I will encourage students to try to work with ChatGPT or whatever, text generation technology, to complete the assignment.

But for this assignment, I will require student to provide some acknowledgment statement in which you need to tell me which kind of tool, which kind of algorithm you use in the class in an assignment and which part of the assignment is considered by yourself, human. Which part is co-authored by you, or the computer. You work together, but which part is just composed by the computer.

So I want to say, I want students to acknowledge the authorship of a computer if they utilize ChatGPT or GBT-4 or even newer generations of text generation technology in the future.

So that’s my thoughts about pedagogical use of text generation technology now, and the near future. Thank you.

Geoff Davis

Thank you, Shu. That’s a really interesting approach because often with lecturers and students, they just ban it. I know, I’ve got teenage children, and the schools just ban it completely. But I think with younger children, they have to learn things more than just use a generator, whereas in higher education the students are more mature and they can understand that they have to co-author things. I read a statistic somewhere that lecturers use the generators more than the students, for producing coursework. So it’s kind of unfair in some ways, but I think the students have to be mature enough to work sensibly on it. So there is a problem there, definitely.

I think your approach is very good to get people to co-author and then acknowledge. So yeah, that’s very good.

Well, I think we’ve come to the end of the speaker section now, so we can go into a discussion section now where if anybody has any questions.


Sean Clark (Zoom)

“David’s iPad” has a question.

“David’s iPad”

I’m finding it really deeply fascinating to play around with ChatGPT as a poetry writing tool. And I’m really working on a lot of prompt engineering with regard to the poetry, such as change this into the style of so and so, where I’ve gotten to is that the state of the art right now is that a lot of sonnets have been written by ChatGPT and it seems to be quite good at haiku and generally things like that.

What I’m interested in is what sort of prompts the panel is interested in exploring, in particular the fact that there’s no longer a need to actually build the language model. In the way that that very interesting work from the University of Washington [Tivon Rice], but it’s sort of a more organic relationship with ChatGPT. And I just wonder if there’s any interesting lines of inquiry the panel feel, especially in the area of poetry.

Tivon Rice

Can I jump in, just give my two cents. I think that for prompt engineering, a couple of the things that I’ve found to be really useful are to ask ChatGPT to give multiple versions of something. Give me ten of this thing. Of course, you’re going to provide your own context for it, but then I always typically end my prompts with in the style of as well. And so instead of fine tuning at that point, you can steer it towards whatever paranoid fiction, or towards surrealism, or towards absurdity or these sort of things. This becomes a replacement for actually fine tuning.

I would also argue that if you have the opportunity, Chat GPT is very accessible and very easy to play around with. But if you sign up for OpenAI’s API, you can pretty much access the exact same models GPT-3, different versions of GPT-3, and now even GPT-4 through their API. Not necessarily through a code line interface, but through their sort of playground. And it’s going to behave much like ChatGPT, but you get access to things like temperature, which modulates the weirdness or the sort of normalcy of the language. You can modulate things like you can penalize it for repeating itself and these sort of things, even though you’re not fine tuning a model, they can get you closer to having that kind of authorship and directorial, it’s sort of like the next level for prompt engineering.

So whether or not you go that direction, just keep in mind that that’s what’s up to you when you use OpenAI’s playground rather than the basic ChatGPT.

“David’s iPad”

But, I mean, bottom line is I’m kind of onto something here because there’s computers, there’s coding, there’s structure, there’s poetry, there’s definitely something there. Isn’t that? I feel it in my poem.

Tivon Rice

Yeah. No, I agree. I think that, as I mentioned earlier with Maria, there’s a lot of people individually using this equipment, kind of at home doing this thing called personal content generation or ambient literature, where nobody’s really thinking they’re a poet and they will be published, they’re just doing it because it’s so absorbing and so interesting. And the same applies to image generation. One thing I’d say, I’ve used the older hand built systems and I used to kind of load in all I write, fiction have been published, not recently, but have been. So I put a lot of my own fiction in and used that as the training data. And it’s amazing how it can follow the style. Now, that can also be done in the new systems just by putting in a big section of your own writing and then telling GPT Four or Chat GPT to use that as a style. Copy that style from a text you’ve given it and then it will carry on with new material, which could be your personal style or a style rather than saying in the style of James Joyce or in the style of Welsh or somebody famous, which it will know.

Geoff Davis

Just put your own work in and it’s a way of doing the fine tuning without having to do any coding, which it used to be in the old days. So the bigger models now are kind of flexible in this way, and I think it gives bigger access to people that don’t do any coding whatsoever, which is obviously the vast majority of the population. Maybe not the vast majority of the population here, but outside there, most poets don’t know how to code at all or use an interface like an API. They wouldn’t know what to do, but they can understand the idea of putting their work in and then copying it. So, yeah, very interesting, this whole area, I think.

Any more questions?

Sean Clark

Okay, well, I think that’s been a really interesting evening. I’m still trying to make sense myself of these AI tools, and I find the best way to try and make sense is to try and use them. But I think even with the experts here, I’m sure you’ll agree that where you’ll be in a few years time is probably going to be very different to where you are now because the technology changes so quickly. So I think it’s important for all of us, certainly those interested in using technology in a creative way, that we do try to understand this technology and we do generate or get some experience in doing it. So thanks very much for giving us some pointers. I also thought, Geoff, you should mention that book again, actually.

Oh, the book again. It’s called the AI Creative Writing Anthology. It’s the first of its type I think. It’s from Leopard Print Publishing in London, which is an indie press. But if you put in AI creative Writing anthology into Amazon or wherever you get your ebooks from, it will turn up and there’s quite a big sample, you can read for free.

The book has got 20 authors and artists in, including the four people tonight. I’ve put a few things in and I’ve written the introduction and I put some pieces at the end about the background and so on. It’s got lots of references, lots of interesting work, but there’s also a lot of other material.

One of the most interesting things in it is that each writer, I asked them a whole set of questions about how they felt about using the generators and how it affected their work and so on. And all of that is published with each story.

I think probably the first time you get creative work plus the writer’s explanation of how they did it, how they felt about it. And this provides really interesting insights into using generators. And that’s all in this Anthology. So it’s not just a collection of stories, it actually has all this kind of meta level discussion of how they did it. So it’s worth having a look at even just for it.

Certainly it hasn’t been out very long and the paperback isn’t out yet, so it might have a few slight changes. But think the most interesting educational side of it apart from the entertainment, the art value, is the fact that you can get an insight into how people thought about using the generators because this is such a new area. Now, I think the writers, the people here in the group all know this because they are in the book with their comments as well as the story or piece.

Sean Clark

Well, I think if you could make sure we’ve got a link and likewise your speakers, if you collect links and contact information from them. I’ll put all of that information on the CAS website.

Geoff Davis

Yeah, that’s great. If you go to the website, which is my name,, if you look at the most recent blog, it’s got this talk in it, plus the references are in there. So everything should be in there just to checking and then we get it up on CAS website as well. And if anybody wants to contact me directly for further help, then that’s fine, obviously. So, yeah, excellent.

Sean Clark

Thank you very much. And next time. I was going to say next month, but it’s slightly more than a month. It’s the 1 June, you’re going to be hosting a session about the use of image based tools in creativity. So that’ll be an interesting sort of counterpoint to the use of text tools.

Geoff Davis

That’s right. And we’ve got some interesting people there, including Anna Ridler, who uses machine learning, Mark Webster, I mentioned tonight, Patrick  Lichty, who’s an AI conceptualist, and it’s introduced by Luba Elliott, who’s an AI curator. So she’s going to do a brief history of the field.

And the video will be online as well at some point.

Sean Clark

Yeah, towards the end of the week. I’ll pop that up on the CAS channel and I’ll try and mail out all the attendees. So if, Geoff, you can collect that information over the next couple of days, I’ll make sure that goes out in the email.

Geoff Davis

Excellent. Okay, goodbye. Bye, everyone. Bye.

References (in order of appearance; extra references are at the end)

Geoff Davis is the editor of the AI Creative Writing Anthology (Leopard Print London, 2023) which has 20 stimulating entries and a lot of extra material. It includes the speakers. This is on Amazon and most other sites and has a large free sample.

Please visit:

AI Creative Writing Anthology: 20 Authors share how to use computer tools


Geoff Davis

Blog and research –

AI Creative Writing Art Anthology 2nd Ed

Editor – AI Creative Writing Anthology (Leopard Print London, 2023)

AI Creative Writing Anthology Geoff Davis 2023 GPT-4 ChatGPT
AI Creative Writing Anthology Geoff Davis 2023

MA4 Story Generator – Geoff Davis 

MA4 Story Generator is on the Micro Arts Group website

Story Software creative storyboards

Notes Storyboard v2.2 – text and images


Story Lite – text only


Micro Arts Group – generative art, magazine, exhibitions, community



Tivon Rice

Ray LC

Maria Cacelia Reyes

Shu Wan


Mark Webster

Show in London 2022

Sasha Stiles

Digital poetry site theVERSEverse

theVERSEverse is a literary gallery where poems are works of art.


Janelle Shane

You Look Like a Thing and I Love You (book)

Gwern Branwen


Inside the Mind of BRUTUS, a Storytelling Machine (2002)

RNNs: The Unreasonable Effectiveness of Recurrent Neural Networks

Large Language Models


Sparks of AGI: early experiments with GPT-4 (2023)

“The new wave of AI systems, ChatGPT and its more powerful successors, exhibit extraordinary capabilities across a broad swath of domains. In light of this, we discuss whether artificial INTELLIGENCE has arrived.”

Video recorded at MIT on March 22nd, 2023

Sebastien Bubeck lecture with many demonstrations

Apr 6, 2023

Paper available here:


Liberal Bias and the Right Wing AI

David Rozada

Elon Musk X.AI

Geoff Davis – Emotional LLMs

Please find this in the blog. The paper is in review.

Jaron Lanier – There is No AI

Connie Loizos – We all contribute to AI — should we get paid for that?

We all contribute to AI — should we get paid for that?

Nick Bostrom

Superintelligebce book (Oxford, 2014)

James Bridle

Books –  New Dark Age; Ways of Being.

Brian Reffin Smith

Me to ChatGPT:

Me: Write a BASIC program that is at least as good as ELIZA, and which can talk about art as well as general topics

ChatGPT: Sure, here’s a BASIC program that uses natural language processing techniques to simulate conversation and can talk about art as well as general topics. It’s not as advanced as ELIZA, but it should still be able to hold a basic conversation.





To see the code please visit his Facebook page and scroll to 12 March 2023.


How do AI art generators work, and should artists fear them?

Ambient Art

Games: AI in Video Games: Toward a More Intelligent Game

AI in Video Games: Toward a More Intelligent Game


Sudowrite AI writing Assistant

David Byrne comment

Eliminating the Human

We are beset by—and immersed in—apps and devices that are quietly reducing the amount of meaningful interaction we have with each other.

MIT Technology Review, April 2023



AI writing apps and software CST – top 10 – top 50

(Updated frequently) A long list of writing software that uses AI, quoting their by-lines (more than 50 now)

Geoff Davis AI writing and art
It’s not that bad.. quite useful in fact….

AI text processing writing software, also including Notes Story Board (zooming), Granthika, Scrivener.

Includes NLP and text generation techniques.

October 2021, updated ocasionally – last Nov 2022

After The Deadline

“We use artificial intelligence and natural language processing technology to find your writing errors and offer smart suggestions. Our technology is available under the GNU General Public License. ”

AI Writer

“Generate unique text with the ai article writer”


“Generate effective copy for ads, emails, landing pages, and content. ”


“Create unique textual content in a flash”


“The best self-editing platform available for a writer. ”

AX Semantics from Gartner

Increase Your Online Sales With Better Automated Content Writing

Our easy-to-use Natural Language Generation software helps you and your team

Conversion AI

“Your AI copywriting assistant. Now Jarvis can help you write blog articles, social media posts, sales letters, and even books. ”


“AI powered software that generates ad copy, product descriptions, sales copy, blog paragraphs, video scripts & more.”


“Supercharge Your Content Brainstorming with AI. ”


“Create content for every stage of your marketing funnel. Start your first campaign free. Broca generates content for ads, blogs, email, social media, and more using AI. ”


“EssayBot is your personal AI writing tool. With your essay title, EssayBot suggests most relevant contents. It paraphrases for you to erase plagiarism concerns”

Explain Paper

Upload a paper, highlight confusing text, get an explanation. A better way to read academic papers.


“Flowrite turns words into ready-to-send emails, messages, and posts in your personal style”

Galactica (from Meta – now offline)
“Researchers are buried under a mass of papers, increasingly unable to distinguish between the meaningful and the inconsequential.”

This has been taken offline after three days as it produced too much false information, which is acceptable with normal language production as it can be easily spotted and edited, but not science, where people don’t know the topics, and can’t tell randomly generated science waffle from actual scientific results.

Gavagai Explorer

“Optimize customer perception, boost operational excellence,
manage brand reputation, and detect potential crisis instantly. ”


“With fast, easy, and effective content generation, artificial intelligence is here to take away writing blues”


“Make writing easier. Team up with our AI-powered writing assisitant”

Grammarly Business

“Professional Communication For Your Team

With Grammarly Business, every member of your team can compose credible, mistake-free writing that makes your business look good.”

Granthika (not AI)

“The writing super-app built by writers.”


“Writing copy is time-consuming and difficult. Headlime’s artificial intelligence can take your thoughts and turn them into words, saving you tons of time so you can focus on what matters: your business”

Hemingway App

“Makes your writing bold and clear.”

Hypotenuse AI

“AI Generated Product Descriptions. Automatically generate copywriting for your e-commerce website in seconds. ”

From Linus Lee.

See Merlot.

A focused environment where you can write freely. Now with lasers.
(iA is information architecrure.)


Ink For All

“Explore over 40 AI writing tools for short form content, ads, email, product, startups and more. ”

Jarvis AI

“Artificial intelligence makes it fast & easy to create content for your blog, social media, website, and more!”

Jarvis has been renamed Jasper because it was the name of Tony Stark’s AI assistant in the Marvel movie Iron Man. Marvel sent a C&D to them. So hello…

Jasper AI

“Artificial intelligence makes it fast & easy to create content for your blog, social media, website, and more!”


“Write Smarter, with Confidence. Take your typing to the next level using Lightkey’s AI-powered text predictions in applications you use every day.”

The World’s fastest editing tool became 10x more faster after our latest update.


From Linus Lee

See iAwriter

Merlot is a web-based writing app that supports Markdown. It replaces iA Writer

Muse Creative Content Assistant (Muse CCA)

“Create More. Work Less. 3 Easy Steps! ”


“Your AI copywriting tool for more conversions with less work.”


“Text understanding/generation (NLP), ready for production, at a fair price.
Fine-tune and deploy your own AI models. No DevOps required.” (Also has text to image using Stable Diffusion.)


“Driven by AI, construct unique stories, thrilling tales, seductive romances, or just fool around. Anything goes!”

Peppertype AI

“Your Virtual Content Assistant. Generate better content copies in seconds with the power of Artificial Intelligence”

ProWritingAid (not AI)

“For the smarter writer.”

Sapling AI

“AI writing assistant for customer-facing teams”

Scrivener (not AI)

“Scrivener is the go-to app for writers of all kinds, used every day by best-selling novelists, screenwriters and non-fiction writers”

Story Software (includes Notes Story Board (not AI), Story Live AI (GPT-J), Story Lite) – from Geoff Davis (this blog author)


“The first and best 5 star story board text & images zooming notes app”

Story Live

“AI text generator and editor , with GPT-J Text Synth by Fabrice Bellard.”


“Bust writer’s block and be more creative with our magical writing AI.”


“Text Cortex uses its advanced AI to generate Product Descriptions, App Reviews, App Descriptions and many other marketing texts.”

Verse By Verse (poetry)

“Google’s New AI Helps You Write Poetry Like Poe”

Virtual Ghost Writer

“Writer’s block? Never stare at a blank screen again!”

Word AI

“Automatically create human quality content with WordAi. WordAi uses artificial intelligence to understand text and is able to automatically rewrite your article with the same readability as a human writer”


“With Writesonic’s AI-powered writing tools, you can generate high-performing Ads, Blogs, Landing Pages, Product Descriptions, Ideas and more in seconds.”


“Your thoughts in words. Say exactly what you mean through clear, compelling and authentic writing.”

Writer! (Qordoba)

“AI writing, content intelligence, and AI writing assistants—these are the waystations for what will soon become just simply writing. Writing with the full breadth and depth of your objectives, audience, messaging, and brand at your fingertips.”


“The most powerful writing improvement software in the world. Powered by advanced artificial intelligence (AI) technology, WritingAssistant can assess and enhance your writing”

A Mountain of Pent Up Tears – children’s stories generated texts

Children’s stories this is part of the classic literature series on this blog, experiments in hybrid fiction. 

I turned out so fast, I barely looked back. (I turned to look, only to find the figure had gone.) What has gone before was the dark room.

In the far left corner lay a pile of books. The ones on the page, all full of life’s lessons; the black ones, I thought of the colorless, the dark books, my soul had never seen red in my life. These weren’t books of old stories. These were children’s stories told by old schoolboys, and children’s books have been around ever since:

This was written in the 1840s when young, red dwarfs lived in the forest. They wore their clothes brown and brown and purple. At the close of the story, the author makes the child a dwarf, the woods were too far for them to go, so they are made brown. His book is told like many children’s stories.

“This is where the forest is.”

“The forest, where do I go then?”

“In the woods. In the woods, as you said.”

“I, too, am brown.”

“Yes, I am. I am in the forest. It is the way of the forest.”

“And me?”

“Yes, too, me too.”

“And you too?”

“Yes, too.”

The forest is the only place in which these children can know what things are true. They see the forest as their only home. If they go away, then they see them as an enemy who must be conquered. But these children have all travelled over, and gone past. They’ve seen it all over again.

They know what the forest is; how it works, how things go. They can see everything. And for some reason they know that they are all in the same boat, that they can never cross over to other paths. So they know, even in that boat, what the forest means, and why it is there.

What’s behind the green, silver-tinted door. Where’s the white door? That’s not the forest, is it? The white door has never been there. What was behind that door, the door to the land?

They do not know why they were born into the woods. They think that the forest is God’s gift for them. But what’s there to be gifted for? They are the only ones, after all.

When asked how the sun comes out, and when asked why the sun comes out.

Answer: There is no one here who knows.

And they need not have seen the sun.


GD: the first 68 words of the generated text (above) was next used as the prompt to generate the text (below). The 68 words are shown in italics.

I turned out so fast, I barely looked back. (I turned to look, only to find the figure had gone.) What has gone before was the dark room.

In the far left corner lay a pile of books. The ones on the page, all full of life’s lessons; the black ones, I thought of the colorless, the dark books, my soul had never seen red in my life.  

There, I thought, was the door leading to what was yet to come. But in the darkness, an unseen figure, one I couldn’t yet recognize, looked from the left to the right, slowly. As it followed, my eyes scanned the walls, but I couldn’t find the same room. I reached out to touch the door, but the figure stayed, a blank shadow across the room, it never left the door. It seemed to vanish into nothingness.

Then came an accelerating sound, as the figure dropped, and it moved slowly back into the room.

“What have you done?” I cried, the words begins to rise up like a mountain of pent up tears. There, I found, was the door. It turned, and my body seemed to lift it, before the figure itself left to my side.

A smile appeared on my face as I looked at the room, the books filled a giant library with life and lessons, the black ones I had hoped would be my own in my own time, the colorless ones, the ones I’ve already read, the ones I’ve been looking for. They were to tell me what I would need to know, how to survive this night, to know the unknown. They were a path, a map.

In the darkest hall, the room I saw the figure enter, a pale shadow in the light. The place was dark, it was cold. He took me in, and  I felt he was going to kill me, he was taking me inside. The sound woke me, and I opened my eyes to find another shadow, a figure standing behind me. I didn’t know what he was, but I was in my own home.

That man walked towards me, eyes glow green, his eyes were gloomy, the healers he wore, his hair was matted with grey, it was grey that faded in between them. He was big, at least, if a little tall. At least I had grown the right size for this thing.  I don’t think his arms were big, so that is probably just his arms, or perhaps his face was too short for his eyes. His fingers were lank, the seated fingers were black, and  in the dimmest corner of his head was a hood, with no lights.

It was very dark, there was an open door beyond it. He held my hand like a…well, for I was small. I could tell the size of his hand. He had long grey hair in his hands. He held my hand, and I saw red, it was black, as if it was a red colour.

I thought, and in that moment, my skin was soft and shiny. In between my knees. So, I moved over and looked, in my hands, and there was a dark green hand, with red hands, I knew this was a shadow, but that doesn’t mean anything to him.

The first hand, the first hand was big, its face was black, it was large, for I was small. The black was green, its color was darker than red. I touched it, and it was cold.

The second hand was big, but the hands were dark, and had big fingers, the first hand was long and dark green, it was like a purse, I didn’t know how it was, but it was cold, in that moment, I froze.

I could only watch.


You can guess the original story from the image (below).

Little Red Riding Hood and Wolf


Photo credit

Sentiment Analysis of Caption, News and Fiction text generation experiments

From: text generation editor research (UAL London 2020 see credits).
What happens when writers use a computer text generator to write articles, giving them only an image prompt.

Go to Index of AI research

Sentiment Analysis

The Study had three text generation and editing tasks, to make a Caption,  a News article, and a Fiction story, using the same image prompt of a dog and man.


This shows differences in Positive sentiment affect between the three different experiments. Most positive at the start, by the end, a balanced neutral view had become evident.

Fear was shown in the first Caption experiment, but was lost in the second News and third Fiction, showing acclimatisation by experience. Generally Negative scores were low.

By Fiction experiment, the third and final, only Sadness was left.


This shows a learning process during the three experiments.

All results are cautioned by the strong ‘Tentative’ score 0.91 and lack of any ‘Confidence’ scores over 0.5.

Details – Method

For overall sentiment of responses, all text feedback was summed into a total text field per respondent.

Text comment fields were:

Caption, News and Fiction Experiments (3 fields);

Questions 1 (2 fields), 2-6a (5 fields), 6b Fake news (1 field).

This gives 11 feedback text samples per respondent (not all were filled). These are summed vertically in Excel to give the overall text block per column/field.

Texts were also summed per respondent, horizontally in Excel.

NLP and IBM Tone Analyser

NLP (natural language processing) allows computer analysis of text blocks. For this volume of text, the online IBM Tone Analyser (See References at bottom) was used. Writing a custom analyser was outside the scope of the study. Human grading was not possible due to the size of texts when totalled, however human analysis is used for the summary of texts.

IBM Tone Analysis gives a rating for:

Anger Fear Sadness Joy Analytical Confident Tentative

(Coded on data as Ang, A, F, S, J, A, C, T.)

The “most prevalent tones that are detected for each utterance” are shown at a document level, and sentence level.

The document level analysis has scores, and the sentence level (which shows lower occurrences) was added in brackets. This gives a results for example, where the detected tones have a numeric score over 0.5. Scores: <.5 None; =>.5 – .75 Mid; >.75 Strong

At document level, each tone if found, has a score .5-.1.0

Lower graded tones (placed in brackets in data) are placed at the 0.25 level


J,S,A,T(C,F) – Joy, Sadness, Analytic and Tentative have scores > .5 (and C Confidence, F Fear have lower occurrences only, between >0 and < 0.5)

Ang,F,S() – Ang is Anger, Fear and Sadness have scores > .5 (no others over 0)

F(S) –Fear scores > .5 (Sadness between >0 and < 0.5)

In my data display, a ‘lower occurrence’ (bracketed) is scored at 0.25

Confidence and Tentative are general attitudes shown in the text.


All respondents summed

Caption experiment – all feedback comments

Graph - IMB TA Caprion.png

With motivated stakeholders as respondents, there are high scores for ‘Analytical’ and ‘Tentative’. ‘Confidence’ did not appear at all as a document level tone in all 82 people, and occasionally as a sentence level tone.

Using the highest score amongst ‘Anger’, ‘Fear’ and ‘Sadness’ as Negative, and using ‘Joy’ as Positive, shows a higher degree of positive response.

Fear is evident, but at a low level. Sadness is the strongest of the negative reactions.

Positive is about 20% more than Negative. (Significance.)

News experiment – all feedback comments

Graph - IMB TA News.png

More overall positive result than Caption experiment.

Fear has gone, low levels for Anger and Sadness Negative tones. Positive is about 42% more than Negative.

Fiction experiment – all feedback comments

Graph - IMB TA Fiction.png

Sadness at its highest level. Not Positive or Negative. Anger and Fear do not appear.


This shows differences in Positive sentiment affect between the three different experiments. Most positive at the start, by the end, a balanced neutral view had become evident.

Fear was shown in the first Caption experiment, but was lost in the second News and third Fiction, showing acclimatisation by experience. Generally Negative scores were low.

By Fiction experiment, the third and final, only Sadness was left.


This shows a learning process during the three experiments.

All results are cautioned by the strong ‘Tentative’ score 0.91 and lack of any ‘Confidence’ scores over 0.5.


IBM Tone Analyser

Please see full Report  for further statistics (tba).

All the Rubbish of a Great City – classic literature vs text generation

All the Rubbish of a Great City


From the series of classic literature vs the future…

All The Rubbish of a Great City

Part 1: No Sun Ever Since That Day


Dear Farewell

You may be glad to see your letter of 6th April last from me. You are still in the good humour of the last time, and I believe that the people will be kind and kind to you in your letters.

I hope you will send me the following on the 15th of June: 1st: to my brother, a messenger, and my wife; 2nd: my daughter; and to my sister; then my brother; and my sister to my husband; and my brother to my son; and my father to my son; and my daughter to my husband and sons; and to my daughter’s father.

It is impossible for me to perceive a trace of the abominable scenes which I have experienced. There are but a few houses destroyed, and most of them, that is, very pretty ones, and all are occupied with families, and a few shops: one street is covered with all the rubbish of a great city; its streets are of a grey nature; and the streets are all closed off by some heavy iron gate.

I take a seat in a corner of the square; and after taking food from a little table and taking a seat beside a shopkeeper, or at least an old man with a hat on, I look about me. Nothing remarkable is seen or seen; there is no ruin or any signs of destruction; you might as well go near the ruins of the pyramids. The women seem to be quite contented, and are making the little fires that are burning. We are very anxious, we are very sad, to see them.

As I was about to arrive at the coast, I was suddenly knocked out by the wind; my companions, who were not surprised, rushed to me. I lay in their arms, and told them I could not recover myself, and said it was time for my expedition to proceed.

I begged them to give me some of the best part of the sea to make my recovery. They assented, and then threw out with me a large quantity of salt that I could not bring home to myself, and I fell dead.

They gave me some of their gold as I lay dying.

I never heard of such an occurrence; I should have been ashamed to have done so; but I had too much hope in the fortune of the sea; for if I were lost by such misfortunes, one does not have what has been given him; for if the fortune be bad, man do have a right to hope.

They put me into the boat with their captain, Sir Richard, and took me back to the ship where we were sitting. I lay there several days; I thought I had done well, but they told me the fortune was the same; the sun set over the mountains that night, and gave no sun ever since that day.

My mind was so troubled about my condition, that I could not bear the noise of the ship, so I cried, and fell into a terrible state of sleep, and then lay, my head, and neck, and legs, down upon a bed.

[These words, which do not make any impression on the ear, should appear to prove the correctness of the saying.]



Frankenstein  or The Modern Prometheus

Mary Wollstonecraft (Godwin) Shelley 1818

Letter 1

To Mrs. Saville, England.

St. Petersburgh, Dec. 11th, 17—.

You will rejoice to hear that no disaster has accompanied the commencement of an enterprise which you have regarded with such evil forebodings. I arrived here yesterday, and my first task is to assure my dear sister of my welfare and increasing confidence in the success of my undertaking.

I am already far north of London, and as I walk in the streets of Petersburgh, I feel a cold northern breeze play upon my cheeks, which braces my nerves and fills me with delight. Do you understand this feeling? This breeze, which has travelled from the regions towards which I am advancing, gives me a foretaste of those icy climes. Inspirited by this wind of promise, my daydreams become more fervent and vivid. I try in vain to be persuaded that the pole is the seat of frost and desolation; it ever presents itself to my imagination as the region of beauty and delight.

There, Margaret, the sun is for ever visible, its broad disk just skirting the horizon and diffusing a perpetual splendour. There—for with your leave, my sister, I will put some trust in preceding navigators—there snow and frost are banished; and, sailing over a calm sea, we may be wafted to a land surpassing in wonders and in beauty every region hitherto discovered on the habitable globe. Its productions and features may be without example, as the phenomena of the heavenly bodies undoubtedly are in those undiscovered solitudes. What may not be expected in a country of eternal light?

I may there discover the wondrous power which attracts the needle and may regulate a thousand celestial observations that require only this voyage to render their seeming eccentricities consistent for ever. I shall satiate my ardent curiosity with the sight of a part of the world never before visited, and may tread a land never before imprinted by the foot of man.

These are my enticements, and they are sufficient to conquer all fear of danger or death and to induce me to commence this laborious voyage with the joy a child feels when he embarks in a little boat, with his holiday mates, on an expedition of discovery up his native river. But supposing all these conjectures to be false, you cannot contest the inestimable benefit which I shall confer on all mankind, to the last generation, by discovering a passage near the pole to those countries, to reach which at present so many months are requisite; or by ascertaining the secret of the magnet, which, if at all possible, can only be effected by an undertaking such as mine.


Your affectionate brother,
R. Walton

Stanley Lying in his Lap – classic literature

Stanley Geoff Davis


Classic literature vs artificial intelligence – try and guess classic source.


Stanley Lying in his Lap

His face was almost as pale as his fur and the top part of his ears were slightly raised above the shoulder blades.

“Oh, God, what’s happened to me?” he said. “How on Earth have they left me here?”

He saw Stanley lying in his lap. He was standing there naked and looking at nothing. This seemed too strange and too inhuman. Stanley was dead. The whole floor was shaking with the force of the shaking.

“I don’t know,” he thought. “Something’s happened to me. My father… how? God, how have they… done it? What has gone wrong? Where are they?”

And then he heard Stanley’s voice. “Hello, Stanley!”

He turned and saw what looked like him, though his face looked a little too pale to be him, sitting in the chair next to the boy. His hair was in a mess and the fur hat had come loose. He was looking very, very… unwell.

“Why?” he asked.

“I said: ‘Why can you not see me?’ ”


Stanley looked up at him. “Your mother… her eyes! Her… look!”

He smiled very happily. “They were mine.”

Stanley looked at the boy and then at him. “I see you. I see the world. I’m a fool. I’m too good for the world. But, in the end, what is this? The world that you can see? Where my father will come when he wakes up in this, this bed, on the other side of the wall, on the other side of this wall, and I won’t have to come here. Where will I find someone? Who? Where will I find him?”

It was the most beautiful and sweet thing he’d ever heard Stanley say.

“Where will I find him?”

Stanley tried to keep his eyelids closed, which was much too hard when the strange visage that appeared before him was so familiar. The picture seemed to say: I am your true self. Stanley imagined himself the girl. An alien being, a human girl at first glance but it should be said he certainly looked like a human girl. Even his eyes, that were always open, did not seem to be aware of his reality. He had no eyes.

The whole room. The whole world, that was. There was only a black box that Stanley had brought with him, a small metal cylinder with three small black valves, and there were four smaller tubes with levers that the girl would let loose with her nose, and she would let them press the small black buttons up and down, all of which were pressed with a certain sort of subtlety and even less subtlety than the valves, a certain kind of subtlety that Stanley supposed was just a thing he did like to do. Stanley was trying to help with the manipulation, but what needed to be done wasn’t to press the levers; it was to open the box, to allow the room to breathe.

His mind had become fragmented as Stanley was trying to find what seemed to be an easy solution and even some understanding of Stanley’s intentions. But even then he couldn’t see the girl from his point of view, and only saw the strange visage.

“I’ll send you an owl,” he said.

He wasn’t exactly sure whether his voice was hoarse and distant or how close to death he was. It was his first time talking to anyone in a foreign language.

“Do it,” said a small voice.

Stanley stood up, looked around and couldn’t believe that his bed was the only place the floor was covered. It was the first morning. But he remembered everything. It was the first real thing he had lost before he went in the hospital. He knew what it was.

“You did,” said the woman. “You did so, and I thought you had passed into a nightmare but something happened next thing and I came back.”

“Oh, you did,” said Stanley. “I guess I got over it.”

“I mean I thought you’d gotten over it but this time you didn’t,” the woman said to herself.

Franz Kafka 1915

One morning, when Gregor Samsa woke from troubled dreams, he found himself transformed in his bed into a horrible vermin. He lay on his armour-like back, and if he lifted his head a little he could see his brown belly, slightly domed and divided by arches into stiff sections. The bedding was hardly able to cover it and seemed ready to slide off any moment. His many legs, pitifully thin compared with the size of the rest of him, waved about helplessly as he looked.

“What’s happened to me?” he thought. It wasn’t a dream. His room, a proper human room although a little too small, lay peacefully between its four familiar walls. A collection of textile samples lay spread out on the table – Samsa was a travelling salesman – and above it there hung a picture that he had recently cut out of an illustrated magazine and housed in a nice, gilded frame. It showed a lady fitted out with a fur hat and fur boa who sat upright, raising a heavy fur muff that covered the whole of her lower arm towards the viewer.

See the other classic manglings in this blog.

Why Don’t Cannibals Eat Clowns?

Part of the text generation series – see blog index.

Why don’t cannibals eat clowns?

Because cannibalism doesn’t produce the same health benefits as killing clowns, you will have only about 60% of your body weight of body fat left, leaving you with less body fat and no protection against the other 50%.

By choosing a suitable size clown, you can take advantage of that. If I am in a small town and in need of a good pair of shoes, I’ll eat an ogre and I’ll have about 100% body fat and 70% of my body weight in a pair of shoes.

What the hell am I supposed to do, I am going to starve?!

In that case I would just have to get one of those, because those are probably my only options.

Also, by choosing a size bigger or smaller than I am currently supposed to be, you can take advantage of that as well. I’m going to give up on these shoes and use the boots instead. I mean that literally.

If I were in a small town where there is limited supplies, and the only food available is a variety of meats and fruit that I’m supposed to eat (such as a spider or something), I would eat some squirrel.

But if there’s too much food and no other choice, then I will instead go for the more dangerous monster I can get.

Now the issue of choice is just that these are all options. You don’t know what your favourite will be unless you decide to look into it.

For example, while you can choose a size small enough to be your “smallest” and go for the larger you’re going to be the bigger your body fat will be, it just won’t work like that. The bigger you get, the bigger your body fat will be so it’s not going to be as easy to “do the right thing.”

What you want is for your body fat to be close to your own body weight, which is probably going to be under 0 (the ideal is probably between 10 and 12).

Also what you want is to weigh on average only about 70-75% of your body weight (about 70lbs for one person, or roughly a fat person for another).

That’s what makes you a normal person.


Why don’t cannibals like clowns?

If they’re not being eaten by the clown, it’s because they’re so fat they don’t have a stomach, so they get crushed by the horse. In the real world, people’s appetite changes over time as well. A hungry hippo’s hunger will rise over time so an old horse gets eaten by a zombie, and so on.

In fact, a lot of people have to eat a lot in order to keep the hunger in check. And there are also the many social cues that cause our appetite to rise and fall over time. Food is good for us, because it tastes good and is a good source of calories. And when it’s too much, we have a panic attack. When it’s just right, we can just be happy to just eat a bag of popcorn. And once we’re just right, we can eat the popcorn and forget about it.

Why aren’t hippos getting eaten by horses? Because they have a digestive system that has to move in to the horse’s stomach first, or there will be too much food in the horse’s stomach. The idea that this food goes in straight through the horse’s digestive system is just silly.

The only way I’ve seen this food in the wild is that it was consumed by some people who were infected with a fungal life-form and got it into their digestive system and their appetite was just too great.

The best part about all this is that it’s simple enough to understand. The only thing that we can do is stop eating, to do that you just wait till your health gets better. If you could just get rid of all these stupid foods for a week or so and let your appetite return to the normal state, even better. It’ll be like the beginning of autumn in the wild, there’s just not enough sun to cook food like it used to be and it’ll feel like no one’s eating.

As you have experienced, I’ve never.

This from a joke in Geoff Davis’s new novel The Circular River which will be serialised on this website next week

Photo credit – the Solomon Islanders, feasting trough.

Guess the original classics – Born Into Slavery

Born into Slavery

This is a game to see if you can identify the original story author in the generated text below. It has a new title: Born Into Slavery. The generated text is followed by the classic story which was used as the prompt for the computer generation. For technical details see end.


Born Into Slavery

What would occur when the daughter came for a visit? Her daughter could not wish to come here but if she had to she was certain to be disappointed.

When her eldest daughter was in her early thirties, Mr. Smith thought it might be advisable to take her away with him to her own country. The time had been long since passed; what had gone before was now forgotten. She was quite happy at home, though she knew the consequences of her leaving the family.

Mrs. Smith, who lived on her own farm, was the more interested of the two, as she had a son she loved. She would rather she had one of her own daughters than, with him, a son. As it was she was obliged to take him along, though with a slight advantage in health and strength. The child, however, was well behaved, and was very fond of her.

The old couple would have had a child when Mrs. Smith was dead; the latter would not have died till Mr. Smith, as they thought, had been ninety years old, and with her, after him. The child, as they said, would live till old Mr. Smith had died; if that should prove impossible, they would have had an heir to one of the first families to the west of the river.

Mrs. Smith was still an old woman, she remembered; her eyes had become dim, her hands and feet were weak, her feet were dull and bent, her hands wrinkled and loose. A change from her old condition, she thought, would have been too much for her now. She had always been happy in her old condition, though always in the present mode.

This story made her do something she thought necessary for the little girl, and she went into the hall and sat down in the great old chair opposite to Mrs. Smith

A woman’s strength, she thought, was her knowledge of her father’s affairs. She knew that as long as her children could walk with her, they could not be married.

Her husband knew that too; he knew where he was going, what he was going to do, and was never the same afterwards. There was a very large number of children, her daughters, living abroad, in the most irregular manners. He had grown somewhat deaf, with a peculiar difficulty about their voices.

And Mrs. Smith never liked it when she was in any degree unhappy; she could not bear to see her men, much less her children, so miserable. Every time they came she wanted to have a chat with them. She was a woman of very little self-control, and she would have felt an extraordinary strain in talking to men in whom she was so anxious to be connected. She had grown quite aware of the dangers of these visits. She felt that she had the moral to avoid them. It was the same with her husband.

One of the dangers she had to observe was whether they should try to give her good advice on an important subject; then she could say nothing but good things about them. And she did not give you any reason why.

And so he took her into another house, where she found him dead. Here is the explanation of one of our own writers, that was born into slavery, and who has since been made a public writer.

In the first place, we say that his wife knew, but she did not have sufficient excuse for going back to him. For she had been married to his eldest son, whom he kept with her, but she had never had a son, not that she was less prone to be the subject of any kind of cruelty than any other woman.

She was a woman well grounded, and could be trusted not to become a mistress or to marry a knave. Now, the reason why Master Smith was the property of Mr. Smith was, that there were several houses there, called for the use of this one Mr. Smith, and he was not there, but was there at a different time; so he did not know him or know of his own family.

But of course this also became a reason for the destruction of his father’s property; for those other houses were to be used by Mr. Smith at a later time, and hence there was no excuse to lose them. And he knew of the condition of his father’s property, and that he had been made a public writer.

Now he said to Master Smith,
“What is the reason of your going to me at this time, that I do not go to him myself?”

“Well, I have said to him before, I do not go to him, because my father was in debt to you.”

“How did I know it?”

“He had a contract of sale of my house, for you had a lease for the premises. You and your father made a bargain, and did not pay; but he does me to make good my debt. He gave me this lease, but left the property to me.”

“What can I do for it?”

“I will not go with you.”

And Mr. Smith went away in his ship; and while he was doing this, he heard the voice of his father’s son, who was living in the ship, saying to him,

“Your father has made you a public writer, at a time when I should have told you everything that you ought to know about me; and he is coming to me to sell my property for your property, and that we must not meet there till the day after the feast.”

As it happened, at the end of his talk with Mr. Smith, who would then have come to him, he heard of the destruction of Mr. Smith’s house, and of the damage done, for a great many months afterwards, to the houses belonging to his son, because of that man’s writing; and Mr. Smith went away in his ship, that there might be no necessity of his telling Mr. Brown that he might not receive anything from him from him without reason.

And it was, at that time, a great pleasure to him to have the ship and his house in the same box, and he said nothing of it.


Pride and Prejudice

Jane Austen 1813

It is a truth universally acknowledged, that a single man in possession of a good fortune, must be in want of a wife.

However little known the feelings or views of such a man may be on his first entering a neighbourhood, this truth is so well fixed in the minds of the surrounding families, that he is considered the rightful property of some one or other of their daughters.

“My dear Mr. Smith,” said his lady to him one day, “have you heard that Manorfield Park is let at last?”

Mr. Smith replied that he had not.

“But it is,” returned she; “for Mrs. Long has just been here, and she told me all about it.”

Mr. Smith made no answer.

“Do you not want to know who has taken it?” cried his wife impatiently.

You want to tell me, and I have no objection to hearing it.”

This was invitation enough.

“Why, my dear, you must know, Mrs. Long says that Manorfield is taken by a young man of large fortune from the north of England; that he came down on Monday in a chaise and four to see the place, and was so much delighted with it, that he agreed with Mr. Morris immediately; that he is to take possession before Michaelmas, and some of his servants are to be in the house by the end of next week.”

“What is his name?”


“Is he married or single?”

“Oh! Single, my dear, to be sure! A single man of large fortune; four or five thousand a year. What a fine thing for our girls!”

“How so? How can it affect them?”

“My dear Mr. Smith,” replied his wife, “how can you be so tiresome! You must know that I am thinking of his marrying one of them.”

“Is that his design in settling here?”

“Design! Nonsense, how can you talk so! But it is very likely that he may fall in love with one of them, and therefore you must visit him as soon as he comes.”

“I see no occasion for that. You and the girls may go, or you may send them by themselves, which perhaps will be still better, for as you are as handsome as any of them, Mr. Bingley may like you the best of the party.”

“My dear, you flatter me. I certainly have had my share of beauty, but I do not pretend to be anything extraordinary now. When a woman has five grown-up daughters, she ought to give over thinking of her own beauty.”

“In such cases, a woman has not often much beauty to think of.”

“But, my dear, you must indeed go and see Mr. Bingley when he comes into the neighbourhood.”

“It is more than I engage for, I assure you.”

“But consider your daughters. Only think what an establishment it would be for one of them. Sir William and Lady Lucas are determined to go, merely on that account, for in general, you know, they visit no newcomers. Indeed you must go, for it will be impossible for us to visit him if you do not.”

“You are over-scrupulous, surely. I dare say Mr. Bingley will be very glad to see you; and I will send a few lines by you to assure him of my hearty consent to his marrying whichever he chooses of the girls; though I must throw in a good word for my little Lizzy.”

“I desire you will do no such thing. Lizzy is not a bit better than the others; and I am sure she is not half so handsome as Jane, nor half so good-humoured as Lydia. But you are always giving her the preference.”

“They have none of them much to recommend them,” replied he; “they are all silly and ignorant like other girls; but Lizzy has something more of quickness than her sisters.”

“Mr. Smith, how can you abuse your own children in such a way? You take delight in vexing me. You have no compassion for my poor nerves.”

“You mistake me, my dear. I have a high respect for your nerves. They are my old friends. I have heard you mention them with consideration these last twenty years at least.”

“Ah, you do not know what I suffer.”

“But I hope you will get over it, and live to see many young men of four thousand a year come into the neighbourhood.”

“It will be no use to us, if twenty such should come, since you will not visit them.”

“Depend upon it, my dear, that when there are twenty, I will visit them all.”

Mr. Smith was so odd a mixture of quick parts, sarcastic humour, reserve, and caprice, that the experience of three-and-twenty years had been insufficient to make his wife understand his character. Her mind was less difficult to develop. She was a woman of mean understanding, little information, and uncertain temper. When she was discontented, she fancied herself nervous. The business of her life was to get her daughters married; its solace was visiting and news.


Prompt was 10-20 words from the original. GPT-2 system by Fabrice Bellard – see the site below for credits etc.
Made on my creativity app Story Live – please visit.

Text from Gutenburg free classic ebooks

A certain amount of cherry-picking of the most grammatical and interesting generated parts, but no actual editing (moving around of words or new words). Identifying names are changed.

More of these will be posted, see the index.