Category: Writing

At the start of November, I ran a seminar for a university transmedia course on ARGs, Alternate Reality Games. I was looking specifically at examples of three ARG-like projects had been taken as real, with disturbing effects. This post lists some of the links that I referred to. Another will follow with some thoughts on ARGs.

• An excellent introduction to ARGs is the 50 year’s of Text Adventures series on The Beast, a 2001 ARG written to promote the Spielberg movie AI. This was the first major ARG.
• I referred to a number of ARGs in my introduction. Majestic, from Electronic Arts, came out shortly after the Beast and was an interesting failed experiment. One of the most successful high-profile games was Why So Serious? (2007), promoting the movie The Dark Knight, which included phones hidden inside cakes.
• Although I didn’t refer to it in the session, I loved the Wired magazine interview with Trent Reznor discussing how his band Nine Inch Nails made an album, Year Zero, based around an ARG. I also came across some fascinating references to EDOC Laundry, a clothing line that was also an ARG.
• Perplex City was another successful ARG, run by a team including Adrian Hon. One of the puzzles form Perplex City was only solved after fifteen years. Some excellent background on Hon is in a 2013 interview, Six to Start: Foundation’s Edge.
• It’s interesting how ARGs provoked so much interest, but have not broken through to the mainstream. Alternate Reality Games Could Still Take Over the World (And Your Life) was a good article discussing this. It quotes ARG designer Andrea Phillips: “A lot of energy has [transferred] into lightly interactive web series, room escape games, narratives-in-a-box. Things that use a few of the ARG tools (tangible artifacts, in-story websites, email) but don’t use the full-fledged ARG formula.”
• I discussed the issues around the funding of ARGs, and how difficult that has proved. I also looked at how TV shows like Westworld and Severance have used the ‘mystery box’ concept to build audiences that research and discuss the plots in a similar manner to the communities that investigated ARGs.
• I then moved on to my three examples, the first of which was Ong’s Hat. Gizmodo produced an excellent overview, Ong’s Hat: The Early Internet Conspiracy Game That Got Too Real. The Ong’s Hat story was created by Joseph Matheny, and his story is excellently told in the two-part Information Golem podcast.
• Also worth mentioning is Matheny’s involvement in the John Titor hoax.
• The Slender Man was created for a photoshop challenge, and immediately inspired a number of ARG-like projects. Cat Vincent did an excellent job of summarising Slender Man for Darklore, paying particular attention to the way ARGs contributed to the development of the mythos. Cat also wrote a follow-up article in 2012. I previously used Cat’s research for my talk on ‘Brown Notes’, The Internet Will Destroy Us. Slender Man became a tragic case of ostentation, when two children who were obsessed with the character stabbed a classmate in Wisconsin.
• I then went onto talking about conspiracy theory, using Abbie Richard’s Conspiracy Chart to discuss the movement of conspiracy theories from (what many people saw as) harmless and silly ideas to dangerous (and often anti-semitic) ones.
• I used the ‘Birds Don’t Exist’ hoax as an example of using transmedia to promote a conspiracy theory, as discussed in a NY Times article, Birds Aren’t Real, or Are They? Inside a Gen Z Conspiracy Theory.
• Adrian Hon wrote an insightful article, What ARGs Can Teach Us About QAnon. While careful to draw clear lines between QAnon and ARGs, the piece nevertheless drew interesting parallels.
• I then concluded by talking about how ARGs often pretend to be real (‘this is not a game’), and the ways in which the lines between real and imaginary can be played with, particularly given how the media has an insatiable need for stories. I talked a little about Chris Parkinson and the film Tusk, referring a 2014 talk where he encouraged people to “Leave your stories lying around in unorthodox, unethical locations”.

A while back, I wrote about how my writing has developed through reading Chuck Palahniuk’s discussions of technique. An even bigger change over the last year has been to focus on publication, in whatever form that takes.

Anxiety over sharing my work has long been a problem. It wasn’t the simple ‘fear of success’ that some people talk about, rather a ridiculous fear of negative effects from publication. At the same time, I’ve been driven to write stories since I could first write a sentence, and these two drives have been in conflict. Sometimes I’ve thought I should quit writing stories and focus more on other parts of my life – but quitting didn’t work for me either, so I needed to find another way through.

Since moving to Yorkshire, I’ve put more effort into sending work out. A lot of my old work was written with little thought of an audience. It was fun, and some of that work was great, but you lose rigour if you don’t define yourself against any external standards. I wrote some good stories that I have no idea what to do with. An example of this is a story I wrote called Richey Edwards vs Godzilla, a mash-up of indie music and kaijus. It’s a great piece of writing, but almost wilfully obscure.

Change is a strange thing – it can take years but feel sudden. I’ve been toying with ways to put my work in public for a while. Part of this was attending a 2018 Arvon course with Tania Hershman and Nuala O’Connor, which provoked me into one flurry of submissions. The South Downs Way zine project has been an interesting way to explore publication, and putting recent volumes onto etsy has worked well. In 2022, I have become more consistent with submissions (41 so far this year) and it feels like a significant change.

It’s not as if I am now writing things only so they can be published. I have a huge number of ideas and it is more about working on the ones I feel I can find a home for.

Recently I thought about writing a folk horror piece about offices. It was interesting, in that it took the elements of folk horror and transposed them to a corporate setting. But, at the same time, it was mostly a cover version of The Wicker Man. If I’d worked on this, it would have been competent, but I couldn’t imagine being enthusiastic about submitting it. Long stories take a lot of time, and need to be worth spending so much energy on. In the end, I stripped out the elements of the piece I liked, and it will emerge as a smaller, stranger piece than it would otherwise. I’ve spent too long writing solely for myself, and I need to make up for lost time.

I recently had a story of mine, Holiday Wardrobe, read by actor Jennifer Aries at the London Liar’s League event. It’s about a disappointing holiday in a magical kingdom.

It’s particularly exciting to have a story selected by the League, as I get to hear my work performed by someone else. When I’m editing, I read my work out and edit it until the text seems to flow perfectly. Another person will take the same text and draw out different pauses and emphasis. It’s an interesting experience.

This is actually my second appearance at Liar’s League, the first one being in 2008, when my story Eat at Lovecraft’s was read by Becky Hands-Wicks. I’ve sent about half a dozen pieces over the 14 years since then, but this is the first one to be selected. Liar’s League is an amazing event, and I’m excited about submitting more in the future.

I’ve been curious about GPT-3 as a creative tool since reading about Matt Webb’s experiments in 2020. GPT-3 (Generative Pre-trained Transformer 3) is a language model that can create realistic text. The results are impressive, and it has even been used to write a Guardian editorial. In his experiments, Webb was confronted by phrases and ideas that did not exist before. The model produced original concepts such as the “The public bank of Britain”, and passages about “a three-mile wide black ring [that] was found in the ocean using sonar“.

The GPT-3 model is based upon millions of words of Internet content, and Webb has described elsewhere how “Reading GPT-3’s output, for me, feels like dowsing the collective unconscious. I’ve never seen anything so Jungian.”

You can get a quick feel for GPT by playing with the Talk to Transformer page, which allows you to experiment with the basic trained model. There’s a good overview by the Verge, ‘OpenAI’s latest breakthrough is astonishingly powerful, but still fighting its flaws.’ Or, for a more whimsical experiment, Janelle Shae tried asking the model how many legs a horse has, concluding, “It’s grammatically correct, it’s confident, and it’s using a lot of the right vocabulary. But it’s also almost completely wrong. I’m sure I’ve had conversations like this at parties” The origins of the model means it’s also particularly well informed about topics such as Miley Cyrus and Harry Potter.

Sadly, I’ve got no chance of getting my hands on GPT-3 any time soon, since it is kept under tight control to stop it from being used for evil. But then I remembered that Shardcore had used the earlier GPT-2 model for his software-generated book length collaboration with John Higgs The Future Has Already Begun.

I realised that GPT-2 ought to be sophisticated enough to produce something worthwhile, so I decided to give the basic GPT-2 model some additional training based on my creative writing. I’ve read recommendations that you need 25MB-100MB of text, but I’m using 6MB of my writing as input (generated from the source documents using Apache Tika). I was then able to use this with a colab notebook build by Max Woolf to do the hard work.

(I’d not used colab notebooks before, but I am stunned at how they combine workbook and instructions, along with a free VM to run it all on. For more detail, check out Robin Sloan’s post The Slab and the Permacomputer. It’s amazing to see how lots of people’s hard work has combined, allowing me to play with sophisticated models without knowing much about python or machine learning).

The snippets of text generated are identifiably mine in a strange way, but there are flights of fancy that surprise me. A description of a character: “He was a man of his word, not a man of action.” A phrase: “Nobody felt safe watching another human being do something with their lives“. There was a whole mad fantasy about “a group of ‘dusk-blue crabs’ who ’went by the name of ‘the great snout’“. There are also moments where the model just goes on and on repeating “Wax tins! Wax tins! Wax tins!”. Weirdly enough there was also a passage about a John Higgs:

John Higgs, the English economist and writer, died on 26th October, 2001. He was 83 years old. He was happy to join the world scene, and for good reason. He and many of his ideas were burned at the stake for their uselessness.

The main issue I have is my training data, which is unbalanced in various ways – a few novel-length texts, lots of notes. As clever as machine learning is, it’s only as good as your inputs.

Writing with GPT-X is not simply about churning out text – this text does needs to be worked on (This is not ‘cheating’ – Burroughs used to screen his manual cut-ups, looking for poignant and interesting generated sections). There are also different ways to work with the system – Robin Sloan has described some of the techniques he has used, such as hiding prompts from the reader (but not the model) to produce effective writing. These techniques are all waiting to be explored.

Matt Webb has written in detail about his experience of this collaboration in GPT-3 is an idea machine:

Using GPT-3 is work, it’s not a one-shot automation like spellcheck or autocomplete. It’s an interactive, investigative process, and it’s down to the human user to interview GPT-3. There will be people who become expert at dowsing the A.I., just as there are people who are great at searching using Google or finding information in research libraries. I think the skill involved will be similar to being a good improv partner, that’s what it reminds me of.

GPT-3 is capable of novel ideas but it takes a human to identify the good ones. It’s not a replacement for creative imagination. In a 15 minute session with the A.I., I can usually generate one or two concepts, suitable for being worked up into a short story, or turned into a design brief for a product feature, or providing new perspectives in some analysis – it feels very much like a brainstorming workshop, or talking something through with a colleague or an editor.

GPT-X can produce text faster than anyone can read it, but as Sloan writes, “it’s clear that the best thing on the page, the thing that makes it glow, is the part supplied by a person“.

For me, the question is whether it can produce interesting art (particularly art that is not solely interesting because of its process). What I’ve seen so far is both spooky and exciting. Whether this is more than a cheap trick of text remains to be seen, but my initial explorations make me very excited about collaborating further with this model.