Game thinking from Adam Clare

Tag: Artificial IntelligencePage 1 of 2

Maple Resistance: AI Trump Annexes Canada

Screenshot of the game Maple Resistance showing dialogue spoken by a fictional Donald Trump with text generated by a local LLM.

Screenshot of the game Maple Resistance showing dialogue spoken by a fictional Donald Trump with text generated by a local LLM.

I built a prototype of a game that explores the takes on of the “bugs” of AI and turns it into a feature. That bug is, of course, hallucinations. The way generative AI works requires hallucinations to function but to the end user the hallucinations can come across as a bug. Hallucinations are what causes the “false truths” and made up facts that generative AI spits out. I started to wonder  if there’s a way to make a game in which the hallucinations are beneficial to the play experience.

I want to create more games about policy and possible futures. In the same vain that the military uses war-games to train we ought to use policy-games to train our politicians and bureaucrats. A game gives us a space to experiment what works and doesn’t without actually causing harm to the real world.

With my AI thinking and interest in policy games I decided to make a game set in the year 2025 in which Donald Trump has won the 2024 election. Since Trump makes up facts and losses track of what’s being discussed he and a simple hallucinating AI could be indistinguishable from one another. The” bug” has become the feature.

The player’s goal is to prevent Trump from annexing Canada, so in Maple Resistance you negotiate with an AI Trump while trying to make political choices to protect Canadian sovereignty.

I also integrated a local LLM in the game; read on for why I made this game and what I learned.

It’s worth noting I started working on Maple Resistance at TOJam back in May and since then the world of both AI and politics has evolved (I was originally going to post this on July 15).

Screenshot of the game Maple Resistance showing dialogue spoken by a fictional Donald Trump with text generated by a local LLM.

Screenshot of the game Maple Resistance showing dialogue spoken by a fictional Donald Trump with text generated by a local LLM.


Maple Resistance: navigating annexation through gameplay

In 2025, the unthinkable happens: Donald Trump, re-elected as President of the United States, declares Canada to be part of the USA, following his successful annexation of Puerto Rico. But this time, there’s no military intervention—just a bold proclamation. This audacious scenario sets the stage for “Maple Resistance,” a text and card-based game that explores the intricate dance of diplomacy, identity, and resistance.

Screenshot of the game Maple Resistance showing dialogue spoken by a fictional Donald Trump with text generated by a local LLM.

Screenshot of the game Maple Resistance showing dialogue spoken by a fictional Donald Trump with text generated by a local LLM.

Designing dystopia

As a game designer, I like to experiment with new technologies and mechanics. One of my primary goals with Maple Resistance was to experiment with local Large Language Models (LLMs) and Unity to create a narrative experience driven by dynamic, AI-generated dialogue. This worked out. The local LLM worked better than I thought, and given that the LLM I was using is from earlier this year I’m sure that the newer ones are even better. For those that are curious I used Mistral 7B.

AI generated image with the prompt "What Canada would like if the United States of America annexed Canada in the year 2025"

AI generated image with the prompt “What Canada would like if the United States of America annexed Canada in the year 2025”

Card collecting mechanic for conversations

Another experiment was the card-collection mechanic tied to player interactions with NPCs. The idea was simple: engage in conversations, gather information, and earn cards that can be strategically played. While this mechanic had mixed results in its execution, it showed promise. In the “Maple Resistance” prototype, players can collect these cards, though the system is not complete and far short of what I originally envisioned. An interconnected inventory system remains an elusive goal; however, the process has sparked numerous ideas for future iterations.

Screenshot of the game Maple Resistance showing dialogue spoken by a fictional Donald Trump with text generated by a local LLM.

Screenshot of the game Maple Resistance showing dialogue spoken by a fictional Donald Trump with text generated by a local LLM.

Futurism and the polycrisis

Set against the backdrop of a polycrisis—a convergence of multiple, interconnected crises—the game explores themes of nationalism, sovereignty, and the fragility of political systems. “Maple Resistance” is a speculative narrative that resonates with current global uncertainties, from geopolitical tensions to technological disruptions. It invites players to ponder the future of nations and the delicate balance of power, all within the framework of an engaging, strategic gameplay experience.

All the cards and dialogue (expect for the AI generated ones) are based on real world instances or statements made in the last few years. The infamous Project 2025 was an influence when I started this back in the spring.

AI generated image with the prompt "A cartoon version of Canadians holding back Americans from entering Canada"

AI generated image with the prompt “A cartoon version of Canadians holding back Americans from entering Canada”

There’s always more

Working on “Maple Resistance” has been a journey of discovery. The integration of LLMs in Unity was a technical success, although the tech I used is already outdated. The card-collection mechanic, while not perfect, offers a compelling layer of strategy and immersion. These experiences have laid the groundwork for future projects that will refine and expand these concepts, ultimately aiming to create richer, more complex game worlds.

I hop that as we navigate an increasingly uncertain future, games like “Maple Resistance” serve as both entertainment and reflection, offering a space to explore the possibilities and challenges that lie ahead. Through games we can create experiences that not only entertain but also provoke thought and inspire dialogue about the world we live in and the futures we can imagine.

Let’s make more policy games!

Screenshot of the game Maple Resistance showing dialogue spoken by a fictional Donald Trump with text generated by a local LLM.

Screenshot of the game Maple Resistance showing dialogue spoken by a fictional Donald Trump with text generated by a local LLM.

 

Play now

Maple Resistance is available to download from Itch.io.

 

 

A bonus image that makes little sense for those of you that read all the way to the end:

AI generated image with the prompt "A cartoon version of America invading Canada in the near future"

AI generated image with the prompt “A cartoon version of America invading Canada in the near future”

Jam This Game: A Book of Game Ideas

What originally started as a fun idea for a game jam is now a book that you can hold in your hands. The book, Jam This Game, contains knowledge about the game industry and focusses on how inspiring creativity in your game design practice. The ideas within the book (and accompanying Twitter bot) will help you in your next game jam and beyond.

Jam This Game explores ideas, creativity, and how to make a video game in today’s hectic industry. The book can help you think of new mechanics and was to approach your design process; however, for me the writing process of the book is more interesting.

This book announcement post got a little out of hand so I here’s a table of contents.

Read the foreward 

See what’s inside the book

A unique writing process

Read the foreward of the book

A decade ago, in 2011, I co-organized and ran an event called Board Game Jam. Back then the idea of making a game in a short amount of time (commonly referred to as a “jam”) was relatively new and board games were yet to hit their peak of popularity in the 2010s. In order to provide additional entertainment for our attendees I decided to run an event in which comedians and game designers are given prompts to pitch a game around.

From there, I took the idea to a class I was teaching at the time at George Brown College. It was a postgraduate class in game design, so the students understood of pitching and thinking on their feet. We played the game once per semester with a new iteration of rules every time. Keeping to the board game impetus of the whole game, it was an in-person card-based game.

This version of the game was titled Game Design Improv.

The goal of Game Design Improv was to produce the greatest quantity of game ideas in a short period of time. For Board Game Jam there was also the goal of making people laugh, thus the word improv in the title.

With each run of the game I asked for people to help expand the list of possible combinations in the game itself. The suggestions were mostly accepted, but occasionally a totally bizarre or offensive concept would be submitted (and promptly rejected). Things started to get out of hand with the quantity of cards needed.

A digital version of Game Design Improv was made in 2014 which contained five separate categories: Theme, Genre, Random, Mechanic, and Thing. Players would tap the screen to get a new, randomly selected, set of prompts to pitch. Still, the intent was to play in person and “pitch” to other players in the room.

The game kept growing and by 2016 I released a proper version of the game with good looking art. Here again, the idea as to keep it a social game. This was a mistake. Sales of the game were mediocre, but it was a great success in all of my game design classes. I still play it with students. During these play sessions I noticed that students liked the ideas generated but didn’t enjoy the stress of presenting their ideas. 

What if I could give them the ideas without the need for social interaction?

Thus, the Twitter bot was born. I took the list of mechanics, genre, and so on that had been honed over the years and reframed them to fit into a sentence (see Using This Book). The resulting Twitter bot known as @JamThisGame generates one game idea per day. You can use these ideas as prompt for whatever purpose you see fit. 

The ideas that have been selected for this book aren’t just random prompts, they have been curated by Ashton Irving. The organization and grouping of the prompts may seem odd at fist, but I assure that Ashton knows what they’re doing as they are as smart as any thinking machine I’ve ever worked with.

If you get at least one thing from these pages I hope it’s a renewed desire to push the boundaries of what’s possible in the world of games.

 

Buy Jam This Game now!

 

What’s Inside the book

Chapters will help you improve your teamwork and communication, or help you better think about the games industry at large. 

If you’re working on a game already – great! These idea prompts are useful to help you add fun to your game.

This book can help you:

  • Get the spark of inspiration!
  • Remix video games!
  • Create an entirely new game idea!
  • Think more creatively!
  • Conceptualize and brainstorm ideas!
  • Practice divergent thinking!
  • Take your idea to the next level!

Chapters to help you better understand the game design process:

  • The Games Industry
  • When You’re Ready to Expand Your Idea
  • Useful Game Making Tools
  • Finding Inspiration
  • What Are Game Mechanics
  • Creativity Matters
  • On Game Genres
  • A Thinking Machine to Inspire You
  • Importance of Divergent and Lateral Thinking
  • Getting Out of a Rut
  • From Idea to Creation
  • Working With a Team
  • Reception of Your Game

Idea lists to inspire you to take your game to the next level:

  •   Explore the Unknown
  •   Subvert Expectations
  •   Question Assumptions
  •   Remix and Expand
  •   Finding Patterns
  •   Repurpose the Familiar
  •   Challenge What You Know
  •   Indecisive Moments
  •   Playing With Friends
  •   Exploring the Edges 
  •   Trying New Approaches
  •   Reimagine The Basics

Bonus:

Includes a glossary of video game design terms!

 

jam this game twitter bot screenshot

The source for ideas

 

A unique writing process

I didn’t think I’d start 2022 with the launch of a new book, nor that the book would be conceived of and written within a week. Plus the book market isn’t doing well.

Previously, over the winter break from school I created Twitter bots, which were focussed on commentary. The Jam This Game Twitter bot doesn’t tweet commentary, it tweets ideas. When my winter desire to create something hit I didn’t want to create a new bot this time; but, I wanted to create something within the winter break (two weeks).

I started by sending a data request to Twitter for all the tweets from the bot. The tweets then got stripped down to pure text, which could be used elsewhere. This was about three thousand words (which is not enough for a book) and honestly, the ideas alone aren’t good enough since the bot already exists.

So where will additional content come from considering I didn’t want to write it all?

When writing a book the problem I keep running into is the actual act of writing. Sometimes the best solution to a problem is to avoid it entirely, and that’s exactly what I did.

Ghostwriters write books under someone else’s name, and in order for them to effectively do their job they need to understand the material. That’s not the case for an AI. Meet industry expert Ashton Irving.

Picture of Ashton Irving

I used a writing AI “assistant” to “write” content for my book, which I then edited. The process wasn’t seamless or very intuitive as AI writing tools are still in their infancy (and have been for what feels like decades). Figuring out how best to feed the AIs with prompts and words took some finessing. The first drafts of content came across as basically incoherent.

I thought up the content of the book and the AI actually wrote it. I subsequently added and edited the content. It was still much faster than writing the content from scratch. I could focus on the ideas instead of the individual sentences.

After figuring out how to tweak the systems to my liking the content improved. Interestingly, the word order mattered in what the AI would generate and greatly impact readability. I know my writing isn’t the best and nor are my editing skills. Thankfully I know I’m still better than an AI.

I learned how to tweak the generated content to be useful and provide insights into how the games industry operates. The base framework of the book leant itself well to a pattern of one chapter all of ideas from the Twitter bot followed by a chapter about creativity or industry issues. A repetitive structure meant the tone of the chapters could be slightly different and that readers will (hopefully) ignore the lack of transitions from one chapter to the next.

Final thoughts

Ultimately, I think readers will find this book “written” by Ashton Irving to be a worthwhile read.

I really enjoyed the creation of Jam This Game and the chance to play with AI writing tools. Some are better than others and by using additional grammar and AI tool can further improve Ashton Irving’s writing.

This post wasn’t written by an AI, or maybe it was. You’ll just have to decide for yourself because I won’t tell you.

The image above, in case you’re wondering,.

What are you waiting for? Go buy it now!

book cover of jam this game

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