Adjacent Possible Playground: Patterns of Play
Cards as roped paths to preferable outcomes
“From the very beginning of her education, the
child should experience the joy of discovery.”
― Alfred Whitehead
103% of the reason for generative center questions, cards, patterns of play and card-play conversation, is facilitating the joy of discovery and providing cards as roped paths to preferable outcomes.
Pick a few cards and gain insight from exploring different perspectives, exploring an adjacent possible.
Patterns of Play
Patterns of play are like human heuristics, with a play^n twist.
Card: Play^n
Play^n is a generative superset of play,
play with great questions, lusory attitude,
small group genius, structured thought,
generative conversation and preferable
outcome in mind.
If you scroll down, there’s patterns of play
(often found between the cards).
They look like this:
… pick cards and add your thoughts to and between them …
The Thing
Questions, cards, patterns of play and card-play conversations combine, forming a dynamic approach to explore paths between generative center questions and preferable outcomes.
A Large Computable Possibility Space
The card deck with its close to five-hundred cards, provides 100k two-card and 16M three-card combinations. You can also pursue four, five and more, but all these combinations are more conveniently explored through human/AI hybrid inquiry approaches. Simply put, you could theoretically purchase all the 100k two-card combination cards, but how would you shufffle the deck?
Solving The World’s Problems
That said, there will be a whole smorgasbord of physical decks and booster pack cards, because sitting down with a group of friends, having a cup of coffee and solve wicked problems is something we should never stop doing. With physical and online cards, you get the best of both worlds. Coffee AND computers.
Patterns of Play: Insight Synthesizer
Insight Synthesizer is a geist(1), a card and a pattern of play.
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https://adjacentpossible.social/#card
As to the practical design question, whether Geists are Geists, Cards or Patterns of Play? This will in large part remain a “game designer judgement call”, part of our human art and skill, and, quite possibly/hopefully, part of a requisite variety of next-gen tools for thought approaches and uses, aided by machine cultures and algorithms of loving grace.
By analogy and extension, each and every one of the around two-hundred patterns of play we’ve designed, are also geists.
All the patterns of play are designed to be added before, after, between and around (sets and sequences of) cards, forming generative sequences between generative questions and shared understanding.
The 100k nuances of a lusory attitude
There’s some subtle but important differences between geists and patterns of play:
Geists are significantly closer to algorithms than patterns of play, and they are slightly more procedural than combinatorial. Algorithms work great for hill-climbing and heuristics, combined with human imagination, anticipatory systems intelligence and creativity (play^n) work great for hill-finding and semiosphere slingshots through fitness landscapes.
Paul Klee, Lonely Flower
(there’s a longer piece here brewing about chreods, living systems, biosemiotics, semiosphere slingshots, chreods and metalayers, creating the relevant next through sign use in light of an adjacent possible, but I’ve already crammed tons of ideas into this post, so, let’s return to that later)
The Interface
In a network, language is the UI and conversation is the UX. Patterns of play are to intelligence augmentation (evolving human heuristics), what geists are to artificial intelligence(procedural generators providing algorithmic provocations).
This analogy is intensely and extensively human, the AI can augment and amplify all human analogies, our every thought turned prompt, but only after we’ve added precisely one gazillion chunks to our DKR/MKR’s and to the SLM/LLM’s and their algorithms and embeddings.
DKR
Dynamic Knowledge Repository (Doug Engelbart)
MKR
Modular Knowledge Repository
(Doug Engelbart with a hybrid Alfred North Whitehead,
Karen Barad, Online Community Commonplace Book
and SLM/LLM twist and hypertext extendability)
It’s cards, Jim, but not as we know it.
SLM
Small Language Models, think anything between individual books and dbPedia, that are both turned embeddings while also remaining readable and human parsable.
LLM
Large Language Models. One gazillion upvoted subreddits sanitized through a Mechanical Kenyan.
Corner of Skynet and Kenyans
Evolutionary novelty, unfolding character(human and cyborg)
and evolutionary purpose remains 103% the province of human
activities, behavior and coordinated efforts. Kenyans and 8bn
other humans. And you.
We have met the Skynet, and it is us, clicking like buttons. Meanwhile, in an adjacent possible timeline, finding ourselves on a bluegreen corner of the universe.
If we all get killed by Skynet, it’s because we programmed our machines to do precisely that. Clicking like buttons IS part of the algorithms. If we all perish in ecocide, it’s because we performed non-committal clicking like buttons and adding emojis, rather than adding our unique skills and joining coordinated efforts, doing something, anything, making for a lasting difference.
Hoping it would say more
My one gazillion like button clicks and my three million emoji adornments, what do they amount to? What difference do they make, over time?
If your conclusion is: “close to zero”, then maybe you would like to explore an adjacent possible to your online “social media” behavior? Did you turn yourself into a proprietary platform minion? Did you end up as an online NPC, by default?
Next time you add three words or less to a chat, once a month, hoping it would say more, then maybe you should explore adjacent possible options?
Social media turned social social media
Let’s say chat has something to do with both social media and social social media. Social social media is 103% about how you and a critical mass of others, extend your social cognition, online.
“Trust movement.”
— Alfred Adler
… formulate and gather around generative center questions …
Card: Moves
Intentionality, consciousness,
path, agency and enaction.
In social media, by default and
in social social media, by choice.
Card: Chat
Chat when it doesn’t include intentional effort
devolves into passive scan, mostly comfortably
numb content consumption, with attention and
reaction extraction by proprietary algorithms.
Card: Chat
Chat when it doesn’t even reproduce what
we think, devolves into increasingly weaponized,
pretend and ersatz communication reinforcing
narrow, reactively negotiated self-interest.
Card: Chat
Chat when it reproduces
what we think, is sign use.
Card: Chat
Chat does not only reproduce what
we think, it makes us think together.
Card: Chat
Chat is a worthwhile
social dilemma.
… cultivate shared understanding as generative closure
and evaluate against envisioned end-game scenario …
The Joy of Discovery
Are we doing social social media yet? Are we making progress? Progress, to what preferable outcomes?
Let’s Meet There
There’s a place beyond content consumption comfort zones and grand theft data. Let’s meet there.
How? How You Doing!?
Let’s start with a why and a whereto. One of the core reasons for my card-design idea “a large finite set cards, card deck, with underlying pattern language and underlying modular process onto-epistemology” is to be able to not only catalyze the joy of discovery and facilitate and measure progress to preferable outcomes, but to take a definite stand on the side of human governance, including individual imagination, small group genius and online community of card-play conversation practice design cybernetics, navigating the new.
Rabota Rabota
Humans need to learn human/AI literacies, in order to skillfully turn intelligence into ability, content consumption comfort zone passivity into adjacent possible explorations, behavior turned agency, information turned knowledge and knowledge turned understanding, with cards used as building blocks of narrative and stepping stones for lines of inquiry, unfolding paths to preferable outcomes, evaluated against envisioned end-game scenarios.
Algorithms of Loving Grace
We can train our ever helpful robots, our algorithms of loving grace, to click all the like buttons for us, to code our new website, leaving us plenty of time pursuing our essential character turned art in light of our making a unique difference to our human evolutionary purpose.
Art of Agency
Games in general and card-play conversations in particular as an art of agency, agency in service to human evolution in general and the individual joy of discovery in particular.
Card-Play Format
The below is a card-play format, with patterns of play between cards, facilitating card-play conversations and forming generative sequences between questions and shared understanding. Replace the Alfred North Whitehead quotes with cards, and there you go.
… patterns of play …
… formulate and gather around generative center questions …
“Every really new idea looks crazy at first.”
― Alfred North Whitehead
… pick cards and add your thoughts to and between them …
“Intelligence is quickness to apprehend as distinct from ability,
which is capacity to act wisely on the thing apprehended.”
― Alfred North Whitehead
… engage in card-play conversations addressing worthwhile
dilemmas related to the chosen generative center question …
“…the only simplicity to be trusted is the simplicity
to be found on the far side of complexity.”
― Alfred North Whitehead
… formulate and gather around generative center questions; pick cards and add your thoughts to and between them; engage in card-play conversations around questions, with human and AI-assisted card annotations addressing worthwhile dilemmas; cultivate shared understanding as generative closure; evaluate thoughts, insights, moves, paths and preferable outcomes against envisioned end game scenarios; collaborate on narratives and co-create knowledge artifacts building on the cards, card-play conversations and annotations …
“Great dreamers’ dreams are never fulfilled, they are always transcended.”
― Alfred North Whitehead
… cultivate shared understanding as generative closure
and evaluate against envisioned end-game scenario …
What you just went through, is a card-play format, with patterns of play between cards (in the above example I replaced the cards with quotes), forming generative sequences between questions and shared understanding.
Since the card deck is a large finite set, it enables computing in general and human/AI annotations in particular. Add your thoughts to the cards and the patterns of play, together with others, adopting a lusory/small group genius attitude, and you’ll find yourself in a card-play conversation.
… formulate and gather around generative center questions …
Card: Card-Play Conversation
Card-play conversations provide a framework for exploring complex ideas and generating new perspectives.
By formulating and gathering around generative center questions, participants can arrange cards, add their thoughts and identify patterns of play that lead to unfolding paths to preferable outcomes.
The external brain (represented by cards, card-play conversations, notes and boundary objects), as an extension of our embodied and social cognition, plays a crucial role in this process, providing the tools and technologies necessary to capture, organize, and share information, with card-play conversation facilitating information turned knowledge.
As we cultivate shared understanding as generative closure, we can evaluate our progress against our envisioned end-game scenarios, continuously refining our understanding and expanding our cognitive horizons.
… cultivate shared understanding as generative closure
and evaluate against envisioned end-game scenario …
Human/AI annotations
I asked ChatGPT, (about geists) here’s part of its response:
Idea Catalyst:
Examining your notes, this geist generates algorithmic provocations to spark innovative ideas and solutions, pushing beyond conventional thinking.
As a note to self, I added the below with the intention of exploring further:
To Create a Game Master: A Decalogue for Procedural Generation of Interactive Stories
— Carles Homs
“How can we digitally recreate the role of a Game Master?”
— Carles Homs
SCAMPER is a procedural idea generator
— Gordon Brander
(1)”Geists are little bots that live in your Subconscious. They do useful things… finding connections between notes, issuing oracular provocations and gnomic utterances.
I’ve been playing with some simple command-line prototypes for Geists. They’re just little scripts that find connections between notes, and use procedural generators to construct algorithmic provocations.”
— Gordon Brander
……………………..
John Kellden:
Elaborate on the notion of “geists”, Gordon Brander’s name for scripts working as procedural generators:
“Geists are little bots that live in your Subconscious.
They do useful things… finding connections between notes
issuing oracular provocations and gnomic utterances.
I’ve been playing with some simple command-line
prototypes for Geists. They’re just little scripts that find
connections between notes, and use procedural generators
to construct algorithmic provocations.”
— Gordon Brander
with geists/scripts working as generative algorithmic provocations, adding to and augmenting our human heuristics, including but not limited to providing additional functionality to notes and note-making, with the ultimate goal of our using geists, learning augmented by more generatively and creatively leveraging combinations of human and AI-assisted annotations.
Expand on the notion of “geists”by relating it to related and adjacent notions, conducive to combinations of “procedural generators to construct algorithmic provocations” and human/AI prompts in general and prompts as an evolving human/AI literacy in particular.
Provide a list of five example geists that you can already produce, in the spirit of adding generative algorithmic provocations, given the above, eg adding something adjacent to your response.
Close with a summary of the above, with emphasis on suggestions what I should ask you next, given the “field of embeddings” related to this prompt, to further explore the nature and potential and possible uses of geists, procedural generators to construct algorithmic provocations.
OpenAI:
The notion of “geists” as conceived by Gordon Brander represents a fascinating intersection of human cognition and artificial intelligence, where scripts act as procedural generators to enhance cognitive processes. Geists, in this context, are envisioned as small programs or bots residing in the subconscious, performing tasks such as finding connections between notes, issuing oracular provocations, and generating algorithmic utterances. The goal is to augment human heuristics, particularly in the realm of note-taking and annotation, by creatively leveraging combinations of human and AI-assisted annotations.
Gordon Brander’s idea of geists aligns with the broader trend of exploring synergies between human intelligence and artificial intelligence. By employing procedural generators, these geists contribute to the creative process by providing algorithmic provocations that go beyond traditional note-making. The emphasis is on enhancing learning and creativity through the symbiotic relationship between human users and AI algorithms.
Related Notions:
- Human/AI Prompts
Geists can be seen as a form of AI prompts, designed to stimulate thought and creativity. The interaction between human users and these prompts contributes to an evolving literacy in which individuals become adept at combining their insights with algorithmically generated suggestions. - Procedural Generators
The use of procedural generators adds a dynamic and algorithmic dimension to the creative process. Geists harness these generators to construct provocations, providing users with novel perspectives and ideas. - Human/AI Collaboration
Geists exemplify the collaborative potential between humans and AI. Instead of replacing human input, they complement it, offering new ways of thinking and generating content that wouldn’t be easily achievable by either party alone. - Note Augmentation
Geists contribute to the augmentation of notes by finding connections and issuing provocations. This goes beyond traditional note-taking, transforming notes into dynamic elements that continuously evolve and inspire further exploration. - Algorithmic Creativity
Geists demonstrate the capacity of algorithms to contribute to the creative process. They become partners in ideation, assisting individuals in exploring unconventional pathways and generating ideas that may not have emerged through traditional methods.
Example Geists:
- Connection Explorer
This geist analyzes your notes and suggests unexpected connections between seemingly unrelated topics, fostering interdisciplinary thinking. - Oracular Advisor
Providing cryptic yet thought-provoking insights, this geist issues algorithmically generated oracles to stimulate creative thinking and problem-solving. - Story Synthesizer
Utilizing procedural generation, this geist assists in constructing narrative structures, suggesting plot twists, and generating creative story elements based on your notes. - Idea Catalyst
Examining your notes, this geist generates algorithmic provocations to spark innovative ideas and solutions, pushing beyond conventional thinking. - Visual Conceptualizer
Transforming textual notes into visual representations, this geist uses procedural generators to create diagrams, mind maps, or other visual aids to enhance understanding and creativity.
Summary, Geists
The concept of geists, as envisioned by Gordon Brander, encapsulates the potential of combining procedural generators and human intelligence to foster creativity and learning. Geists act as algorithmic provocateurs, stimulating new ideas and connections within the context of note-taking and annotation. The synergy between human and AI prompts, procedural generators, and collaborative efforts showcases the evolving landscape of human/AI literacy. To delve deeper into the nature and potential uses of geists and procedural generators, you might want to explore specific applications, ethical considerations, or advancements in AI that could further enhance these generative capabilities.
…………….
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Cards for Insight: LLM’s
Cards, patterns of play and card-play conversations combine,
facilitating exploring paths between worthwhile dilemmas,
generative center questions and preferable outcomes.
There’s around 500 cards in the source deck, with more than 120k
two-card and 21M three-card combinations. With four-, five- and
six-card combinations mapping to LLM’s, Large Language Models, facilitating human associations(card-play) combining with
AI-assisted annotations(prompts and responses).
Think cards with an underlying pattern language and with an underlying Modular Process Onto-Epistemology forming part of an Online Commonplace, with a searchable Knowledge Repository.
